关键词: 多频测试, 神经网络, 模拟电路, 故障诊断, 测试矢量生成

Abstract: Multifrequency test can maximize differences between the failure state and the normal state of the analog circuit’s response, and Neural Networks（NNs） have the ability to solve complex classification problems. An efficient approach for diagnosing faults in analog circuits is presented. It is based on the advantages of both multifrequency test and NNs. The sensitivity analysis is used to generate and choose the multifrequency test vectors of the Circuit Under Test（CUT）. Fault features of the test point in CUT are extracted and fused. NNs are used to classify the features in a variety of state for the detection and location of faulty components in CUT. The experimental results show that this method is very effective and highly practical for fault diagnosis of analog circuits.

Key words: multifrequency test, neural network, analog circuits, fault diagnosis, test vector generation