CN109063353A - The pre- diagnostic method of EMU subsystem fault and system - Google Patents
The pre- diagnostic method of EMU subsystem fault and system Download PDFInfo
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Abstract
The present invention provides a kind of pre- diagnostic method of EMU subsystem fault and systems, this method comprises: establishing fault model according to the fault sample data of EMU subsystem, the fault model includes fault mode；Non-faulting model is established according to the EMU subsystem；The parameter value of the fault mode is input to the non-faulting model, and the behavior expression data of the corresponding analogue system of the EMU subsystem are obtained by simulation calculation；The parameter value includes fault parameter data and the time of failure determining according to setting probability function；Fault pre-diagnosing is carried out to the EMU subsystem according to the behavior expression data.Random time of failure is set by realizing, can be improved the flexibility of fault diagnosis.
Description
Technical field
The present invention relates to Train Operation Control Technology field more particularly to a kind of pre- diagnostic methods of EMU subsystem fault
And system.
Background technique
Each subsystem of EMU is related to fluid solid heat couple, material, heat engine fatigue, electronic technology, control technology, software science
Deng being extremely complex system.It in order to ensure each subsystem can satisfy functional requirement, performs effectively, assurance function safety, and
Direction is provided for the sustained improvement of product, it is very necessary for carrying out effective failure predication to each subsystem.
Current failure prediction method is mainly based upon experimental data progress, first collects fault data, then passes through people
The mode of work intelligent training fault model completes failure predication.But malfunction test data often obtain cost height in reality
High, the compiling costs period is longer, and the process of artificial intelligence learning training model is again extremely complex, so that being based on experimental data
Failure prediction method be difficult to apply.If the artificial manufacturing fault on testing stand, not only the period at high cost is long, but also leads to event
There are many mode of barrier, and workload is very big, and are easy error, are difficult to realize simultaneously.
Failure prediction method based on model does not need the support of lot of experimental data, so at low cost, the period is short, may be used also
Various faults mode is set.However the current failure prediction method based on model, need to preset the position of failure generation
And the time, lack randomness, and can only simulation calculation fail result, EMU subsystem unable to monitor between failure and it is non-therefore
The intermediate state of barrier, so that pre- diagnostic system health status cannot be played the role of.
Summary of the invention
The present invention provides a kind of pre- diagnostic method of EMU subsystem fault and system, to improve the flexible of fault diagnosis
Property.
In order to achieve the above objectives, the present invention is realized by the following scheme:
In an embodiment of the invention, pre- diagnostic method of EMU subsystem fault, comprising: according to EMU subsystem
The fault sample data of system establish fault model, and the fault model includes fault mode；According to the EMU subsystem construction in a systematic way
Vertical non-faulting model；The parameter value of the fault mode is input to the non-faulting model, and institute is obtained by simulation calculation
State the behavior expression data of the corresponding analogue system of EMU subsystem；The parameter value includes that fault parameter data and foundation are set
Determine the time of failure that probability function determines；It is pre- that failure is carried out to the EMU subsystem according to the behavior expression data
Diagnosis.
In another embodiment, fault model is established according to the fault sample data of EMU subsystem, institute
Stating fault model includes fault mode；Non-faulting model is established according to the EMU subsystem, comprising: it is based on Modelica,
Fault model library is established according to the fault sample data of EMU subsystem, the fault model library includes multiple fault models,
The fault model includes fault mode；Based on Modelica, non-faulting model library is established, the non-faulting model library includes root
The non-faulting model established according to the EMU subsystem.
In another embodiment, failure is carried out to the EMU subsystem according to the behavior expression data
Pre- diagnosis, comprising: according to the health status of EMU subsystem described in the behavior expression data monitoring, the health status packet
Include failure, non-faulting and non-health.
In another embodiment, the parameter value of the fault mode is input to the non-faulting model, wrapped
It includes: according to preset failure injection length or random fault injection length, the parameter value of the fault mode being written to described non-
Fault model.
In another embodiment, the fault model also includes: failure title, failure cause and failure knot
Fruit.
