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Rolling bearing performance degradation feature extraction method and system

A rolling bearing and feature extraction technology, applied in special data processing applications, testing of machine/structural components, testing of mechanical components, etc., can solve problems such as fault detection time lag, feature component noise signal submergence, and signal complexity changes, etc. Achieve the effect of enhancing sensitivity, reducing interference, and improving safety of use

Pending Publication Date: 2022-05-03
中国人民解放军战略支援部队航天工程大学士官学校
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a rolling bearing performance degradation feature extraction method and system to solve the problem that the feature components in the early stage of rolling bearing faults are easily submerged by noise signals, which is not enough to cause significant changes in signal complexity and cause a delay in fault detection time

Method used

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  • Rolling bearing performance degradation feature extraction method and system
  • Rolling bearing performance degradation feature extraction method and system
  • Rolling bearing performance degradation feature extraction method and system

Examples

Experimental program
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Effect test

Embodiment 1

[0049] Such as figure 1 As shown in the flow chart, this embodiment provides a rolling bearing performance degradation feature extraction method, including the following steps:

[0050]A1. Decompose the vibration signal of the rolling bearing based on the adjustable wavelet transform of different Q factors, and obtain the wavelet transform coefficients of each frequency band under different Q factors; the vibration signal of the rolling bearing is the vibration signal of the rolling bearing during the running time period.

[0051] A2, process the wavelet transform coefficients of each frequency band under each Q factor into the distribution probability of feature energy in each frequency band, calculate the Shannon entropy of each Q factor, and step A2 specifically includes:

[0052] The wavelet transform coefficients of each frequency band under each Q factor are expressed as the distribution probability of the characteristic energy in each frequency band under the correspond...

Embodiment 2

[0075] In addition, the method of embodiment 1 of the present invention can also be by means of image 3 The architecture of a rolling bearing performance degradation feature extraction system is shown to achieve. Such as image 3 As shown, the rolling bearing performance degradation feature extraction system may include an adjustable wavelet transform unit 1, a Shannon entropy calculation unit 2, an optimal Q factor determination unit 3, an optimal wavelet transform coefficient determination unit 4, a sparse representation unit 5, and a permutation entropy calculation unit Unit 6 and alarm threshold determination unit 7; some modules may also have subunits for realizing their functions. certainly, image 3 The architecture shown is just an example. When implementing different functions, according to actual needs, you can omit image 3 One or at least two components of the system shown.

[0076] The program part in the technology can be regarded as a "product" or "article"...

Embodiment 3

[0079] The method for extracting the performance degradation feature of the rolling bearing provided by the present invention will be described in detail below by way of specific examples.

[0080] When using permutation entropy to reflect the degradation trend of rolling bearing performance, only by minimizing or eliminating the interference caused by noise components can the high sensitivity of permutation entropy to rolling bearing state changes be guaranteed. Taking the rolling bearing fault simulation signal as an example, after superimposing white noise according to different signal-to-noise ratios, the corresponding permutation entropy values ​​are shown in Table 1 below.

[0081] Table 1

[0082]

[0083] It can be seen that the arrangement entropy value of the rolling bearing signal has a significant difference with or without noise interference, and increases with the enhancement of the noise component, so the existence of noise tends to increase the signal arrang...

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Abstract

The invention provides a rolling bearing performance degradation feature extraction method and system, and the method comprises the steps: carrying out the decomposition of a vibration signal of a rolling bearing based on the adjustable wavelet transformation of different Q factors, and obtaining the wavelet transformation coefficients of all frequency bands under different Q factors; the Shannon entropy of each Q factor is calculated, and the Q factor with the minimum Shannon entropy is determined as the optimal Q factor; according to the wavelet transform coefficient of each frequency band under the optimal Q factor, determining the optimal wavelet transform coefficient of the optimal Q factor by adopting a split augmented Lagrange search algorithm; calculating a sparse representation result of the vibration signal of the rolling bearing according to the optimal wavelet transform coefficient of the optimal Q factor; according to a permutation entropy algorithm, calculating a permutation entropy value corresponding to the sparse representation result; and determining a permutation entropy curve capable of reflecting the performance state change of the rolling bearing according to the permutation entropy value.

Description

technical field [0001] The invention relates to the technical field of bearing performance monitoring, in particular to a rolling bearing performance degradation feature extraction method and system. Background technique [0002] Rolling bearings are widely used in various rotating machinery. Statistical results show that the failure of rotating machinery equipment caused by rolling bearings accounts for about 30%. Therefore, by extracting the performance degradation characteristics of rolling bearings, the performance degradation trend of rolling bearings can be effectively monitored, the initial fault can be identified as early as possible, and the best maintenance can be determined. Timing, on the basis of avoiding unexpected downtime of equipment, is crucial to improving the utilization and safety of various rotating machinery. Among various monitoring information sources, the vibration signal of rolling bearing contains the information of the damage existence and fault ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/045G06F17/14
CPCG01M13/045G06F17/148
Inventor 马伦张亮孙丽慧苑改红焦志鑫徐祥红吕艳军周宇
Owner 中国人民解放军战略支援部队航天工程大学士官学校
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