摘要
文章对电火花间隙状态的检测方法进行了介绍,通过分析指出其在精细电火花加工中应用上的限制,将双传感器技术引入电火花加工间隙放电状态的判别中。通过MATLAB软件对所设计的模糊神经网络在计算机上进行训练,待网络达到相应要求后,进行了仿真实验,验证了该设计在实际条件下的可行性,并且与单一传感器的模糊神经网络进行了对比,从这些数据可知,该识别系统在复杂的间隙工作状态下可以稳定地工作。
First, the detection methods of electrical discharge were introduced. The analysis demonstrates the limitations in EDM application; and then double-sensor technology will be lead into the EDM to distinguish interval discharge state. The final training on the computer with fuzzy neural network designed by MATLAB software, after the network reached a corresponding request, conducted a simulation experiment to verify the design＇ s feasibility under realistic conditions, and comparing with a single sensor fuzzy neural network, the result of these data showed that the recognition system in a complex interval working state can carry on stably.
出处
《轻工机械》
CAS
2009年第6期52-54,58,共4页
Light Industry Machinery
基金
浙江省科技厅重点攻关项目(2006C21040)
浙江省机械制造及自动化重中之重开放基金资助项目
关键词
金属加工
电火花
脉冲电源
识别系统
metalworking
electric discharge machining（EDM）
pulse power
discharge condition recognition
