CN103646095A - Common-cause failure reliability judging system and method based on data drive - Google Patents
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Abstract
A common-cause failure reliability judging system and method based on data drive can perform common-cause failure reliability analysis on a large complex system. The system comprises four modules of a data collector, a common-cause failure analyzer, a failure tree model analyzer and a failure tree analyzer, wherein the data collector acquires common-cause failure data and given system information and provides the common-cause failure data and the given system information for other modules; the common-cause failure analyzer determines elementary event grouping according to common-cause failure data and performs common-cause failure analysis on the elementary event groupings; the failure tree model analyzer modifies a failure tree model of a given system according to the elementary event grouping result; and the failure tree analyzer analyzes a given failure tree model. According to the common-cause failure reliability judging system and method, any types of asymmetrical common-cause failure can be analyzed, and reliability of the large complex system can be more accurately analyzed and monitored.
Description
Technical field
The reliability judgement system and method that the present invention relates to a kind of common cause failure based on data-driven, belongs to fail-safe analysis and probabilistic safety analysis field.
Background technology
For example, fail-safe analysis (Reliability Analysis) and probabilistic safety analysis at large-scale complicated system (nuclear power plant system, military hardware system or navigation air line) are worked as (Probabilistic Safety Analysis, PSA) in, existence due to redundant system, common cause failure (Common-Cause Failures, CCF) inevitable, and usually causing the crash rate of whole system greatly to rise, its importance is mathematical.Common cause failure is a kind of of interdependent inefficacy, it is generally acknowledged at present that it is representing because one or more common cause cause a plurality of system units to lose efficacy simultaneously, or a plurality of parts situation about in succession losing efficacy within the short time that cannot alleviate.
Current common cause failure research is very many, but seldom have non-well-balanced common cause failure explored in these researchs, yet due to design concept, manufacture processing, storage transportation installation, operating maintenance, working environment etc. inevitable difference, non-well-balanced property is ubiquitous.In the middle of ratio of precision higher fail-safe analysis and PSA, conventionally require non-well-balanced common cause failure (Asymmetrical Common-Cause Failure) to carry out careful analysis, rather than as present conventional analytic system, make a well-balanced hypothesis, think that their crash rate is duplicate, then they are all placed on to one altogether because of group (Common-Cause Component Group) the inside.
At present the disposal route of non-well-balanced common cause failure is had to three kinds: (1) the first is the modeling method that U.S. core pipe meeting NRC proposed in 1998, but NRC does not provide corresponding Parameter Estimation Method; (2) the second is the difference modeling of Jo proposition in 2005, but the ratio of its error and non-well-balanced common cause failure has relation, has limited to a great extent its degree of accuracy and range of application; (3) the third is the approximate formula method of Kang proposition in 2009, one, because being decomposed into, elementary event all claims part and non-well-balanced part modeling respectively altogether, and suppose that each decomposition unit is well-balanced between dividing, provided BPM(Basic Parameter Model) and AFM(Alpha Factor Model) Parameter Estimation Method of model, yet approximate formula method can not be analyzed the common cause failure of dissimilar redundant component.And these methods are difficult to practice in the middle of reliability judgement system.
Summary of the invention
The technology of the present invention is dealt with problems: overcome the deficiencies in the prior art, a kind of reliability judgement system and method for the common cause failure based on data-driven, can better process the non-well-balanced common cause failure of large-scale complicated system, obtain reliability and security more accurately.
