Failure analysis expert system based member failure mode detection method

An expert system and failure analysis technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as easy loss, low work efficiency, effective storage and full utilization of unfavorable knowledge, and achieve the goal of avoiding human factors Effects of interference, improving the accuracy of analysis, and making up for the lack of personal knowledge and experience

Inactive Publication Date: 2011-05-11
AVIC BEIJING INST OF AERONAUTICAL MATERIALS
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The traditional failure mode detection method is to use manual judgment based on failure information. There are certain problems in this judgment method. For example, judging the failure mode requires rich knowledge and experience, and training an experienced failure analysis engineer or expert It will take several years, and the expert will always leave the job, and the knowledge he possesses will go with him; in addition, in the process of failure analysis, it is often necessary to refer to previous similar faults, and similar faults in the past are usually presented in the form of paper media. The form is scattered everywhere and is easy to lose, which is not conducive to the effective storage and full utilization of knowledge; moreover, in the process of failure analysis, failure analysts may have certain human factors due to the interests of the unit, and the work efficiency is low

Method used

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  • Failure analysis expert system based member failure mode detection method
  • Failure analysis expert system based member failure mode detection method
  • Failure analysis expert system based member failure mode detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0041] After a long test run on the ground, the transmission bevel gear found that the tooth surface of the gear was partially peeled off, accompanied by strip scratches. It is necessary to judge the failure mode of the detected gear. Firstly, the failure analysis of the gear was investigated, observed and tested, and the results are as follows:

[0042] Part name: gear

[0043] Material type: 18CrNi4A carburized and nitrided steel

[0044] Material analysis result: the material is qualified

[0045] Load Type: Contact Fatigue Load

[0046] Crack microscopic growth: transgranular

[0047] Failure location: stress concentration

[0048] Thermal processing technology: die forging

[0049] Microscopic view of fracture growth zone: fatigue bands, secondary cracks

[0050] Environment - Media: Lubricant

[0051] Appearance features: peeling, small pits, wear

[0052] Before using the expert system to detect the failure mode, the observation and measurement information of th...

Embodiment 2

[0055] Austenitic stainless steel springs need to determine their failure mode. First, investigate, observe and test the failure information of the spring, the results are as follows:

[0056] Part Name: Spring

[0057] Material Type: Austenitic Stainless Steel

[0058] Material analysis result: the material is qualified

[0059] Failure location: Defect area caused by corrosion

[0060] Observation results of macroscopic characteristics of cross-section: fatigue arc

[0061] Observation results of microscopic characteristics of the fracture: the expansion zone is fatigue strips and mud patterns, and the instantaneous fracture zone is dimples

[0062] Environment-medium: corrosive medium

[0063] Appearance features: fractures, corrosion pits

[0064] Using the same method as case 1, input the failure information of this case into the failure analysis expert system, and randomly give the case code 263. click figure 1 Click the "Analogical Reasoning System" button in th...

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Abstract

The invention belongs to a member failure analysis technology and relates to a failure analysis expert system based member failure mode detection method on the basis of acquiring failure information. In the invention, a computer is used for assisting a failure analysis expert system to detect a member failure mode, thus the method can quickly and accurately help failure analysis personnel to carry out failure analysis and avoid the interference of artificial factors and can also make up the deficiencies of personal knowledge and experiences, improve the analysis accuracy and shorten the analysis period. With the method, the conditions of appearance, macroscopic views, microcosmic views, and the like of the failure structural piece are sufficiently analyzed, and analysis on the failure mode and the failure mechanism of the failure piece is carried out by combining the failure information such as the material, the load, the environment, and the like of the failure piece, thereby the analysis accuracy of the failure structural piece is improved.

Description

technical field [0001] The invention belongs to component failure analysis technology, and relates to a component failure mode detection method based on a failure analysis expert system on the basis of collecting failure information. Background technique [0002] After the component fails, the failure mode detection is the premise and important basis for giving the failure cause, and it is a necessary means to prevent the recurrence of similar accidents. The failure mode detection is based on the failure information obtained through investigation, observation and testing. Apply the method of logical reasoning to detect and judge the failure mode of the faulty parts. The so-called failure mode refers to the external macroscopic manifestation and process law of failure, which can be understood as the nature and type of failure. [0003] The traditional failure mode detection method is to use manual judgment based on failure information. There are certain problems in this judg...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
Inventor 刘新灵白明远陶春虎胡春燕张兵
Owner AVIC BEIJING INST OF AERONAUTICAL MATERIALS
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