Bearing fault signal feature extraction method based on adaptive multiscale AVGH conversion

A technology for fault signal and feature extraction, which is used in mechanical bearing testing, mechanical component testing, and machine/structural component testing to achieve the effects of wide applicability, elimination of background noise, and accurate analysis.

Active Publication Date: 2017-03-15
SHIJIAZHUANG TIEDAO UNIV
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However, in the prior art, there are no related technical records that can well solve these two key problems.

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  • Bearing fault signal feature extraction method based on adaptive multiscale AVGH conversion
  • Bearing fault signal feature extraction method based on adaptive multiscale AVGH conversion
  • Bearing fault signal feature extraction method based on adaptive multiscale AVGH conversion

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[0042] Attached below Figure 1 to Figure 7 A method for extracting features of bearing fault signals based on adaptive multi-scale AVGH transformation proposed by the present invention will be described in detail with specific embodiments.

[0043] like figure 1 As shown, the purpose of the present invention is to provide a kind of bearing fault vibration signal diagnosis method based on adaptive multi-scale morphology AVG-Hat transformation, and concrete process comprises:

[0044] Step 101: Set the sampling frequency of the acceleration sensor, and collect the fault vibration signal of the rolling bearing;

[0045] Step 102: Obtain the structural parameters of the rolling bearing and the rotational speed of the rotating shaft. According to the calculation formula of the fault characteristic frequency of each component of the rolling bearing, the fault characteristic frequency of each component of the measured bearing is obtained, and then combined with the sampling frequen...

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Abstract

The present invention discloses a bearing fault signal feature extraction method based on adaptive multiscale AVGH conversion. The method comprises the steps: 1, according to the parameter index of the bearing fault signals, determining the number of the initial multiscale structure elements and the initial structure element values of signals; 2, constructing the set formed by the initial multiscale structure elements; 3, calculating the results of the morphology AVG-Hat conversion corresponding to the bearing fault vibration signals in the initial multiscale structure elements, and constructing the set of the results; 4, selecting the specific value of the permutation entropy of the filtered bearing fault vibration signals and the spectrum envelope sparseness as an evaluation index and adaptively determining the optimal weight coefficient corresponding to the filtered initial multiscale structure elements; 5, constructing the optimal multiscale morphology AVG-Hat filter according to the weight coefficient; and 6, calculating the processing result of the bearing fault vibration signals through the filter, and extracting the fault feature components in the signals through the signal spectrum envelope analysis to perform bearing fault diagnosis.

Description

technical field [0001] The invention relates to a bearing fault signal feature extraction method based on adaptive multi-scale AVGH transformation, which belongs to the technical field of mechanical fault diagnosis and signal processing. Background technique [0002] In actual engineering, the vibration signal of rolling bearing fault is a typical nonlinear and non-stationary signal, and the fault characteristics in the signal are easily covered by various background noises. Therefore, it is very difficult to diagnose bearing faults under strong background noise. Mathematical morphology is a typical nonlinear signal processing method. It uses specific scale and shape structural elements to fit and modify the local details of the signal time domain waveform. It can effectively eliminate the background while extracting the main waveform features in the signal. noise interference. The key to using morphological methods to process fault signals is to construct a morphological f...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/04
CPCG01M13/045
Inventor 邓飞跃杨绍普郭文武潘存治郝如江申永军
Owner SHIJIAZHUANG TIEDAO UNIV
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