In an embodiment of the invention, the pre- diagnostic system of EMU subsystem fault, comprising: model foundation unit,
For: fault model is established according to the fault sample data of EMU subsystem, the fault model includes fault mode；According to
The EMU subsystem establishes non-faulting model；Direct fault location unit, is used for: the parameter value of the fault mode is input to
The non-faulting model, and the behavior expression number of the corresponding analogue system of the EMU subsystem is obtained by simulation calculation
According to；The parameter value includes fault parameter data and the time of failure determining according to setting probability function；Fault pre-diagnosing
Unit is used for: carrying out fault pre-diagnosing to the EMU subsystem according to the behavior expression data.
In another embodiment, the model foundation unit, comprising: fault model establishes module, is used for: base
In Modelica, fault model library is established according to the fault sample data of EMU subsystem, the fault model library includes more
A fault model, the fault model include fault mode；Non-faulting model building module, is used for: being based on Modelica, establishes
Non-faulting model library, the non-faulting model library include the non-faulting model established according to the EMU subsystem.
In another embodiment, the fault pre-diagnosing unit, comprising: fault monitor module is used for: according to
The health status of EMU subsystem described in the behavior expression data monitoring, the health status include failure, non-faulting and
It is non-health.
In an embodiment of the invention, computer readable storage medium is stored thereon with computer program, the program quilt
The step of the various embodiments described above the method is realized when processor executes.
In an embodiment of the invention, computer equipment, including memory, processor and storage are on a memory and can
The computer program run on a processor, the processor realize the various embodiments described above the method when executing described program
Step.
The pre- diagnostic method of EMU subsystem fault of the invention, the pre- diagnostic system of EMU subsystem fault, computer
Readable storage medium storing program for executing and computer equipment, due to establishing fault model and non-faulting model, and by failure in the fault model
The parameter value of mode is input to the non-faulting model and carries out simulation calculation, rather than failure is arranged directly in non-faulting model and sends out
The raw time, it is possible to which the time that failure occurs is arranged by fault mode.And the event by being determined according to probability function
Barrier time of origin can make the time of failure have randomness, can overcome time of failure in the prior art with this
Lack disadvantage brought by randomness.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.In the accompanying drawings:
Fig. 1 is the flow diagram of the pre- diagnostic method of EMU subsystem fault of one embodiment of the invention；
Fig. 2 is the Braking System for High Speed Multiple Units direct fault location flow diagram of one embodiment of the invention；
Fig. 3 is the structural schematic diagram of braking system faults injection model in one embodiment of the invention；
Fig. 4 is a kind of structural schematic diagram of pre- diagnostic system of EMU subsystem fault of one embodiment of the invention；
Fig. 5 is the structural schematic diagram of model foundation unit in one embodiment of the invention.
Specific embodiment
Understand in order to make the object, technical scheme and advantages of the embodiment of the invention clearer, with reference to the accompanying drawing to this hair
Bright embodiment is described in further details.Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but simultaneously
It is not as a limitation of the invention.
It needs to preset the position and time that failure occurs to solve existing fault filling method, lacks randomness,
The problem of EMU subsystem unable to monitor is between the intermediate state of failure and non-faulting, the present invention provides a kind of EMU
The pre- diagnostic method of the system failure.
Fig. 1 is the flow diagram of the pre- diagnostic method of EMU subsystem fault of one embodiment of the invention.Such as Fig. 1 institute
Show, the pre- diagnostic method of EMU subsystem fault of some embodiments, it may include:
Step S110: fault model is established according to the fault sample data of EMU subsystem, the fault model includes
Fault mode；Non-faulting model is established according to the EMU subsystem；
Step S120: the parameter value of the fault mode is input to the non-faulting model, and is obtained by simulation calculation
To the behavior expression data of the corresponding analogue system of the EMU subsystem；The parameter value include fault parameter data and according to
The time of failure determined according to setting probability function；
Step S130: fault pre-diagnosing is carried out to the EMU subsystem according to the behavior expression data.
