摘要
为研究采煤机在电动机启动与截割阶段的系统动态特性并达到性能优化的目的,建立了采煤机滚筒载荷数学模型,有效模拟了滚筒截割时的受载过程。通过耦合传动轴、轴承支承作用以及行星齿轮传动和直齿轮传动,建立了齿轮传动系统有限元动态模型。基于d、q轴的三相异步电动机数学模型,通过电动机转子动力学方程实现了电动机与传动系统的耦合。以齿轮运动副的最大动态载荷为目标函数,进行了截割传动系统灵敏度分析和动态优化设计,应用直接微分法测试截割传动系统参数对系统动态现象的灵敏度,并基于遗传算法得到了最优动态力下的最佳设计变量。灵敏度分析与优化设计的结合,合理地选择对采煤机截割传动系统反应灵敏的设计参数,极大地缩短了复杂系统的优化时间与设计周期。
In order to study the system dynamic characteristics of the shearer in the motor starting and cutting stages,and achieve performance optimization,a mathematical model of the drum load was established to effectively simulate the loading process during drum cutting.Then,a finite element dynamic model of the gear drive system was established by coupling the drive shaft,the bearing support,the planetary gear drive and the spur gear drive.The mathematical model of three phase asynchronous motor based on d and q axis was established,at the same time,the coupling of the motor and the drive system was realized by the dynamic equation of the motor rotor.Taking the maximum dynamic load of the gear kinematic pair as the objective function,the sensitivity analysis and dynamic optimization design of the cutting drive system were carried out.Meanwhile,the direct differential method was used to test the sensitivity of the cutting drive system parameters to the dynamic phenomena of the system,and the optimal design variables under the optimal dynamic force were obtained based on the genetic algorithm.The combination of sensitivity analysis and optimization design,with the reasonable selection of design parameters that were sensitive to the cutting drive system of the shearer,greatly shortened the optimization time and design cycle of the complex system.
作者
鲁文佳
黄伟波
朱丽莎
LU Wenjia;HUANG Weibo;ZHU Lisha(College of Mechanical and Automotive Engineering,Zhaoqing University,Zhaoqing 526061,Guangdong,China)
出处
《矿山机械》
2023年第7期55-62,共8页
Mining & Processing Equipment
基金
国家自然科学基金面上项目(51975511)
广东省教育厅青年创新人才项目(2022KQNCX099)。
关键词
采煤机
数学建模
滚筒载荷
截割传动系统
灵敏度分析
动态优化
shearer
mathematical modeling
drum load
cutting drive system
sensitivity analysis
dynamic optimization