CN103854075A - Failure predicting method and device aiming at electronic single chip under hot standby environment - Google Patents
Failure predicting method and device aiming at electronic single chip under hot standby environment Download PDFInfo
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- CN103854075A CN103854075A CN201410115371.4A CN201410115371A CN103854075A CN 103854075 A CN103854075 A CN 103854075A CN 201410115371 A CN201410115371 A CN 201410115371A CN 103854075 A CN103854075 A CN 103854075A
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Abstract
The invention discloses a failure predicting method and a failure predicting device aiming at an electronic single chip under a hot standby environment. The method comprises the following steps: predicting the failure of an electronic device by using a combinational algorithm of an expert system and a gray prediction model, designing a corresponding knowledge table and realizing a reasoning process by using a quick matching method of rules. The device comprises a controller module, a power supply module, a touch display screen, an LED (Light Emitting Diode) alarm module, a test bench chassis, a data collecting and caching module, a gray prediction module and an expert system module. Through the method and the device, latent failures of the electronic single chip can be efficiently and accurately predicted in real time, so that the guarantee for reliable operation of the electronic single chip of the device can be provided.
Description
Technical field
The invention belongs to electronics unit failure prediction technical field, relate in particular to a kind of for failure prediction method and predict device under the hot standby environment of electronics unit.
Background technology
Along with contemporary electronic systems and scientific and technical developing rapidly, contemporary electronic systems increasingly maximizes and is complicated, and function is more and more, structure also becomes increasingly complex, and the loss that stops causing because of electronic system fault also will increase greatly.Failure mechanism to electronic system is furtherd investigate, in the virtual condition monitoring to system, trend analysis and may break down on the basis of predicting, fault is eliminated in " depending on the feelings maintenance " and " Predictive Maintenance " of bud and will be become the following developing direction that ensures maintenance of electronic system.Predictive Maintenance is the fault law formulation maintenance schedule according to electronic system, to ensure that it possesses certain time between failures in Future direction, ensures completing smoothly of Training And Operations task.
At present, the research work of fault diagnosis field mainly concentrates on state evaluation and the fault diagnosis aspect of Study system, what be concerned about is the running status of system " current ", and whether system fault, location of fault etc. have occurred, less to the research of system failure prognostics and health management.But in actual production process, the operating conditions of many productions requires harsher, the consequence that fault produces is more serious, if only know whether current operating mode normally just seems not much of that, because may be finding when fault that operating mode is in dangerous operating area, now operator is difficult to system condition to return to normal region, although or operating mode can be returned to normal region, have a strong impact on the economic benefit of producing.Electronic system is carried out status monitoring and estimated its health status, realize the prediction to its state, according to the probability of its health status precognition electronic system complete failure, and can make early prediction to the propagation and development of fault, so just can prevent and greatly reduce the loss that bust causes.
Summary of the invention
The technical problem to be solved in the present invention is, overcomes the defect that prior art exists, and provides failure prediction equipment and Forecasting Methodology under the hot standby environment of electronics unit that a kind of efficiency is high, in order to the Security Trend of predict electronic unit operation.
To achieve these goals, the technical scheme that the present invention proposes is: failure prediction method under the hot standby environment of a kind of electronics unit, described method comprises the steps:
Step 1: for the feature of electronic equipment, analyze and extract its fault mode, structure, function to typical unit are understood in depth, specify its main composition, function, mode of operation etc., mainly for be typical unit, in fact mainly consider the fault of its electronic equipment;
Step 2: build the typical fault pattern base under hot standby environment, sum up and extract existing fault mode, typical fault pattern is analyzed, build the typical fault pattern base under hot standby environment;
Step 3: by the signal of data acquisition module real-time acquisition system running status, the data that collect are converted to the data type that failure prediction module needs after data processing;
Step 4: extract corresponding failure symptom information by the typical fault pattern base of setting up, set up criterion storehouse, realize status monitoring and failure prediction by criterion reasoning algorithm;
Step 5: failure prediction module adopts two kinds of prediction algorithms, the failure prediction algorithm of employing based on gray level model predicted the state variation of measuring point, then using the predicted value of measuring point as measuring point information, adopt the failure prediction algorithm based on criterion to complete reasoning, realize failure prediction, finally by data communication interface, failure prediction result is presented on touch display screen.