In above-mentioned steps S110, which can be each subsystem in EMU system, for example, leading
Draw system.The fault sample data may include the data of the various failures of EMU subsystem, can be according to EMU system
Running fault data or the fault data of experiment test obtain.The fault mode may include various description failure behaviors
Information or data, such as abort situation, fault type, fault time etc..The non-faulting model may include that this is dynamic for various descriptions
The information or data, such as parameter, variable and equation of physical behavio(u)r etc. that vehicle group subsystem operates normally.Can based on it is various not
Fault model and non-faulting model, such as Modelica language are established with language.In some embodiments, the fault model in addition to
It also may include the other information of the corresponding fault mode comprising fault mode, for example, failure title, failure cause and failure knot
Fruit etc..It can be in order to people finder, analysis or injection failure using failure title, failure cause and fail result.
In above-mentioned steps S120, change linearly or nonlinearly can be presented in some parameter values of fault mode at any time
Change.The fault parameter data may include the information or data of various description failure behaviors, such as abort situation, fault type
Deng.The fault parameter data and the time of failure can be configured by fault mode.According to setting probability function
Determining time of failure can make time of failure have randomness.The setting probability function can be various probability
Distribution function, such as probability distribution: normal distribution, Bernoulli Jacob's distribution, bi-distribution, Poisson distribution, monte carlo distributions etc..It can
Simulation calculation is carried out so that the parameter value of fault mode to be input in the solver of analogue system.Acquired behavior expression data can
With the performance parameter variations curve etc. comprising EMU subsystem one or more position, EMU subsystem may determine that with this
Carrying out practically state.
In above-mentioned steps S130, the preset failure of the EMU subsystem can be diagnosed in advance by showing data according to the behavior
The case where health status and peripheral position of position.The health status may include failure or non-faulting.Moreover, because failure is sent out
The raw time can be preset as a period of time, can according to the element function Parameters variation curve of preset failure position in this time
Be diagnosed to be the preset failure position or its around may break down the case where, it can be diagnosed to be between failure and non-faulting
Between unhealthy status.
In the present embodiment, due to establishing fault model and non-faulting model, and by fault mode in the fault model
Parameter value be input to the non-faulting model carry out simulation calculation, rather than directly in non-faulting model be arranged failure occur when
Between, it is possible to the time that failure occurs is arranged by fault mode.And the failure by determining according to probability function occurs
Time can make the time of failure have randomness, with this can overcome in the prior art time of failure lack with
Disadvantage brought by machine.
In some embodiments, fault model library and non-faulting model library, fault model can be established based on Modelica
Comprising the fault model established based on Modelica in library, non-faulting model library includes the non-faulting mould established based on Modelica
Type.Specifically, above-mentioned steps S110, that is, establish fault model, the failure according to the fault sample data of EMU subsystem
Model includes fault mode, establishes non-faulting model according to the EMU subsystem, it may include: it is based on Modelica, according to
The fault sample data of EMU subsystem establish fault model library, and the fault model library includes multiple fault models, described
Fault model includes fault mode；Based on Modelica, non-faulting model library is established, the non-faulting model library includes according to institute
State the non-faulting model of EMU subsystem foundation.The non-faulting model library can also be corresponding comprising other EMU subsystems
Non-faulting model.
It, can be with since Modelica language is suitable for extensive, complicated, isomery physics system modelling in the embodiment
Meet more physical field modeling and simulating demands such as mechanical, electric air and heat, hydraulic, pneumatic, fluid, and is good at and calculates electro thermal coupling
Stiff problem is very suitable to the modeling and simulating of EMU subsystem, so being the construction in a systematic way of EMU subsystem based on Modelica language
Vertical fault model and non-faulting model are more easily implemented.In addition, since the fault model of foundation is placed in fault model library, it is non-
Fault model is placed in non-faulting model library, with this, can be convenient for being managed fault model and non-faulting model.
In some embodiments, above-mentioned steps S120, that is, the parameter value of the fault mode is input to the non-faulting
Model, it may include: according to preset failure injection length or random fault injection length, the parameter value of the fault mode is written
To the non-faulting model.The preset failure injection length or the random fault injection length, which can be, to be arranged in above-mentioned failure mould
In formula, so fault injection time can be preset or be adjusted by fault mode.The parameter value of fault mode can be write
Enter into the solver of the analogue system of the non-faulting model, completes injection.In the embodiment, when by setting direct fault location
Between, so that direct fault location has bigger flexibility, and the scene that EMU subsystem fault diagnoses in advance can be increased.
