基于经济截割的采煤机运动学参数优化研究

利用Matlab软件编制了采煤机以不同牵引速度、不同截割深度截割不同坚固性系数煤层时的载荷计算程序并生成载荷文本，采用均匀设计法对这些文本进行选择，作为刚柔耦合模型的外载，仿真后通过人工神经网络预测了其他工况下各关键零部件的可靠性。基于神经网络预测结果分析了煤层坚固性系数，采煤机牵引速度以及滚筒截割深度与采煤机工作可靠性的关系。并且在保证采煤机可靠工作的前提下，得到了采煤机经济截割曲线，以及相应的最优生产率。研究表明：该型采煤机截割坚固性系数为3的韧性煤时，推荐牵引速度为4.807 m/min，截割深度为550 mm，此时采煤机落煤率为257.8 t/h，其中，单滚筒理论最大落煤率为165 t/h。将虚拟样机技术与人工神经网络相结合能更快更好地解决工程实际中的多参数复杂优化问题。

Optimization research on shearer’s kinematic parameters based on economical cutting

Using Matlab software，the programs for calculating shearer cutting loads when cutting coal seams with different hardness coefficients at different haulage speeds and cutting depths have been written and the load texts have been generated using Matlab.Subsequently，the load texts have been selected using uniform design method and taken as external loads of the rigid flexible coupling models.In addition，after the simulation，the reliabilities of key parts in other working conditions have been predicted using artificial neural network.Based on the predicted results，the relationship between shearer’s haulage speeds，drum’s cutting depths and the shearer’s reliability has been obtained.To assure the shearer’s working reliability，the optimal cutting curve and corresponding optimal productions have been obtained.The research shows that when the shearer cuts the tough coal with consistent coefficient equal to 3，the recommended haulage speed is 4.807 m/min，the cutting depth is 550 mm，and the shearer’s coal extraction rate is 257.8 t/h，the maximum theoretical coal’s extraction rate for single drum is 165 t/h.The study shows that the combination of virtual prototype technology and artificial neural network can effectively solve complex multi parameter problems in engineering practices.