Research Of Shearer Self-Adaptive Cutting Control Based On Memory Cutting Technology

A shearer is one of the key equipment of mechanized mining face, and is an important technical equipment for achieving efficiently intensive coal-mining, reducing the fatal accidents of coalmine and improving the working conditions of working face. At present, the automatic control of hydraulic support and scraper conveyor of “three-machine interaction” technology has been achieved, but the automatic control of a shearer has not really realized. Therefore, the automatic, intelligent and unmanned control of a shearer is the key to the automatic, intelligent and unmanned control of mechanized mining face. It's necessary to research the automatic control of the shearer for the support to safe and efficient coalmine production.This topic is the important component of the national major basic research program(973 project) of China. Connection with the memory cutting technology, the paper researches the self-adaptive cutting control of shearer to make the three parts control of height, haulage speed and drum revolution speed come ture. The main research work of this paper is as follows.(1)Based on a detailed understanding of the structure, working principle and characteristics of the shearer and each part, this paper build the self-adaptive cutting control system architecture based on the memory cutting technology, including system composition, control principle and the three parts control coupling relationship. Finally, the memory cutting principle, memory strategy and the establishes drum load model of shearer are analyzed.(2)In order to improve the rapidity, stability and accuracy of height adjusting system during memory cutting and find suitable height control method for downhole harsh working conditions, the hydraulic system mathematical model is established and the state space model on the deviation variable for electro-hydraulic position servo system is obtained. Then the variable rate reaching law sliding-mode controller is designed to realize the fast, steady, accurate and small chattering height adjusting. It overcomes the uncertainty and external load disturbance impact of the system.(3)The prediction method of average coal hardness based on memory cutting technology is propesed for the first time. In order to determine the optimal control parameters at tracking stage and obtain the integrated optimal cutting performance of the unmanned shearer, a multi-objective optimization model of the shearer is built which takes the movement parameters as the design variables and different performance indexes as the sub-objectives. Then the integrated optimal movement parameters under different coal seam hardness are obtained. Finally, the traditional movement parameters matching and the optimal movement parameters matching are compared. The result shows that the performance of the dynamic matching with optimal movement parameters at different coal seam hardness is better than that with the traditional movement parameters.(4)In order to realize the self-adaptive modified control of shearer three parts control to adapt to the variation of coal and rock condition during memory cutting process, the cutting motor current, dragging motor current and height adjusting hydraulic cylinder pressure signal is decomposed by wavelet packet for further data integration. Then the coal cutting state BP neural networks recognition model is established to recognize the state. Connection with the cutting risk coefficient, the paper proposes the self-adaptive modified control strategy of three parts control for shearer. The simulation results show that self-adaptive modified control strategy can achieve the adaptivity to the variation of coal and rock condition during memory cutting process. It will guarantee the safety and efficiency of the whole shearer.