A Novel Sequential Diagnostic Method for Complex Equipments

The complexity of technology and structure of equipments increasing significantly raise challenges in equipment diagnosis. Extensive researches make us recognize that Design for Testability (DFT) must be carried out concurrently with functional design of equipments in order to fundamentally solve these problems. Diagnostic strategy design, as an important aspect during DFT, is crucial for reducing test cost and improving diagnostic accuracy and efficiency. This paper considers the problem of constructing near-optimal diagnostic strategies for complex equipments. Firstly, the diagnostic strategy optimization problem is formulated. Secondly, a novel algorithm is presented. The proposed algorithm is based on the existing one-step look-ahead search algorithm (greedy algorithm) and multi-step look-ahead search algorithm (AO* algorithm), employs the information gain as its heuristic strategy, and can provide an efficient tradeoff between optimality and computational complexity. The experimental results show that the proposed algorithm provides a better computational precise than one-step look-ahead search algorithm and less consume time than multi-step look-ahead search algorithm, and verify its correctness and validity. Finally, an application study on a helicopter attitude and heading system is presented. The results demonstrate that the diagnostic strategy constructed by the proposed algorithm can improve the optimality, reduce diagnostic cost, and is suitable for diagnosis in large and complex systems.