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VGSET time-frequency analysis method, device and equipment for bearing fault signal and storage medium

A fault signal, time-frequency analysis technology, applied in the direction of measuring devices, mechanical bearing testing, mechanical parts testing, etc., can solve the problem of not being able to obtain key characteristic information of bearing fault signals, so as to avoid modal aliasing and improve time-frequency Aggregation, the effect of improving robustness

Pending Publication Date: 2021-11-19
CHINA UNIV OF GEOSCIENCES (WUHAN)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In order to solve the technical problem that the traditional method cannot obtain the key characteristic information of the bearing fault signal, the present invention combines the variational mode decomposition and the improved synchronous extraction transformation to realize the analysis of nonlinear and non-stationary signals, and through the variational mode decomposition The Wiener filter in the signal filters the redundant noise components and eliminates the pseudo components in the traditional synchronous extraction transformation to obtain several intrinsic mode components (IMF), and then performs GSET processing on each IMF component, and finally processes each component The results are accumulated one by one, so that a better non-stationary signal processing result is obtained

Method used

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  • VGSET time-frequency analysis method, device and equipment for bearing fault signal and storage medium
  • VGSET time-frequency analysis method, device and equipment for bearing fault signal and storage medium
  • VGSET time-frequency analysis method, device and equipment for bearing fault signal and storage medium

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Experimental program
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Effect test

Embodiment 1

[0079] The given frequency hopping signal is:

[0080]

[0081]

[0082] f (t) = v 1 + V 2

[0083] The sampling time is set to 20s, the sampling frequency is 100 Hz, and the second penalty factor of the VMD algorithm is set to 3000, and the number of decomposition layers is set to 4. Gausson white noise is added to a signal-to-noise ratio of 16 dB.

[0084] Decomposition of frequency hopping signals to decompose multiple IMF signals, reference figure 2 , figure 2 It is the decomposition result of the VMD algorithm for the original signal (after noise), from top to bottom, the raw signal, the hopping of V1, the hopping of V1, the hopping before the hopping of V1, the hopping of V2, linear frequency modulation components , The constant frequency components of the V2 of the V2, the decomposition of the visible signal noise reduction is still considerable, and there is a clear physical meaning.

[0085] refer to image 3 , image 3 Is a time-frequency analysis result of different ...

Embodiment 2

[0091] Radar signals have an important role in people's daily lives, so the analysis of radar signals has become an indispensable research hotspot in time-frequency analysis. Commonly used radar signals include LFM, EQFM, Barker code two-phase signal, FRANK code signal, multipart-phase code signal, etc. Anti-noise performance. In this portion, the signal sampling frequency is 1000 Hz, the secondary penalty factor of the VMD algorithm is set to 1000, and the number of decomposition layers is set to 1.

[0092] refer to Figure 4 , Figure 4 (a) is a time-frequency diagram of the EQFM signal based on STFT-based SET algorithm, Figure 4 (b) is the result of the VGSET algorithm to process the EQFM signal. It can be seen from the comparison of two pictures. Figure 4 The noise component in (b) has been significantly inhibited, and Figure 4 The problem of effective component loss in (a) has also been improved, and the time-frequency aggregation of the entire map has also been significantly ...

Embodiment 3

[0095] The method is applied to mechanical bearing fault signal analysis, and parameters such as the characteristic frequency of the mechanical bearing can be obtained, and the parameters such as the related fault cause, help to solve the characteristic frequency at the time of failure of mechanical bearings, and provide a basis for the diagnosis and research of mechanical bearings. help. The VGSET algorithm can effectively analyze the complete signal characteristics of the bearing fault signal, and predict it, which has a good analysis of the bearing fault.

[0096] The mechanical bearing fault signal is complicated by a typical non-stationary signal, which contains a variety of modal signals, and it contains more noise, so it is suitable to apply this algorithm to the mechanical bearing fault signal. This algorithm has selected the data provided on the CWRU bearing center on the network. The bearing model used in the CWRU bearing center trial is SKF's 6205-2RS deep groove ball b...

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Abstract

The invention provides a VGSET time-frequency analysis method and device for a bearing fault signal, equipment and a storage medium. The method comprises steps of carrying out variational mode decomposition of the bearing fault signal, and obtaining a plurality of IMF signals; sequentially carrying out GSET conversion on each IMF signal to obtain a converted IMF signal; and sequentially superposing the converted IMF signals to obtain a time-frequency analysis result of the bearing fault signal. A variational mode decomposition method is used to avoid mode aliasing caused by low time-frequency resolution of multi-component signals in bearing fault signals to a certain extent, the time-frequency resolution of GSET is variable, the length of a time-frequency window is adaptively adjusted along with the frequency of the signals, and the adjustment trend is controllable; the influence of the STFT fixed-length time window function in the traditional SET method is effectively solved, the time-frequency resolution is improved, false components in the traditional SET result can be avoided by combining the two methods, and robustness and the time-frequency aggregation degree of the signal are improved.

Description

Technical field [0001] The present invention relates to the field of bearings troubleshooting, particularly relates to analytical methods, apparatus, device, and a storage medium when VGSET A bearing fault signal frequency. Background technique [0002] Mechanical bearing failures to human life brought great inconvenience, bearing failure could cause harm engineering machine is not working properly, resulting in reduced efficiency engineering, severe mechanical engineering will lead to bearing failure accident, to work personnel harm to life, as well as how to detect bearing failure occurs because security is for the project has been a hot topic, however, the bearing has a complex structure and is not easily accessible, work status, and detect bearing bearing failure analysis has become a project application a difficult problem, the analysis of the cause of bearing failure signal, current methods there are a variety of defects, there is no way to get a good key feature informatio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/04G01M13/045G06F17/14
CPCG01M13/04G01M13/045G06F17/14
Inventor 石光耀郝国成锅娟金亚睿甘宇
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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