Fault Diagnosis in Digital Part of Mixed-Mode Circuit

In this paper artificial neural networks (ANNs) are applied to diagnosis of catastrophic defects in the digital part of a nonlinear mixed-mode circuit. The approach is demonstrated on the example of a relatively complex sigma-delta modulator. A set of faults is selected first. Then, fault dictionary is created, by simulation, using the response of the circuit to an input ramp signal. It is represented in a form of a look-up table. Artificial neural network is then trained for modeling (memorizing) the look-up table. The diagnosis is performed so that the ANN is excited by faulty responses in order to present the fault codes at its output. There were no errors in identifying the faults during diagnosis