The technology of the present invention solution: the concept of the multiple common cause failure that the present invention proposes: when elementary event is subject to 2 or 2 above common cause failures impacts simultaneously, this event is placed on simultaneously a plurality of altogether because of in the middle of group (by of the same race common because causing the combination of failure event).Non-well-balanced common cause failure through processing because of STRUCTURE DECOMPOSITION method altogether, can adopt various conventional common cause failure models to analyze it, and carry out corresponding parameter conversion, the following content of specific implementation step:
A reliability judgement system for common cause failure based on data-driven, comprising: data collector, analysis of common cause failure device, fault tree models resolver and fault tree analysis device;
Data collector: to giving fixed system, utilize test to obtain the common cause failure data of system redundancy equipment, also can use and the existing common cause failure data of other system like this system class; And obtain by analyst, according to system architecture information, built not containing the system failure tree-model of common cause failure; The system failure tree-model of also storing elementary event reliability model, common cause failure model, analysis of common cause failure result and containing common cause failure; For other module;
Analysis of common cause failure device: according to common cause failure data with not containing the system failure tree-model of common cause failure, adopt altogether because of STRUCTURE DECOMPOSITION method, to system equipment or parts automatic distribution and the combination because organizing altogether, obtain allly altogether because of group, and the grouping situation of common cause failure is verified and adjusted; Selection is to elementary event reliability model corresponding to the parts of fixed system, same altogether because the elementary event of group can only be selected same reliability model; Provide each altogether because of the reliability model of group selection; According to common cause failure data, adopt altogether that elementary event because of the automatically definite non-well-balanced common cause failure of STRUCTURE DECOMPOSITION method relates at it altogether because of the ratio in group, after verifying adjustment, determine again each common cause failure model because organizing altogether, finally calculate the ultimate failure probability of elementary event in each group, and by all result stores to data collector;
Fault tree models resolver: obtain analysis of common cause failure result from data collector, adopt altogether and because of STRUCTURE DECOMPOSITION method, the fault tree models of not considering common cause failure to fixed system is resolved and revised, construct a fault tree models that can reflect common cause failure; Result store is to data collector;
Fault tree analysis device: obtain the fault tree models that can reflect common cause failure from data collector, it is analyzed, obtain the fail-safe analysis result to fixed system; This result informs the common cause failure characteristic of fixed system; And according to real-time system monitoring signal, calculate the real-time reliability result of system, by described feasibility result store to data collector.
Described altogether because STRUCTURE DECOMPOSITION method is achieved as follows:
(1) when an elementary event A who represents certain equipment or parts is subject to affecting of n common cause failure simultaneously, according to test figure, this elementary event is resolved into (n+1) individual elementary event (A
0, A
1, A
2, A
3..., A
n), A wherein
0the representative that A occurs separately, and A
1, A
2, A
3..., A
nbe subordinated to respectively n altogether because of group; And ignore A
1, A
2, A
3..., A
nindependent failure probability, only get its common cause failure probability, in order to represent respectively the contribution of the common cause failure of the A that n causes because of group altogether; After carrying out this decomposition to all elementary events of fixed system, obtain distribution and the combined result because organizing altogether of system;
(2) probability of elementary event A calculates according to following formula: P
t=P
0+ P
1+ P
2+ ...+P
n; Wherein: P
tfor the general probability that A occurs, P
0for A occurs separately, i.e. A
0probability, P
1for A
1under the common cause failure probability of the A that brings because of group altogether, i.e. A
1common cause failure probability, P
2for A
2under the common cause failure probability of the A that brings because of group altogether, i.e. A
2common cause failure probability, P
nfor A
nunder the common cause failure probability of the A that brings because of group altogether, i.e. A
ncommon cause failure probability; According to this formula and each, altogether because organizing corresponding common cause failure model formation, each that determine that the elementary event of non-well-balanced common cause failure relates at it is altogether because of the ratio in group;
(3) because organizing the selected common cause failure model of inner employing, analyze altogether for n, then according to the formula of step (2), calculate the ultimate failure probability of elementary event.
A reliability determination methods for common cause failure based on data-driven, performing step is as follows:
(1) according to common cause failure data with not containing the system failure tree-model of common cause failure, adopt altogether because of STRUCTURE DECOMPOSITION method, to system equipment or parts, altogether because of automatic distribution and the combination of group, obtain allly altogether because of group, and the grouping situation of common cause failure is verified and adjustment; Selection is to elementary event reliability model corresponding to the parts of fixed system, same altogether because the elementary event of group can only be selected same reliability model; And select each altogether because of the common cause failure model of group selection; According to common cause failure data, adopt altogether that elementary event because of the automatically definite non-well-balanced common cause failure of STRUCTURE DECOMPOSITION method relates at it altogether because of the ratio in group, obtain analysis of common cause failure result;
(2) according to analysis of common cause failure result, adopt altogether and because of STRUCTURE DECOMPOSITION method, the fault tree models of not considering common cause failure to fixed system is resolved and revised, construct a fault tree models that can reflect common cause failure;
(3) obtain elementary event reliability model, set up given system failure tree-model, obtain the grouping situation of common cause failure, set up the elementary event group of multiple common cause failure, adopt altogether because of STRUCTURE DECOMPOSITION method, revise elementary event group, obtain reflecting the fault tree models of common cause failure;
(4) from data collector, obtain the fault tree models that can reflect common cause failure, it is analyzed, obtain the fail-safe analysis result to fixed system; This result informs the common cause failure characteristic of fixed system; And according to real-time system monitoring signal, calculate the real-time reliability result of system.
