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Method for fault diagnosis of rotating mechanical equipment based on interval-type evidence fusion

A technology of rotating mechanical equipment and evidence fusion, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as insufficient capacity

Active Publication Date: 2011-04-27
TSINGHUA UNIV
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Problems solved by technology

[0003] In the face of the complex correspondence between failure modes and their characteristics, as well as various uncertain factors in the diagnosis process, the capabilities of traditional single-sensor, single-factor monitoring and diagnosis methods are insufficient.

Method used

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  • Method for fault diagnosis of rotating mechanical equipment based on interval-type evidence fusion
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  • Method for fault diagnosis of rotating mechanical equipment based on interval-type evidence fusion

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Embodiment Construction

[0050] The fault diagnosis method for rotating mechanical equipment based on interval type evidence fusion proposed by the present invention, its flow chart is as follows figure 1 shown, including the following steps:

[0051] (1) Set the fault set of rotating mechanical equipment as Θ={F 1 ,...,F j ,...,F N}, F j Represent the jth fault in the fault set Θ, j=1, 2, ..., N, N is the number of faults;

[0052] (2) Let x be a fault characteristic parameter of the fault set Θ, and establish a fault model model of the fault characteristic parameter x for fault F j A membership function set of , Get the membership function set The steps of each membership function in are as follows:

[0053] (2-1) Observe each fault F in the fault set Θ j The fault characteristic parameter x of the fault is recorded continuously for 30 to 50 times, and the observation results are recorded as one group, and a total of m groups of observations are carried out, 5≤m≤10;

[0054] (2-2) Calcu...

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Abstract

The invention relates to a method for fault diagnosis of rotating mechanical equipment based on interval-type evidence fusion, belonging to the technical field of fault monitoring and diagnosis of rotating mechanical equipment. The method is based on statistical analysis of typical fault data, comprising the following steps: building a set of fuzzy membership functions, and modeling each fault model mode in a fault archival repository by using the set of functions; modeling a fault inspection pending mode extracted during on-line monitoring by using a single membership function; matching the inspection pending mode with each model mode to obtain a reliability match interval of each fault supported by the inspection pending mode; providing an interval-type diagnostic evidence method obtained from the reliability interval by using the Monte Carlo Latin Hypercube sampling method; and fusing evidences, and then under the decision criterion, making the fault decision according to the fusion result. The decision based on the multi-evidence fusion result is more accurate than the decision made by the single-evidence fusion.

Description

technical field [0001] The invention relates to a method for fault diagnosis of rotating machinery equipment based on interval type evidence fusion, and belongs to the technical field of fault monitoring and diagnosis of rotating machinery equipment. Background technique [0002] Online fault diagnosis technology is a powerful guarantee for the safe production and efficient operation of rotating machinery equipment, but the implementation of this type of technology still faces many challenges: due to the uncertainty of the occurrence of faults, it is usually difficult to obtain the value of "0" or " The failure probability is 1", that is, the failure often has the characteristics of randomness or ambiguity; the cause of the failure is more complicated, and usually the same failure can show multiple characteristics, and the same failure characteristic may be caused by different failures; in addition, due to The measurement error of the sensor itself or the limited monitoring ...

Claims

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Application Information

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IPC IPC(8): G06F17/50
Inventor 周东华徐晓滨吉吟东孙新亚冯海山
Owner TSINGHUA UNIV
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