An Intelligent Coal Shearer Cutting Pattern Recognition System

Abstract

The invention discloses an intelligent coal mining machine cutting pattern recognition system consists of a sensing module and a control module. The sensing module measures the running speed, currentand voltage of a motor when a coal mining machine works, and transmits the data to the control module. The control module combines an intelligent parameter optimization algorithm and a GBDT classifierto intelligently identify a current geological condition according to the operation data, and transmits a result to the coal mining machine so that the coal mining machine can adjust the cutting pattern in time. By adopting the intelligent coal mining machine cutting pattern recognition system, the defects are overcome that a detection device is complex and the recognition accuracy is not high enough in recognition in a current cutting pattern of the coal mining machine, the running speed, current and voltage of the motor are taken as detection signals, detection devices are simple, and the detection signals have reliable corresponding relation with cutting patterns; the GBDT algorithm is selected as the classifier, so that the identification accuracy is high; the parameters of the classifier are optimized by using the improved optimization algorithm, and the identification accuracy is further improved.

Description

technical field [0001] The invention relates to the field of coal mining, in particular to an intelligent shearer cutting pattern recognition system. Background technique [0002] The shearer is the key equipment in the fully mechanized coal mining work area. In order to ensure the smooth operation of the equipment, prevent the damage of electromechanical components, realize the automatic control of coal mining, and reduce the number of personnel in the working face, it is of great significance to identify the cutting mode of the shearer. [0003] The cutting mode recognition of coal shearer is mainly based on the identification of coal-rock interface. At present, the identification methods of coal-rock interface include gamma ray scattering method, radar detection method, vibration test method, optical measurement technology, thermal measurement technology, etc. Although the above studies have given a lot of valuable experimental data and results on cutting pattern recogni...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of complex detection equipment and insufficient recognition accuracy in current shearer cutting pattern recognition, the purpose of the present invention is to provide an intelligent shearer cutting pattern recognition system, which uses the motor's operating speed, current and The voltage is the detection signal, the detection equipment is simple and there is a reliable correspondence between the detection signal and the cutting mode; the improved intelligent optimization algorithm is used to determine the optimal parameters of the model to improve the accuracy of recognition

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