The present invention's advantage is compared with prior art: the concept that the present invention is based on multiple common cause failure, develop the reliability judgement system and method for a kind of " altogether because of STRUCTURE DECOMPOSITION method ", can analyze judgement to general non-well-balanced common cause failure, comprise the non-well-balanced common cause failure that those are comprised of dissimilar parts, and can process various altogether because of model.Can better process to the non-well-balanced common cause failure of large-scale complicated system the reliability of analytic system and security more accurately.
Accompanying drawing explanation
Fig. 1 is system construction drawing of the present invention;
Fig. 2 is the realization flow figure of data collector in Fig. 1;
Fig. 3 is the realization flow figure of analysis of common cause failure device in Fig. 1;
Fig. 4 is the realization flow figure of fault tree models resolver in Fig. 1;
Fig. 5 is the realization flow figure of fault tree analysis device in Fig. 1;
Fig. 6 is that the poisonous substance of No. two reactor shut-off systems of Qinshan San nuclear power plant is opened soon introduction valve schematic diagram and (driven soon introduction valve for 6, injection canal of formation of every two series connection; As long as any channel function in three passages is normal, meet safety requirements, three get one redundant system.Carry out automatic network open source information);
Fig. 7-1-Fig. 7-2nd, the fault tree graph that Fig. 6 system is carried out to fail-safe analysis, Fig. 7-1st wherein, containing the analysis chart of common cause failure; Fig. 7-2nd, is used the analysis chart of " altogether because of STRUCTURE DECOMPOSITION method " of the present invention; In Fig. 7-2, there are 4 altogether because of group: [1I, 2I], [1G, 2G], [1H, 2H], [1I, 1G, 1H];
In the conventional residual heat removal pump system of fortune nuclear reactor, (four get one redundant system in the Tu8Shi U.S..Carry out automatic network open source information);
Fig. 9-1-9-2 carries out the fault tree graph of fail-safe analysis to Fig. 8 system, Fig. 9-1st wherein, and not containing the analysis chart of common cause failure, Fig. 9-2nd, is used the analysis chart of " altogether because of STRUCTURE DECOMPOSITION method " of the present invention; In Fig. 9-2, pump B3 belongs to 2 altogether because of group simultaneously: [B1, B2, B3], [B3, B4].
Embodiment
As shown in Figure 1, System Operation mode of the present invention is as follows:
(1) first adopt data collector: to fixed system, use statistical test to obtain the common cause failure data of system redundancy equipment, also can use and the existing common cause failure data of other system like this system class; And memory system architecture information, systematic analysis border and system failure tree-model;
(2) then adopt analysis of common cause failure device: from data collector, obtain common cause failure data, adopt " altogether because of STRUCTURE DECOMPOSITION method " to data analysis, to obtain the ratio of its common cause failure component combination and various combinations, result store is to data collector;
(3) then adopt fault tree models resolver: the result of obtaining analysis of common cause failure from data collector, adopt " altogether because of STRUCTURE DECOMPOSITION method " to resolving and revise to the fault tree models of not considering common cause failure of fixed system, construct a fault tree models that can reflect common cause failure; Result store is to data collector;
(4) finally adopt fault tree analysis device: from data collector, obtain the fault tree models that can reflect common cause failure, it is analyzed, obtain the fail-safe analysis result to fixed system; This result informs the common cause failure characteristic of fixed system; And according to real-time system monitoring signal, calculate the real-time reliability result of system; Result store is to data collector.
Of the present invention altogether because STRUCTURE DECOMPOSITION method is described in detail as follows:
When an elementary event A who represents certain equipment or parts is subject to affecting of n common cause failure simultaneously, can be according to test figure or experience, artificial this elementary event is resolved into a plurality of elementary event (A
0, A
1, A
2, A
3..., A
n), A wherein
0the representative that A occurs separately, and A
1, A
2, A
3..., A
nbe subordinated to respectively n altogether because of group; Because A
1, A
2, A
3..., A
nnot the event of necessary being, so will ignore its independent failure probability here, and only get its common cause failure probability, in order to represent respectively the contribution of n the A common cause failure causing because of group altogether.
So the probability of elementary event A decomposes following formula:
P
t(general probability that A occurs)=P
0(A occurs separately, i.e. A
0probability)+P
1(A
1under the common cause failure probability of the A that brings because of group altogether, i.e. A
1common cause failure probability)+P
2(A
2under the common cause failure probability of the A that brings because of group altogether, i.e. A
2common cause failure probability)+...+P
n(A
nunder the common cause failure probability of the A that brings because of group altogether, i.e. A
ncommon cause failure probability).
