Audio-based intelligent fault diagnosis method for carrier roller of belt conveyor.

A belt conveyor, fault diagnosis technology, applied in voice analysis, sub-station installation, registration/indication of machine work, etc., can solve problems such as inability to detect various idler faults, low real-time performance, etc. The effect of improving accuracy

Pending Publication Date: 2021-11-16
SHANGHAI UNIV
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Problems solved by technology

[0007] The present invention aims to provide an audio-based intelligent fault diagnosis method for idler rollers of belt conveyors,

Method used

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  • Audio-based intelligent fault diagnosis method for carrier roller of belt conveyor.
  • Audio-based intelligent fault diagnosis method for carrier roller of belt conveyor.
  • Audio-based intelligent fault diagnosis method for carrier roller of belt conveyor.

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[0055] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0056] The present invention provides an audio-based intelligent fault diagnosis method for a belt conveyor idler, such as figure 1 shown, including the following steps:

[0057] Step 1: Install the LM386 and Arduino Ethernet W1500 on the Arduino, and then install each Arduino with peripherals installed next to the roller;

[0058] Step 2: Connect the Arduino to the switch through optical fiber, so that multiple sensors are connected to one switch, and then transmit the signal;

[0059] Step 3: The audio data of the idler is transmitted to the terminal server through the switch and router, and the audio data of the idler is saved in the database at the same time;

[0060] Step 4: Preprocessing of the audio data of the idler: using the wavelet packet algorithm to preprocess the audio data of the idler, and divide the audio data into...

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Abstract

The invention provides an audio-based intelligent fault diagnosis method for a carrier roller of a belt conveyor. The method comprises the following steps that firstly, an audio sensor is installed beside a carrier roller to collect an audio signal of the carrier roller, and the audio signal is sent to a server through an optical fiber; secondly, the sent carrier roller audio signal is preprocessed on a processor; then, a mean value of each frequency band is extracted as a data feature of the frequency band; then , classifying of the data after feature extraction is carried out by using a convolutional neural network; and finally, after the diagnosis algorithm completes fault diagnosis, the result is displayed on an interface of an upper computer for a user to check. According to the invention, the fault of the carrier roller can be detected in real time without depending on manpower, and the economic benefit and the intelligent level of a coal preparation plant are improved.

Description

technical field [0001] The invention relates to the field of fault diagnosis of large-scale mechanical equipment in an industrial automation production line, in particular to an audio-based intelligent fault diagnosis method for idler rollers of belt conveyors. Background technique [0002] The idler roller is the most used, most faulty and most repaired part in the belt conveyor of the coal preparation plant. The idler rollers are prone to eccentricity, jamming, breakage and other faults during work, causing the belt to deviate and seriously affecting the normal use of factory equipment. [0003] The traditional idler fault diagnosis is a manual inspection method, and workers need to be arranged to check the idlers regularly. The manual inspection method is time-consuming and labor-intensive, and cannot detect faults in time. In recent years, fault diagnosis methods have made rapid progress, from traditional manual diagnosis to intelligent diagnosis. The basic process of...

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Application Information

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IPC IPC(8): G10L19/02G10L25/18G10L25/30G10L25/51H04Q9/00H04Q11/00G06N3/04G07C3/00
CPCG10L19/0216G10L25/18G10L25/30G10L25/51G07C3/005H04Q11/0005H04Q11/0062H04Q9/00H04Q2209/84G06N3/045
Inventor 彭晨李志朋杨明锦
Owner SHANGHAI UNIV
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