U.S. patent number RE33,162 [Application Number 07/141,304] was granted by the patent office on 1990-02-13 for method and apparatus for guidance of an operation of operating power plants.
This patent grant is currently assigned to Hitachi, Ltd.. Invention is credited to Takashi Kiguchi, Takao Watanabe, Kenichi Yoshida.
United States Patent |
RE33,162 |
Yoshida , et al. |
February 13, 1990 |
**Please see images for:
( Reexamination Certificate ) ** |
Method and apparatus for guidance of an operation of operating
power plants
Abstract
This invention refers to a .[.plant operating.]. method
.Iadd.and apparatus for guidance of an operation .Iaddend.for
overcoming an abnormal status of a plant. A plant data is detected
from the plant, and all plant state members indicating an
abnormality of the plant are identified from the plant data. The
plant operating method .Iadd.and apparatus .Iaddend.includes
.Iadd.apparatus for .Iaddend.estimating a cause whereby the plant
status members are produced, predicting all plant status members
arising after passing a given period of time according to the
estimated cause, determining whether or not actual plant status
members are present in the plant state members predicted and when
the latter members are not present in the former members,
repeatedly carrying out the processing of the steps of estimating
and predicting to which the plant status members forcasted at the
predicting step are inputted until all the actual plant status
members come to exist in the plant status members forecasted at the
predicting step. When all the actual plant status members are
present in the plant status members predicted at the predicting
step, a plant operation for overcoming the cause obtained at the
step of estimating which produces the predicted plant status
members is selected, and the plant operation is carried out
according to the selected operation.
Inventors: |
Yoshida; Kenichi (Hachioji,
JP), Watanabe; Takao (Hitachi, JP),
Kiguchi; Takashi (Mito, JP) |
Assignee: |
Hitachi, Ltd. (Tokyo,
JP)
|
Family
ID: |
15796884 |
Appl.
No.: |
07/141,304 |
Filed: |
January 6, 1988 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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Reissue of: |
433908 |
Oct 12, 1982 |
04563746 |
Jan 7, 1986 |
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Foreign Application Priority Data
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Oct 14, 1981 [JP] |
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56-164632 |
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Current U.S.
Class: |
700/291;
976/DIG.296 |
Current CPC
Class: |
G21D
3/00 (20130101); G05B 9/02 (20130101); Y10S
706/914 (20130101); Y02E 30/30 (20130101); Y10S
706/915 (20130101); Y10S 706/907 (20130101); Y02E
30/00 (20130101); Y10S 706/906 (20130101) |
Current International
Class: |
G05B
9/02 (20060101); G21D 3/00 (20060101); G06F
015/46 (); G06F 015/18 () |
Field of
Search: |
;364/200,300,900,148,184,492,550,551,513 ;376/216,217 |
References Cited
[Referenced By]
U.S. Patent Documents
Primary Examiner: Lall; Parshotam S.
Assistant Examiner: Teska; Kevin
Attorney, Agent or Firm: Antonelli, Terry & Wands
Claims
What is claimed is:
1. A plant operating method comprising the steps of:
detecting plant data from a plant;
identifying the actual status of all members of the plant
indicating an abnormality of the plant from the detected plant
data;
estimating a cause of an occurrence of the abnormality in
accordance with the actual status of the plant members;
predicting the status of all plant members after a given period of
time has passed in accordance with the estimated cause;
determining whether or not the actual status of the plant members
are present in the predicted status of the plant members;
repeatedly carrying out the step of estimating a cause of
occurrence of the abnormality and predicting the status of all
plant members in accordance therewith when it is determined that
the actual status of all the plant members are not present in the
predicted status of the plant members detected until the actual
status of all the plant members come to exist in the predicted
status of the plant members;
selecting a plant operation plan for overcoming the estimated cause
of occurrence of the abnormality when the actual status of all of
the plant members are present in the status of the predicted plant
members; and
operating the plant according to the selected operation plan.
2. The plant operating method according to claim 1, wherein the
step of estimating the cause of occurrence of the abnormality is
based upon data providing a cause and effect relationship.
3. The plant operating method as defined in claim 1, wherein the
step of selecting an operation plan for overcoming the estimated
cause of the abnormality includes predicting the status of the
plant members when the selected operation is put into practice for
a given period of time, determining whether or not the selected
operation plan should be selected, and repeatedly carrying out
selection of an operation plan to overcome an occurrence of the
predicted status of the plant members in accordance with the
selected operation plan until no operation plan is selected, and
thereafter selecting an operating plan which satisfies operating
conditions for the plant as the selected operation plan from among
the operation plans thus obtained.
4. The plant operating method according to claim 3, wherein the
step of selecting an operation plan includes retrieving data
indicating the operation plan corresponding to the predicted status
of the plant members.
5. The plant operating method according to claim 3, including the
step of determining the status of the plant members arising as a
consequence of the predicted status of the plant members.
6. The plant operating method according to claim 5, wherein the
status of the plant members arising as a consequence of the
predicted status of the plant members is obtained by retrieving
data providing a cause and effect relationship.
7. The plant operating method according to claim 1 or 3, further
comprising the steps of obtaining a detail procedure for the
selected operating plan and determining whether the detail
procedure is contrary to the limitations on the plant operation,
and carrying out the selected operation plan when the detail
procedure is not contrary to limitations on the plant operation,
and selecting another operation plan for overcoming the estimated
cause of the abnormality when the detail procedure is contrary to
the limitations on the plant operation. .Iadd.
8. An operating method comprising the steps of:
(1) inputting data of a system to be operated;
(2) identifying the actual status of all members of the system
indicating an abnormality of the system from the inputted data;
(3) estimating at least one cause of an occurrence of the
abnormality in accordance with the actual status of the
members;
(4) predicting the status of all members after a given period of
time has passed in accordance with the estimated cause;
(5) determining whether or not the actual status of the members are
present in the predicted status of the members;
(6) repeatedly carrying out the step of estimating at least one
cause of occurrence of the abnormality and predicting the status of
all members in accordance therewith when it is determined that the
actual status of all members are not present in the predicted
status of the members until the actual status of all members come
to exist in the predicted status of the members;
(7) selecting an operation plan for overcoming the estimated cause
of occurrence of the abnormality when the actual status of all of
the members are present in the status of the predicted members;
and
(8) operating the system according to the selected operation plan.
.Iaddend. .Iadd.9. An operating method according to claim 8,
wherein the step of estimating the cause of occurrence of the
abnormality is based upon data providing a cause and consequence
relationship. .Iaddend. .Iadd.10. An operating method according to
claim 8, wherein the step of selecting an operation plan for
overcoming the estimated cause of the abnormality includes the
steps of:
(1) predicting the status of the members when the selected
operation is put into practice for a given period of time;
(2) determining whether or not the selected operation plan should
be selected;
(3) repeatedly carrying out selection of an operation plan to
overcome an occurrence of the predicted status of the members in
accordance with the selected operation plan until no operation plan
is selected; and thereafter
(4) selecting an operation plan which satisfies operating
conditions for the system as the selected operation plan from among
the operation plans thus obtained. .Iaddend. .Iadd.11. An operating
method according to claim 10, wherein the step of selecting an
operation plan includes the step of retrieving data indicating the
operation plan corresponding to the predicted status of the
members. .Iaddend. .Iadd.12. An operating method according to claim
10, further comprising the step of determining the status of the
members arising as a consequence of the predicted status of the
members. .Iaddend. .Iadd.13. An operating method according to claim
12, wherein the status of the members arising as a consequence of
the predicted status of the members is obtained by retrieving data
providing a cause and consequence relationship. .Iaddend. .Iadd.14.
A method according to claim 8 or 10, further comprising the steps
of:
(1) obtaining a detail procedure for the selected operation
plan;
(2) determining whether the detail procedure is contrary to the
limitations on the operation;
(3) carrying out the selected operation plan when the detail
procedure is not contrary to limitations on the operation; and
(4) selecting another operation plan for overcoming the estimated
cause of the abnormality when the detail procedure is contrary to
the limitations on the operation. .Iaddend. .Iadd.15. A method
comprising the steps of:
(1) inputting data of an object;
(2) identifying the actual status of all members of the object
indicating an abnormality of the object from the inputted data;
(3) estimating at least one cause of an occurrence of the
abnormality in accordance with the actual status of the
members;
(4) predicting the status of all members after a given period of
time has passed in accordance with the estimated cause;
(5) determining whether or not the actual status of the members are
present in the predicted status of the members;
(6) repeatedly carrying out the step of estimating at least one
cause of occurrence of the abnormality and predicting the status of
all members in accordance therewith when it is determined that the
actual status of all members are not present in the predicted
status of the members detected until the actual status of all
members come to exist in the predicted status of the members;
and
(7) selecting an operation plan for overcoming the estimated cause
of occurrence of the abnormality when the actual status of all of
the members are present in the status of the predicted members.
