A method to diagnose faults in linear analog circuits using an adaptive tester

Abstract

This work presents a new diagnosis method for use in an adaptive analog tester. The tester is able to detect faults in any linear circuit by learning a reference behavior in a first step, and comparing this behavior against the output of the circuit under test in a second step. Considering the same basic structure, the diagnosis method consists on injecting probable faults in a mathematical model of the circuit, and later comparing its output with the output of the real faulty circuit. This method has been successfully applied to a case study, a biquad filter. Component soft, large, and hard deviations, and faults in operational amplifiers were considered. The results obtained from practical experiments with this analog circuit are discussed in the paper.

Electronic Circuits Diagnosis Using Artificial Neural Networks

“…Large parametric fault diagnosis was described in (Worsman & Wong, 2002) using piecewise linear models for DC analysis, and separate considerations were given for diagnosis of faults in the dynamic part of the network (considered linear) based on large change sensitivity computations. Further, in (Cota et al, 1999) the diagnostic method applied consists of injecting probable faults in a mathematical model of the linear circuit, and later comparing its output with the output of the real faulty circuit. Transfer functions transformed into the Z domain were created and fault injection was performed.…”