A New Optimal Test Node Selection Method for Analog Circuit

The existing test node selection methods of analog dictionary technique assume that the voltage gap of ambiguity group is 0.7 V. However, this technique is not always accurate to determine the right ambiguity gap for each fault mode. As the probability density of the circuit output approximately satisfies the normal distribution, an accurate technique is introduced to determine the ambiguity gap. Then, this paper proposes a new test node selection method with an extended fault dictionary and the overlapped area values. Firstly, the fault dictionary is constructed with the mean and standard variance values of node voltage. Then, the area detection table is generated by the overlapped area values under normal curves for ambiguity faults, which represent the failure probability of ambiguity faults. Finally, the optimal test node set is selected by fusing fault isolation and overlapped area information. The results show that the proposed method is effective to select the optimal test node set and improve the performance of analog fault diagnosis.