CN108229049A - The method that multistate system mission reliability modeling is carried out based on performance model - Google Patents
The method that multistate system mission reliability modeling is carried out based on performance model Download PDFInfo
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Abstract
The present invention provides a kind of method that multistate system mission reliability modeling is carried out based on performance model, includes the following steps：S1, target multistate system design information is collected：S2, target multistate system performance model is established；S3, the failure criterion for determining target multistate system；S4, analysis modeling is carried out to the fault mode of target multistate system；The acquisition of information of S5, target multistate system failure；S6, target multistate system direct fault location and emulation；S7, fail-safe analysis and assessment are carried out to target multistate system task：Target multistate system Mean Time Between Critical Failure MTBCF and Task Reliability RM is calculated using the mission reliability Simulation Evaluation method injected based on timing failure.The present invention carries out the analysis of multistate system mission reliability and assessment by building the failure transitive relation between failure mechanism, key parameter, assembly property, system failure criterion from bottom to top, has better integrality and accuracy.
Description
Technical field
The present invention relates to reliability consideration technical fields, and multistate system is carried out based on performance model more particularly to one kind
The method of mission reliability modeling.
Background technology
When multistate system refers to perform appointed task, there is the system of certain amount performance level.Usually there are following feelings
The system of condition generally can be considered multistate system：1. two condition (work or failure) element of the system of composition is to systematic entirety energy
When having cumulative effect, such as k-out-of-n systems；2. the performance level of system element (fatigue, local fault) or environment at any time
The variation of situation and when degenerating, element fault can lead to the decline that systematic entirety can be horizontal.
Mission reliability refers to the ability that product completes predetermined function in assignment of mission section, characterize product to task into
The requirement of work(.The failure (catastrophe failure) that mlssion success mainly leads to product with product and cannot complete assignment of mission has
It closes.It is Mean Time Between Critical Failure MTBCF and Task Reliability MR that mission reliability, which is analyzed with the major parameter of assessment,
Middle MTBCF measures are the ratio between product task total time and catastrophe failure sum in a series of defined mission profiles；MR
Measure in a series of defined mission profiles, Mission Success performs the ratio between number and task total degree.
It is both at home and abroad at present to the reliable of complication system to the focus of multistate system mission reliability Modeling Method
Property analysis and assessment.Especially in the fields such as weaponry field, computer techno-stress, energy supply, many complication systems
Working condition there is very important multimode characteristic, traditional two-state reliability theory has been difficult to successfully manage.Cause
This, it is a large amount of to come into being for multistate system mission reliability modeling analysis with the modeling method assessed, as Boolean Model expands
It is exhibition method (polymorphic fault tree, polymorphic Bayesian network), Stochastic Process Method (CTM Approach, stochastic Petri net), general
Generating function, Monte Carlo simulation method etc..However, these methods fail to structure failure mechanism, key parameter, component
Failure transitive relation between energy, system failure criterion (performance indicator) from bottom to top.Failure mechanism in Practical Project is in itself
Much also there is multimode characteristic, therefore this transitive relation from bottom to top is built to analysis based on performance model and is assessed more
Status system mission reliability has a very important significance.
By retrieving existing literature data, closed it is not yet found that domestic scholars propose to transmit based on performance model structure failure
System carries out the modeling method of the analysis of multistate system mission reliability and assessment.
Invention content
The defects of in order to overcome the prior art, it is proposed that one kind carries out multistate system mission reliability based on performance model
The method of modeling.