In addition, the invention provides the failure prediction equipment under the hot standby environment of a kind of electronics unit, comprise controller module, power module, liquid crystal display, test board cabinet, data acquisition cache module, gray scale prediction module, expert system module.
Described controller module selects the conventional PLC of Industry Control as core devices, is mainly used in carrying out the collection, monitoring, communication, storage of data etc.;
Described power module is for providing 24V DC voltage to power module, liquid crystal display and test board cabinet;
Described touch display screen is used for the information that the users such as display working condition need to observe, and is convenient to carry out input and the display device monitoring result in service of correlation parameter and predict the outcome;
Described test board cabinet is mainly used in installing integrated various interface, comprises the output of 24V power supply, analog quantity and digital quantity interface, communication interface, status lamp and button etc.
Described data acquisition cache module is used for obtaining the data of 8 passages that gather from analog input port, and is stored in corresponding storage unit;
Described gray scale prediction module, when receiving after the predictable signal of data cache module transmission, reads 8 data array from data cache module, and carries out gray scale prediction, and result of calculation is 8 status predication values, and gives expert reasoning system by result;
Described expert system module is used to the gray scale predicted state value of 8 analog channel image data, adopting an Output rusults is the status predication to tested electronics unit, comprise contingent fault and fault type, and the maintenance of tested electronics unit is advised.
The invention has the advantages that:
(1), the present invention has realized the failure prediction under the hot standby environment of electronics unit, the security that has improved electronics unit operation.
(2), the present invention can realize the input of correlation parameter and the monitoring of fault demonstration by friendly human-computer interaction interface.
(3), the present invention can carry out efficient, accurate, real-time failure prediction to tested electronics unit, stable performance, reliability are high.
Brief description of the drawings
Fig. 1 is fault prediction expert system basic block diagram of the present invention.
Fig. 2 is the combined fault prediction algorithm block diagram under the hot standby environment of electronics unit of the present invention.
Fig. 3 is failure prediction algorithm process flow diagram of the present invention.
Fig. 4 is the failure prediction equipment structure chart under the hot standby environment of electronics unit of the present invention.
Embodiment
Below in conjunction with structure and the process flow diagram of accompanying drawing, embodiments of the invention are elaborated.Should be emphasized that, following explanation is only exemplary, instead of in order to limit the scope of the invention and to apply.
Method provided by the invention comprises:
Step 1: for the feature of electronic product, analyze and extract its fault mode, structure, function to typical unit are understood in depth, specify its main composition, function, mode of operation etc., mainly for be typical unit, in fact mainly consider the fault of its electronic equipment; For example, for general purpose diode, extract and know that its main fault omen parameter has by analysis: inverse current leakage, forward voltage drop, thermal resistance, power consumption and radio frequency noise, therefore can predict its incipient fault by detecting these fault omen parameters for general purpose diode.
Step 2: build the typical fault pattern base under hot standby environment, sum up and extract existing fault mode, typical fault pattern is analyzed, build the typical fault pattern base under hot standby environment; Under the hot standby environment of electronic product, typical fault pattern base mainly comprises failure symptom, the failure symptom of amplifier and the failure symptom of field effect transistor etc. of Switching Power Supply.
Step 3: by the signal of data acquisition module real-time acquisition system running status, the data that collect are converted to the data type that failure prediction module needs after data processing;
Step 4: extract corresponding failure symptom information by the typical fault pattern base of setting up, set up criterion storehouse, realize status monitoring and failure prediction by criterion reasoning algorithm; Electronic product is aging gradually along with the growth of service time, and the characteristic of its circuit also will be degenerated thereupon.Therefore, on the failure mode of device, circuit and system and the basis of criticality analysis (FMEA), the suitable physical amount of choosing and lost efficacy relevant, if frequency response, enlargement factor, matched impedance etc. are as fault tendency or indication, set up failure prediction model, by monitoring selected circuit characteristic parameter, can evaluation electronics and the performance of electronic equipment, the fault of prediction device and equipment.