.Iaddend. .Iadd.16. A method according to claim 15, wherein the
cause of occurrence of the abnormality is based upon data providing
a cause and consequence relationship. .Iaddend. .Iadd.17. A method
according to claim 15, wherein the step of selecting an operation
plan for overcoming the estimated cause of the abnormality includes
the steps of:
(1) predicting the status of the members when the selected
operation plan is put into practice for a given period of time,
(2) determining whether or not the selected operation plan should
be selected,
(3) repeatedly carrying out selection of an operation plan to
overcome an occurrence of the predicted status of the members in
accordance with the selected operation plan until no operation plan
is selected, and thereafter
(4) selecting an operating plan which satisfies operating
conditions for the object as the selected operation plan from among
the operation plans thus obtained. .Iaddend. .Iadd.18. A method
according to claim 17, wherein the step of selecting an operation
plan includes the step of retrieving data indicating the operation
plan corresponding to the predicted status of the members.
.Iaddend. .Iadd.19. A method according to claim 17, further
comprising step of determining the status of the members arising as
a consequence of the predicted status of the members. .Iaddend.
.Iadd.20. A method according to claim 19, wherein the status of the
members arising as a consequence of the predicted status of the
members is obtained by retrieving data providing a cause and
consequence relationship. .Iaddend. .Iadd.21. A method according to
claim 15 or 17, further comprising the steps of:
(1) obtaining a detail procedure for the selected operation
plan;
(2) determining whether the detail procedure is contrary to the
limitations on the operation; and
(3) selecting another operation plan for overcoming the estimated
cause of the abnormality when the detail procedure is contrary to
the limitations
on the operation. .Iaddend. .Iadd.22. An apparatus including a
computer comprising:
(1) a memory for storing data bases including
(a) a data base recording relations of causes and consequences,
(b) a data base recording information to predict transitional
behavior of an object, and
(c) a data base recording operation plans; and
(2) means for carrying out a processing program to make a guidance
consultation to overcome a cause of abnormality of the object
including
(a) means for inputting data of the object,
(b) means responsive to the inputting means for identifying the
actual status of all members of the object indicating an
abnormality of the object from the inputted data,
(c) means responsive to the identifying means for estimating a
cause of an occurrence of the abnormality in accordance with the
actual status of the members,
(d) means responsive to the estimating means for predicting the
status of all members after a given period of time has passed in
accordance with the estimated cause,
(e) means responsive to the predicting means for determining
whether or not the actual status of the members are present in the
predicted status of the members,
(f) means responsive to the determining means for repeatedly
carrying out the estimating of a cause of occurrence of the
abnormality and predicting the status of all members in accordance
therewith when it is determined that the actual status of all
members are not present in the predicted status of the members
detected until the actual status of all members come to exist in
the predicted status of the member, and
(g) means responsive to the repeatedly carrying out means for
selecting an operation plan for overcoming the estimated cause of
occurrence of the abnormality when the actual status of all of the
members are present in
the status of the predicted members. .Iaddend. .Iadd.23. An
apparatus according to claim 22, wherein the means for estimating
the cause of occurrence of the abnormality are based upon data
providing a cause and
consequence relationship. .Iaddend. .Iadd.24. An apparatus
according to claim 22, wherein the means for selecting an operation
plan for overcoming the estimated cause of the abnormality
includes:
(1) means for listing at least one operation plan;
(2) means responsive to the listing means for predicting the status
of the members when a selected operation plan is put into practice
for a given period of time;
(3) means responsive to the predicting means for determining
whether or not the selected operation plan should be selected;
(4) means responsive to the determining means for repeatedly
carrying out selection of another operation plan to overcome an
occurrence of the predicted status of the members in accordance
with the selected operation plan until no operation plan is
selected; and thereafter
(5) means responsive to the repeatedly carrying out means for
selecting an operation plan which satisfies operating conditions
for the object as the selected operation plan from among the
operation plans thus obtained.
.Iaddend. .Iadd.25. An apparatus according to claim 24, wherein the
means for selecting an operation plan further includes means for
retrieving data indicating the operation plan corresponding to the
predicted status of the members. .Iaddend. .Iadd.26. An apparatus
according to claim 24, further comprising means for determining the
status of the members arising as a consequence of the predicted
status of the members. .Iaddend. .Iadd.27. An apparatus according
to claim 26, wherein the status of the members arising as a
consequence of the predicted status of the members is obtained by
retrieving data providing a cause and consequence relationship.
.Iaddend.
.Iadd.28. An apparatus according to claim 22 or 24, further
comprising:
(1) means responsive to the selecting means for obtaining a
detailed procedure for the selected operation plan;
(2) means responsive to the detail means for determining whether
the detailed procedure is contrary to the limitations on the
operation; and
(3) means responsive to the determining means for selecting another
operation plan for overcoming the estimated cause of the
abnormality when the detailed procedure is contrary to the
limitations on the operation. .Iaddend. .Iadd.29. An apparatus
including a computer comprising:
(1) memory means for storing information forming a knowledge base
including
(a) data as facts expressed as at least one identifier portion
indicative of a state of an object and a corresponding value
portion, and
(b) rules including IF parts and corresponding THEN parts, each of
the IF parts and corresponding THEN parts including an identifier
portion and a corresponding value; and
(2) means for carrying out a processing program including
interpretation of the knowledge base for guidance including
(a) means for searching the knowledge base in accordance with a
predetermined fact for comparing facts and rules so as to obtain at
least one of an IF part or THEN part of a rule as a result of the
comparison,
(b) means responsive to the searching means for utilizing the
comparison result as a new fact for searching of the knowledge base
by the searching means,
(c) means responsive to no comparison result from the searching
means for terminating the search of the knowledge base, and
(d) means responsive to termination of the search of the knowledge
base by the terminating means for outputting a result of carrying
out the
processing program. .Iaddend. .Iadd.30. An apparatus according to
claim 29, wherein the means for carrying out a processing program
further includes:
(1) means for inputting data of the object;
(2) means responsive to the storing means for utilizing the actual
status of all the members of the object indicating a state of the
object as different facts, each having an identifier portion
indicative of the state of the object and a corresponding
value;
(3) means responsive to the utilizing means for searching the
knowledge base to obtain an IF part of a rule in accordance with a
predetermined fact when utilizing the predetermined fact as a THEN
part of the rule;
(4) means responsive to the searching means for predicting the
status of all members after a given period of time has passed in
accordance with the IF part obtained as a new fact; and
(5) means responsive to the predicting means for searching the
knowledge base to determine whether or not the actual status of the
members are
present in the predicting status of the members. .Iaddend.
.Iadd.31. An apparatus according to claim 30, further comprising
means for selecting an operation plan including:
(1) means for listing at least one operation plan;
(2) means responsive to the listing means for predicting the status
of the members when the selected operation plan is put into
practice for a given period of time;
(3) means responsive to the predicting means for determining
whether or not the selected operation plan should be selected;
(4) means responsive to the determining means for repeatedly
carrying out selection of another operation plane in accordance
with the selected operation plan until no operation plan is
selected; and thereafter
(5) means responsive to the repeatedly carrying out means for
selecting an operation plan from among the operation plans thus
obtained. .Iaddend.
.Iadd.32. An apparatus according to claim 31, wherein the means of
selecting an operation plan includes means for retrieving data
indicating the operation plan corresponding to the predicted status
of the members. .Iaddend. .Iadd.33. An apparatus according to claim
31, further comprising:
(1) means responsive to the selecting means for obtaining a
detailed procedure for the selected operation plan;
(2) means responsive to the detail means for determining whether
the detailed procedure is contrary to the limitations on the
operation; and
(3) means responsive to the determining means for selecting another
operation plan when the detailed procedure is contrary to the
limitations on the operation plan. .Iaddend. .Iadd.34. An apparatus
according to claim 31, further comprising means for determining the
status of the members arising as a consequence of the predicted
status of the members. .Iaddend. .Iadd.35. An apparatus according
to claim 34, wherein the status of the status of the members
arising as a consequence of the predicted status of the members is
obtained by retrieving data providing a cause and
consequence relationship. .Iaddend. .Iadd.36. A method comprising
the steps of:
(1) storing a data base forming a knowledge base including
(a) data as facts expressed as at least one identifier portion
indicative of the state of an object and a corresponding value
portion, and
(b) rules including IF parts and corresponding THEN parts, each of
the IF parts and corresponding THEN parts including an identifier
portion and a corresponding value; and
(2) carrying out a processing program including interpretation of
the knowledge base for guidance including
(a) searching the knowledge base in accordance with a predetermined
fact for comparing facts and rules so as to obtain at least one of
an IF part or THEN part of a rule as a result of the
comparison,
(b) utilizing the comparison result as a new fact for searching the
knowledge base,
(c) terminating the search of the knowledge base when no comparison
result is obtained, and
(d) outputting a result of carrying out the processing program in
response
to termination of the search of the knowledge base. .Iaddend.
