Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic element is the test-diagnosis fault unit. Every underlying fault cause's membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples, the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.
Li, J., & Shen, S. T. (2007). Research on the algorithm of avionic device fault diagnosis based on fuzzy expert system. Chinese Journal of Aeronautics, 20(3), 223–229. https://doi.org/10.1016/S1000-9361(07)60036-3