Working face periodic weighting early warning method, device and equipment based on deep learning

A technology of periodic pressure prediction and deep learning, applied in design optimization/simulation, special data processing applications, instruments, etc., can solve problems such as low accuracy, low efficiency, and inability to accurately realize early warning, so as to avoid roof accidents and ensure real-time effect

Pending Publication Date: 2021-01-08
CCTEG COAL MINING RES INST +1
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Problems solved by technology

[0005] In view of this, this application provides a deep learning-based early warning method, device and equipment for the periodic pressure of the working face, mainly to solve the existing method of predicting the periodic pressure of the working face, which is inefficient, low in accuracy, and cannot be accurately realized early warning problem

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  • Working face periodic weighting early warning method, device and equipment based on deep learning
  • Working face periodic weighting early warning method, device and equipment based on deep learning
  • Working face periodic weighting early warning method, device and equipment based on deep learning

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[0023] Hereinafter, the present application will be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0024] In view of the problems that the current existing methods for predicting the periodic pressure of the working face are inefficient, low in accuracy, and unable to accurately realize the early warning, the embodiment of the present application provides an early warning method for the periodic pressure of the working face based on deep learning, such as figure 1 As shown, the method includes:

[0025] 101. Train the periodic pressure prediction model based on the historical support pressure data, so that the periodic pressure prediction model meets the preset training standard.

[0026] For this embodiment, in a specific application scenario, when training the periodic pressur...

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Abstract

The invention discloses a working face periodic weighting early warning method, device and equipment based on deep learning, relates to the technical field of coal mine underground mining, and can solve the problems of low working face periodic weighting prediction efficiency, low accuracy and incapability of accurately realizing early warning in the prior art. The method comprises the steps thata periodic weighting prediction model is trained based on historical stent pressure data, so that the periodic weighting prediction model meets a preset training standard; acquiring pressure data of each bracket in the working surface in real time; and inputting the pressure data into a periodic weighting prediction model conforming to the preset training standard, and obtaining a periodic weighting prediction result of the working face. The method is suitable for predicting the periodic pressure of the working face.

Description

technical field [0001] The present application relates to the technical field of underground coal mining, and in particular to a deep learning-based early warning method, device and equipment for the periodic pressure of the working face. Background technique [0002] The existing underground coal mining basically adopts the longwall mining process, that is, the mining area of ​​the working face adopts equipment such as hydraulic supports to support the roof, while the back of the working face is an unsupported area, and the roof collapses by itself after coal mining fall and fill the goaf. The collapse of the roof at the rear of the working face directly affects the safety of the working face in front. If the lower roof at the rear of the working face falls behind, the upper roof can form a giant rock joint structure similar to an "arch", which can reduce the front working face to a certain extent. The pressure of the hydraulic support is conducive to the safety of the min...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20G06F119/14
CPCG06F30/20G06F2119/14
Inventor 徐刚范志忠赵岩峰卢振龙左胜黄志增张雪峰
Owner CCTEG COAL MINING RES INST
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