.Iadd.37. A method according to claim 36, further comprising the
steps of:
(1) inputting data of the object,
(2) utilizing the actual status of all members of the object
indicating a state of the object as different facts, each having an
identifier portion indicative of the state of the object and a
corresponding value,
(3) searching the knowledge base to obtain an IF part of a rule in
accordance with a selected fact when utilizing the selected fact as
a THEN part of a rule,
(4) predicting the status of all members after a given period of
time has passed in accordance with the IF part obtained as a new
fact, and
(5) searching the knowledge base to determine whether or not the
actual status of the members are present in the predicted status of
the members. .Iaddend. .Iadd.38. A method according to claim 37,
further comprising the step of selecting an operation plan
including the steps of
(1) predicting the status of the plant members when the selected
operation plan is put into practice for a given period of time,
(2) determining whether or not the selected operation plan should
be selected,
(3) repeatedly carrying out selection of an operation plan in
accordance with the selected operation plan until no operation plan
is selected, and thereafter
(4) selecting an operation plan from among the operation plans
thus
obtained. .Iaddend. .Iadd.39. A method according to claim 38,
wherein the step of selecting an operation plan includes the step
of retrieving data indicating the operation plan corresponding to
the predicted status of the members. .Iaddend. .Iadd.40. A method
according to claim 38, further comprising the steps of:
(1) obtaining a detail procedure for the selected operation
plan,
(2) determining whether the detail procedure is contrary to the
limitations on the operation, and
(3) selecting another operation plan when the detail procedure is
contrary
to the limitations on the operation. .Iaddend. .Iadd.41. A method
according to claim 38, further comprising the step of determining
the status of the members arising as a consequence of the predicted
status of the members. .Iaddend. .Iadd.42. A method according to
claim 41, wherein the status of the members arising as a
consequence of the predicted status of the members is obtained by
retrieving data providing a cause and
consequence relationship. .Iaddend. .Iadd.43. An apparatus
including a computer comprising:
(1) memory means for storing data forming a knowledge base
including
(a) data as facts expressed as at least one identifier portion
indicative of a state of an object and a corresponding portion,
and
(b) rules including IF parts and corresponding THEN parts, each of
the IF parts and corresponding THEN parts including an identifier
portion and a corresponding value; and
(2) means for carrying out a processing program for interpretation
of the knowledge base including
(a) means for searching the knowledge baes in accordance with a
selected fact for comparing facts and rules so as to obtain at
least one of an IF part or THEN part of a rule as a result of the
comparison,
(b) means responsive to the comparison result of the searching
means for terminating the search of the knowledge base, and
(c) means responsive to the terminating means terminating the
search of the knowledge base for outputting a result of carrying
out the processing
program. .Iaddend. .Iadd.44. An apparatus according to claim 43,
wherein the means for carrying out a processing program further
includes
(1) means for inputting data of the object,
(2) means for utilizing the actual status of all members of the
object indicating an state of the object as different facts, each
having an identifier portion indicative of the state of the object
and a corresponding value, and
(3) means for searching the knowledge base to obtain an IF part of
a rule in accordance with a selected fact when utilizing the
selected fact as a THEN part of a rule. .Iaddend. .Iadd.45. An
apparatus according to claim 44, further comprising means for
selecting an operation plan including
(1) means for predicting the status of the members when the
selected operation plan is put into practice for a given period of
time,
(2) means for determining whether or not the selected operation
plan should be selected,
(3) means for repeatedly carrying out selection of an operation
plan in accordance with the selected operation plan until no
operation plan is selected, and thereafter
(4) means for selecting an operation plan from among the operation
plans thus obtained. .Iaddend. .Iadd.46. An apparatus according to
claim 45, wherein the means of selecting an operation plan includes
means for retrieving data indicating the operation plan
corresponding to the predicted status of the members. .Iaddend.
.Iadd.47. An apparatus according to claim 45, further
comprising:
(1) means for obtaining a detail procedure for the selected
operation plan, and
(2) means for determining whether the detail procedure is contrary
to the limitations on the operation, and means for selecting
another operation plan when the detail procedure is contrary to the
limitations on the
operation. .Iaddend. .Iadd.48. An apparatus according to claim 45,
further comprising the means of determining the status of the
members arising as a consequence of the predicted status of the
members. .Iaddend. .Iadd.49. An apparatus according to claim 48,
wherein the status of the members arising as a consequence of the
predicted status of the members is obtained by retrieving data
providing a cause and consequence
relationship. .Iaddend. .Iadd.50. A method comprising the steps
of:
(1) storing a data base forming a knowledge base including
(a) data as facts expressed as at least one identifier portion
indicative of a state of an object and a corresponding value
portion, and
(b) rules including IF parts and corresponding THEN parts, each of
the IF parts and corresponding THEN parts including an identifier
portion and a corresponding value;
(2) carrying out a processing program including interpretation of
the knowledge base including the steps of
(a) searching the knowledge base in accordance with a selected fact
for comparing facts and rules so as to obtain at least one of an IF
part or THEN part of a rule as a result of the comparison, and
(b) terminating the search of the knowledge base in response to the
comparison result, and outputting a result of carrying out the
processing program in response to termination of the search of the
knowledge base.
.Iaddend. .Iadd.51. A method according to claim 50, further
comprising the steps of:
(1) inputting data of the object
(2) utilizing the actual status of all members of the object,
indicating a state of the object as different facts, each having an
identifier portion indicative of the state of the object and a
corresponding value, and
(3) searching the knowledge base to obtain an IF part of a rule in
accordance with a selected fact when utilizing the selected fact as
a THEN part of a rule. .Iaddend. .Iadd.52. A method according to
claim 50, further comprising the step of selecting an operation
plan including the steps of:
(1) predicting the status of the plant members when the selected
operation plan is put into practice for a given period of time,
(2) determining whether or not the selected operation plan should
be selected,
(3) repeatedly carrying out selection of an operation plan in
accordance with the selected operation plan until no operation plan
is selected, and thereafter
(4) selecting an operation plan from among the operation plans thus
obtained. .Iaddend. .Iadd.53. A method according to claim 52,
wherein the step of selecting an operation plan includes the step
of retrieving data indicating the operation plan corresponding to
the predicted status of the members. .Iaddend. .Iadd.54. A method
according to claim 52, further comprising the steps of:
(1) obtaining a detail procedure for the selected operation plan,
and
(2) determining whether the detail procedure is contrary to the
limitations on the operation, and
(3) selecting another operation plan when the detail procedure is
contrary
to the limitations on the operation. .Iaddend. .Iadd.55. A method
according to claim 52, further comprising the step of determining
the status of the members arising as a consequence of the predicted
status of the members. .Iaddend. .Iadd.56. A method according to
claim 55, wherein the status of the members arising as a
consequence of the predicted status of the members is obtained by
retrieving data providing a cause and
consequence relationship. .Iaddend. .Iadd.57. A process comprising
the steps of:
(1) storing information forming a knowledge base in memory means of
a computer including
(a) data as facts expressed to be at least one identifier as a
state of an object and corresponding values,
(b) rules including IF parts and corresponding THEN parts with at
least one value for an identifier;
(2) storing a processing program in memory means of the computer,
the processing program enabling interpretation of the knowledge
base by
(a) searching the knowledge base for comparing facts and rules,
(b) comparing facts with one of IF parts or THEN parts of the rules
to obtain at least one of an IF part or THEN part as a result of
the comparison,
(c) adding new facts to the knowledge base as a result of the
comparison,
(d) terminating the search of the knowledge base, and outputting a
result of carrying out the processing program; and
(3) running the processing program for interpretation of the
knowledge
base. .Iaddend. .Iadd.58. A process according to claim 51, further
comprising the steps of:
(1) inputting data of the object,
(2) utilizing the actual status of all members of the object
indicating a state of the object as different facts, each having an
identifier portion indicative of the state of the object and a
corresponding value,
(3) searching the knowledge base to obtain an IF part of a rule in
accordance with a selected fact when utilizing the selected fact as
a THEN part of a rule,
(4) predicting the status of all members after a given period of
time has passed in accordance with the IF part obtained as a new
fact, and
(5) searching the knowledge base to determine whether or not the
actual status of the members are present in the predicted status of
the members. .Iaddend. .Iadd.59. A process according to claim 58,
