Key Techniques And Decision Support System Of Automatic Mechanised Longwall Mining Face In Thin Coal Seam

Aiming at decision support system and key technology of automatic fully mechanized mining system for thin coal seam, this dissertation systematically studies optimal selection of mining method, expert system of completed equipment selection and matching, pattern clustering analysis and evaluation of fully mechanized mining technical process and key techniques of automatic fully mechanized mining technology using theoretical analysis, numerical simulation, industrial test and field measurement and other research methods. Research results provide theoretical guidance for automatic mining design of thin coal seam. The main innovative points are as follows:(1) Define decision-making index system of optimal selection of mining method for thin coal seams at evaluation criteria of economy, technique and human-computer interface environment. Design Monte Carlo simulation test of index weight vector probability distribution based on theory of discrete random variables probability statistics and develop multi-attribute and multi-objective decision model for optimal selection of mining method for longwall fully mechanized face in thin coal seam, which provide guidance for mining method design in thin coal seam.(2) Build expert system of completed equipment selection based on genetic algorithm optimization and develop decision software for completed intelligent equipment selection. Discuss the reliability of intelligent selection and potential technical risks. Intelligent selection of key equipment for fully mechanized face in thin coal seams is achieved.(3) Pattern classification strategy of fully mechanized mining technology for thin coal seam is presented in this dissertation and evaluation system of clustering analysis of fully-mechanized technology is established. Neural network model of optimal selection of fully mechanized technology is designed and intelligent selection of fully mechanized technology for thin coal seams is achieved. Phased implementation plan for automatic fully mechanized mining technology pattern is designed and completed.(4) Key technique system of automatic mechanized mining process in thin coal seams is set up. Refined classification strategy and implementation plan for automatic coal cutting technique of thin coal seam are provided. Automatic coal cutting technique in complex conditions is developed. Moreover, advanced regulation technology for changing zone of coal seam thickness, preset cutting trace of structure zone and automatic control of cutting speed is achieved, which enriches and improves automatic mining techniques for thin coal seam. Working principle for position and gesture of shearer and video monitoring technology is revealed. In conclusion, decision support system of automatic mechanized mining process is enriched and improved.