In some embodiments, above-mentioned steps S130, that is, according to the behavior expression data to the EMU subsystem
Carry out fault pre-diagnosing, it may include: it is described according to the health status of EMU subsystem described in the behavior expression data monitoring
Health status includes failure, non-faulting and non-health.In the embodiment, in the case where time of failure is a period of time,
The performance curve of element in EMU subsystem can be measured, with this can analysis element it is non-between failure and non-faulting
Health status can be predicted break down before breaking down by monitoring the unhealthy status of EMU subsystem
Element, diagnosis more fine granularity.
It will illustrate implementation of the invention by taking Braking System for High Speed Multiple Units as an example below.
Fig. 2 is the Braking System for High Speed Multiple Units direct fault location flow diagram of one embodiment of the invention.Fig. 3 is the present invention
The structural schematic diagram of braking system faults injection model in one embodiment.It can be related to mass block, work in Fig. 3, in braking system
Plug, spring, gas volume, reversing valve, input interface and interface etc. can will be set as at direct fault location at reversing valve, be carried out
Direct fault location.In conjunction with shown in Fig. 2 and Fig. 3, the fault pre-diagnosing method of the Braking System for High Speed Multiple Units of an embodiment, including with
Lower step:
(1) fault-free model library is built using the system model library based on Modelica, which can be with modeling and simulating
Behavior expression under the nominal situation of braking system；
(2) fault model library is built by fault sample data, which includes each fault mode of braking system；
(3) it can be preset using direct fault location module by the parameter of fault model write-in non-faulting model, it can also be with
Fault injection time, behavior expression when emulation braking system breaks down is arranged in machine；
(4) EMU subsystem health monitoring platform is built, is injected in non-faulting model by different faults mode, definition
The corresponding system health degree of fault parameter value, the health status of system is monitored by different fault parameter values.
The method of the present embodiment collects the fault sample data of fault model, so by establishing trouble-free system model
After establish fault model and be injected into system model, finally carry out failure predication and diagnosis, can preset or be randomly provided
The time of direct fault location, model is more flexible, and can monitor the health status of EMU subsystem.
Based on inventive concept identical with the pre- diagnostic method of EMU subsystem fault shown in FIG. 1, the embodiment of the present application
A kind of pre- diagnostic system of EMU subsystem fault is additionally provided, as described in following example.Due to EMU subsystem event
It is similar to the pre- diagnostic method of EMU subsystem fault to hinder the principle that pre- diagnostic system solves the problems, such as, therefore the EMU subsystem
The implementation of fault pre-diagnosing system may refer to the implementation of the pre- diagnostic method of EMU subsystem fault, and it is no longer superfluous to repeat place
It states.
Fig. 4 is a kind of structural schematic diagram of pre- diagnostic system of EMU subsystem fault of one embodiment of the invention.Such as Fig. 4
It is shown, a kind of pre- diagnostic system of EMU subsystem fault of some embodiments, it may include: model foundation unit 210, failure note
Enter unit 220 and fault pre-diagnosing unit 230, above-mentioned each unit is linked in sequence.
Model foundation unit 210, is used for: fault model is established according to the fault sample data of EMU subsystem, it is described
Fault model includes fault mode；Non-faulting model is established according to the EMU subsystem；
Direct fault location unit 220, is used for: the parameter value of the fault mode being input to the non-faulting model, and is led to
It crosses simulation calculation and obtains the behavior expression data of the corresponding analogue system of the EMU subsystem；The parameter value includes failure
Supplemental characteristic and the time of failure determined according to setting probability function；
Fault pre-diagnosing unit 230, is used for: carrying out failure to the EMU subsystem according to the behavior expression data
Pre- diagnosis.
