Bearing fault quantitative trend diagnosis method based on morphology and multi-scale permutation entropy mean value

A technology based on morphology and diagnostic methods, used in mechanical bearing testing, measuring devices, complex mathematical operations, etc.

Active Publication Date: 2018-12-11
BEIJING UNIV OF TECH
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Problems solved by technology

[0004] The purpose of the present invention is to provide a bearing fault quantitative trend diagnosis method based on morphology

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  • Bearing fault quantitative trend diagnosis method based on morphology and multi-scale permutation entropy mean value
  • Bearing fault quantitative trend diagnosis method based on morphology and multi-scale permutation entropy mean value
  • Bearing fault quantitative trend diagnosis method based on morphology and multi-scale permutation entropy mean value

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Embodiment Construction

[0074] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0075] figure 1 It is a flow chart of the bearing fault quantitative trend diagnosis method based on morphology and multi-scale permutation entropy value of the present invention. The principle of the bearing fault quantitative trend diagnosis method based on morphology and multi-scale permutation entropy value is described in detail below in combination with the flow chart.

[0076] (1) Use the acceleration sensor to obtain the bearing vibration acceleration signals of different fault degrees as the signal X(t) to be analyzed;

[0077] (2) Perform multi-scale morphological analysis on the vibration signal of the faulty bearing to obtain the denoised signal Xε(t), where ε=1,2,....[fs / fc-2], fs is the sampling frequency, and fc is Fault characteristic frequency. In order to save time and cost, the shape of the structural elements adopts a str...

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Abstract

The invention discloses a bearing fault quantitative trend diagnosis method based on morphology and a multi-scale permutation entropy mean value. When the fault size of the inner ring or the outer ring of a bearing is changed, the modulation degree of the vibration signal of the bearing is changed. The change affects the complexity and randomness of the vibration signal. The method, by using the superiority of the multi-scale permutation entropy in the aspect of representing the degree of uncertainty of vibration signals, draws a relational graph of the multi-scale permutation entropy mean values and the fault sizes, and then realizes quantitative trend diagnosis of the rolling bearing faults. The vibration signal acquired by an experiment contains serious noise and a large number of interference signals. In order to remove the noise interference and enhance the impact performance of the vibration signal, the multi-scale morphology is introduced into the method so as to greatly improvethe accuracy of rolling bearing fault quantitative trend.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis, and relates to a quantitative diagnosis method for bearing faults, in particular to a quantitative trend diagnosis method for bearing faults based on morphology and multi-scale array entropy mean Background technique [0002] Rolling bearings are indispensable parts in rotating machinery, but their failure rate is very high under harsh working conditions. It is far from enough to study rolling bearing faults from a qualitative point of view to prevent and maintain the entire mechanical transmission mechanism. Only by understanding the severity of rolling bearing faults can we better guide the maintenance of mechanical equipment. [0003] The permutation entropy algorithm proposed by Christoph is a method to detect the randomness and complexity of time permutation order. This method has the advantages of small amount of calculation and strong robustness. Vakharia uses multi-scale permutat...

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Application Information

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IPC IPC(8): G01M13/04G06F17/18
CPCG01M13/045G06F17/18
Inventor 崔玲丽王加龙孟宗姜宏王鑫
Owner BEIJING UNIV OF TECH
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