工程科学学报2017，Vol.39Issue(7)：1101-1106,6.DOI:10.13374/j.issn2095-9389.2017.07.017
基于小波包的开关电流电路故障诊断
Fault detection in switched current circuits based on preferred wavelet packet
摘要
Abstract
In order to improve the accuracy of switched current circuit fault diagnosis, a feature extraction and recognition method of switched current circuit based on wavelet packet optimization and optimization of BP neural network was proposed.Firstly, the wavelet packet decomposition of the original response signal of the switched current circuit was carried out.Then, the normalized energy value after the decomposition of the N layer was calculated, and the optimal wavelet packet basis was selected by using the characteristic deviation as the evaluation.Finally, the optimal fault feature vector was constructed.The extracted optimal fault characteristics were classified by BP neural network optimized by genetic algorithm.The results of this method were verified by the example circuit.The results show that all the soft faults are effectively classified, and the superiority of the method in the fault diagnosis of the switched current circuit is illustrated.关键词
开关电流电路/故障诊断/小波包变换/遗传算法/BP神经网络Key words
switched current circuit/fault detection/wavelet packet transform/genetic algorithm/BP neural network分类
机械制造引用本文复制引用
张镇,段哲民,龙英..基于小波包的开关电流电路故障诊断[J].工程科学学报,2017,39(7):1101-1106,6.基金项目
国家自然科学基金资助项目(61201108,61102035) （61201108,61102035）