Fig. 5 is the structural schematic diagram of model foundation unit in one embodiment of the invention.As shown in figure 5, the model foundation
Unit 210, it may include: fault model establishes module 211 and non-faulting model building module 212.Fault model establishes module
211, it is used for: based on Modelica, establishing fault model library, the failure mould according to the fault sample data of EMU subsystem
Type library includes multiple fault models, and the fault model includes fault mode.Non-faulting model building module 212, is used for: being based on
Modelica, establishes non-faulting model library, and the non-faulting model library includes the non-event established according to the EMU subsystem
Hinder model.
In some embodiments, the fault pre-diagnosing unit 230, it may include: fault monitor module is used for: according to institute
State the health status of EMU subsystem described in behavior expression data monitoring, the health status includes failure, non-faulting and non-
Health.
In some embodiments, direct fault location unit 220, comprising: direct fault location module, according to preset failure injection length
Or random fault injection length, the parameter value of the fault mode is written to the non-faulting model.
In some embodiments, the fault model also includes: failure title, failure cause and fail result.
In one embodiment, in order to achieve the above technical purposes, which is based on
Modelica model realization, specifically, it may include non-faulting model library, fault model library, direct fault location based on Modelica
Module and health monitoring platform etc..
The non-faulting model library is for storing non-faulting system model, and non-faulting system model is built based on Modelica
Vertical, it can support more physical field modelings such as machinery, power electronics, hydraulic and control.Comprising describing it in each element
Parameter, variable and the equation of physical behavio(u)r.
The fault model library is for storing failure system model, and failure system model is again based on Modelica and builds
, different fault modes can be stored, its information can also be stored, for example, failure title, failure cause, failure effect etc..
The direct fault location module is for the parameter value of fault model to be written in corresponding non-faulting model, in operation
Fault parameter value is written in the solver of emulation by Cheng Zhong, completes injection.Fault injection time can be it is preset, can also
To be random.Since linear or nonlinear variation, the ginseng of direct fault location may be presented in different fault parameters at any time
Numerical value and time can be preset by fault mode.
The health monitoring platform is the system for monitoring the health status of high-speed EMUs subsystem.When fault parameter quilt
After being injected into non-faulting model, emulation can solve corresponding model parameter value after direct fault location.Therefore, reach and injecting not
In the case where same fault parameter, the probability that may be broken down to components certain in system is predicted, so that monitoring is dynamic
The health status of vehicle group: failure, non-faulting and non-health.One EMU subsystem can be defined as complete fault-free and failure
Two stages occur, the intermediate stage can be defined as the non-health stage.
High-speed EMUs subsystem fault pre- diagnostic system provided in this embodiment based on Modelica model, advantage exist
In the time that can be randomly provided failure generation, and EMU subsystem health status can be monitored, in time to EMU into
Row maintenance and maintenance.Health monitoring platform is built by way of direct fault location, can preset or be randomly provided direct fault location
Time, model is more flexible, and can monitor the health status of EMU subsystem, and EMU staff is helped to overhaul in time
It safeguards each subsystem of EMU, reduces fault rate, improve the safety and stability of EMU.
The embodiment of the present invention also provides a kind of computer readable storage medium, is stored thereon with computer program, the program
The step of being executed by processor above-described embodiment the method.
Also a kind of computer equipment of the embodiment of the present invention, including memory, processor and storage are on a memory and can be
The computer program run on processor, the processor realize the step of above-described embodiment the method when executing described program
Suddenly.
In conclusion the pre- diagnostic method of EMU subsystem fault, the EMU subsystem fault of the embodiment of the present invention are pre-
Diagnostic system, computer readable storage medium and computer equipment, due to establishing fault model and non-faulting model, and should
The parameter value of fault mode is input to the non-faulting model and carries out simulation calculation in fault model, rather than directly in non-faulting mould
The time that failure occurs is set in type, it is possible to the time that failure occurs be arranged by fault mode.And by according to general
The time of failure that rate function determines can make the time of failure have randomness, can overcome the prior art with this
Middle time of failure lacks disadvantage brought by randomness.
