Rotating machinery fault diagnosis method based on independent component analysis and correlation criteria

A technology of independent component analysis and rotating machinery, applied in the direction of measuring devices, computer parts, machine/structural parts testing, etc., can solve the difficult artificial intelligence diagnosis algorithm input vector, independent component analysis amplitude and order uncertainty and other issues to achieve good use value and improve accuracy

Active Publication Date: 2020-09-22
HANGZHOU ZETA TECH
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AI Technical Summary

Problems solved by technology

[0004] Due to the amplitude and order uncertainty of independent component analysis, it is difficult to be used as the input vector of artificial intellige

Method used

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  • Rotating machinery fault diagnosis method based on independent component analysis and correlation criteria
  • Rotating machinery fault diagnosis method based on independent component analysis and correlation criteria
  • Rotating machinery fault diagnosis method based on independent component analysis and correlation criteria

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Embodiment Construction

[0061] In order to make the purpose, technical solution and advantages of the present invention more clear, further detailed description will be made in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention.

[0062] First of all, it needs to be explained that the present invention relates to signal processing and artificial intelligence technology, and is an application of computer technology in the field of mechanical equipment operation. During the implementation of the present invention, the application of multiple software function modules will be involved. The applicant believes that, after carefully reading the application documents and accurately understanding the realization principle and purpose of the present invention, combined with existing known technologies, those skilled in the art can fully implement the present inve...

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Abstract

The invention relates to signal processing and artificial intelligence, and aims to provide a rotating machinery fault diagnosis method based on independent component analysis and correlation criteria. The method comprises the steps of: measuring multi-channel vibration signals of the rotating machine, and performing transformation through an independent component analysis algorithm; selecting a separation signal based on a correlation criterion and a Bayesian information criterion, and extracting a fault feature vector; and training and diagnosing the diagnosis model of a rotary machine support vector machine, inputting the feature vector R into the model to perform fault diagnosis on the rotary machine, classifying diagnosis results according to a preset judgment condition, and giving analarm. According to the method, the problem that previous independent component analysis is only applied to artificial diagnosis and is rarely applied to artificial intelligence diagnosis is solved,and the accuracy of fault diagnosis of the rotary machine is improved to a greater extent, so that the method has a very good use value.

Description

technical field [0001] The invention relates to the application of signal processing and artificial intelligence in mechanical fault diagnosis, in particular to an artificial intelligence fault diagnosis method based on independent component analysis and correlation maximization criterion for rotating machinery. Background technique [0002] Rotating machinery is a very important and widely used type of mechanical equipment in the industrial field, such as fans, water pumps, compressors, etc., and plays an important role in various industrial fields. During the working process of rotating machinery, it is inevitable that large or small faults will occur. These faults may cause economic losses in the slightest, and cause casualties in severe cases. Therefore, the fault diagnosis of rotating machinery plays a very important role in the industrial field. The research on fault diagnosis methods has never stopped. [0003] At present, most of the fault diagnosis of rotating mach...

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Application Information

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IPC IPC(8): G01M99/00G06K9/00G06K9/62
CPCG01M99/005G01M99/004G06F2218/06G06F2218/08G06F2218/12G06F18/2134G06F18/2411
Inventor 汪抑非黄志龙付立柴秋子李创吕巧玲王绪康沈新荣
Owner HANGZHOU ZETA TECH
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