Belt conveyor fault diagnosis method based on sound signals

A belt conveyor and sound signal technology, which is applied in the field of belt conveyor fault diagnosis based on sound signals, can solve the problem of high fault detection accuracy requirements, increased labor risks for inspectors, and many belt conveyor fault detection points, etc. problems, to achieve the effect of fast detection speed, high real-time performance, and reduced labor intensity

Active Publication Date: 2021-09-17
QUFU NORMAL UNIV
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  • Abstract
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  • Application Information

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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

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  • Belt conveyor fault diagnosis method based on sound signals
  • Belt conveyor fault diagnosis method based on sound signals
  • Belt conveyor fault diagnosis method based on sound signals

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Embodiment Construction

[0079] Such as figure 1 Shown, a kind of belt conveyor fault diagnosis method based on sound signal of the present invention comprises the following steps:

[0080] S1, collecting the sound signal of the belt conveyor:

[0081] Specifically, in step S1, the sound signal of each running state when the belt conveyor is working is collected with a sampling frequency of 48kHz and a sampling point of 4096 using the sound collection device; the running state of the belt conveyor includes normal state and idler failure, Belt tear fault, drum fault three fault states;

[0082] S2. Perform improved wavelet threshold denoising processing on the collected sound signal. The denoising processing process includes wavelet base selection, decomposition layer number selection, threshold selection and threshold function improvement, and signal reconstruction;

[0083] Specifically, in step S2, the denoising process includes the following steps:

[0084] S2.1. Select a wavelet base db6 with s...

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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. ...

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Application Information

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IPC IPC(8): G01M99/00G01H17/00
CPCG01M99/005G01M99/008G01H17/00
Inventor 李磊孙永明张立华王化建卢立晖孙芝强陈金健
Owner QUFU NORMAL UNIV
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