计算机技术与发展2019，Vol.29Issue(3)：154-158,5.DOI:10.3969/j.issn.1673-629X.2019.03.032
基于改进EWT的模拟电路故障诊断研究
Research on Analog Circuit Fault Diagnosis Based on Improved EWT
摘要
Abstract
Aiming at the nonlinearity, non-stationary and poor component tolerances in extracting analog circuit fault signals features, we propose a new method based on EWT. However, it is difficult to set the number of modes in separating Fourier spectrum. To fulfill an adaptive separation of Fourier spectrum, we put forward an adaptive nonparametric EWT (APEWT) which can separate the amplitude modulation-frequency modulation components effectively. It has been applied to analyze the output signals of different faults in the Leapfrog benchmark circuit, to perform modal decomposition and time-frequency energy spectrum analysis. The experimental analysis carried by artificial intelligence algorithm shows that the resolution modes obtained by EWT have the corresponding time domain signal characteristics. By comparing with the method of HHT, the proposed method can not only extract features of soft fault features in analog circuit effectively, diagnose more accuracy than the latter, but it has complete wavelet theory, high calculation speed without no false mode. This will help to provide a new idea in extracting features in analog circuit soft fault diagnosis online.关键词
模拟电路/故障诊断/经验小波分解/人工智能/信号分离Key words
analog circuit/fault diagnosis/empirical wavelet transform/artificial intelligence/signal decomposition分类
信息技术与安全科学引用本文复制引用
王宁,李志华,窦修超..基于改进EWT的模拟电路故障诊断研究[J].计算机技术与发展,2019,29(3):154-158,5.基金项目
江苏省自然科学基金(BK20151500) （BK20151500）
