摘要
采煤机实现牵引运动是通过牵引部的齿轮进行啮合传动,齿轮啮合传动过程的可靠性决定了采煤机运动的稳定性。为了对采煤机牵引部传动系统运动的可靠性实现有效评估,通过BP神经网络拟合静态啮合和动态啮合基本参数和接触应力之间的关系,并通过一次二阶矩阵分析其可靠度、可靠性灵敏度。训练完成的BP神经网络模型对80组随机生成的参数进行拟合分析,结果显示在对静态啮合过程进行分析时,误差为±0.006 MPa;进行动态啮合分析时的误差为0.006 MPa,符合设定要求。这一结果说明研究构建的模型能够有效评估牵引部齿轮转动系统的可靠性,可为提升采煤机运动的稳定性提供有效数据。
Shearer realizes traction movement through meshing transmission of traction gear,so the reliability of gear meshing transmission process determines stability of shearer motion.In order to effectively evaluate reliability of driving system of shearer traction unit,the relationship between the basic parameters of static meshing and dynamic meshing and the contact stress is fitted by BP neural network,and its reliability and reliability sensitivity are analyzed through the first and second order matrix.The results show that the error is±0.006 MPa in static meshing process analysis and 0.006 MPa in dynamic meshing analysis,which meets the set requirements.The results show that the model can effectively evaluate the reliability of traction gear rotation system,and can provide effective data for improving stability of shearer motion.
作者
曹建民
Cao Jianmin(Anyang Zhujiao Coal Industry Co.,Ltd.,Anyang 450000,China)
出处
《能源与环保》
2021年第12期196-201,共6页
CHINA ENERGY AND ENVIRONMENTAL PROTECTION
基金
河南省重点科技攻关计划(152102210103)。
关键词
采煤机
牵引部
传动系统
运动精度
可靠性
shearer
traction part
transmission system
motion accuracy
reliability
