CN104597892B - One kind is used for electronic information equipment stratification method for diagnosing faults - Google Patents
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- CN104597892B CN104597892B CN201410785081.0A CN201410785081A CN104597892B CN 104597892 B CN104597892 B CN 104597892B CN 201410785081 A CN201410785081 A CN 201410785081A CN 104597892 B CN104597892 B CN 104597892B
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
- G05B23/0245—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a qualitative model, e.g. rule based; if-then decisions
- G05B23/0251—Abstraction hierarchy, e.g. "complex systems", i.e. system is divided in subsystems, subsystems are monitored and results are combined to decide on status of whole system
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Abstract
One kind proposed by the present invention is used for electronic information equipment stratification method for diagnosing faults, solves the problems such as existing weaponry and equipment fault diagnosis technology fault detect rate is low, fault coverage is not high, trouble isolation serviceability is poor.Step 1: equipment Failure Modes are analyzed：Assessed including equipment failure model construction, fault signature extraction, fault simulation and checking；Step 2: structure stratification fault model：Equipment Failure Modes analysis result is optimized according to the simulation results of step 1, and then reversely instructs system failure model hierarchyization to optimize；Step 3: structure fault diagnosis system：The failure mode analysis (FMA) result and stratification fault model obtained according to above-mentioned steps one and two, from software and hardware resources；Step 4: change system level fault diagnosis is verified：Complete the system level diagnostic test of equipment.
Description
Technical field
The present invention relates to weaponry integration test diagnostic techniques field, more particularly to one kind to be used for electronic information equipment layer
Secondaryization method for diagnosing faults.
Background technology
In integration test and diagnostic field, with the raising of electronic information weapon system-of-systems complexity, equipment configuration group
Close into being contacted between complicated each subsystem, its failure has level, correlation and comprehensive feature, while conventional equipment event
Barrier diagnosis thought, realize technological approaches, system constructive method, use software and hardware technology exist it is low to fault detect rate,
The problems such as fault coverage is not high, trouble isolation serviceability is poor, false alarm rate is high, greatly limit the performance of Military Equipment Battling efficiency, nothing
Method meets Maintenance for Equipment mission requirements.
The content of the invention
The technical problem to be solved in the present invention is for existing weaponry and equipment fault diagnosis technology fault detect rate is low, failure covering
The problems such as rate is not high, trouble isolation serviceability is poor, electronic information equipment Methods for Diagnosing System Level Malfunctions technology is broken through, builds the event of stratification
Hinder diagnostic system, to improve the efficiency and accuracy of equipping diagnosis.
In order to solve the above technical problems, one kind proposed by the present invention is used for electronic information equipment stratification fault diagnosis side
Method, comprise the following steps：
Step 1: equipment Failure Modes are analyzed：Including equipment failure model construction, fault signature extraction, fault simulation and
Checking is assessed；First by user requirements analysis, equipment failure arrange and firsthand information collect to equipment carry out hierachical decomposition and
Testability analysis obtains equipment Failure Modes and impact analysis FMEA reports, and establishes the system failure in TEAMS simulation softwares
Model；With TEAMS simulation softwares according to FMEA simulated injection all kinds failures are equipped, to system failure feature extraction, and
Testing and diagnosing is carried out to injection failure, and then verifies the testability of assessment system, obtains simulation results；
Step 2: structure stratification fault model：Equipment Failure Modes are analyzed according to the simulation results of step 1
As a result optimize, and then reversely instruct system failure model hierarchyization to optimize；
Step 3: structure fault diagnosis system：The failure mode analysis (FMA) result and layer obtained according to above-mentioned steps one and two
Secondaryization fault model, examined from software and hardware resources, including direct fault location software and hardware configuration, test software and hardware configuration, structure failure
Disconnected system；
Step 4: change system level fault diagnosis is verified：The equipment Failure Modes obtained according to above-mentioned steps one, two are analyzed
As a result, direct fault location, fault signature extraction and fault reasoning is carried out to equipment with the fault diagnosis system of step 3 structure to obtain
To change system fault diagnosis result, the software emulation result for contrasting step 1 is verified to change system level fault diagnosis,
Complete the system level diagnostic test of equipment.