The invention is realized in this way：
The present invention provide it is a kind of based on performance model carry out multistate system mission reliability modeling method, including with
Lower step：
S1, target multistate system design information is collected：The design information includes operation principle, structure composition, operating mode
Information, performance indicator, structural parameters, sample parameter and test data；
S2, target multistate system performance model is established：It includes following sub-step：
1. by system modular；2. according to bottom-up hierarchical modeling principle, first component or equipment are carried out using module
Modeling, verification and encapsulation；3. carrying out system integration modeling, system-level model is built；4. complete system performance model modeling
And verification；
S3, the failure criterion for determining target multistate system：According to the multistate system design information collected in S1, given
The failure criterion gone out includes at least performance indicator and its threshold range：The performance that target multimode performance can be characterized comprehensively refers to
Mark；Performance indicator influences the threshold range that system function is realized with performance；
S4, analysis modeling is carried out to the fault mode of target multistate system：Failure is done to target multistate system first
Pattern, influence and HAZAN FMECA obtain influencing the critical failure pattern of system task reliability, analyze these keys
The affiliated fault category of fault mode and failure mechanism type；
The acquisition of information of S5, target multistate system failure：For the critical failure pattern obtained in S4, believe according to failure
The fault message that breath acquisition methods obtain generally comprises：Failure-rate data, fault state data and Performance Degradation Data；
S6, target multistate system direct fault location and emulation：According to the fault message that S5 is obtained, modeling based on script with
Emulation mechanisms complete direct fault location and emulation, extract multimode fault simulation result；
S7, fail-safe analysis and assessment are carried out to target multistate system task：Appointed using what is injected based on timing failure
Target multistate system Mean Time Between Critical Failure MTBCF is calculated for business Reliablility simulation appraisal procedure and task is reliable
Spend RM；
The mission reliability Simulation Evaluation method based on timing failure injection, it is desirable that meet following hypothesis：Often
The subtask execution time is tm；Influence of the non task time to failure is not considered；It breaks down and repairs and fix immediately as new；It takes out
Sample number is n times.It is sampled using Monte Carlo, the minimum fault time of acquired mutual indepedent critical failure is primary serious
Time between failures TBCFi(1≤i≤N) obtains N number of catastrophe failure interval time data by emulation, and such MTBCF is used
Following formula is calculated：
Meanwhile the Task Reliability MR of multistate system is evaluated, it is calculated using following formula：
Due to having recorded the catastrophe failure interval time TBCF of ith sampling generating system failure in simulation processi(1
≤ i≤N), therefore the number of the subtask can be denoted as this subsystem catastrophe failure interval time divided by each task time most
Big positive integer, i.e.,
Preferably, the system modular described in S2 refers to for system to be separated into the basic module being easily processed,
First component or equipment performance modeling refer to take according to system function logical relation after module imparting parameter
Build first component or equipment performance model.
Preferably, first component described in S2 or equipment performance model are verified, are referred to using being collected into tuple in S1
Part relevant information verifies the model for establishing first component or equipment, and error point is carried out if error is within error threshold
Analysis calculates relative error, if error except error threshold, needs analytical error reason, corresponding correction model is wanted until meeting
It asks；
The member component or equipment performance model are packaged, and are referred to the principle modeled according to hierarchy, will be had verified that
By first component be encapsulated as the simple module for having certain functional interfaces.
Preferably, the detailed process that first component described in S2 or equipment performance model are verified refers to will be obtained
The emulation data of first component or equipment performance model are placed in respective tuple part or device capability information under the same coordinate system, are observed
Whether trend is consistent for the two.
Preferably, the error threshold is 5%；
The source of error includes abstract error, equivalent error, numerical error or environmental error, and the abstract error, which refers to, builds
The necessary deviation assumed between truth done during abstract modeling target mathematical model before mould, the equivalent error refer to for
Facilitate and carry out analysis calculating, improve simulation efficiency, the introduced error of approximate simplified operation, the numerical value are carried out to mathematical model
Error refers to replaces the truncated error of original equation generation and computer storage precision using the discrete equation of different numerical methods
Rounding error caused by deficiency, the environmental error refers to first component or equipment sample or test data corresponds to experimental enviroment and emulation
Error between environment；
It needs to carry out abstract mathematical model appropriate amendment according to actual conditions if being main error if abstract error；If
Equivalent error is main error, then needs to re-start model simplification；If numerical error is main error, innovatory algorithm is considered
Or improve memory precision；If environmental error is main cause, need to consider to reset simulated conditions.
Preferably, the system integration modeling described in S2 is modeled including but not limited to multi-field hybrid modeling, hybrid system
And the modeling of redundant system；
The system performance model modeling refers to that logically relationship structure is by first component model or subsystem model
System performance model；
The system performance model verification, refers to the phase for obtaining obtained system performance model emulation data with S1
System performance information is answered to be placed under the same coordinate system, observation both whether trend is consistent, if error is within error threshold into
Row error analysis calculates relative error, if error is allowing except threshold range, analytical error reason, corresponding correction model is straight
To meeting performance requirement.
