Method for extracting feature information of weak faults of low-speed heavy-duty equipment

Abstract

The invention discloses a method for extracting feature information of weak faults of low-speed heavy-duty equipment, which can be used for extracting signals of the weak faults of the equipment. Themethod comprises the following steps: acquiring vibration signals under the working state of the equipment through an acceleration sensor arranged on a bearing seat of the equipment; carrying out wavelet decomposition on the acquired vibration signals; performing stochastic resonance processing and mutual correlation processing for low-frequency signals obtained by the decomposition; and carryingout Fourier transform on the mutual correlation result to extract the feature of the weak faults of the equipment. The method can effectively extract the feature information of the weak faults of thelow-speed heavy-duty equipment, and provides effective basis for the fault diagnosis of the equipment.

Description

technical field [0001] The invention relates to a method for extracting equipment fault feature information, in particular to a method for extracting weak fault feature information of low-speed heavy-load equipment. Background technique [0002] Low-speed and heavy-duty large-scale equipment is the lifeblood of modern steel production enterprises. If an unexpected accident occurs, it may cause production paralysis, cause the enterprise to suffer huge economic losses, and even cause casualties. In order to discover the hidden troubles of equipment in time to ensure the smooth progress of production, the research work on the feature extraction of weak faults of low-speed and heavy-duty equipment is particularly urgent. [0003] The speed of low-speed heavy-duty equipment is below 300 revolutions per minute. When the equipment fails, the impact response frequency of the failure is low, and the frequency range is between a few tenths of hertz to five hertz. These low-frequency w...

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Problems solved by technology

[0003] The speed of low-speed heavy-duty equipment is below 300 revolutions per minute. When the equipment fails, the impact response frequency of the failure is low, and the frequency range is between a few tenths of hertz to five hertz. These low-frequency weak characteristic signals are easily detected by the strong environment. Submerged by noise, it is difficult to effectively extract these fault feature information through existing signal processing methods, so that fault diagnosis cannot be performed

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