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Rolling bearing fault real-time monitoring method

A rolling bearing and real-time monitoring technology, which is applied in mechanical bearing testing, measuring devices, testing of mechanical components, etc., can solve problems such as inaccurate real-time monitoring, achieve weak signal fault diagnosis, suppress smooth noise, and have low computational complexity Effect

Inactive Publication Date: 2019-04-05
北京谛声科技有限责任公司
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, an embodiment of the present invention provides a method for real-time monitoring of rolling bearing faults to solve the problem of inaccurate real-time monitoring of rolling bearings in the prior art

Method used

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  • Rolling bearing fault real-time monitoring method

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Embodiment Construction

[0038] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0039] In order to illustrate the technical solutions of the present invention, specific examples are used below to illustrate.

[0040] Such as figure 1 As shown, the rolling bearing fault real-time monitoring method includes:

[0041] Step S101, obtaining the vibration signal x of the rolling bearing N (n), and for the vibration signal x N (n) Perform discrete Fourier transform to obtain sig...

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Abstract

The invention relates to the technical field of bearing fault monitoring, and provides a rolling bearing fault real-time monitoring method. A rolling bearing vibration signal x<N>(n) is acquired, anddiscrete Fourier transformation is conducted to obtain a signal frequency spectrum X<N>(k); cycle-spectrum relative density (please see the specification) of the signal frequency spectrum X<N>(k) is calculated; a smoothing window function and a smoothing point M are determined, Fourier transform of a normalization windowing function is calculated, and thus a window function frequency spectrum W<N>(f) is obtained; cycle-spectrum smoothing processing is conducted on the cycle-spectrum relative density (please see the specification), and thus smoothing cycle-spectrum relative density (please seethe specification) is obtained; a resolution ratio is determined, the smoothing cycle-spectrum relative density (please see the specification) is traversed, and slicing is conducted; the first L spectral vectors with maximum spectrum energy are selected from cycle-spectrum slices and are regarded as a template; N data after the vibration signal x<N>(n) are selected and divided into K sections, andthe smoothing cycle-spectrum relative density (please see the specification) of the each section is calculated; the smoothing cycle-spectrum relative density (please see the specification) of the each section is compared with the cycle-spectrum relative density (please see the specification) of the template, peak matching number O at the different spectrum vectors is counted, and fault judgment is conducted according to the peak matching number O.

Description

technical field [0001] The invention belongs to the technical field of bearing fault monitoring, in particular to a method for real-time monitoring of rolling bearing faults. Background technique [0002] With the advancement and development of science and technology and the continuous improvement of industrialization, the precision, complexity and automation of mechanical equipment are getting higher and higher. There are countless examples of significant and even catastrophic loss of life and property caused by mechanical equipment failure. In rotating machinery, rolling bearings are a class of widely used components that are also the most vulnerable to damage. According to statistics, in rotating mechanical equipment using rolling bearings, about 30% of mechanical failures are related to bearing damage. Carrying out research on rolling bearing fault diagnosis technology has important practical significance for avoiding major accidents and other industrial production saf...

Claims

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Application Information

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IPC IPC(8): G01M13/04G01M13/045
CPCG01M13/04G01M13/045
Inventor 丁东亮李少洋
Owner 北京谛声科技有限责任公司
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