Preferably, in system performance model verification, the error threshold is 10%.
Preferably, the fault modeling refers to that the type for fault mode determines suitable modeling pattern：To discrete two
Status fault, using newly-increased redundant component method and change parametric method modeling；It can be soft by using modeling to discrete multimode failure
Part modeling language creates malfunctioning module and change parametric method modeling；To continuous multimode failure can by continuously change parametric method with
Sequential sampling assignment method models.
Preferably, the modeling and simulation mechanism based on script refers to for the corresponding emulation script of fault model definition in S6
Script。
Compared with prior art, the invention has the advantages that：
The present invention is by building between failure mechanism, key parameter, assembly property, system failure criterion (performance indicator) certainly
Failure transitive relation on down carries out multistate system mission reliability and analyzes and assess, with better integrality and accurately
Property.
The present invention is applied widely, can analyze discrete multistate system with continuous multistate system, by external environment and mould
Type itself restricts smaller advantage, it is contemplated that dynamic, correlation, coupling between the characteristic of element and model in itself, i.e. member/component
The features such as conjunction property, make emulation more targeted, can effectively improve the accuracy and meter of the analysis of multistate system mission reliability
Calculate efficiency.
Description of the drawings
Fig. 1 is the flow chart that multistate system mission reliability modeling method is carried out based on performance model of the present invention；
Fig. 2 is the system modular flow diagram of the present invention；
Fig. 3 is the discrete state failure information obtaining method schematic diagram of the present invention；
Fig. 4 is the continuous state failure information obtaining method schematic diagram of the present invention；
Fig. 5 is the mission reliability Simulation Evaluation method schematic diagram based on timing failure injection of the present invention；
Fig. 6 is that the AC electrical fuel pump overall performance in the embodiment of the present invention verifies model schematic；
Fig. 7 is the AC electrical fuel pump starting process performance verification schematic diagram in the embodiment of the present invention；
Fig. 8 is the AC electrical fuel pump steady-state process performance verification in the embodiment of the present invention；
Fig. 9 is that the redundant component in the embodiment of the present invention models schematic diagram；
Figure 10 is the change parameter model schematic diagram in the embodiment of the present invention；
The Modelica that Figure 11 is the present invention models schematic diagram；
The supply frequency abnormal failure that Figure 12 is the present invention injects schematic diagram；
The fuel pump that Figure 13 a are the present invention exports the analogous diagram that fluid flow changes with supply frequency；
Figure 13 b are the analogous diagram that the fuel pump pump intake pressure of the present invention changes with supply frequency；
Figure 14 is the coil degradation failure injection script schematic diagram of the present invention；
Figure 15 a are that the coil aging of the present invention causes the probability density function and its fitting function of system failure time；
Figure 15 b are that the coil aging of the present invention causes the cumulative distribution function and its fitting function of system failure time.
Specific embodiment
Below with reference to the attached drawing exemplary embodiment that the present invention will be described in detail, feature and aspect.It is identical attached in attached drawing
Icon note represents functionally the same or similar element.Although the various aspects of embodiment are shown in the drawings, unless special
It does not point out, it is not necessary to attached drawing drawn to scale.
The present invention provide it is a kind of based on performance model carry out multistate system mission reliability modeling method, including with
Lower step：
S1, target multistate system design information is collected：The design information includes operation principle, structure composition, operating mode
Information, performance indicator, structural parameters, sample parameter and test data.
S2, target multistate system performance model is established：It includes following sub-step：
1. by system modular；2. according to bottom-up hierarchical modeling principle, first component or equipment are carried out using module
Modeling, verification and encapsulation；3. carrying out system integration modeling, system-level model is built；4. complete system performance model modeling
And verification.
System modular described in S2 refers to for system to be separated into the basic module being easily processed,
First component or equipment performance modeling, refer to by module assign parameter (such as resistive element is given resistance value,
Mass block gives quality etc.) after according to system function logical relation, (system function logical relation, such as connects resistive element and its
The element connection of mouth relationship) build first component or equipment performance model.
