Rotating machinery bearing fault diagnosis method

Abstract

The invention discloses a rotating machinery bearing fault diagnosis method. The method is characterized by, to begin with, carrying out wavelet packet decomposition on an original signal, and extracting first half of wavelet coefficients obtained after wavelet packet decomposition for reconstruction to obtain a reconstruction signal set; then, extracting corresponding characteristic values for reconstruction signals on the time domain and frequency domain, and carrying out pattern recognition by utilizing a BP nerve network to obtain fault classification weight values; fusing the fault classification weight values obtained by the time domain and frequency domain through a D-S evidence theory to obtain a final fusion result; and finally, selecting the maximum value of the fusion result asa decision making result of fault diagnosis, and obtaining a final result of unit diagnosis. The rotating machinery bearing fault diagnosis method not only greatly improves accuracy of fault diagnosis, but also can judge, diagnose and predicate different fault types of a rotating machinery bearing; and the method is better in effect than independent time domain and frequency domain analysis, and can improve fault classification accuracy and stability.

Description

technical field [0001] The invention relates to a fault diagnosis method, in particular to a fault diagnosis method for rotating machinery bearings, and belongs to the technical field of fault diagnosis of industrial rotating machinery. Background technique [0002] With the continuous development of science and technology, rotating machinery is widely used in petrochemical, industrial and other fields, and plays a key role in enterprises. However, due to the long-term operation of rotating machinery, bearings are extremely easy to cause damage to varying degrees, resulting in various types of failures. When the bearing failure reaches a certain level, if it cannot be found and repaired in time, it may cause unnecessary shutdown of the machinery, which will not only affect the economic benefits of the enterprise, but also cause safety accidents. [0003] Therefore, in order to better determine and distinguish the fault types of rotating machinery bearings, and improve the r...

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Problems solved by technology

[0004] The main purpose of the present invention is to overcome the deficiencies in the prior art and provide a fault diagnosis method for rotating machinery bearings, which can effectively solve the problems of difficult to distinguish and low precision in fault diagnosis of existing mechanical equipment

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