Belt conveyor fault diagnosis method based on sound signals

Abstract

The invention provides a belt conveyor fault diagnosis method based on sound signals, which can reduce the labor intensity of inspection personnel and has the characteristics of high detection speed, high real-time performance, high safety and the like. The diagnosis method comprises the following steps: S1, collecting a sound signal of the belt conveyor; S2, carrying out improved wavelet threshold de-noising processing on the collected sound signals; s3, performing MFCC and deep learning feature extraction on the noise-reduced sound signal of the belt conveyor; s4, establishing a support vector machine classification model, and forming a trained SVM model; and S5, putting the extracted feature information data into the trained SVM model to obtain a posterior probability, then carrying out decision-level fusion by utilizing a D-S evidence theory, and finally, matching a fusion output result with the running state of the belt conveyor in the known running state of the SVM, the running state with the highest matching degree with the fusion output result corresponding to the current running state of the belt conveyor, so that the fault diagnosis of the belt conveyor is completed.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis of belt conveyors, in particular to a method for fault diagnosis of belt conveyors based on sound signals. Background technique [0002] With the rapid development of science and technology, industrial production is increasingly modernized, and various highly intelligent and highly integrated large-scale mechanical equipment gradually appear. In ports, mines, coal and other industries, the production and operation of belt conveyors has the characteristics of large consumption, difficult inspection, and difficult to predict failures. After field research on the port production site, because of its large production and transportation throughput, belt conveyors Long-term high-load operation is required, and failure events that cannot be found in time by manual inspection often occur. Based on this production pain point, the research on belt conveyor fault diagnosis technology is promoted. ...

AI Technical Summary

Problems solved by technology

[0003] At present, the belt conveyor adopts the traditional manual inspection method. The inspectors need to carry heavy inspection tools to shuttle around the site, which greatly increases the labor risk of the inspectors. Moreover, there are many fault detection points on the belt conveyor. High precision requirements, this inspection method makes it difficult for the inspection work of the belt conveyor to achieve fault detection characteristics such as fast detection speed, high real-time performance, and strong safety

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