further comprising the step of selecting an operation plan
including the steps of:
(1) predicting the status of the plant members when the selected
operation plan is put into practice for a given period of time,
(2) determining whether or not the selected operation plan should
be selected,
(3) repeatedly carrying out selection of an operation plant in
accordance with the selected operation plan until no operation plan
is selected, and thereafter
(4) selecting an operation plan from among the operation plans thus
obtained. .Iaddend. .Iadd.60. A process according to claim 59,
wherein the step of selecting an operation plan includes the step
of retrieving data indicating the operation plan corresponding to
the predicted status of the members. .Iaddend. .Iadd.61. A process
according to claim 59, further comprising the steps of:
(1) obtaining a detail procedure for the selected operation plan,
and
(2) determining whether the detail procedure is contrary to the
limitations on the operation, and
(3) selecting another operation plan when the detail procedure is
contrary
to the limitations on the operation. .Iaddend. .Iadd.62. A process
according to claim 59, further comprising the step of determining
the status of the members arising as a consequence of the predicted
status of the members. .Iaddend. .Iadd.63. A process according to
claim 62, wherein the status of the members arising as a
consequence of the predicted status of the members is obtained by
retrieving data providing a cause and
consequence relationship. .Iaddend. .Iadd.64. A process comprising
the steps of:
(1) storing information forming a knowledge base in memory means of
a computer including
(a) data as facts expressed to be at least one identifier as a
state of an object and corresponding values,
(b) rules including IF parts and corresponding THEN parts with at
least one value for an identifier;
(2) storing a processing program in memory means of the computer,
the processing program enabling interpretation of the knowledge
base for guidance by
(a) searching the knowledge base for comparing facts and rules,
(b) comparing facts with one of IF parts or THEN parts of the rules
to obtain at least one of an IF part or THEN part as a result of
the comparison, and
(c) terminating the search of the knowledge base, and outputting a
result of carrying out the processing program; and
(3) running the processing program for interpretation of the
knowledge base
for guidance. .Iaddend. .Iadd.65. A process according to claim 64,
further comprising the step of selecting an operation plan
including the steps of:
(1) predicting the status of the plant members when the selected
operation plan is put into practice for a given period of time,
(2) determining whether or not the selected operation plan should
be selected,
(3) repeatedly carrying out selection of an operation plan in
accordance with the selected operation plan until no operation plan
is selected, and thereafter
(4) selecting an operation plan from among the operation plans
thus
obtained. .Iaddend. .Iadd.66. A process according to claim 64,
further comprising the steps of:
(1) inputting data of the object,
(2) utilizing the actual status of all members of the object
indicating a state of the object as different facts, each having an
identifier portion indicative of the state of the object and a
corresponding value, and
(3) searching the knowledge base to obtain an IF part of a rule in
accordance with a selected fact when utilizing the selected fact as
a THEN part of a rule. .Iaddend. .Iadd.67. A process according to
claim 66 or 65, further comprising the steps of:
(1) obtaining a detail procedure for the selected operation plan,
and
(2) determining whether the detail procedure is contrary to the
limitations on the operation, and
(3) selecting another operation plan when the detail procedure is
contrary to the limitations on the operation. .Iaddend. .Iadd.68. A
process according to claim 65, wherein the step of selecting an
operation plan includes the step of retrieving data indicating the
operation plan corresponding to the predicted status of the
members. .Iaddend. .Iadd.69. A process according to claim 65,
further comprising the step of determining the status of the
members arising as a consequence of the
predicted status of the members. .Iaddend. .Iadd.70. A process
according to claim 69, wherein the status of the members arising as
a consequence of the predicted status of the members is obtained by
retrieving data
providing a cause and consequence relationship. .Iaddend. .Iadd.71.
A method comprising the steps of:
(1) storing information including rules relating to status of a
system in a memory of a computer, each of the rules having a cause
portion and a corresponding consequence portion,
(2) inputting data of the status of the system,
(3) making interferences based upon the inputted data in accordance
with rules stored in the memory,
(4) predicting time-variant changes in the status of the system by
utilizing the inputted data in accordance with the interferences
made, and
(5) terminating the making of interferences in accordance with the
predicted changes of the status of the system. .Iaddend.
Description
BACKGROUND OF THE INVENTION
This invention relates to a method .[.of.]. .Iadd.and apparatus for
guidance such as .Iaddend.operating power plants, and particularly
to that by which a pertinent guide for operation can be provided to
cope with an abnormality of the plants.
A method to utilize Cause-Consequence Tree (hereinafter referred to
as "CCT") has been proposed hitherto for providing a guide for
operation at the time of a plant abnormality.
CCT is a process of putting the relation of cause and effect of a
phenomenon taking place at a plant on the tree and is powerful to
function when utilized for a guidance implementation of operation
at the time of a plant abnormality. However, a huge quantity of CCT
will have to be prepared to multiply the phenomenon with which the
operation guide apparatus for a plant utilizing CCT is capable of
coping, thus involving a difficulty for implementation and
maintenance.
Then, a technique of knowledge engineering which is utilized for a
medical consultation system will be taken up as the technique for
implementation of a guidance system utilizing a small-scale data
base effectively.
SUMMARY OF THE INVENTION
An .Iadd.object of this invention is to provide a method and
apparatus for guidance of an operation. Another .Iaddend.object of
this invention is to obtain a cause of an abnormality arising at a
plant with precision.
Another object of this invention is to obtain an optimal and secure
operation necessary to cope with an abnormality arising at a
plant.
Further object of this invention is to minimize capacity of a data
base.
A feature of this invention is to .Iadd.provide a method and
apparatus to .Iaddend.repeat a processing comprising a step to
decide an existence of an actual plant state member in a forecasted
plant state member and also to estimate a cause of bringing about
the state member, when the latter member is not present in the
former member, by inputting the forecasted plant state member until
all the actual plant state members come to exist in the forecasted
plant state member, and a step to forecast all the plant state
members to arise after passing a given period of time according to
the cause so estimated.
FIG. 1 is a system diagram of an apparatus for putting a plant
operating method into practice which is given in one preferred
embodiment of this invention to apply on a boiling water reactor
plate;
FIG. 2 is an explanatory drawing representing an example of the
contents of a cause-consequence data base shown in FIG. 1;
FIG. 3 is an explanatory drawing representing an example of the
contents of a transition forecast data base shown in FIG. 1;
FIG. 4 is an explanatory drawing representing an example of the
contents of an operation data base shown in FIG. 1;
FIG. 5 is an explanatory drawing representing an example of the
contents of a particularization data base shown in FIG. 1;
FIG. 6 is an explanatory drawing representing an example of the
contents of a case data base shown in FIG. 1;
FIG. 7 and FIG. 8 are flowcharts of a processing program shown in
FIG. 1;
FIG. 9 is a block diagram of a data conversion division shown in
FIG. 7;
FIG. 10 is a block diagram of a state grasp division shown in FIG.
7;
FIG. 11 is a block diagram of a cause enumeration division shown in
FIG. 7;
FIG. 12 is a block diagram of a forecast division shown in FIG.
7;
FIG. 13 is a block diagram of a non-contradiction confirmation
division shown in FIG. 7;
FIG. 14 is a block diagram of a decision division shown in FIG.
7;
FIG. 15 is a block diagram of an operation enumeration division
shown in FIG. 8;
FIG. 16 is a block diagram of a determination division shown in
FIG. 8;
FIG. 17 is a block diagram of a particularization division shown in
FIG. 8;
FIG. 18 is a block diagram of an analogous case retrieval division
shown in FIG. 8;
FIG. 19 is a block diagram of a guidance implementation division in
FIG. 8;
FIG. 20 is an explanatory drawing of a plant state signal outputted
from the data conversion division;
FIG. 21 is an explanatory drawing of a plant state signal outputted
from the state grasp division;
FIG. 22A and FIG. 22B are explanatory drawings of a plant state
signal outputted from the state grasp division in the cause
decision division;
FIG. 23A and FIG. 23B are explanatory drawings of a plant state
signal outputted from the forecast division in the cause decision
division;
FIG. 24A and FIG. 24B are explanatory drawings of a plant state
signal outputted from the cause enumeration division and the state
grasp division of the cause decision division called
recursively;
FIG. 25 is an explanatory drawing of a plant state signal outputted
from the state grasp division of the optimal operation
determination division;
FIG. 26A and FIG. 26B, FIG. 27A and FIG. 27B are explanatory
drawings of a plant state signal outputted from the forecast
division and the state grasp division of the optimal operation
determination division called recursively.
A plant operating method which is given in one preferred embodiment
of this invention to apply on a boiling water reactor plant will
now be described with reference to FIG. 1.