Step 5: failure prediction module adopts two kinds of prediction algorithms, the failure prediction algorithm of employing based on gray level model predicted the state variation of measuring point, then using the predicted value of measuring point as measuring point information, adopt the failure prediction algorithm based on criterion to complete reasoning, realize failure prediction, finally by data communication interface, failure prediction result is presented on touch display screen.By failure symptom parameter input channel 1 data of electronics unit, at the input interface access measurand passage 1 of failure prediction equipment, other passage accesses the data in its normal range of operation.Under normal condition, each channel data is all in corresponding regime values scope, the test later stage, the numerical value of the failure symptom parameter of passage 1 declines gradually, gray scale predicted state value also reduces gradually, to finally reaching failure symptom value, expert system receives the gray scale predicted data being obtained by actual data measured, in conjunction with sign table, rule list and conclusion table that before prediction, expert system arranges, it is concrete failure message that expert system is exported true blackboard, and provide red light warning, fault picture provides failure prediction conclusion.
Fig. 1 is expert system structure figure, and expert system is a kind of calculation procedure of knowledge-based inference, solves a certain professional domain problem for simulating human expert.Expert system comprises man-machine interface, inference machine, knowledge base, Knowledge Management System, explanation module and six parts of dynamic data base.Wherein knowledge base and inference machine are the most basic, most important two modules of expert system.
Fig. 2 is combined fault prediction algorithm block diagram.According to the concrete feature of research object, first fault prediction system selects appropriate Numerical model, then by prediction module, historical data is made a prediction, give diagnostic system numerical prediction result, form diagnostic event, by diagnostic system, predicted value is made to diagnosis, send display screen diagnostic result, make failure prediction.
Fig. 3 is failure prediction algorithm process flow diagram, and flow process is as follows:
First systematic sampling time T, predicted time length T S, prediction dimension m, measuring point quantity N are set.
After system brings into operation, can read from input port the data of N measuring point at interval of time T, and deposit storer in.
Each measuring point memory stores data amount is m(prediction dimension), in the time that data volume exceedes m, system can be by data cover early in historical data, and new data is added.
When measuring point data amount reaches m, start fault model predicted method, during to the following moment TS of current measuring point, state value is estimated, then result is given to expert system and carries out reasoning, finally shows result.
Before diagnosing, in the calculator memory that expert system will be moved in system in advance, be written into knowledge base, knowledge base insmods and has moved before the operation of Fault Quick Diagnosis module, the pattern being written into due to rule will determine method, the usefulness of rule match and reasoning, be the technique guarantee of quick diagnosis, therefore rule is written into the important component part that pattern is Fault Quick Diagnosis technology.
Rule Fast Match Algorithm adopts operation of bits pattern to mate, and this kind of method is better than the common recycle ratio adopting compared with reasoning algorithm on matching speed, ensured rapidity and the accuracy of fault diagnosis.
Expert system receives after the status data of being estimated by model prediction, is deposited in measuring point table storer, gives and closes sign table, rule list and the conclusion table that expert system has been set up, and adopts forward reasoning can obtain diagnosis.In expert system, first program will set up its true blackboard and result blackboard, so-called blackboard is exactly a data storage area, and what in true blackboard, store is that system detects the sign variable obtaining, and before diagnosis, need to arrange true blackboard according to sign variable content.
After reasoning finishes, on conclusion blackboard, obtain the conclusion number of failure symptom, in order by conclusion numbering, conclusion footnote, conclusion countermeasure is presented on display screen, and reminding user has failure symptom.
Fig. 4 is the failure prediction equipment structure chart under the hot standby environment of electronics unit.As shown in Figure 4, the failure prediction equipment under the hot standby environment of a kind of electronics unit, comprises controller module, power module, touch display screen, LED alarm module, test board cabinet, data acquisition cache module, gray scale prediction module and expert system module.
Described controller module selects PLC as core devices, is mainly used in carrying out the collection, monitoring, communication, storage of data etc.;
Described power module is for providing 24V DC voltage to power module, liquid crystal display and test board cabinet;
Described touch display screen is used for the information that the users such as display working condition need to observe, and is convenient to carry out input and the display device monitoring result in service of correlation parameter and predict the outcome;
Described LED alarm module is for providing mark to the current running status of equipment under test;
Described test board cabinet is mainly used in installing integrated various interface, comprises the output of 24V power supply, analog quantity and digital quantity interface, communication interface, status lamp and button etc.;
Described data acquisition cache module is used for obtaining the data of 8 passages that gather from analog input port, and is stored in corresponding storage unit;
Described gray scale prediction module, when receiving after the predictable signal of data cache module transmission, reads 8 data array from data cache module, and carries out gray scale prediction, and result of calculation is 8 status predication values, and gives expert system by result;
Described expert system module is used to the gray scale predicted state value of 8 analog channel image data, and adopting an Output rusults is the status predication to tested electronics unit, comprises contingent fault and fault type, and the maintenance of equipment is advised.