First component described in S2 or the verification of equipment performance model refer to using being collected into first device related information pair in S1
The model for establishing first component or equipment is verified, if error except threshold value, needs analytical error reason, accordingly corrects mould
Type is until meet the requirements.
Verification：By obtained performance model emulation data and respective tuple part or device capability information (test data, sample
Notebook data) it is placed under the same coordinate system, whether trend is consistent for both observations, and error analysis is carried out if consistent, calculates relatively accidentally
Difference.To the first component or equipment of no particular/special requirement, maximum relative error generally requirement is no more than 5%.
Source of error：Abstract error, necessary hypothesis and the true feelings done during abstract modeling target mathematical model before modeling
Deviation between condition assumes that asynchronous machine (ignores space harmonics and tooth socket effect for desired motor when being modeled such as threephase asynchronous machine
It should；Ignore magnetic circuit saturation；Ignore core loss；Do not consider that frequency variation and temperature change influence coil windings)；Equivalent mistake
Difference carries out analysis calculating for convenience, improves simulation efficiency, the introduced error of approximate simplified operation is carried out to mathematical model, such as
Mini-derivative linearization is carried out to nonlinear differential equation；Numerical error is replaced original using the discrete equation of different numerical methods
Rounding error caused by truncated error and computer the storage precision deficiency that equation generates；Environmental error, first component or equipment
Sample or test data correspond to the error between experimental enviroment and simulated environment.
Solution：If abstract error is main error, need moderately to repair abstract mathematical model according to actual conditions
Just, as considered, temperature change influences coil resistance value；If simplification error is main error, need to re-start model simplification, such as
When doing mini-derivative linearization, increase certain higher order term；If numerical error is main error, considers innovatory algorithm or improve memory
Precision；If validation error is main cause, need to consider to reset simulated conditions.
The member component or equipment performance model encapsulation, refer to the principle modeled according to hierarchy, pass through having verified that
First component be encapsulated as the simple module for having certain functional interfaces, to be used in more high-level, more complicated system, can have
Effect simplifies system-level model.
Encapsulation, is exactly packaged as some customized module by the model of first component or equipment, that is, input-output is kept to close
It is constant, the input of model, input, the output of output difference respective modules.Therefore, encapsulation operation is white in essence
Box.
System integration modeling described in S2 is including but not limited to multi-field hybrid modeling, hybrid system modeling, redundancy system
The modeling of system；
Multi-field hybrid modeling refers to that same model accommodates the model from different field, electric as involved in motor model
The multiple fields such as magnetics, electricity, machinery, calorifics, information exchange between the element in same field can be by establishing mutually similar
The field connector (behavior of the arbitrary field element of math equation description) of type, due to model between different field component models
Interface can not be directly connected to, and the energy conversion devices by actual physics system is needed to be abstracted and are mapped as what an expression energy converted
Model element is realized the information exchange of different field component models by the different type interface of energy transfer machine, is finally completed
Modeling.
Hybrid system modeling refers to comprising dynamic continuous model and Discrete Event Models in same model, wherein dynamically connecting
Continuous model is based on basic physical laws such as the conservation of energy, the conservation of mass, the conservations of momentum, describes the continuous time-varying behavior of system, and
Discrete Event Models are then description and the discrete behavior of system dependent event.When hybrid system models, all variables are protected in model
Its actual value is held, until these values are explicitly changed.These variate-values can be in continuous integral and event time by the equation of activity
It accesses, movable equation shows the restriction relation that must satisfy between variable, and only movable equation can solve.Only exist
When triggering discrete event, the dependent equation for describing discrete event is only the equation of activity.
Redundancy and tolerant system modeling refer to that same model not only comprising the first component of backup or equipment, is also included and closed therewith
The complex logics such as fault detect, fault diagnosis, failure decision, the failure response of connection.To first component of backup or the modeling of equipment,
Using Model Reuse；The modeling of fault detect is generally realized by various sensors；Fault diagnosis is by by first component
Or the output information of equipment is compared to obtain residual error realization with preset information, if residual error is more than specified value, positions
This yuan of component or equipment fault；The modeling of failure decision generally writes decision function and decision by script or logical operation model
Rule；Failure response modeling can carry out redundancy transfer or reconstruct by first component such as switch, clutch.
