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Scraper conveyor chain fluttering fault diagnosis method

A scraper conveyor and fault diagnosis technology, which is applied in the field of coal mining, can solve the problem of no good detection method for floating chain faults, and achieve the effects of reasonable design, simple implementation, and high recognition accuracy

Active Publication Date: 2017-02-15
XIAN UNIV OF SCI & TECH
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Problems solved by technology

However, there is no good detection method for the fault of the floating chain of the scraper conveyor.

Method used

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  • Scraper conveyor chain fluttering fault diagnosis method
  • Scraper conveyor chain fluttering fault diagnosis method
  • Scraper conveyor chain fluttering fault diagnosis method

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Embodiment Construction

[0017] Below in conjunction with accompanying drawing, content of the present invention is described in detail:

[0018] 1. The sources of equipment sound during the production process of fully mechanized mining face are scraper conveyor and shearer. Among them, the shearer is mainly the vibration of the fuselage and the sound of the drum cutting the coal wall, and the scraper conveyor is mainly It is the sound of the scraper and the chain rubbing against the trough. The sound of these two devices is relatively stable under normal conditions. When a floating chain failure occurs somewhere on the scraper conveyor, there will be a sound of the scraper and the chain hitting the trough. Metal impact sound, when the shearer drum cuts to the shovel plate of the scraper conveyor, the metal impact sound of the shearer blade colliding with the shovel plate of the scraper conveyor will also be issued. When it is rocky or overloaded, it will also emit different abnormal sounds; the spect...

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Abstract

The invention discloses a scraper conveyor chain fluttering fault diagnosis method. According to the method, whether a scraper conveyor has a chain fluttering fault at a bending section thereof is diagnosed through correlation classification of a sound signal recognition model based on a deep convolutional neural network (CNN) and a support vector machine (SVM). The model is mainly composed of a related input sample, related sound signal features and a classifier, wherein the related input sample is a spectrogram during operation of fully-mechanized coal mining face equipment after principal component analysis (PCA) and whitening treatment, and the related sound signal features are sound signal features extracted by a deep convolutional neural network (CNN), and the classifier is a support vector machine (SVM) with the sound signal features as input. Whether a scraper conveyor has a chain fluttering fault at a bending section thereof is diagnosed by classifying sound signals through the classifier. The method has the advantages of simple steps, reasonable design, easy implementation, and good use effect which is proved by experiments.

Description

technical field [0001] The invention belongs to the technical field of coal mining, and in particular relates to a method for diagnosing a fault of a floating chain of a scraper conveyor. Background technique [0002] The role of the scraper conveyor in the fully mechanized mining face is to transport coal along the trough, provide a running track for the coal shearer, and provide an anchor point for the hydraulic support, which advances with the working face as a whole under the advancement of the hydraulic support. shift. During the advancing process of the working face, some sections of the scraper conveyor will bend in the horizontal or vertical direction. It will jump out of the groove of the scraper conveyor and cause the fault of the floating chain, and the fault of the floating chain can easily cause the chain breaking accident of the scraper conveyor. Therefore, it is of great significance to detect the floating chain fault of the scraper conveyor and find the flo...

Claims

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Application Information

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IPC IPC(8): G01M13/02
CPCG01M13/028
Inventor 马宏伟董刚南源桐张旭辉毛清华聂珍
Owner XIAN UNIV OF SCI & TECH
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