A method for extracting fault features of rotating machinery equipment

Abstract

The present invention provides a fault feature extraction method for rotating mechanical equipment, including: (1) sampling vibration signals at equal time intervals and performing time domain processing to extract time domain features; (2) sampling vibration signals at equal time intervals x (n) Perform envelope detection processing to obtain the envelope signal with equal time interval sampling, and extract the characteristics of the envelope signal; (3) Utilize the equal time interval sampling envelope signal and rotational speed information to reconstruct the equal angle interval sampling envelope signal y( n); (4) Perform equiangular moving average filtering on the equiangular interval sampling envelope signal y(n) to obtain the signal z(n); (5) Find the Fourier transform of z(n) and use the characteristic frequency matching method to find Eigenfrequency, to extract fault features in the frequency domain. This method can not only suppress the interference without reducing the resolution of the frequency domain, but also extract the actual characteristic frequency when the rotational speed deviates and the mechanical parts deviate, which can effectively find smaller hidden troubles.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis of mechanical equipment, in particular to a method for extracting fault features of rotating mechanical equipment. Background technique [0002] With the development of modern industry and science and technology and the further improvement of automation, machinery is developing in the direction of large-scale, high-speed, continuous, centralized, and automated. Rotating mechanical equipment has been in high-speed operation for a long time (generally more than 3000 revolutions per minute or even as high as tens of thousands of revolutions). Due to the influence of various factors, some failures will inevitably occur, and these failures often cause huge economic losses or even catastrophic consequences. , so it is very important for fault diagnosis of rotating machinery equipment. [0003] Vibration detection and diagnosis method is the most commonly used diagnosis method in fault diagnosis...

AI Technical Summary

Problems solved by technology

However, since this method uses the method of segmenting the data and then adding and averaging different segments of data to suppress noise, the continuity of the data is destroyed, and continuous monitoring of the state cannot be realized; in addition, because the long data is divided into short data , this method also reduces the frequency-domain resolution of the subsequent Fourier transform

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