The system performance model modeling refers to that logically relationship structure is by first component model or subsystem model
System performance model.
Described system performance model verification refers to using being collected into system performance relevant information in S1 to established system
Performance model is verified, if error is allowing except threshold range, analytical error reason, corresponding correction model is until satisfaction property
It can requirement.
Verification：By obtained performance model emulation data and corresponding system performance information (test data, sample data)
It is placed under the same coordinate system, whether trend is consistent for both observations, and error analysis is carried out if consistent, calculates relative error.To nothing
The system of particular/special requirement, worst error generally requirement are no more than 10%.
Source of error：Systematic error caused by the model error cumulative effect of accumulated error, system member component or equipment；Number
It is worth error, the truncated error of original equation generation and computer is replaced to store precision using the discrete equation of different numerical methods
Rounding error caused by deficiency；Environmental error, product sample or test data correspond to the mistake between experimental enviroment and simulated environment
Difference.
Solution：If accumulated error is main error, the first component for trying to reduce that accounting is larger in systematic error is needed
Or equipment error；If simplification error is main error, need to re-start model simplification, when such as doing mini-derivative linearization, increase
Certain higher order term；If numerical error is main error, considers innovatory algorithm or improve memory precision；If validation error is main
Reason needs to consider to reset simulated conditions.
S3, the failure criterion for determining target multistate system：According to the multistate system design information collected in S1, given
The failure criterion gone out includes at least performance indicator and its threshold range：The performance that target multimode performance can be characterized comprehensively refers to
Mark；Performance indicator influences the threshold range that system function is realized with performance.
S4, analysis modeling is carried out to the fault mode of target multistate system：Failure is done to target multistate system first
Pattern, influence and HAZAN FMECA obtain influencing the critical failure pattern of system task reliability, analyze these keys
The affiliated fault category of fault mode and failure mechanism type.
The acquisition of information of S5, target multistate system failure：For the critical failure pattern obtained in S4, believe according to failure
The fault message that breath acquisition methods obtain generally comprises：Failure-rate data, fault state data and Performance Degradation Data.
S6, target multistate system direct fault location and emulation：According to the fault message that S5 is obtained, modeling based on script with
Emulation mechanisms complete direct fault location and emulation, extract multimode fault simulation result.
S7, fail-safe analysis and assessment are carried out to target multistate system task：Appointed using what is injected based on timing failure
Target multistate system Mean Time Between Critical Failure MTBCF is calculated for business Reliablility simulation appraisal procedure and task is reliable
Spend RM.
The mission reliability Simulation Evaluation method based on timing failure injection, it is desirable that meet following hypothesis：Often
The subtask execution time is tm；Influence of the non task time to failure is not considered；It breaks down and repairs and fix immediately as new；It takes out
Sample number is n times.It is sampled using Monte Carlo, the minimum fault time of acquired mutual indepedent critical failure is primary serious
Time between failures TBCFi(1≤i≤N) obtains N number of catastrophe failure interval time data by emulation, and such MTBCF is used
Following formula is calculated：
Meanwhile the Task Reliability MR of multistate system is evaluated, it is calculated using following formula：
Due to having recorded the catastrophe failure interval time TBCF of ith sampling generating system failure in simulation processi(1
≤i≤
N, therefore the number of the subtask can be denoted as this subsystem catastrophe failure interval time divided by each task time
Maximum positive integer (rounds up, is taken if 2.1 3), i.e.,
The fault modeling refers to that the type for fault mode determines suitable modeling pattern：To the event of discrete two-state
Barrier, using newly-increased redundant component method and change parametric method modeling；Discrete multimode failure can be modeled by using modeling software
Language creates malfunctioning module and change parametric method modeling；Continuous multimode failure can be taken out by continuously changing parametric method with continuous
Sample assignment method models.
The modeling and simulation mechanism based on script refers to for the corresponding emulation script Script of fault model definition in S6,
In Dymola softwares, batch processing simulation script primary structure is：
checkModel()；
Parameter and numerical value；
simulateModel()；
…
checkModel()；
Parameter and numerical value；
simulateModel()；
Wherein checkModel () function is that selected target model carries out model compilation, and simulateModel () is by setting
Determine simulation time, derivation algorithm, result storing path etc. and simulation calculating and result preservation are carried out to object function.