Beneficial effects of the present invention：
The present invention can utilize electronic information equipment self structure, the level feature of function, by propagating equipment failure
The analysis and research of characteristic, system-level distinguishing hierarchy is carried out in terms of equipping with equipment Failure Modes two, establish stratification diagnosis mould
Type, test data is obtained with reference to distributed BIT and outside ATE tests are equipped, is mutually tied with D-S evidence theory using BP neural network
The information fusion algorithm of conjunction carries out fault reasoning, to realize the Methods for Diagnosing System Level Malfunctions of equipment.According in equipment and failure
Contacting, with the selection in change system level hierarchical model specification fault mode space, equipment knowledge and expert are instructed into sex knowledge
Failure diagnostic process is introduced so as to merge information of both equipment knowledge and fault knowledge, to instruct failure diagnostic process.
Brief description of the drawings
Fig. 1 is electronic information equipment Methods for Diagnosing System Level Malfunctions technology overall plan schematic diagram of the present invention；
Fig. 2 is equipment Failure Modes analytical plan flow chart of the present invention；
Fig. 3 is change system level stratification Fault Diagnosis Strategy process schematic of the present invention；
Fig. 4 is that present system level fault diagnosis verifies system block diagram；
Fig. 5 is fault reasoning flow chart of the present invention.
Embodiment
The present invention is described in further detail with embodiment below in conjunction with the accompanying drawings.
(1) electronic information equipment failure mode analysis (FMA) is by the integrated information based on equipment, with reference to tested electronic information equipment
Testable parameter deploys.Failure mode analysis (FMA) process include equipment failure model construction, fault signature extraction, fault simulation and
Checking assessment etc..Effective foundation of electronic information equipment fault model can be fault diagnosis system testing algorithm generate and
The application of corresponding fault simulation and inference technology provides the support on system mechanism.
(2) using equipping self structure, functional hierarchy feature, by the analysis and research to equipment failure propagation characteristic,
Hierarchical Programming is carried out in terms of equipping with equipment Failure Modes two, according to equipment and the inner link between failure, establishes stratification
Fault model, make fault diagnosis thinking methodization.
(3) fault diagnosis system is built according to electronic information equipment failure mode analysis (FMA) result, hardware platform is with portable survey
Test instrument, PXI bus instruments, restocking instrument and Fault Insertion Equipment etc. form, and system software platform is to obtain equipment Test number
According to input, the functions such as fault message fusion, fault reasoning diagnosis are realized.
(4) using actual electronic information equipment as identifying object, by the Methods for Diagnosing System Level Malfunctions to actually equipping, and therefore
Hinder diagnostic system self-test, self diagnosis experiment, examine fault detect and failure of the fault diagnosis system to electronic information equipment to push away
Reason ability, verify the reasonability of stratification method for diagnosing faults.
Fig. 1 is electronic information equipment Methods for Diagnosing System Level Malfunctions technology overall plan schematic diagram of the present invention.As illustrated, electronics
Information equipment Methods for Diagnosing System Level Malfunctions technology is divided into the demand analysis of electronic information equipment testing and diagnosing, fault mode and influences to divide
Analysis, stratification fault model structure and testability design optimization, Methods for Diagnosing System Level Malfunctions technique study and software are realized, are system-level
Several respects research contents such as fault diagnosis system is built and fault diagnostic test is verified.Wherein, equipment failure model will combine
Many equipment informations such as equipment configuration feature, equipment Test data, BIT data, equipment failure characteristic parameter, to equipment
Demand analysis is carried out, and electronic information equipment fault model is subjected to stratification decomposition, structure equipment hierarchical model, is filled to be formed
Standby stratification Fault Diagnosis Strategy provides support.
