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Rolling bearing fault diagnosis method

A rolling bearing and fault diagnosis technology, applied in knowledge expression, instrument, character and pattern recognition, etc.

Inactive Publication Date: 2016-11-16
SHANGHAI DIANJI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] The technical problem to be solved by the present invention is: It is difficult to make an accurate assessment of the working health status of rolling bearings by using traditional time domain and frequency domain methods

Method used

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Embodiment Construction

[0048] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0049] A rolling bearing fault diagnosis method based on an improved fractal box dimension algorithm and an adaptive gray correlation theory algorithm provided by the present invention includes the following steps:

[0050] Step 1. Sampling the vibration signals of the target rolling bearing in the rotating machinery under normal operating conditions and different failure modes to obtain bearing vibration signal data samples, w...

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Abstract

The invention discloses an improved fractal box dimension algorithm and self-adaptive grey relation theory algorithm-based rolling bearing fault diagnosis method. The method comprises the following steps of: firstly extracting fault features (comprising information which is capable of reflecting different working sates of a bearing, and is more useful and easier to distinguish) from bearing vibration signals through an improved fractal box dimension; and automatically recognizing fault types of the bearing and different severity degrees through a self-adaptive grey relation theory algorithm. The invention aims at solving the problem that the traditional time domain and frequency domain methods are difficult to correctly estimate the working health conditions of rolling bearings, so that different rolling bearing fault types and fault severity degrees can be correctly and effectively recognized.

Description

technical field [0001] The invention relates to a rolling bearing fault diagnosis method based on an improved fractal box dimension algorithm and an adaptive gray correlation theory algorithm. Background technique [0002] As an important component, rolling bearings are widely used in almost all types of rotating machinery. Rolling bearing failure is one of the most important causes of failure and damage of rotating machinery, and brings huge economic losses. In order to ensure reliable operation of the unit and reduce economic losses, it is extremely necessary to develop a reliable and effective rolling bearing fault diagnosis method. Among the many bearing fault diagnosis methods, the diagnosis method based on vibration signal has received extensive attention in the past few decades. [0003] The vibration signal of the bearing contains rich information on the health status of the machine, which also makes it possible to extract the dominant features representing the hea...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N5/02
CPCG06N5/022G06F2218/08G06F2218/12
Inventor 李靖超应雨龙王英赫董春蕾
Owner SHANGHAI DIANJI UNIV
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