基于倒谱和决策树的模拟电路故障诊断

针对非线性模拟电路故障诊断中参数型故障元件定位的难题,提出一种结合倒谱和决策树的模拟电路故障诊断的方法。首先对采集到的模拟电路离散电压信号进行倒谱变换;然后对变换后的数据进行小波分解并提取相应子频带的能量谱,将提取的能量谱作为对应模式的故障特征;最后利用决策树的分类功能对电路的模式进行判断。仿真结果表明,有效地提取了模拟电路不同模式的故障特征,提高了模拟电路故障诊断的效果。

Analog circuit fault diagnosis based on cepstrum and decision tree

Aiming at the problem of parametric fault diagnosis in nonlinear circuits, an approach utilizing cepstrum and decision tree is proposed.Firstly, the acquired fault response signals are converted by cepstrum.Then, the wavelet analysis is used to decompose the converted data and the energy is taken from different frequency bands.Finally, the obtained fault features are inputted into decision tree to identify different faults.The simulation results show that the proposed method can extract the fault signature effectively and can get a good diagnosis result.