摘要
对模拟电路提出了一种基于小波变换与神经网络相结合的故障诊断方法,该方法用小波变换对模拟电路故障信号提取小波特征,并经小波变换压缩,再将故障特征量输入至神经网络处理。结果表明,该方法有效地减少神经网络输入层单元数,简化了神经网络结构,提高了故障诊断能力。
The methods based on the neural network technology combined with the wavelet for fault diagnose were developed, which used wavelet transforms as analogy circuit fault signal preprocessor to make the number of input neural network decreased effectively. The structure of neural network was predigested and the ability of fault diagnoses was prompted.
出处
《大连工业大学学报》
CAS
北大核心
2010年第1期59-61,共3页
Journal of Dalian Polytechnic University
关键词
模拟电路
小波变换
故障诊断
神经网络
analogy circuit
wavelet transforms
fault diagnoses
neural network