Steam generated at a core 2 in a reactor pressure vessel 1 is sent
to a turbine 6 by way of a main steam pipe 13 and then condensed in
a condenser 7 to water. The water is supplied into the reactor
pressure vessel 1 as a cooling water by way of a feed-water piping
14. The feed-water piping 14 connects a condensate pump 8, a
desalter 9, feed-water pumps 10A, 10B, 11A and 11B and a feed-water
heater 12 from the upstream side in that order. The feed-water
pumps 10A, 10B, 11A and 11B are of motor-driven type. The
feed-water pumps 11A and 11B are driven temporarily for start-up
and shutdown of a reactor but left in stanby for backup of the
feed-water pumps 10A and 10B during a normal operation of the
reactor. The feed-water pumps 10A and 10B are driven all the time
during operation of the reactor. The cooling water coming into the
reactor pressure vessel 1 is sent to the core 2 by way of a jet
pump 3 by a recirculating pump 4 which is provided on a
recirculating system piping 5.
A water gauge 15 detects a water level (reactor level) 17 in the
reactor pressure vessel 1. A flow meter 16 detects a discharge
flowing in the jet pump 3. The sum of all discharges flowing in the
jet pump 3 will indicate a quantity of the cooling water flowing in
the core 2. The process amount including the reactor level 17 and
the jet pump discharge which are measured on various detectors is
inputted to a central processor 18B of an electronic computer 18 by
way of a process input/output unit 18A of the electronic computer
18. The electronic computer 18 has a memory (internal memory and
external memory) 18C, besides. A consequence processed on the
central processor 18B is displayed on a Braun tube (or CRT) 21
provided on a control panel 20.
The present embodiment comprises obtaining an operation guide for
the above reactor plant abnormality through utilizing a technique
of knowledge engineering, carrying out an operation at the time of
abnormality occurrence according to the guidance, thereby coping
with an abnormal state of the reactor plant. Such operating method
will be described as follows. The memory 18C of the electronic
computer 18 stores a cause-consequence data base 22, a transition
forecast data base 23, an operation data base 24, a detail data
base 25, a case data base 26 and a processing program 27.
The cause-consequence data base 22 is that in which the relation of
cause and .[.effect.]. .Iadd.consequence .Iaddend.is recorded which
comprises combining a cause .Iadd.or a premise .Iaddend.and a
consequence .Iadd.or a conclusion .Iaddend.to be determined
directly related to the cause .Iadd.as a rule.Iaddend.. This is a
data storing area which corresponds to that of the general "rule"
as termed by people who research knowledge engineering .Iadd.and
which may be considered as a knowledge base storing area.Iaddend..
An example of the cause-consequence data base 22 in a boiling water
reactor plant is shown in FIG. 2.
The transition forecast data base 23 is a data base for storing
information to build up a data of the cause-consequence data base
22 in accordance with the lapse of time. Stored herein are
information on the operating state of each equipment of the plant
and the state of each process amount and a technique to obtain, for
the process amount for which a value representing the state has
been obtained, a time to change the value and a value after a
certain time passes. An example of the transition forecast data
base 23 in a boiling water reactor plant is shown in FIG. 3.
FIG. 4 represents an example of the operation data base 24 in a
boiling water reactor plant. The operation data base 24 is a data
base for adding a combination of a condition division and an
operation plan with a combination of the state of each process
amount and the operating state of each equipment of the plant as
the condition division and an operation then conceivable as the
operation plan.
The detail data base 25 is a data base for recording a detail
operating method and operating limit of each equipment of the
plant.
The case data base 26 is a data base for enclosing a consequence of
prior analysis and a record at the time of past operation.
The detail data base 25 and the case data base 26 in a boiling
water reactor plant are shown in FIG. 5 and FIG. 6,
respectively.
An example of the processing program 27 will be described with
reference to FIG. 7 and FIG. 8. The processing program 27 consists
of an abnormality detector portion 28, a data translator portion
30, a status recognizer portion 31, a cause decision division 32,
an optimal operation determination division 38, a detail searcher
portion 42, an example searcher portion 43 and a guidance
implementation portion 44. The cause decision division 32 has a
cause lister portion 33, a status recognizer portion 31, a
predictor portion 34, a checker portion 35, a recursion controller
portion 36 and a decider portion 37 of the cause decision division
32. Further, the optimal operation determination division 38 has
countermeasure lister portion 39, a predictor portion 34, a status
recognizer portion 31, a recursion controller portion 40 and a
selector portion 41 of the optimal operation determination division
38.
The data translator portion 30 inputs a plant data which comes in a
measured process amount, unifies values of each plant data through
a logical decision like majority decision, obtains a member state
or status (an item to indicate one state of the plant) through
combining an identifier for the plant data and a consequence
transformed into a special value in an apparatus to obtain a
guidance for plant operation which indicates a value of the plant
data in the processing given below (hereinafter referred to as
"operation guide apparatus"), and then outputs these member states
in a plant state signal. A flowchart of the data translation
portion 30 is shown in FIG. 9.
The status recognizer portion 31 compares each "cause" enclosed in
the cause-consequence data base 22 with the inputted plant state
signal and selects a "consequence" to come out according to the
"cause" corresponding to the plant state signal. Then, the selected
consequence is added to the inputted plant state signal as a new
member state. A flowchart for the status recognizer portion 31 is
shown in FIG. 10.
The cause lister portion 33 obtains a member state capable of
causing each member state of the inputted plant state signal or a
combination thereof through retrieving the "consequence" enclosed
in the cause-consequence data base 22, thus outputting a retrieved
.[."consequence".]. .Iadd."cause".Iaddend.. The flowchart is shown
in FIG. 11.
The predictor portion 34 inputs the plant state signal and obtains
the time until values of each member state of the inputted plant
state signal change to those of the next level through executing a
calculating technique (program) stored in the prediction data base
23. Next, it selects the shortest time of those obtained as above
and obtains the value of each member state after passing the
shortest time also through executing the calculating technique
stored in the prediction data base 23. Each member state is then
unified and outputted as a plant state signal for the next step. A
flowchart of the precitor portion 34 is shown in FIG. 12.
The checker portion 35 inputs a reference plant state signal and a
single or plural plant state signal for which non-contradiction is
confirmed and outputs a plant state signal not included in the
original plant state signal and not including a member state taken
in by the data translator portion 30. FIG. 13 shows a flowchart of
the non-contradiction confirmation division 35.
The decider portion 37 inputs a plurality of plant state signals
and outputs a plant state signal including each member state most
approximate to each member state constituting the plant state
signal inputted to the cause decision division 32. FIG. 14 shows
the contents.
The countermeasure lister portion 39 inputs a plant state signal
and lists to output operation plans then conceivable by retrieving
the condition division of the countermeasure data base 24. A
flowchart of the countermeasure 39 is shown in FIG. 15.
The selector portion 41 inputs a plurality of plant state signals,
as hsown in FIG. 16, and outputs the plant state signal most
approximate to the operation object then prevailing.
The cause decision division 32 inputs a plant state signal at the
time of a plant abnormality, actuates the cause lister portion 33,
the status recognizer protion 31, the prediction portion 34, the
checker portion 35, the recursion controller portion 36 and the
decider portion 37 to decide a cause of the plant abnormality, and
then outputs the plant state signal to which the cause is added.
The plant state signal outputted from the cause decision division
32, actuates the countermeasure lister portion 39, the predictor
portion 34, the status recognizer portion the recursion controller
portion 40 and the selector portion 41 to determine an optimal
operating method, and outputs the plant state signal to which a
consequence obtained through executing the operation is added.
The detail searcher portion 42 inputs the plant state signal
outputted from the optimal operation determination division 38 and
retrieves what signifies an operation of the equipment of the plant
according to each member state of the plant state signal. And after
ensuring that the retrieved operation satisfies an operation limit
of the detail data base 25, it adds a detail operation procedure to
the plant state signal. Where the retrieved operation does not meet
the operation limit of the detail data base 25, it reruns the
optimal operational determination division 38. A flowchart of the
detail searcher portion 42 is shown in FIG. 17.
The example searcher portion 43 inputs the plant state signal
outputted from the detail searcher portion 42, retrieves a cause
and a keyword of the case data base 26 and adds that in which the
cause coincides or the keyword coincides with a member state of the
plant state signal at a constant rate or over to the plant state
signal as an analogous case.
The guidance implementation portion 44 inputs the plant state
signal outputted for the example searcher portion 43 and changes
the format to output it to CRT 21.
An operating method of a boiling water reactor plant on an
apparatus having the above-mentioned features will be described as
follows.
While such a phenomenon will not be conceivable actually, the
phenomenon wherein a shaft of the recirculating pump 4 to feed a
cooling water to the core 2 happens to adhere during operation of
the boiling water reactor plant is premised for description. When
the shaft is adherent as mentioned, the quantity of a cooling water
flowing in the core 2 decreases and a void in the core 2 increases.
The increase in void may lead to an ascent of the reactor level 17.
