Multidimensional search space for catastrophic faults diagnosis in analog electronic circuits

This paper describes new method of fault diagnosis in analog electronic circuits (AEC). Fault diagnosis in analog electronic circuits is in general tested along with one dimension: the generator frequency. In this paper, we present a novel approach that uses more than one dimension to test AEC (those new dimensions are: the load resistance & reactance, generator resistance & reactance). Proposed novelty can be perceived as a hardware solution of tester of AEC - old approach: tester with one dimension search space, new approach: tester with multidimensional search space. A search space is defined as the set of input variables. In this article, we focus on how an increasing number of dimension of search space (in analog circuit diagnosis) can influence on the identification of states of circuit under test (CUT). The criterion of optimization is the maximum number of unequivocally identified states of CUT, and for that purpose a heuristic algorithm that uses Particle Swarm Optimization (PSO) is used. Some new terms are introduced like: group, testing strategy, testing path. The proposed method has been checked for single catastrophic faults of CUT.