Fig. 2 is failure mode analysis (FMA) protocol procedures figure of the present invention, in electronic information equipment failure mode analysis (FMA), equipment failure
Model construction is extremely important.Multi-signal flow graph model method can be applied to the testability design of complication system, failure mode effect
With criticality analysis, fault diagnosis and testability assess etc..Knowledge base is the important component of fault diagnosis system, main
It is used to deposit the fault signature that the special knowledge of domain expert obtains with emulation reasoning.Knowledge base is according to qualitative analysis
With expertise knowledge, rule and obtain fault signature etc. in practice data form for information about, and with certain knowledge shape
Formula represents.Knowledge base should constantly expand, changes, update, the increase and acquisition of particularly new fault knowledge.
Fig. 3 is present system level stratification Fault Diagnosis Strategy process schematic.First, according to the fault signature of acquisition
Parameter, the system chosen in fault mode level carry out fault reasoning diagnosis, obtained corresponding to preliminary system and diagnostic result
Node A；Equipment level model node S1 corresponding to node A is chosen, the section with node S1 interactions is determined by incidence relation
Point；By the node chosen in hierarchical model is equipped, with reference to the Failure Characteristic Parameter and primary fault diagnostic message of acquisition, pair event
Barrier hierarchical model progress is related to cut out, it is determined that corresponding to the node S1 ' of the second layer in equipment level, diagnosis here
Journey corresponds to diagnosis process in the layer in hierarchy diagnosis；Chosen in the failure subpattern space for being cut out coming the in equipment level
Two node layer S1 ' carry out fault reasoning diagnosis, obtain node B corresponding to failure level result, diagnosis process here corresponds to
Interlayer diagnosis process in hierarchy diagnosis；Equipment level model node S2 corresponding to node B is chosen, is determined by incidence relation with saving
Point S2 interaction node, with reference to acquisition Failure Characteristic Parameter and once, secondary failure diagnostic message, to failure level mould
Type progress is related to cut out, it is determined that corresponding to the node S2 ' of third layer in equipment level, by electronic information equipment fault location
To LRU/LRM.
Fig. 4 is invention Methods for Diagnosing System Level Malfunctions checking system block diagram.Using actual electronic information equipment as checking
Object, constructing system level fault diagnosis checking system, as illustrated, checking system is mainly by tested equipment and fault diagnosis system
Composition.
Fig. 5 is fault reasoning flow chart of the present invention.Tested equipment failure status data is gathered according to fault diagnosis system, will
Major error parameter after feature extraction is as input layer, and fault mode is as output layer, and each layer is hidden layer among remaining.It is right first
Various sign domains carry out artificial neural networks, and the local message that output result is carried out with D-S evidence theory merges, in system
It is middle that single channel output is converted into Evidence Reasoning Model, i.e., normalized is passed through into the single channel output of neutral net,
Directly as the basic probability assignment of each focus element, so as to avoid the complexity of construction Basic probability assignment function, then
Gradually merge the diagnostic message of each passage with the rule of combination of D-S evidence theory, obtain the local diagnosis knot of the sign domain independence
Fruit.
This method according to equipment failure between inner link, by system-level stratification analysis can provide one it is complete
Space, make it is any diagnosis answer can be all found in this space, hierarchical structure can make equipment can during diagnosis
The internal connection systematically reflected between each fault mode, and solve latent fault mode beneficial to according to explicit fault mode；This
Method is based on equipment level, the malfunction reason for the ground analytical equipment that has levels comprehensively, and provides patrolling between associated failure
The relation of collecting, the fault mode level equipped with clear complete expression, guidance is provided to detect, isolating and fix a breakdown；With
Each main gene characteristic parameter acquired based on distributed BIT and outside ATE tests are equipped, is demonstrate,proved using BP neural network and D-S
Carry out positive and negative diagnostic reasoning according to the information fusion method that is combined of theory, that is, be effectively combined diagnostic reasoning system efficiency and
Completeness, so as to meet requirement of the fault diagnosis system to real-time and accuracy.