Actually, a phenomenon of the shaft adherence and the void increase
is not apparent but a process amount of the measured reactor level
and the jet pump discharge is only known. The reactor level 17
normally comes at a level L4. When the reactor level 17 reaches a
level L8, the reactor is shut down urgently (scram). When the
reactor level 17 reaches a level L7 immediately before the scram,
an indication is given to that effect on the control panel 20. An
operator is thus acquainted with an ascent of the reactor level. A
plant data representing a process amount of the reactor level 17
and the jet pump discharge is inputted to the central processor 18B
by way of the input/output unit 18A. The inputted plant data is
then subjected to an analog-digital conversion so as to serve well
for a processing in the central processor 18B. Upon inputting the
plant data, the central processor 18B calls the processing program
27 (FIG. 7 and FIG. 8) which is an operation guide apparatus in the
memo 18C and performs a given processing according to the
processing program 27. The abnormality detector portion 28
determines a plant data indicating an abnormal value of those which
are inputted. When the plant data indicating an abnormal value (the
reactor level 17 reaching L7 level in the case of this embodiment)
is present, a command 29 is outputted and contents of the
abnormality are displayed on the control panel 20. When there is
present further such plant data indicating an abnormal value, the
processing after the data translator portion 30 of the processing
program 27 is executed.
One or plural plant data 45 measured at the boiling water reactor
plant is inputted to the data translator portion (FIG. 9) 30. Such
data as will not satisfy a set point (exceeding or coming lower)
are all selected from the plant data 45 and then converted into a
plate state signal 46. The data translator portion 30 outputs the
plant state signal 46 shown in FIG. 20.
In the boiling water reactor plant, a plural detectors are provided
for an important process amount like reactor level. Therefore, it
must be ensured that the measured results are coincident with each
other. If not, then an erroneous value measured on the detector
which is so given through a majority decision is prevented from
being inputted to the operation guide apparatus.
In FIG. 21, contents are given in ordinary characters, however,
EBCDIC character code or integral number can be used
practically.
The plant state signal 46 which is an output of the data translator
portion 30 is inputted to the status recognizer portion (FIG. 10)
31, which portions supplements information, if any, which is
missing with the plant state signal 46 shown in FIG. 20. Namely,
the cause division of the cause-consequence data base 22 shown in
FIG. 2 is retrieved according to each member state of the inputted
plant state signal 46. Next, a decision is made on the retrieved
result, and if "YES", the retrieved result is added to the plant
state signal 46. After that, the cause division of the
cause-consequence data base 22 is again retrieved. A decision is
made on the retrieved result, and if "NO", then a plant state
signal 47 to which the above-mentioned retrieved result is added is
outputted. There is nothing to add in this embodiment, and the
plant state signal 47 similar to that of FIG. 20 which is shown in
FIG. 21 is outputted. In the embodiment, input and output of the
status recognizer portion 31 are identical.
Since the time of occurrence of the abnormality is assumed for
operation of the embodiment, a processing of the cause decision
division 32 is executed by inputting the plant state signal 47.
The plant state signal 47 is inputted first to the cause lister
portion 33 in the cause decision division 32. With each member
state of the plant state signal 47 as a "consequence", the cause
lister portion 33 retrieves the member state of the plant state
signal 47 from a consequence division of the cause-consequence data
base 22 (FIG. 2) and adds an item of the cause division coping with
the member state to the plant state signal 47. Namely, the member
state of the plant state signal 47 indicates "reactor level=L7" and
"jet pump discharge decreasing". Where the member state is present
in two or more, the member state higher in importance is subjected
to retrieval. An importance of the member state is specified
beforehand. In this embodiment, "reactor level=L7" is more
important and hence is subjected to retrieval. "Reactor level=L7"
is so given as a consequence of the reactor level having ascended,
therefore "reactor level ascending" is retrieved from the
consequence division of the cause-consequence data base 22, and
"void increase" and "feed water flow increase" which are items of
the cause division corresponding thereto are added to the plant
state signal 47. The consequence division of the cause-consequence
data base 22 is again retrieved. However, nothing will be
retrieved. Next, a decision is made on the retrieved consequence.
Since nothing can be retrieved in this case, the cause lister
portion 33 outputs plant state signals 48A and 48B to which "void
increase" and "feed water low increase" are added as shown in FIG.
22A and FIG. 22B.
The status recognizer portion 31 retrieves items of "void increase"
and "feed water flow increase" from the cause division of the
cause-consequence data base 22 by inputting the plant state signals
48A and 48B and obtains "reactor water level rise" which is an item
of the consequence division corresponding thereto. Then, plant
state signals 49A and 49B with the above added thereto are
outputted. The plant state signals 49A and 49B are inputted to the
predictor portion 34 (FIG. 12).
A transition of the plant state when the void increases and the
feed water flow increases from a combination of "cause" and
"consequence" enclosed in the cause-consequence data base 22 can be
forecasted by using the predictor portion 34. The predictor portion
34 retrieves a member state in the plant state signals 49A and 49B
for which a change time is not calculated and calculates the time
in which each retrieved member state changes until there is no
member state to be retrieved. The time in which the retrieved
member state changes refers to a time required for the member state
to change from the current level to the next level (the next level
being L7 to the current level L6 in the reactor level). Next,
whether or not the change time thus obtained is minimum will be
decided. A change time for "reactor water level increase" to each
of "void increase" and "feed water flow increase" of the plant
state signals 49A and 49B is obtained according to the calculating
method (time calculating method) shown in the predictor data base
23 of FIG. 3. Then, each member state after the minimum change time
thus obtained passes is calculated according to a technique (state
calculating method) of the predictor data base 23. The predictor
portion 34 outputs plant state signals 50A, 50B with a new plant
state signal added which is shown in FIG. 23A and FIG. 23B. A
change of the phenomenon arising according to "cause" specified by
the cause lister portion 33 (or "consequence" retrieved by the
status recognizer portion 31 of the cause decision division 32),
which will be brought as time passes can be obtained by the
predictor portion 34. A decision on whether or not the "cause"
estimated by the cause lister 33 is a true cause will thus be
facilitated, even if an abnormality occurs with a dynamic process
amount of the boiling water reactor plant. In other words, the true
cause which brings a plant data indicating the abnormality measured
actually at the boiling water reactor can be obtained easily
thereby.
The checker portion 35 shown in FIG. 13 which has inputted the
plant state signals 50A and 50B ensures that the plant state signal
produced in consequence does not include a member state which is
not present in the plant state actually produced and for which the
cause is not estimated by the cause lister portion 33 itself. The
confirmed plant state signal is outputted as it is, however, that
of having produced a member state which is not present in the
actual plant state but taken in by the data translator portion 30
as a consequence is regarded improper as a cause and hence is not
outputted. In this embodiment, the state signals 50A and 50B of
FIG. 23A and FIG. 23B are not contradictory and outputted as they
are from the non-contradiction checker portion 35.
The plant state signals 50A, 50B outputted from the checker portion
35 are inputted to the recursion controller portion 36. The
recursion controller portion 36 compares the plant state signals
50A and 50B which are outputs of the checker portion 35 with the
plant state signal 47 outputted to the cause decision division 32.
Where either one member state of the plant state signals 50A and
50B coincides with the plant state signal 47, the recursion
controller portion 36 will not function. In this case, the plant
state signals 50A and 50B are transferred to the decider portion
37. In this embodiment, a member state "jet pump flow decrease" is
included in the plant state signal 47 but not included in both the
plant state signals 50A and 50B. The recursion controller portion
36 therefore calls recursively the cause decision division 32 for
which the plant state signals 50A and 50B work as inputs. Namely,
the processing from the cause lister portion 33 to the checker
portion 35 is rerun. The plant state signals 50A and 50B are
inputted to the cause lister portion 33. The cause lister portion
33 retrieves the consequence division of the cause-consequence data
base 22 with the member states "void increase" and "feed water flow
increase" of the plant state signals 50A and 50B as "consequence",
thereby obtaining "cause" corresponding thereto. Seizure of primary
loop recirculation pump" indicated by 51A in FIG. 24A is retrieved
for the former; "feed water control system failure" indicated by
51B in FIG. 24B is retrieved for the latter. Plant state signals
51A and 51B with these member states added to the plant state
signals 50A and 50B are outputted from the cause lister portion 33.
The The status recognizer portion 31 retrieves all "consequences"
coming from the "cause" of member states of the plant state signals
51A and 51B from the cause-consequence data base 22. "Jet pump flow
decrease" is retrieved for "seizure of primary loop recirculation
pump" of the plant state signal 51A in addition to "void increase",
and "flow mismatch" is retrieved for "feed water control system
failure" of the plant state signal 51B in addition to "feed water
flow increase". Each plant state signal 52A and 52B (FIG. 24A and
FIG. 24B) to which these member states are added are outputted from
the status recognizer portion 31 and inputted to the predictor
portion 34. No change will be brought on the plant state signal
from forecasting the transition of the plant state signals 52A and
52B as mentioned by the predictor portion 34, and hence they are
inputting straight to the checker portion 35. The are also decided
as not contradictory here and outputted straight accordingly.
