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Rotary machine vibration signal fault identification method

A technology of rotating machinery and vibration signals, which is applied in the testing of mechanical components, mechanical bearings, and testing of machine/structural components. It can solve the problem of limited number of fault samples, difficulty in obtaining fault samples, and failure to consider the frequency classification of mechanical vibration signals, etc. problems, to achieve accurate results

Inactive Publication Date: 2017-06-30
伍婷婷
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Today's fault analysis of mechanical vibration signals has difficulty in obtaining fault samples, the number of fault samples is often limited, and the frequency classification of mechanical vibration signals is not considered. Therefore, it is necessary to provide a vibration signal fault identification method for rotating machinery that solves the above problems

Method used

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  • Rotary machine vibration signal fault identification method

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Embodiment 1

[0012] Due to the influence of factors such as rotational speed, load and impact caused by faults, the vibration signals of mechanical equipment often show strong non-stationarity. For the non-stationary signal of the vibration signal, it is not enough to only know the global characteristics of the signal in the time domain or frequency domain, and it is also hoped to obtain the signal spectrum of the vibration signal changing with time. Time-frequency analysis technology is to transform the signal into two-dimensional time-frequency domain for analysis, and it is an effective means to analyze non-stationary signals. The fault diagnosis method based on the time-domain characteristics of different frequency bands after the vibration signal is decomposed does not consider the frequency-domain characteristics of the vibration signal. The fault diagnosis method of mechanical vibration signal based on time-frequency domain features can use singular value decomposition method for fe...

Embodiment 2

[0016] Signal noise reduction for mechanical vibration signals. The signal noise reduction method based on empirical mode decomposition has a better noise reduction effect on low-frequency components. The reason is that the filter can smooth the signal, and the low-frequency components are relatively smooth. , which can better preserve the characteristics of low-frequency components; while the threshold-based noise reduction method has a better noise reduction effect on high-frequency components, and it can better maintain the high-frequency characteristics of high-frequency components. In order to make the noise reduction method based on the noise reduction method based on the low frequency part and the high frequency part of the signal can achieve better noise reduction effect, it is considered to combine the method based on the threshold value noise reduction method with the noise reduction method based on the first few components obtained by decomposition (higher frequencie...

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Abstract

The invention discloses a vibration signal fault identification method of a rotating machine, which includes fault type discrimination, fault feature extraction, fault index refinement, and fault mode recognition. The characteristics of the fault vibration signal are processed, and the signal is calculated and analyzed through a mathematical process to identify the fault of the signal. Therefore, the result is more accurate and scientific.

Description

technical field [0001] The invention relates to the field of fault diagnosis of mechanical vibration signals, and relates to a vibration signal fault identification method of rotating machinery. Background technique [0002] Fault diagnosis of mechanical vibration signals is of great significance to ensure the safe and stable operation of mechanical equipment. The mechanical fault diagnosis method based on mechanical vibration signal analysis has the advantages of online, real-time, non-destructive, convenient and accurate diagnosis, etc., and has been widely used. Today's fault analysis of mechanical vibration signals has difficulties in obtaining fault samples, the number of fault samples is often limited, and the frequency classification of mechanical vibration signals is not considered. Therefore, it is necessary to provide a vibration signal fault identification method for rotating machinery that solves the above problems. Contents of the invention [0003] In view o...

Claims

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Application Information

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IPC IPC(8): G01M13/00G01M13/04
CPCG01M13/00G01M13/045
Inventor 伍婷婷
Owner 伍婷婷
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