摘要
为了改进人工智能方法在配电网故障诊断系统中的应用,给出了基于粗糙集理论的RBF神经网络的模型结构,然后利用训练好的神经网络对配电网进行故障诊断。采用VC++语言开发工具,调用Matlab神经网络工具箱建立了一个简化的故障诊断系统,并通过配电网实例验证了方法的正确性。实践证明不但提高了配电网故障诊断的容错性,使故障诊断变得更加准确有效,而且减少了神经网络样本数据,减少了故障诊断过程的时间。
This article introduced the using of USB model block where it was used in automated welding machine and the design. The design of automated welding controlling system which was based on USB model block could satisfy large amount of data that was about welding trajectories, and could avoid interference which was from communications between the control system and the PC. The controller could directly acquire data from USB disk,by this method it could reduce data processing,so that it could improve the efficiency of controller.
出处
《机械与电子》
2008年第8期67-70,共4页
Machinery & Electronics
基金
湖南省重大科技基金项目(E067878197)
关键词
配电网
故障诊断
粗糙集
人工神经网络
distribution network
fault diagnosis
rough sets
artifical neural
