摘要
为实现高效旋转超声振动辅助电火花加工的要求,设计基于FPGA阀值比较的门槛监测法及电火花高频分量监测法的基础判别机制,判别其复杂的加工状态后实时调整输出的占空比。经采集的加工间隙参数通过RS232通信协议实时通信给上位机,经过自适应控制器训练后的BP神经网络PID控制优化Z轴伺服电动机进给量,实现加工间隙在线调整,提升加工效率。
In order to meet the requirement of high efficiency rotary ultrasonic vibration assisted EDM,the threshold monitoring method based on FPGA threshold comparison and the basic discrimination mechanism of EDM high frequency component monitoring method are designed,and the duty cycle of the output is adjusted in real time after distinguishing the complex machining state.The acquired machining gap parameters are communicated to the upper computer in real time through RS232 communication protocol.After training by the adaptive controller,the BP neural network PID control optimizes the Z-axis servo motor feed,realizes online adjustment of machining gap and improves machining efficiency.
作者
徐明刚
宋恩禹
吴志伟
XU Minggang;SONG Enyu;WU Zhiwei(School of Mechanical and Material Engineering,North China University of Technology,Beijing 100144,China)
出处
《机械工程师》
2020年第8期10-12,共3页
Mechanical Engineer
基金
北京市自然科学基金“精度驱动的旋转超声辅助电磁激励调制高效电弧加工技术及机理”(3162011)。
