CNG compressor rolling bearing fault feature extraction method

A technology of rolling bearings and extraction methods, applied in the testing of mechanical components, testing of machine/structural components, instruments, etc., can solve problems such as uselessness and modal mixing

Pending Publication Date: 2022-05-13
BEIJING GAS LYUYUANDA CLEANING FUEL
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Problems solved by technology

However, there is a problem of modal aliasing in the results of the two algorithms, EM

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  • CNG compressor rolling bearing fault feature extraction method
  • CNG compressor rolling bearing fault feature extraction method
  • CNG compressor rolling bearing fault feature extraction method

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Embodiment Construction

[0033] The method of the present invention takes the mixed fault signal of the inner and outer rings of a certain rolling bearing as an example, the motor speed is 1496r / min, the sampling frequency is 15360Hz, and the number of sampling points is 8192. After calculation, the inner ring fault characteristic frequency f of the bearing i =122.74Hz, the characteristic frequency of outer ring fault is f o =76.88Hz.

[0034] First select the faulty CNG compressor, start the compressor, use the data collector to collect data, and transfer the collected data to the computer, and use this method for subsequent data processing and analysis.

[0035] Perform Fourier transform on the collected signal. figure 2 is the collected fault signal waveform and its spectrum. It can be seen that there is no obvious periodic impact in the waveform of the signal, and the sideband components in the frequency spectrum are also difficult to distinguish.

[0036] Using the method of envelope demodul...

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Abstract

The invention discloses a CNG (compressed natural gas) compressor rolling bearing fault feature extraction method, which comprises the following steps of: constructing a frequency spectrum trend according to a frequency spectrum of an acquired complex bearing signal, and dividing the frequency spectrum by taking a minimum value point of the trend as a boundary so as to realize self-adaptive decomposition of the signal to obtain sub-bands of the signal. According to the method, the modal aliasing phenomenon is avoided, and it is ensured that excessive invalid components do not appear in the decomposition result. Besides, singular value decomposition is carried out on the signal sub-bands to obtain singular values of all the sub-bands, and then the singular values are selected by using amplitude filtering characteristics of singular value decomposition and combining a time domain negentropy index, so that noise reduction processing is realized. And carrying out envelope demodulation on the denoised sub-bands, extracting a fault characteristic frequency, and finally realizing fault diagnosis of the CNG compressor rolling bearing.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of rotating machinery, and in particular relates to a method for extracting fault features of rolling bearings of CNG compressors with self-adaptive decomposition and noise reduction Background technique [0002] Rolling bearings are common components in CNG compressors, and are also one of the most vulnerable components in CNG compressors. Therefore, the necessity of state detection and fault diagnosis of bearings in CNG compressors is reflected in: when the bearing fails At times, large-scale vicious accidents are likely to occur, which may even cause serious property damage and personal injury or death. [0003] Vibration signal processing is of great significance to the condition monitoring and fault diagnosis of CNG compressor equipment, and its main purpose is to extract the fault features in the signal. However, during the operation of the CNG compressor, the vibration signal usually present...

Claims

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Application Information

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IPC IPC(8): G01M13/045
CPCG01M13/045
Inventor 王京荣魏宇航孙磊潘晓
Owner BEIJING GAS LYUYUANDA CLEANING FUEL
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