Run Script functions is recycled to perform above-mentioned script and carry out Multi simulation running, is i.e. control software performs batch processing automatically
Emulation.
The operation principle of the present invention is further described with reference to specific embodiment：
Certain type AC electrical fuel pump is mainly by threephase asynchronous machine and the centrifugal pump group with inducer impeller inducer into function is
For fuel tank and heat dissipation subsystem oil transportation.During oil transportation, it is desirable that AC electrical fuel pump meets system demand pressure and flow will
It asks.AC electrical fuel pump meets following hypothesis：Task execution time is every time
tm=1h；Influence of the non task time to failure is not considered；It breaks down and repairs and fix immediately as new, repair is not
It can influence the state of other fault modes；Frequency in sampling is n times.
The mission reliability that electric fuel punp is now carried out using the present invention is modeled, and realizes that process is as follows：
Design information needed for electric fuel punp performance model is established in collection.Table 1 gives AC electrical fuel pump centrifugal pump
Design information needed for partial properties modeling.
1 AC electrical fuel pump of table centrifuges pump portion design parameter
AC electrical oil fuel pump performance model is established, using modular modeling ideology, takes bottom-up modeling principle
Establish attached AC electrical oil fuel pump performance shown in fig. 6 verification model, wherein module 1 is power supply, and module 2 is measurement module, mould
Block 3 is fluid module, and module 4 is threephase asynchronous machine module, and module 5 is fuel pump module；Module 6 is load simulation module.
Module 4 and module 5 are all the package modules completed after performance verification, form AC electrical oil fuel pump performance model.It is attached drawing 7, attached
The verification to AC electrical performance in fuel pump starting process and steady-state process is set forth in Fig. 8, the results showed that is built
AC electrical oil fuel pump performance model must emulate that data are very identical with actual test data, and maximum relative error is no more than
8%, in allowed band, that is, the performance model built can accurately reflect the performance of AC electrical fuel pump.
AC electrical fuel pump failure criterion is provided, table 2 gives the failure criterion of AC electrical fuel pump, due to exchange
Under the operating mode that electric fuel punp is operated in that power line voltage is 200V, frequency is 400Hz in most task phases, therefore this
Using the failure criterion under the operating mode in case.
2 AC electrical fuel pump failure criterion of table
AC electrical fuel pump critical failure pattern is analyzed, table 3, which gives, influences AC electrical fuel pump mission reliability
The information such as critical failure pattern, affiliated parts, fault type and research method.
3 AC electrical fuel pump critical failure pattern of table
AC electrical fuel pump critical failure model is established, attached drawing 9-11 is set forth to be closed with AC electrical fuel pump
Key fault mode is object, and the case of fault modeling is realized by redundant component, change parameter, Modelica modeling methods.Its
In, Fig. 9 is on the basis of fuel oil alternating-current electric pump performance model, using redundant component method, by increasing dash-dotted gray line institute in figure
Redundant component (clutch Cluth modules) the simulated machine shaft shown, which is broken or is connect with fuel pump impeller, loosens failure behavior, i.e.,
Before clutch Cluth modules are triggered, motor drives fuel pump normal work；After triggering clutch Cluth modules, motor output shaft
Disconnection is connect with fuel pump.Figure 10 is given on the basis of fuel oil alternating-current electric pump performance model, using change parametric method, is passed through
Modification motor key parameter stator, rotor resistance value Rs and Rr carry out former-wound coil degradation failure behavior, i.e., different ageing times correspond to
Different Rs and Rr, and then influence fuel oil alternating-current electric pump performance.Figure 11 be on the basis of fuel oil alternating-current electric pump performance model,
Using Modelica modeling methods, the failure behavior of phase shortage is simulated by establishing threephase switch model, that is, passes through trigger switch
Simulated machine lacks a phase, the fault condition for lacking two-phase or three-phase.
Obtain AC electrical fuel pump critical failure information.It is ground according to AC electrical fuel pump critical failure in subordinate list 3
Study carefully method, with reference to discrete state, the fault message acquisition modes of continuous state failure in attached drawing 3, attached drawing 4, obtain handing over shown in table 4
Flow the discrete two-state of electric fuel punp, discrete multimode, continuous multi-mode fault message.
