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Fault diagnosis method for rolling bearing

A rolling bearing and fault diagnosis technology, applied in the direction of mechanical bearing testing, measuring devices, instruments, etc., to achieve the effect of automatic fault diagnosis and detection, reducing errors and high efficiency

Inactive Publication Date: 2013-12-04
KUNMING UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention proposes a fault diagnosis method for rolling bearings, in order to solve the problems of automatic detection of the optimal envelope frequency band in envelope analysis and improve its accuracy and diagnostic performance

Method used

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  • Fault diagnosis method for rolling bearing
  • Fault diagnosis method for rolling bearing
  • Fault diagnosis method for rolling bearing

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Experimental program
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Embodiment approach 1

[0023] Embodiment 1: In the rolling bearing fault diagnosis method of this embodiment, the parameters of the faulty rolling bearing are as follows: (1) The contact angle of the rolling bearing: 0°; (2) The rolling element diameter of the rolling bearing: 15mm; (3) The number of rolling elements of the rolling bearing : 18 pieces; (4) The pitch diameter of the rolling bearing is 104mm; (5) During the high-frequency sampling, the rotating speed of the rolling bearing is 499rpm, and the fault type is pitting failure of the outer ring. The sensor selected in this embodiment is a piezoelectric sensor, and the piezoelectric sensor is arranged on the outer ring of the rolling bearing to prepare for the subsequent steps.

[0024] The method in the present invention carries out the step of fault diagnosis to the fault rolling bearing in the present embodiment: as follows figure 1 shown.

[0025] A After fixing the piezoelectric sensor on the outer ring of the rolling bearing in this e...

Embodiment approach 2

[0050]Embodiment 2: The rolling bearing fault diagnosis method of this embodiment, the parameters of the fault rolling bearing in this embodiment are as follows: (1) The contact angle of the rolling bearing: 0°; (2) The rolling body diameter of the rolling bearing: 15mm; (3) The rolling bearing The number of rolling elements: 18; (4) The pitch diameter of the rolling bearing: 104mm; (5) During the high-frequency sampling, the rotating speed of the rolling bearing was 749rpm, and the fault type was pitting failure of the outer ring. The sensor selected in this embodiment is a piezoelectric sensor, and the piezoelectric sensor is arranged on the outer ring of the rolling bearing to prepare for the subsequent steps.

[0051] The method in the present invention carries out the step of fault diagnosis to the faulty rolling bearing in this embodiment:

[0052] A After fixing the piezoelectric sensor on the outer ring of the rolling bearing in this embodiment, high-frequency sampling...

Embodiment approach 3

[0077] Embodiment 3: The rolling bearing fault diagnosis method of this embodiment, the parameters of the fault rolling bearing are as follows: (1) The contact angle of the rolling bearing: 0°; (2) The diameter of the rolling element of the rolling bearing: 15mm; (3) The number of rolling elements of the rolling bearing : 18 pieces; (4) The pitch diameter of the rolling bearing is 104mm; (5) During high-frequency sampling, the rotating speed of the rolling bearing is 1001rpm, and the fault type is pitting failure of the outer ring. The sensor selected in this embodiment is a piezoelectric sensor, and the piezoelectric sensor is arranged on the outer ring of the rolling bearing to prepare for the subsequent steps.

[0078] The steps of applying the method of the present invention to carry out fault diagnosis on the faulty rolling bearing in this embodiment are:

[0079] A After fixing the piezoelectric sensor on the outer ring of the rolling bearing in this embodiment, high-fre...

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Abstract

The invention discloses a fault diagnosis method for a rolling bearing, and belongs to the technical field of fault diagnosis and signal processing analysis. High-frequency sampling and preprocessing of vibration signals are firstly performed on the rolling bearing with faults, the preprocessed signals are sequentially filtered by the aid of a Morlet wavelet filter, spectral kurtosis and unit spectral kurtosis of the filtered signals are calculated, and a filter parameter corresponding to the maximum value of the unit spectral kurtosis is selected by comparison, namely, a global optimization filter parameter is selected. According to the fault diagnosis and detection method, an operator can extract the optimal filter parameter in the diagnosis process without a lot of detection experience and numerous historical data, the method is wider in application range, errors caused by human errors are greatly decreased, the extracted optimal filter parameter can be more accurate, a diagnosis result is more correct, fault diagnosis and detection automation is more facilitated, more time is saved, and efficiency is higher.

Description

technical field [0001] The invention relates to a fault diagnosis method for a rolling bearing, in particular to a fault diagnosis method for a rotating mechanical body, and belongs to the field of fault diagnosis technology and signal processing and analysis technology. Background technique [0002] Envelope analysis is a vibration feature extraction technology widely used at present, and it has a good effect on the extraction of signal shock components. The extraction process of envelope analysis includes determining the center frequency and bandwidth for bandpass filtering, and then using Hilbert (Hilbert) transform to extract the signal envelope of this frequency band. However, the selection of the filter center frequency and bandwidth requires the operator to have a wealth of prior knowledge and historical data. Otherwise, analysis errors will occur when the filter center frequency and bandwidth are selected, and the purpose of using envelope analysis to diagnose faults...

Claims

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Application Information

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IPC IPC(8): G01M13/04G01H11/08
Inventor 郭瑜梁瑜
Owner KUNMING UNIV OF SCI & TECH
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