List the P of current general 4 kinds of general common cause failure models below
iand θ
icomputing formula (other model also can similarly draw correlation computations formula, below the parameter estimation of 4 kinds of models, can carry out according to the method for estimation of original model):
For BPM model, have: P
i=Q
t-Q
1, θ so
i=P
i/ P
t=(Q
t-Q
1)/P
t, Q here
1representative is altogether because of the independent failure probability of certain common elementary event in group, Q
trepresentative is altogether because of the general probability of certain common elementary event in group.
For BFM model, have: P
i=Q
m=β
b* Q
t, θ
i=P
i/ P
t=β
b* Q
t/ P
t, Q here
trepresentative is altogether because of the general probability of certain common elementary event in group.
AFM model for staggered experiment, has: P
i=(α
2+ α
3+ ...+α
m) * Q
t, θ
i=P
i/ P
t=(α
2+ α
3+ ...+α
m) * Q
t/ P
t, suppose that i altogether because group has m elementary event here.
For MGLM model, have: P
i=β
m* Q
t, θ
i=P
i/ P
t=β
m* Q
t/ P
t, as for γ, δ, can just can according to the definition of MGLM model.
To use " altogether because of STRUCTURE DECOMPOSITION method " of the present invention to analyze to Fig. 6.
Analysis of common cause failure device, according to the common cause failure data of nuclear power plant's real system, obtains its common cause failure component combination, for example: this system should have 4 altogether because of group: [1I, 2I], [1G, 2G], [1H, 2H], [1I, 1G, 1H].Set up the fault tree models of Fig. 7-2.Then adopt fault tree analysis device to analyze it, obtain the fail-safe analysis result to fixed system; This result can inform the common cause failure characteristic of fixed system.
In Fig. 7-2, circle represents elementary event, and the character in circle " 1I(2I) " the simultaneous common cause failure event of representative " 1I " " 2I ", other character implication is similar.
For ease of contrast, Fig. 7-1 has provided according to traditional analysis method for reliability the fault tree models of Fig. 6 system when not considering common cause failure, and Fig. 7-1 is also analysis starting point of the present invention simultaneously.
Embodiment 2
To use " altogether because of STRUCTURE DECOMPOSITION method " of the present invention to analyze to Fig. 8.
Analysis of common cause failure device, according to the common cause failure data of nuclear power plant's real system, obtains its common cause failure component combination, for example: this system should have 2 altogether because of group: [B1, B2, B3], [B3, B4].Set up the fault tree models of Fig. 9-2.Then adopt fault tree analysis device to analyze it, obtain the fail-safe analysis result to fixed system; This result can inform the common cause failure characteristic of fixed system.
In Fig. 9-2, circle represents elementary event, the simultaneous common cause failure event of the character in circle " B123 " representative " B1 " " B2 " " B3 ", and other character implication is similar.
For ease of contrast, Fig. 9-1 has provided according to traditional analysis method for reliability the fault tree models of Fig. 8 system when not considering common cause failure, and Fig. 9-1 is also analysis starting point of the present invention simultaneously.
The content not being described in detail in instructions of the present invention belongs to the known prior art of professional and technical personnel in the field.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (3)
1. the reliability of the common cause failure based on a data-driven judgement system, is characterized in that comprising: data collector, analysis of common cause failure device, fault tree models resolver and fault tree analysis device;
Data collector: to giving fixed system, utilize test to obtain the common cause failure data of system redundancy equipment, also can use and the existing common cause failure data of other system like this system class; And obtain by analyst, according to system architecture information, built not containing the system failure tree-model of common cause failure; The system failure tree-model of also storing elementary event reliability model, common cause failure model, analysis of common cause failure result and containing common cause failure; For other module;
Analysis of common cause failure device: according to common cause failure data with not containing the system failure tree-model of common cause failure, adopt altogether because of STRUCTURE DECOMPOSITION method, to system equipment or parts automatic distribution and the combination because organizing altogether, obtain allly altogether because of group, and the grouping situation of common cause failure is verified and adjusted; Selection is to elementary event reliability model corresponding to the parts of fixed system, same altogether because the elementary event of group can only be selected same reliability model; Provide each altogether because of the reliability model of group selection; According to common cause failure data, adopt altogether that elementary event because of the automatically definite non-well-balanced common cause failure of STRUCTURE DECOMPOSITION method relates at it altogether because of the ratio in group, after verifying adjustment, determine again each common cause failure model because organizing altogether, finally calculate the ultimate failure probability of elementary event in each group, and by all result stores to data collector;
Fault tree models resolver: obtain analysis of common cause failure result from data collector, adopt altogether and because of STRUCTURE DECOMPOSITION method, the fault tree models of not considering common cause failure to fixed system is resolved and revised, construct a fault tree models that can reflect common cause failure; Result store is to data collector;
Fault tree analysis device: obtain the fault tree models that can reflect common cause failure from data collector, it is analyzed, obtain the fail-safe analysis result to fixed system; This result informs the common cause failure characteristic of fixed system; And according to real-time system monitoring signal, calculate the real-time reliability result of system, by described feasibility result store to data collector.
