Automatic coal discharge control system and method based on machine learning

Abstract

The embodiment of the invention discloses an automatic coal caving control system and method based on machine learning. The automatic coal caving control system comprises top-coal caving supports, first sensor sets, a second sensor set and a monitoring host; support controllers are connected to the top-coal caving supports; the first sensor sets are used for detecting support data; the second sensor set is used for detecting top-coal data; the monitoring host is in communication connection with the support controllers; and the monitoring host determines coal caving parameters according to thesupport data and the top-coal data and sends a control instruction to the support controllers according to the coal caving parameters, the support controllers control the coal caving supports to makeaction according to the control instruction, and thus automatic coal caving is completed. The automatic coal caving control method implements automatic coal caving by adopting the automatic coal caving control system. By adopting the automatic coal caving control system and method, manual intervention is not needed in the whole coal caving process, and automatic coal caving of a working face can be achieved based on big data machine learning, so that the coal caving efficiency is improved, and the labor intensity or workers is reduced.

Description

technical field [0001] The invention relates to the technical field of automatic mining of top coal caving working faces in underground coal mines, in particular to a machine learning automatic coal caving control system and method. Background technique [0002] At present, for the top-coal caving face in underground mining, coal mining is carried out at the front end of the top-coal caving face by a shearer, a hydraulic support, and a scraper conveyor; ; The hydraulic support adopts the hydraulic support electro-hydraulic control system to realize the automatic control of the machine, thus realizing the automatic control of the working face. In the coal discharge system at the rear of the hydraulic support, due to factors such as the coal discharge process and the development of top coal cracks, top coal thickness, roof pressure, mining and caving ratio, hydraulic support posture, tail beam swing range, and coal discharge port plate expansion and contraction range, etc. Re...

AI Technical Summary

Problems solved by technology

In the coal discharge system at the rear of the hydraulic support, due to factors such as the coal discharge process and the development of top coal cracks, top coal thickness, roof pressure, mining and caving ratio, hydraulic support posture, tail beam swing range, and coal discharge port plate expansion and contraction range, etc. Related, the gangue identification technology is immature, there is no good way to realize the automatic control of the coal discharge process, basically the manual control of the coal discharge process is still used, the labor intensity of the underground workers is high, the working environment is harsh, and the coal discharge efficiency is low

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