小波滤波器组在模拟电路故障特征提取中的应用  

Application of Wavelet Filter Banks in Fault Feature Extraction of Analog Circuits

作　　者：张倩[1] ZHANG Qian(Sanmenxia Polytechnic,Sanmenxia 472000,Henan)

机构地区：[1]三门峡职业技术学院智能制造学院,河南三门峡472000

出　　处：《湖南工业职业技术学院学报》2023年第3期26-33,共8页Journal of Hunan Industry Polytechnic

摘　　要：针对模拟电路伪随机信号测试输出响应的特点,提出基于小波滤波器组技术的模拟电路故障特征提取,利用小波滤波器组将测试响应信号分解成多个子频带后分析其时域和功率谱特征,比较正常电路响应各子频带的时域、功率谱特征量,从中选择与无故障特征差异最明显的特征量作为测试与诊断依据。实验结果表明,该故障特征提取方法有效减少故障混叠,提高故障测试分辨率和测试精度。Analog circuit excitation response technique is an important method for analog circuit fault diagnosis.According to the characteristics of pseudo-random signals in analog circuits,the fault feature extraction of analog circuits based on wavelet filter banks is proposed,and the test response signals are decomposed into several sub-bands by using wavelet filter banks,the time domain and power spectrum of the signal in each sub-band are analyzed,and then compared with the time domain and power spectrum characteristic of the normal circuit response to each sub-band signal,the most obvious difference between fault feature and non-fault feature is selected as the basis of test and diagnosis.Experimental results show that the fault feature extraction method can effectively reduce fault aliasing,improve fault resolution and test precision.

关 键 词：故障诊断 伪随机激励信号 小波滤波器组 仿真 

分 类 号：TN713[电子电信—电路与系统]