Table 1 is some test results of the failure prediction test carried out for exemplary electronic unit PLC:
Table 1 electronics unit failure prediction integration test table
For the fault type of prediction scheme, can obtain table 2 data below according to table 1 test result above:
Table 2
| Test duration | Correct forecast | False-alarm number | Fail to report number |
| XXXX | 7 | 0 | 0 |
This failure prediction equipment can be realized 8 channel data monitorings and status predication, 7 kinds of typical fault patterns setting up are reached to 100% failure prediction, and false alarm rate is 0.
Two kinds of algorithms of integration test failure prediction equipment correct, failure prediction equipment various functions is normal, and failure prediction equipment reaches 100% failure prediction to 7 kinds of typical fault patterns setting up, and false alarm rate is 0.
The above; it is only preferably embodiment of the present invention; but protection scope of the present invention is not limited to this; any be familiar with those skilled in the art the present invention disclose technical scope in; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention, therefore; of the present invention, protection domain should be as the criterion with the protection domain of claim.
Claims (2)
1. for the failure prediction method under the hot standby environment of electronics unit, it is characterized in that described method comprises:
Step 1: for the feature of electronics stand-alone device, analyze and extract its fault mode;
Step 2: build the typical fault pattern base under hot standby environment, sum up and extract existing fault mode, typical fault pattern is analyzed, build the typical fault pattern base under hot standby environment;
Step 3: by the signal of data acquisition module real-time acquisition system running status, the data that collect are converted to the data type that failure prediction module needs after data processing;
Step 4: extract corresponding failure symptom information by the typical fault pattern base of setting up, set up criterion storehouse, realize status monitoring and failure prediction by criterion reasoning algorithm;
Step 5: failure prediction module adopts two kinds of prediction algorithms, the failure prediction algorithm of employing based on gray level model predicted the state variation of measuring point, then using the predicted value of measuring point as measuring point information, adopt the failure prediction algorithm based on criterion to complete reasoning, realize failure prediction, finally by data communication interface, failure prediction result is presented on touch display screen.
2. for the failure prediction equipment under the hot standby environment of electronics unit, it is characterized in that: comprise controller module, power module, touch display screen, LED alarm module, test board cabinet, data acquisition cache module, gray scale prediction module and expert system module;
Described controller module selects PLC as core devices, for carrying out collection, monitoring, communication and the storage of data;
Described power module is for providing corresponding DC voltage to power module, liquid crystal touch display screen and test board cabinet;
Described touch display screen is used for the information that the users such as display working condition need to observe, and is convenient to carry out input and the display device monitoring result in service of correlation parameter and predict the outcome;
Described LED alarm module is for providing mark to the current running status of equipment under test;
Described test board cabinet is mainly used in installing integrated various interface, comprises the output of 24V power supply, analog quantity and digital quantity interface, communication interface, status lamp and button;
Described data acquisition cache module is used for obtaining the data of 8 passages that gather from analog input port, and is stored in corresponding storage unit;
Described gray scale prediction module, when receiving after the predictable signal of data cache module transmission, reads 8 data array from data cache module, and carries out gray scale prediction, and result of calculation is 8 status predication values, and gives expert system module by result;
Described expert system module is used to the gray scale predicted state value of 8 analog channel image data, adopting an Output rusults is the status predication to tested electronics unit, comprise contingent fault and fault type, and the maintenance of tested electronics unit is advised.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107024915A (en) * | 2016-02-02 | 2017-08-08 | 同济大学 | A kind of power system controller board faults detecting system and detection method |
| CN111768113A (en) * | 2020-07-03 | 2020-10-13 | 许艳杰 | Public cloud-based hydraulic engineering management system and method |
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- 2014-03-25 CN CN201410115371.4A patent/CN103854075A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107024915A (en) * | 2016-02-02 | 2017-08-08 | 同济大学 | A kind of power system controller board faults detecting system and detection method |
| CN107024915B (en) * | 2016-02-02 | 2019-10-01 | 同济大学 | A kind of power system controller board faults detection system and detection method |
| CN111768113A (en) * | 2020-07-03 | 2020-10-13 | 许艳杰 | Public cloud-based hydraulic engineering management system and method |
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