CEEMD-based noise reduction method for train bearing vibration signals

A bearing vibration and signal technology, which is applied in the recognition of patterns in signals, testing of mechanical components, testing of machine/structural components, etc., can solve problems such as inseparability and influence on denoising effect, reduce low-frequency interference, improve Effect of kurtosis value

Pending Publication Date: 2021-10-29
大连海天兴业科技有限公司 +1
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Problems solved by technology

However, EMD has the problem of modal aliasing, and it cannot completely separate the high-frequency resonance components in the signal from the low-frequency interference components, which seriously affects the denoising effect based on the EMD method.

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  • CEEMD-based noise reduction method for train bearing vibration signals
  • CEEMD-based noise reduction method for train bearing vibration signals
  • CEEMD-based noise reduction method for train bearing vibration signals

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Embodiment Construction

[0036] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0037] A noise reduction method based on CEEMD for a train bearing vibration signal, comprising the following steps: performing CEEMD decomposition on the signal; calculating the kurtosis value of each IMF component and the cross-correlation coefficient with the original signal; screening the IMF component according to the IMF component screening criteria refactor.

[0038] Compared with the EEMD method, the CEEMD method used in this embodiment has smaller reconstruction errors and faster decomposition speed. The CEEMD method uses white noise auxiliary decomposition like the EEMD method. The difference is that the CEEMD method adds a pair of white noise signals with the same amplitude and opposite direction to the orig...

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Abstract

The invention provides a CEEMD-based noise reduction method for train bearing vibration signals, which comprises the following steps: firstly, decomposing the signals by using CEEMD, then calculating a kurtosis value of each IMF component and a cross correlation coefficient with an original signal, and screening and reconstructing the IMF components by comprehensively considering the kurtosis value and the cross correlation coefficient. The effectiveness of the noise reduction algorithm provided by the invention is verified by analyzing the simulation signal, the reconstructed signal can highlight the high-frequency resonance component in the vibration signal, reduce the low-frequency interference and improve the kurtosis value of the signal, the non-linear and non-stationary characteristics of the original signal are retained, and the further application of the resonance demodulation technology is facilitated.

Description

technical field [0001] The invention relates to the field of train bearing fault diagnosis, in particular to a CEEMD-based noise reduction method for train bearing vibration signals. Background technique [0002] Resonance demodulation technology is a very effective method in bearing fault diagnosis, but when the signal contains strong background noise, the diagnosis effect is usually not ideal. During the operation of the train, the vibration signal collected by the sensor contains many vibrations that have nothing to do with the characteristics of the bearing fault, such as the vibration generated by the motor, the vibration generated by the meshing of the gears, and the vibration caused by external factors such as track irregularities. Vibrations that are not characteristic of bearing faults are collectively referred to as background noise. Early vibration signals of bearing faults are relatively weak and are easily submerged by noise. Therefore, before using resonance d...

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Application Information

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IPC IPC(8): G01M13/045G06K9/00G06K9/40
CPCG01M13/045G06F2218/10G06F2218/04
Inventor 刘全利张元庆康强周成龙
Owner 大连海天兴业科技有限公司
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