辽宁石油化工大学学报Issue(2)：58-61,4.DOI:10.3696/j.issn.1672-6952.2015.02.013
一种基于量子神经网络的模拟电路故障诊断方法
An Analog Circuit Fault Diagnostics Approach Based on QNN
摘要
Abstract
To solve the overlap of part of fault classes in the analog circuit fault diagnostics,a novel analog circuit fault diagnostics approach based on quantum neural networks algorithm was presented.Kurtosis and entropy were calculated as features after the time domain response signals of the circuit under test were measured,and then the different fault classes were identified by quantum neural networks algorithm.The simulation demonstrated that constructed neural network had simple network structure and the fault diagnosis accuracy was higher,which reached 99.62%.关键词
模拟电路/故障诊断/峭度/熵/量子神经网络Key words
Analog circuit/Fault diagnostics/Kurtosis/Entropy/Quantum neural networks分类
信息技术与安全科学引用本文复制引用
张朝龙,何怡刚,袁莉芬,陈立平..一种基于量子神经网络的模拟电路故障诊断方法[J].辽宁石油化工大学学报,2015,(2):58-61,4.基金项目
国家杰出青年科学基金项目(50925727) （50925727）
国防科技计划项目(C1120110004、9140A27020211DZ5102) （C1120110004、9140A27020211DZ5102）
国家自然科学基金项目(61102035,61401139,61403115) （61102035,61401139,61403115）
教育部科学技术研究重大项目(313018) （313018）
安徽省科技计划重点项目(1301022036)。 （1301022036）
