基于IDDT标准差和偏斜度的故障诊断方法

Diagnosis method based on the standard deviation and skewness of IDDT

以CMOS电路动态电流(IDDT)为研究对象,提出了一种针对IDDT测试信号数据的预处理方法。该方法从统计角度出发,通过计算故障电路IDDT的标准差和偏斜度得到故障特征。文中采用CMOS与非门电路进行仿真,将该方法与小波变换预处理方法进行对比,并结合概率神经网络分类方法对故障进行诊断。仿真结果证明了基于IDDT标准差和偏斜度预处理方法的有效性,并且结合概率神经网络对晶体管桥接故障、阻性开路故障和晶体管参数故障的故障诊断平均正确率达到90.7%。

In this paper,the dynamic current（IDDT）of CMOS circuit is studied,and a preprocessing method for IDDT is proposed.the fault characteristics are obtained from the standard deviation and the skewness of the IDDT.This paper uses CMOS NAND gate circuit simulation,the method of wavelet transformation pretreatment methods were compared,and combined with the probabilistic neural network classification method of fault diagnosis.The simulation results demonstrate the effectiveness of the proposed method based on the IDDT standard deviation and the skewness of the method,and the average correct rate of the fault diagnosis of the transistor bridge fault,the open circuit fault and the transistor parameters is 90.7%.