The fault message of the discrete two-state failure of 4 AC electrical fuel pump of table
The fault message of the discrete multimode failure of 5 AC electrical fuel pump of table
Carry out the injection of AC electrical fuel pump critical failure and emulation.To discrete multimode failure, by calling attached drawing 12
Shown scanning function modification parameter (supply frequency value) realizes direct fault location, obtains the event of frequency anomaly shown in attached drawing 13a and Figure 13 b
Simulation result during barrier；To continuous multimode failure, software Multi simulation running is directly controlled by writing script shown in attached drawing 14, is obtained
To coil aging shown in Figure 15 a and Figure 15 b cause the probability density function of system failure time and cumulative distribution function and its point
Cloth fitting function.
Analysis and assessment AC electrical fuel pump mission reliability, to discrete state failure (such as axle fracture, phase shortage, frequency
It is abnormal etc.), it is sampled according to fault message in table 4, table 5；More continuous state failure (such as coil aging, seal aging, bearings
Abrasion etc.), it is sampled according to gained simulation result in step 7, obtains the continuous multimode of AC electrical fuel pump shown in table 6
The fault message of failure.According to algorithm shown in attached drawing 5, N=100000 Monte-Carlo step is carried out, obtains the type AC electrical
The Mean Time Between Critical Failure MTBCF=2842.23h of fuel pump, Task Reliability MR=99.965%, and obtain attached drawing
Coil aging shown in 15 causes the probability density function and cumulative distribution function of system failure time.
The fault message of the continuous multimode failure of 6 AC electrical fuel pump of table
Finally it should be noted that：Above-described embodiments are merely to illustrate the technical scheme rather than to it
Limitation；Although the present invention is described in detail referring to the foregoing embodiments, it will be understood by those of ordinary skill in the art that：
It can still modify to the technical solution recorded in previous embodiment or to which part or all technical features into
Row equivalent replacement；And these modifications or substitutions, it does not separate the essence of the corresponding technical solution various embodiments of the present invention technical side
The range of case.
Claims (9)
- A kind of 1. method that multistate system mission reliability modeling is carried out based on performance model, it is characterised in that：It include with Lower step：S1, target multistate system design information is collected：The design information include operation principle, structure composition, work information, Performance indicator, structural parameters, sample parameter and test data；S2, target multistate system performance model is established：It includes following sub-step：1. by system modular；2. according to bottom-up hierarchical modeling principle, building for first component or equipment is carried out using module Mould, verification and encapsulation；3. carrying out system integration modeling, system-level model is built；4. complete target multistate system performance mould The modeling and verification of type；S3, the failure criterion for determining target multistate system：According to the multistate system design information collected in S1, failure criterion Including at least performance indicator and its threshold range：The performance indicator can characterize target multimode performance comprehensively；The threshold value Ranging from performance indicator influences the threshold value that system function is realized with performance；S4, analysis modeling is carried out to the fault mode of target multistate system：Target multistate system is done first fault mode, Influence and HAZAN obtain influencing the critical failure pattern of system task reliability, analyze these critical failure pattern institutes Belong to fault category and failure mechanism type；The acquisition of information of S5, target multistate system failure：For the critical failure pattern obtained in S4, obtained according to fault message The fault message that method obtains is taken to generally comprise：Failure-rate data, fault state data and Performance Degradation Data；S6, target multistate system direct fault location and emulation：According to the fault message that S5 is obtained, the modeling and simulation based on script Mechanism completes direct fault location and emulation, extracts multimode fault simulation result；S7, fail-safe analysis and assessment are carried out to target multistate system task：It can using being injected based on timing failure for task Target multistate system Mean Time Between Critical Failure MTBCF and Task Reliability is calculated by property Simulation Evaluation method RM；The mission reliability Simulation Evaluation method based on timing failure injection, it is desirable that meet following hypothesis：Appoint every time The business execution time is tm；Influence of the non task time to failure is not considered；It breaks down and repairs and restore immediately；Frequency in sampling is N times；It is sampled using Monte Carlo, the minimum fault time of acquired mutual indepedent critical failure is a catastrophe failure interval Time TBCFi(1≤i≤N) obtains N number of catastrophe failure interval time data by emulation, and such MTBCF is carried out using following formula It calculates：Meanwhile the Task Reliability MR of multistate system is evaluated, it is calculated using following formula：Due to having recorded the catastrophe failure interval time TBCF of ith sampling generating system failure in simulation processi(1≤i≤ N, therefore the number of the subtask can be denoted as this subsystem catastrophe failure interval time divided by the maximum of each task time is just whole Number, i.e.,
- 2. the method according to claim 1 that multistate system mission reliability modeling is carried out based on performance model, special Sign is：System modular described in S2 refers to for system to be separated into the basic module being easily processed,First component or equipment performance modeling refer to that member will be built according to system function logical relation after module imparting parameter Component or equipment performance model.