2. the reliability of a kind of common cause failure based on data-driven according to claim 1 judges system, it is characterized in that: described altogether because STRUCTURE DECOMPOSITION method is achieved as follows:
(1) when an elementary event A who represents certain equipment or parts is subject to affecting of n common cause failure simultaneously, according to test figure, this elementary event is resolved into (n+1) individual elementary event (A
0, A
1, A
2, A
3..., A
n), A wherein
0the representative that A occurs separately, and A
1, A
2, A
3..., A
nbe subordinated to respectively n altogether because of group; And ignore A
1, A
2, A
3..., A
nindependent failure probability, only get its common cause failure probability, in order to represent respectively the contribution of the common cause failure of the A that n causes because of group altogether; After carrying out this decomposition to all elementary events of fixed system, obtain distribution and the combined result because organizing altogether of system;
(2) probability of elementary event A calculates according to following formula: P
t=P
0+ P
1+ P
2+ ...+P
n; Wherein: P
tfor the general probability that A occurs, P
0for A occurs separately, i.e. A
0probability, P
1for A
1under the common cause failure probability of the A that brings because of group altogether, i.e. A
1common cause failure probability, P
2for A
2under the common cause failure probability of the A that brings because of group altogether, i.e. A
2common cause failure probability, P
nfor A
nunder the common cause failure probability of the A that brings because of group altogether, i.e. A
ncommon cause failure probability; According to this formula and each, altogether because organizing corresponding common cause failure model formation, each that determine that the elementary event of non-well-balanced common cause failure relates at it is altogether because of the ratio in group;
(3) because organizing the selected common cause failure model of inner employing, analyze altogether for n, then according to the formula of step (2), calculate the ultimate failure probability of elementary event.
3. a reliability determination methods for the common cause failure based on data-driven, is characterized in that performing step is as follows:
(1) according to common cause failure data with not containing the system failure tree-model of common cause failure, adopt altogether because of STRUCTURE DECOMPOSITION method, to system equipment or parts, altogether because of automatic distribution and the combination of group, obtain allly altogether because of group, and the grouping situation of common cause failure is verified and adjustment; Selection is to elementary event reliability model corresponding to the parts of fixed system, same altogether because the elementary event of group can only be selected same reliability model; And select each altogether because of the common cause failure model of group selection; According to common cause failure data, adopt altogether that elementary event because of the automatically definite non-well-balanced common cause failure of STRUCTURE DECOMPOSITION method relates at it altogether because of the ratio in group, obtain analysis of common cause failure result;
(2) according to analysis of common cause failure result, adopt altogether and because of STRUCTURE DECOMPOSITION method, the fault tree models of not considering common cause failure to fixed system is resolved and revised, construct a fault tree models that can reflect common cause failure;
(3) obtain elementary event reliability model, set up given system failure tree-model, obtain the grouping situation of common cause failure, set up the elementary event group of multiple common cause failure, adopt altogether because of STRUCTURE DECOMPOSITION method, revise elementary event group, obtain reflecting the fault tree models of common cause failure;
(4) from data collector, obtain the fault tree models that can reflect common cause failure, it is analyzed, obtain the fail-safe analysis result to fixed system; This result informs the common cause failure characteristic of fixed system; And according to real-time system monitoring signal, calculate the real-time reliability result of system.
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| CN104460337A (en) * | 2014-10-08 | 2015-03-25 | 机械工业仪器仪表综合技术经济研究所 | Control system common cause failure analysis method based on factor beta correction |
| CN104298825A (en) * | 2014-10-10 | 2015-01-21 | 中国科学院合肥物质科学研究院 | Fault tree collaborative analysis system based on authority management and model decomposition |
| CN104298825B (en) * | 2014-10-10 | 2017-09-26 | 中国科学院合肥物质科学研究院 | A kind of fault tree Cooperative Analysis system based on rights management and model decomposition |
| CN104268432A (en) * | 2014-10-16 | 2015-01-07 | 中国科学院合肥物质科学研究院 | Common cause failure reliability distributing system based on fault tree analysis |
| CN104268432B (en) * | 2014-10-16 | 2017-02-08 | 中国科学院合肥物质科学研究院 | Common cause failure reliability distributing system based on fault tree analysis |
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