A procedure for the determination of an optimum set of testable components in the fault diagnosis of analog linear circuits is presented. The proposed method has its theoretical foundation in the testability concept and in the canonical ambiguity group concept. New considerations relevant to the existence of unique solution in the k k k-fault diagnosis problem of analog linear circuits are presented, and examples of application of the developed procedure are considered by exploiting a software package based on symbolic analysis techniques.

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This paper discusses a numerically efficient approach to identify complex ambiguity groups for the purpose of analog fault diagnosis in low-testability circuits. The approach presented uses a numerically efficient QR factorization technique applied to the testability matrix. Various ambiguity groups are identified. This helps to find unique solution of fault diagnosis equations or identifies which groups of components can be uniquely determined. This work extends results reported earlier in literature, where QR factorization was used in low-testability circuits, significantly increasing efficiency to determine ambiguity groups. Matlab program that implements this method was integrated with a symbolic analysis program that generates test equations. The method is illustrated on two low-testability electronic circuits. Finally, method efficiency is tested on larger electronic circuits with several hundred tested parameters.

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