基于随机投影和NB网络的模拟电路故障诊断

针对模拟电路故障诊断中故障类型复杂多样、典型故障信息难以获取以及易受噪声、温度等环境影响的难题,提出一种基于随机投影和朴素贝叶斯网络的模拟电路故障诊断方法。该方法首先提取模拟电路故障信息,并利用随机投影算法降维后获取模拟电路故障特征向量,然后通过朴素贝叶斯分类器诊断模型识别模拟电路各个故障。通过对CSTV滤波器电路、四运放双二次高通滤波器电路和实际Sallen-Key带通滤波器电路的实验结果分析表明,相对于传统的模拟电路故障诊断方法,该方法表现出更优的故障诊断性能,并具有更强的抗干扰能力。

Analog circuit fault diagnosis based on random projection and NB network

Aiming at the difficult problems of complex types of faults, difficulties in obtaining typical fault information and being subject to the impacts of environment, such as noise and temperature in analog circuit fault diagnosis, an analog circuit fault diagnosis method based on random projection and naive Bayesian network is proposed in this paper. The method firstly extracts the analog circuit fault information, and random projection method is used to perform the dimension reduction of the fault features and obtain the analog circuit fault feature vectors. Then, the naive Bayesian classifier diagnostic model is used to identify various faults of the analog circuit. The experiment results of CSTV filter circuit, four opamp biquad highpass filter circuit and actual Sallen Key bandpass filter circuit indicate that compared with traditional analog circuit fault diagnosis method, the proposed method shows higher fault diagnosis performance and stronger anti interference ability.