Abstract
When developping a fuzzy diagnosis system for machinery condition diagnosis, fuzzy relation between failure symptoms and failure categories must be defined for fuzzy inference. However, it is not easy to search out the failure symptoms by which all failure categories can be distinguished perfectly and automatically. In order to resolve the problem, we proposed: (1) a new type of parameter called typed (2) the identification method of the membership function of the parameter, (3) the algorithm of fuzzy inference by using the parameters and their membership functions for diagnosis. The efficiency of the above methods has been verified by applying them to the ball bearing diagnosis system and others. In this system of ball bearing diagnosis, the sequence typed parameters are calculated by the symptom goodness of fit with spectrum analysis and the results of sequential fuzzy diagnosis showed the correct conclusions when inputting the field data to the system.
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