- 3. the method according to claim 2 that multistate system mission reliability modeling is carried out based on performance model, special Sign is：First component or equipment performance model described in S2 verified, refers to believe using being collected into first component correlation in S1 It ceases and the model for establishing first component or equipment is verified, error analysis is carried out if error is within error threshold, calculate Relative error, if error except error threshold, needs analytical error reason, corresponding correction model is until meet the requirements；The member component or equipment performance model are packaged, and are referred to the principle modeled according to hierarchy, are passed through having verified that First component be encapsulated as the simple module for having certain functional interfaces.
- 4. the method according to claim 3 that multistate system mission reliability modeling is carried out based on performance model, special Sign is：The detailed process that first component or equipment performance model described in S2 are verified refer to obtained first component or The emulation data of equipment performance model are placed in respective tuple part or device capability information under the same coordinate system, and whether both observations Trend is consistent.
- 5. the method according to claim 3 that multistate system mission reliability modeling is carried out based on performance model, special Sign is：The error threshold is 5%；The source of error includes abstract error, equivalent error, numerical error or environmental error, before the abstract error refers to modeling The necessary deviation assumed between truth done during abstract modeling target mathematical model, the equivalent error refer to for convenience Analysis calculating is carried out, improves simulation efficiency, the introduced error of approximate simplified operation, the numerical error are carried out to mathematical model Refer to and replace the truncated error of original equation generation and computer storage precision insufficient using the discrete equation of different numerical methods Caused by rounding error, the environmental error refers to first component or equipment sample or test data corresponds to experimental enviroment and simulated environment Between error；It needs to carry out abstract mathematical model appropriate amendment according to actual conditions if being main error if abstract error；It is if equivalent Error is main error, then needs to re-start model simplification；If numerical error is main error, considers innovatory algorithm or carry High memory precision；If environmental error is main cause, need to consider to reset simulated conditions.
- 6. the method according to claim 3 that multistate system mission reliability modeling is carried out based on performance model, special Sign is：System integration modeling described in S2 is including but not limited to multi-field hybrid modeling, hybrid system modeling and redundancy The modeling of system；The system performance model modeling refers to that logically relationship structure is systemic by first component model or subsystem model It can model；The system performance model verification, refers to the corresponding system for obtaining obtained system performance model emulation data to S1 System performance information is placed under the same coordinate system, and whether trend is consistent for both observations, is missed if error is within error threshold Difference is analysed, and calculates relative error, if error is allowing except threshold range, analytical error reason, corresponding correction model is until full Sufficient performance requirement.
- 7. the method according to claim 6 that multistate system mission reliability modeling is carried out based on performance model, special Sign is：In system performance model verification, the error threshold is 10%.
- 8. the method according to claim 1 that multistate system mission reliability modeling is carried out based on performance model, special Sign is：The fault modeling refers to that the type for fault mode determines suitable modeling pattern：To discrete two-state failure, Using newly-increased redundant component method and change parametric method modeling；Event is created using modeling software modeling language to discrete multimode failure Barrier module and change parametric method modeling；Continuous multimode failure is built using continuous change parametric method with sequential sampling assignment method Mould.
- 9. the method according to claim 1 that multistate system mission reliability modeling is carried out based on performance model, special Sign is：The modeling and simulation mechanism based on script refers to for the corresponding emulation script Script of fault model definition in S6.
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