In the description of this specification, reference term " one embodiment ", " specific embodiment ", " some implementations
Example ", " such as ", the description of " example ", " specific example " or " some examples " etc. mean it is described in conjunction with this embodiment or example
Particular features, structures, materials, or characteristics are included at least one embodiment or example of the invention.In the present specification,
Schematic expression of the above terms may not refer to the same embodiment or example.Moreover, the specific features of description, knot
Structure, material or feature can be combined in any suitable manner in any one or more of the embodiments or examples.Each embodiment
Involved in the step of sequence be used to schematically illustrate implementation of the invention, sequence of steps therein is not construed as limiting, can be as needed
It appropriately adjusts.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Particular embodiments described above has carried out further in detail the purpose of the present invention, technical scheme and beneficial effects
Describe in detail it is bright, it should be understood that the above is only a specific embodiment of the present invention, the guarantor being not intended to limit the present invention
Range is protected, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should be included in this
Within the protection scope of invention.
Claims (10)
1. a kind of pre- diagnostic method of EMU subsystem fault characterized by comprising
Fault model is established according to the fault sample data of EMU subsystem, the fault model includes fault mode；According to
The EMU subsystem establishes non-faulting model；
The parameter value of the fault mode is input to the non-faulting model, and EMU is obtained by simulation calculation
The behavior expression data of the corresponding analogue system of system；The parameter value include fault parameter data and according to setting probability function
Determining time of failure；
Fault pre-diagnosing is carried out to the EMU subsystem according to the behavior expression data.
2. the pre- diagnostic method of EMU subsystem fault as described in claim 1, which is characterized in that according to EMU subsystem
Fault sample data establish fault model, the fault model includes fault mode；It is established according to the EMU subsystem
Non-faulting model, comprising:
Based on Modelica, fault model library, the fault model library are established according to the fault sample data of EMU subsystem
Including multiple fault models, the fault model includes fault mode；Based on Modelica, non-faulting model library is established, it is described
Non-faulting model library includes the non-faulting model established according to the EMU subsystem.
3. the pre- diagnostic method of EMU subsystem fault as described in claim 1, which is characterized in that according to the behavior expression
Data carry out fault pre-diagnosing to the EMU subsystem, comprising:
According to the health status of EMU subsystem described in the behavior expression data monitoring, the health status include failure,
Non-faulting and non-health.
4. the pre- diagnostic method of EMU subsystem fault as described in claim 1, which is characterized in that by the fault mode
Parameter value is input to the non-faulting model, comprising:
According to preset failure injection length or random fault injection length, the parameter value of the fault mode is written to described non-
Fault model.
5. the pre- diagnostic method of EMU subsystem fault as described in claim 1, which is characterized in that the fault model also wraps
Contain: failure title, failure cause and fail result.
6. a kind of pre- diagnostic system of EMU subsystem fault characterized by comprising
Model foundation unit, is used for: establishing fault model, the fault model according to the fault sample data of EMU subsystem
Include fault mode；Non-faulting model is established according to the EMU subsystem；
Direct fault location unit, is used for: the parameter value of the fault mode being input to the non-faulting model, and passes through emulation meter
Calculation obtains the behavior expression data of the corresponding analogue system of the EMU subsystem；The parameter value includes fault parameter data
With the time of failure determined according to setting probability function；
Fault pre-diagnosing unit, is used for: carrying out fault pre-diagnosing to the EMU subsystem according to the behavior expression data.
7. the pre- diagnostic system of EMU subsystem fault as claimed in claim 6, which is characterized in that the model foundation list
Member, comprising:
Fault model establishes module, is used for: being based on Modelica, establishes failure according to the fault sample data of EMU subsystem
Model library, the fault model library include multiple fault models, and the fault model includes fault mode；
Non-faulting model building module, is used for: being based on Modelica, establishes non-faulting model library, the non-faulting model library packet
Include the non-faulting model established according to the EMU subsystem.
8. the pre- diagnostic system of EMU subsystem fault as claimed in claim 6, which is characterized in that the fault pre-diagnosing list
Member, comprising:
Fault monitor module is used for: described according to the health status of EMU subsystem described in the behavior expression data monitoring
Health status includes failure, non-faulting and non-health.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
The step of claim 1 to 5 the method is realized when row.
10. a kind of computer equipment including memory, processor and stores the meter that can be run on a memory and on a processor
Calculation machine program, which is characterized in that the step of processor realizes claim 1 to 5 the method when executing described program.
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