Claims (4)
1. one kind is used for electronic information equipment stratification method for diagnosing faults, including equipment failure model construction, fault signature carry
Take, fault simulation and checking are assessed, it is characterised in that further comprising the steps of：
Step 1: equipment Failure Modes are analyzed：Pass through user requirements analysis, equipment failure arrangement and firsthand information collection pair first
Equipment carries out hierachical decomposition and testability analysis obtains equipment Failure Modes and impact analysis FMEA reports, and is emulated in TEAMS
System failure model is established in software；With TEAMS simulation softwares according to equipment FMEA simulated injection all kinds failures, to being
Fault signature of uniting extracts, and carries out testing and diagnosing to injection failure, and then verifies the testability of assessment system, obtains simulating, verifying
As a result；
Step 2: structure stratification fault model：According to the simulation results of step 1 to equipment Failure Modes analysis result
Optimize, and then reversely instruct system failure model hierarchyization to optimize；
Step 3: structure fault diagnosis system：The failure mode analysis (FMA) result obtained according to above-mentioned steps one and two and stratification
Fault model, from software and hardware resources, including direct fault location software and hardware configuration, test software and hardware configuration, structure fault diagnosis system
System；
Step 4: change system level fault diagnosis is verified：The equipment Failure Modes obtained according to above-mentioned steps one, two analyze knot
Fruit, direct fault location, fault signature extraction and fault reasoning are carried out to equipment with the fault diagnosis system of step 3 structure and is obtained
Change system fault diagnosis result, the software emulation result for contrasting step 1 is verified to change system level fault diagnosis, complete
System level diagnostic into equipment is tested；
Fault reasoning wherein described in step 4 gathers tested equipment failure status data according to fault diagnosis system, and feature is carried
Major error parameter after taking is as input layer, and fault mode is as output layer, and each layer is hidden layer among remaining；First to various signs
Million domains carry out artificial neural networks, and the local message that output result is carried out with D-S evidence theory merges, in systems will be single
Passage output is converted into Evidence Reasoning Model, i.e., the single channel output of neutral net is passed through into normalized, directly made
For the basic probability assignment of each focus element, so as to avoid the complexity of construction Basic probability assignment function, then demonstrate,proved with D-S
Gradually merge the diagnostic message of each passage according to the rule of combination of theory, obtain the local diagnosis result of the sign domain independence.
2. one kind as claimed in claim 1 is used for electronic information equipment stratification method for diagnosing faults, it is characterised in that wherein
It is more that described equipment failure model will combine equipment configuration feature, equipment Test data, BIT data, equipment failure characteristic parameter
The equipment information of aspect, demand analysis is carried out to equipment.
3. one kind as claimed in claim 1 is used for electronic information equipment stratification method for diagnosing faults, it is characterised in that described
Fault diagnosis system also include knowledge base, for depositing the special knowledge and the obtained failure of emulation reasoning of domain expert
Feature；Knowledge base is according to qualitative analysis and expertise knowledge, rule and obtains fault signature in practice for information about
Data forms, and is represented with certain knowledge form.
4. one kind as claimed in claim 1 is used for electronic information equipment stratification method for diagnosing faults, it is characterised in that wherein
The optimization of stratification fault model comprises the following steps：
4.1 according to the Failure Characteristic Parameter of acquisition, and the system chosen in fault mode level carries out fault reasoning diagnosis, obtained just
Node A corresponding to the system and diagnostic result of step；
4.2 choose equipment level model node S1 corresponding to node A, and the section with node S1 interactions is determined by incidence relation
Point；
4.3 node by being chosen in stratification fault model, letter is diagnosed with reference to the Failure Characteristic Parameter and primary fault of acquisition
Breath, it is related to the progress of stratification fault model to cut out, it is determined that the node S1 ' corresponding to the second layer in equipment level；
4.4 choose the second node layer S1 ' of equipment from the failure subpattern space for being cut out carries out fault reasoning diagnosis, obtains
Node B corresponding to failure level result；
4.5 choose equipment level model node S2 corresponding to node B, and the section with node S2 interactions is determined by incidence relation
Point, it is related to the progress of stratification fault model to cut out with reference to the Failure Characteristic Parameter and failure diagnosis information of acquisition, it is determined that
Corresponding to the node S2 ' of third layer in equipment level, by electronic information equipment fault location.
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