摘要
介绍人工神经网络在电磁无损检测领域的应用现状,重点讨论BP(误差反向传播)神经网络、模糊BP神经网络和径向基函数(RBF)神经网络,分别以应用实例讨论了它们在漏磁和涡流无损检测中的应用。人工神经网络是实现电磁无损检测定量化的有效途径。
The status of electromagnetic nondestructive testing based on artificial neural network is introduced. The BP(error back propagation) neural network, fuzzy BP neural network and RBF(radial basis function) neural network are analyzed in detail. Examples of their application to magnetic flux leakage testing and eddy current testing are also given. Artificial neural network is an effective means for quantitative electromagnetic nondestructive testing.
出处
《无损检测》
2003年第12期638-640,643,共4页
Nondestructive Testing
基金
国家863计划资助项目(2001AA616170
20 0 1AA6 0 2 0 2 1 )
铁路信息科学与工程部级开放实验室资助项目(TDXX0 2 0 2 )
关键词
漏磁检测
涡流检测
人工神经网络
信号处理
无损检测
Magnetic flux leakage testing
Eddy current testing
Artificial neural network
Signal processing