The plant state signals 52A and 52B outputted from the checker
portion 35 are inputted to the recursion controller portion 36. As
described hereinabove, the recursion controller portion 36 compares
the plant state signal 47 with the plant state signals 52A and 52B.
The two member states reactor level L7" and "jet pump flow
decrease" of the plant state signal 47 are also present in the
plant state signal 52A. The recursion controller portion 36
therefore does not carry out a recursive call of the cause decision
division 32 and outputs the plant state signals 52A and 52B to the
decider portion 37.
The decider portion 37 compares the plant state signals 52A and 52B
shown in FIG. 24A and FIG. 24B respectively with the plant state
signal 47 of FIG. 21 which indicates an actual plant state of the
boiling water reactor plant.
Where "seizure of primary loop recirculation pump" is the cause,
the plant state signal 52A coincides with the plant state signal
47. However, where "feed water control system failure" is the
cause, the plant state signal 52B does not coincide with the plant
state signal 47. Therefore, "seizure of primary loop recirculation
pump" is decided as the cause, and the plant state signal 52A shown
in FIG. 24A is outputted as a plant state signal 53 which is an
output of the cause decision division 32. The processing on the
cause decision division 32 is thus closed.
Since there exists the recursion controller portion 36, it can
easily be decided whether or not the plant state resulting from the
"cause" estimated according to this embodiment will be identified
with a plant state indicating abnormality occurring at the boiling
water reactor plant. Therefore, a true "cause" for the plant state
indicating abnormality can be obtained simply and precisely.
A feature to decide whether or not a recursive call will have to be
carried out through comparing a member state of the first plant
state signal inputted to the cause decision division 32 with a
member state of the second plant state signal outputted from the
checker portion 35 can be placed on the front stage of the
recursion controller portion 36 separately from the recursion
controller portion 36. In case the member state of the second plant
state signal coincides with a part of the member state of the first
plant state signal and a new cause is not retrieved at the cause
lister portion 22 after recursive call, it is taken that an
abnormal phenomenon due to a different cause has occurred in two or
more (multiple phenomenon). In such case, a cause to produce the
member state of the first plant state signal after the member state
of the second plant state signal is eliminated from that of the
first plant state signal is obtained at the cause decision division
32 similarly as mentioned hereinabove.
The plant state signal 53 (the plant state signal 52A essentially
this time) which is an output of the decider portion 37 of the
cause decision division 32 is inputted to the countermeasure lister
portion 39 of the optimal operation determination division 38. The
countermeasure lister portion 39 retrieves the condition division
of the countermeasure data base 24 for each member state of the
plant state signal 52A and obtains an operation plane corresponding
to the item of the condition division. In this embodiment, the
corresponding item is not present in the condition division of the
countermeasure data base 24, as "reactor level L7". Therefore,
there is no concrete operation plan in this case, and a plant state
signal 54 with the operation plan "nothing operated" added to the
plant state signal 53 is outputted from the countermeasure lister
portion 39.
Next, the predictor portion 34 will function from inputting the
plant state signal 54. The predictor portion 34 outputs a plant
state signal 55 to which the change time of each member state of
the plant state signal 54 and each member state after the minimum
change time passes are added. Concretely, a state changing at the
minimum change time is the reactor level, and a member state after
passing the minimum time is the "reactor water level rise, L8". The
plant state signal 55 to which the member state is added is
outputted from the predictor portion 34.
The plant state signal 55 is inputted to the status recognition
portion 31. The status recognition portion 31 retrieves a
consequence "turbine trip" to the member state "reactor level rise,
L8" which is added newly according to the cause-consequence data
base 22. The state grasp division 31 further retrieves consequences
"scram: switch electric bus and "reactor pressure rise" to the
cause of retrieved member state "turbine trip". A plant state
signal 56 (FIG. 25) to which these new member states are added is
the output of the status recognition portion 31.
The plant state signal 56 is inputted to the recursion controller
portion 40. The portion 40 has a means to compare the plant state
signal inputted to the countermeasure lister portion 39 with the
plant state signal outputted therefrom, thereby deciding whether or
not a new operation plan is added to the latter signal. Upon
deciding that a new operation plan has been added, the recursion
controller portion calls the optimal operation determination
division 38 recursively, however, if the decision comes contrary
thereto, then the recursive call will not be carried out. The
operation plan "no operation carried out" is given in this
embodiment, therefore a recursive call is made to the optimal
operation determination division 38, and a processing is again
effected on the countermeasure lister portion 39, the predictor
portion 34 and the status recognition portion 31, each. The plant
state signal 56 which is an output of the status recognition
portion 31 is inputted to the countermeasure lister portion 39.
The countermeasure lister portion 39 inputs the plant state signal
56 and retrieves an operation plan to cope with the member state of
this signal from the countermeasure data base 24. In this
embodiment, an operation "motor driven feed water pump trip"
corresponding to "reactor level rise, L8" is retrieved, and further
"no operation carried out" is enumerated as an operation plan.
Plant state signals to which these operation plans are added, i.e.
plant state signals 57A and 57B shown in FIG. 26A and FIG. 26B
respectively are inputted to the predictor portion 34. A transition
of the plant state when each operation is carried out is forecasted
by the predictor portion 34 as mentioned above. Namely,
consequences of "reactor pressure rise, high" and "reactor level
suddenly decreasing, L4" will be forecasted after the minimum
change time passes further from the minimum change time obtained
through the previous processing of the predictor portion 34 by
executing "motor driven feed water pump trip" of the plant state
signal 57A. "Reactor pressure rise, high" and "reactor water level
fall, L6" will also be forecasted in the case of "no operation
carried out". Plant state signals 58A and 58B to which these member
states are added are inputted to the status recognition portion 31
from the predictor portion 34.
The status recognition portion 31 retrieves a "consequence"
corresponding to each member state from the cause-consequence data
base 22. Namely, for the plant state signal 58A having an operation
plan "motor driven feed water pump trip", a consequence "bypass
valve open" to the cause "reactor pressure high", a consequence
"reactor water level low" to the cause "motor driven feed water
pump trip", a consequence "void decrease" to the cause "scram
(after a given time passes)" (since the minimum change time passed
two times after scram), and a consequence "reactor level fall" to
the cause "void decrease" are retrieved. A plant state signal 59A
of FIG. 26A to which these retrieved consequences are added is
obtained through processing of the status recognition portion 31.
Then, for the plant state signal 58B having an operation plan "no
operation carried out", the consequence "bypass valve open" to the
cause "reactor pressure high", the consequence "void decrease" to
the cause "scram (after a given time passed)", and the consequence
"reactor level fall" to the cause "void decrease" are retrieved. A
plant state signal 59B of FIG. 26B to which these retrieved
consequences are added is obtained through processing of the status
recognition portion 31.
The plant state signals 59A and 59B are inputted to the recursion
controller portion 40. The portion 40 determines whether or not the
optimal operation determination division 38 will have to be called
recursively again according to whether or not the above-mentioned
new operation plan has been added in the processing of the
countermeasure lister portion 39 after recursive call. Since "motor
driven feed water pump trip" is added as a new operation plan this
time, a recursive call of the optimal operation determination
division 38 is rerun. The plant state signals 59A and 59B are
inputted to the countermeasure lister portion 39. However, the
portion 39 does not add an operation plan newly to those of plant
state signals 59A and 59B. Next, the predictor portion 34 inputs
the plant state signals 59A and 59B outputted from the
countermeasure lister portion 39 to forecast a state of each member
state of the plant state signals after the minimum change time
passes. Namely, for the plant state signal 59A having an operation
plan "motor driven feed water pump trip", the reactor level is
changed to "L2" and the reactor pressure is changed to
"descending". Then, for the plant state signal 59B having an
operation plan "no operation carried out", the reactor level is
changed to "L4" and the reactor pressure is changed to
"descending". The predictor portion 34 outputs plant state signals
60A and 60B shown in FIG. 27A and FIG. 27B for each operation
plan.
The plant state signals 60A and 60B are inputted to the recursion
controller portion 40. Since nothing is added newly at the
countermeasure lister portion 39, a recursive call is not carried
out this time. Therefore, the plant state signals 60A and 60B are
inputted to the selected portion 41. The selector portion 41
selects either one of the plant state signals 60A and 60B as an
optimal operation. Namely, "reactor level L2" will result from
carrying out "motor driven feed water pump trip" of the plant state
signal 60A, and "reactor level L4" will result from carrying out
"no operation carried out". "No operation carried out" will be most
pertinent to "seizure of primary loop recirculation pump" this
time, thereby complying with the operation condition of the boiling
water reactor plant, "not to drop reactor level". Therefore, the
plant state signal 60B of FIG. 27B is outputted from the optimal
operation determination division.
