ZHANG Minjun, CHENG Rong, ZHU Yu, ZHANG Ming, ZANG Fuyu, WU Miao. Study on roadheader rectification running performance and control in the in-cline coalmine roadway[J]. Journal of China Coal Society, 2021, 46(S1): 549-557. DOI: 10.13225/j.cnki.jccs.2020.0855
Citation: ZHANG Minjun, CHENG Rong, ZHU Yu, ZHANG Ming, ZANG Fuyu, WU Miao. Study on roadheader rectification running performance and control in the in-cline coalmine roadway[J]. Journal of China Coal Society, 2021, 46(S1): 549-557. DOI: 10.13225/j.cnki.jccs.2020.0855

Study on roadheader rectification running performance and control in the in-cline coalmine roadway

  • The boom-type roadheader is the key equipment in the coal mine roadway excavation, and the au-to-movement and auto-rectification of the roadheader are the key step in the roadway auto-cutting.In terms of the severe working condition of the fully mechanized excavation face, the roadway floor is full of humidity muddy and irregularity.Aimed on the problem in driving performance and rectification control without the consideration of track slippage and roadway angle, the kinematics and dynamic parameters could be determined under the severe working condition.At first, the rectification kinematic equations are obtained based on the incline roadway angle and track slippage.Given the actual working conditions and tracked vehicle terramechanics, the resistance model of the track are proposed by the infinitesimal method.The resistance and force moment equation are also obtained.Based on the kinematics and resistance model, the dynamic model of the roadheader rectification in the incline roadway is proposed.Combining the above model and the roadheader driving hydraulic model, the transfer function of the roadheader rectification is obtained.Aimed at the severe working condition, rectification dynamic model and the nonlinearity of the driving system, the roadheader rectification PID control method based on the neural network is proposed.The PID parameters of the control system could be corrected by the nonlinear mapping and self-learning of the neural network to ensure the optimality of the control parameters.Then the simulation model is built in Matlab to verify the rectification dynamic model and the validity of the control algorithm.Also the experimental system including the intelligent roadheader prototype, simulated roadway and intelligent control system is built to verify the rectification dynamic model and control algorithm.The control parameters could be calculated in the intelligent industrial control computer.The rectification control system is operated in the experimental system.
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