Research On Cutting Load Identification And Intelligent Control Method Of Shearer

As the core equipment of fully mechanized mining face,electric traction shearer has the problems of low working efficiency,low degree of automation and intelligence.Therefore,it is necessary to study the key technology of intelligent control of electric traction shearer to provide technical guarantee for safe and efficient mining.Through the research of cutting load identification technology,traction speed regulation control and cutting trajectory tracking control methods,this paper lays a foundation for the realization of intelligent control of electric traction shearer.Aiming at the problem of relying on manual control in the control process of shearer,in order to improve the automation level of coal mining,by analyzing the basic structure and working principle of electric traction shearer,an intelligent control strategy based on cutting load regulation is proposed to realize drum height adjustment,traction speed regulation and coordinated control between them.Aiming at the problem that it is difficult to detect the cutting load of shearer directly,by analyzing the load detection mechanism of AC asynchronous cutting motor,a cutting load prediction method based on Elm neural network is proposed based on soft sensing modeling theory.The improved elm neural network is used to establish the soft sensing model of cutting load,and compared with BP and RBF neural network models respectively.The results show that the goodness of fit of the improved elm neural network model is 0.978 and the root mean square error is 1.565.It can accurately predict the cutting load under different working conditions,which provides a theoretical basis for the traction speed regulation of shearer.Aiming at the problem that the speed regulation of shearer depends on manual experience,the load of cutting and traction motor is analyzed,the coupling dynamic model of cutting and traction is established,and the variation law of "load traction speed" is revealed.Through the speed regulation characteristics of traction motor,the speed regulation control strategy of constant power control is proposed.The traction drive system model is built according to Simulink.The speed regulation effect is analyzed by comparing fuzzy PID and BP-PID control methods.The simulation results show that BP-PID control method has shorter response time and can realize rapid control of traction speed regulation.Aiming at the problem of poor tracking effect of shearer on planned height adjustment cutting trajectory,a PID control tracking method based on BP neural network is proposed.By establishing the relationship between the drum height curve and the swing angle of the rocker arm,the displacement of the hydraulic oil cylinder and the swing angle of the oil cylinder,the transfer function model of the hydraulic servo height adjustment system of the shearer is obtained.Two different control methods,traditional PID and fuzzy PID control,are compared and analyzed to track different planned traj ectories.The results show that the BP-PID control method has the smallest error when tracking and controlling the planned cutting traj ectory,and the tracking error is less than 0.015m,which can effectively improve the tracking effect of cutting trajectory.