The predictor portion 34 is provided at the optimal operation
determination division 38 in this embodiment, therefore when an
operation (retrieved by the countermeasure lister portion 39) to
dissolve the true cause of an abnormal state obtained at the cause
decision division 32 is carried out, the future plant state which
will be so obtained through carrying out the operation can be
forecasted. In other words, the value of a dynamic process amount
in the future can be forecasted. Moreover, the recursion controller
portion 40 is also provided at the optimal operation determination
division 38, therefore an optimal operation can easily be
determined in consideration of the future plant state obtained at
the predictor portion 34. According to this embodiment, an abnormal
state occurring currently at the boiling water reactor plant can be
dissolved easily, and an optimal operation high in safety can be
selected, too. Further in the embodiment available by combining the
cause decision division 32 having the predictor portion 34 and the
recursion controller portion 36 with the optimal operation
determination division 38 having the predictor portion 34 and the
recursion controller portion 40, since the true cause of an
abnormal state can be precisely recognized, the operation obtained
for dissolving the abnormal state might be the best possible one.
Furthermore, a correct cause can be found thereby, therefore
whether or not the plant must be repaired immediately can be
decided efficiently, a spot to repair can be detected beforehand
for necessary repair, if any, and the repair after shutdown of the
plant can be effected within a short period of time.
The plant state signal 60B outputted from the selector portion 41
of the optimal operation determination division 38 is inputted to
the detail searcher portion 42. In this embodiment, the optimal
operation being "no operation carried out", the detail searcher
portion 42 does not function. The detail searcher portion 42
outputs the plant state signal 60B as an output (a plant state
signal 61) of the detail searcher portion 42. For example, in case
"motor driven feed water pump trip" of the plant state signal 60A
is carried out and thus a high pressure injection system is
operated by "reactor level L2" of the plant state signal 60A, a
detail operating method (FIG. 5) of the high pressure injection
system is picked out of the detail data base 25, and a plant state
signal to which the above is added is outputted from the detail
searcher portion 42. And where there is observed an offense from
carrying out a close confirmation on the operation limit, a plant
state signal to which "high pressure injection system cannot be
used" is added is outputted, the output is then transferred to the
optimal operation determination division 38 to rerun the
above-mentioned processing of the optimal operation determination
division 38, and a planning of the operation is again
requested.
The example searcher portion 43 shown in FIG. 18 is actuated from
inputting the plant state signal 61. The example searcher portion
43 retrieves a case analogous to the plant state signal 61 from the
example data base 26 which encloses practical cases as shown in
FIG. 6. In this Embodiment, Case 1 representing "seizure of primary
loop recirculation pump" shown in FIG. 6 is retrieved, and the
contents are added to the plant state signal 61 to develop to a
plant state signal 62, which is outputted from the example searcher
portion 43.
The plant state signal 62 is inputted to the guidance
implementation portion 44 shown in FIG. 19. The guidance
implementation portion 44 outputs the plant state signal 60B shown
in FIG. 27B through converting it into a CRT display output (into a
character code for CRT, for example). In this case, the detail
operating method and the contents of the analogous case are
converted likewise. When converting the plant state signal 60B into
the CRT display output, the guidance implementation portion 44
outputs that for CRT display which indicates the member state
representing a cause and also the member state representing
contents of the operation to cope therewith. For example, words
(cause) and (operation contents) are added after the corresponding
member states as: "seizure of primary loop recirculation pump
(cause)" and "no operation carried out (operation contents)".
An output (plant state signal 60B) of the guidance implementation
portion 44 is transferred to CRT 21 to display thereon. Observing
the operation contents displayed on CRT 21, an operator of the
boiling water reactor plant will operate an object equipment of the
boiling water reactor plant on a control panel accordingly. The
operation contents of this embodiment being "no operation carried
out", a concrete operation will not be made for the boiling water
reactor plant. To say reversely, an operation "no operation carried
out" is performed for the boiling water reactor plant. From
carrying out such operation, a void decreases, the reactor level 17
descends to the level L4, the bypass valve opens automatically, and
thus the reactor pressure drops to a safe state in the boiling
water reactor plant. In case, for example, contents of the plant
state signal 60A are determined to be an optimal operation at the
selector portion 41, the operator will operate the control panel 20
so as to trip a motor driven feed water pump according to the
operation contents displayed on CRT 21. The command is given to
feed water pumps 10A and 10B in operation from the control panel
20. Thus the feed water pumps 10A and 10B come to shutdown.
According to this embodiment, phenomena arising on the plant are
all displayed on CRT when an actual operation is carried out based
on the displayed operation contents, therefore a progress of the
operation can be supervised by confirming the change of an actual
state of the plant. Further, when "cause decision" and "operation
determination" are made by utilizing the cause-consequence data
base 22, a use of the predictor portion 34 may ensure a safe
operation of the boiling water reactor plant (safety being ensured
even from the motor driven feed water pump in trip) against an
abnormal phenomenon which is not conceivable actually like "seizure
of primary loop recirculation pump", thus obtaining an optimal
operation high in safety.
When a guidance for such operating method as is high in safety
against an abnormal phenomenon actually not conceivable for
occurrence will have to be secured on an operation guide apparatus
merely utilizing CCT and a technique of knowledge engineering (not
including the predictor portion and the recursion controller
portion unlike this embodiment), a large-scale data base must be
provided, and labor will be required much for rules for the
guidance implementation and maintenance. A materialization by the
technique may involve difficulty, accordingly. Namely, a method to
utilize CCT requires a vast amount of CCT to difficulty of
implementation and maintenance. And in case the technique of
knowledge engineering is utilized, the data runs vast inevitably in
volume from the requirements that a data representing cause and
consequence must be prepared to cover the case wherein the measured
result to indicate the state of a plant is present plurally and
that a data limited for the range of application must be prepared
in consideration of forecasting a transition (or forecasting a
change in dynamic process amount) of the plate beforehand since it
cannot be forecasted.
According to a technique of this embodiment, operators are kept
from troubles to improve the guidance operation, carry out such
erroneous operation as will reduce an effect of the guidance
operation, or take much time to cope with a load fluctuation when
the plant is activated.
Then, a guidance coping at all times with a renewed situation can
be provided to operators by rerunning the above processing through
a generation of a new alarm, another request by the operator, or an
interruption of an internal clock of the operation guide
apparatus.
When the embodiment is put into practice, the plant data can be
inputted at every member states at the point in time when the
status recognition portion 31 is actuated, and the cause division
of the cause-consequence data base 22 and the plant state signal
are compared with each other.
When a plurality of plant states are obtained on the data
transition portion 30, other technique to select such value as is
not preferable for the plant than a majority decision can be used
for logical decision to narrow down the states to one.
In the cause decision division 32, causes which are not
contradictory each other will be outputted as a plural cause
instead of concluding the cause to one only, and the ensuing
processing can be done for each of them.
In the optimal operation determination division 38, the operation
will not be determined to one only, those which meet the object of
operation will be outputted accordingly, and the operator may have
an option to select suitably from among them. Then, the processing
can be cut to outputting at the point in time when those of meeting
the object of operation are found more than the number set
initially instead of obtaining an optimal operation.
The same one as the cause-consequence data base 22 will be used for
the countermeasure data base 24, which can be identified by marking
up properly for the contents.
The detail portion 42 and the example searcher portion 43 may be
actuated upon indication of the operator. Then, a retrieval of
analogous cases may be processed antecedently, or both may be
processed concurrently, or either one only may be processed.
The predictor portion 34 can interpret an expression on the
prediction data base 23 directly to execution, or it can operate
for calculation by calling a subroutine for which information is
stored on the prediction data base 23. Then, a table search can be
done directly by the forecast feature or by a private subroutine
with a similar technique.
For control of the cause decision division 32 and the optimal
operation determination division 38, a similar processing can be
implemented on a software by means of a stack instead of using a
recursive call feature, or a function to realize the cause decision
division 32 and the optimal operation determination division 38 is
built on a hardware, which will be connected in series therefor by
the number taken enough.
According to the embodiment given in FIG. 1, a large-scale data
base is not required, which may facilitate implementation and
maintenance. Then, since contents of the data base are independent
at every units of configuration as shown in FIG. 2 to FIG. 6, in an
extreme case, if any, where a phenomenon which is not included in
the data base is produced, a trained operator will cope with such
phenomenon by inputting the feature only to the data base, and thus
a function of the operation guide apparatus can be amplified.
This invention can be applied to a pressurized water reactor plant,
a fast breeder reactor plant and a thermal power plant, too.
According to this invention, a true cause of an abnormal state of
the plant can be recognized.
* * * * *