Fault Diagnosis and Automatic Extraction of Fuzzy Rules in Ac Motors
نویسندگان
چکیده
In this paper a new approach to fault diagnosis in an AC motor is introduced. This system combines a neuro-fuzzy system called FasArt (Fuzzy Adaptive System ART based) and the well-known fuzzy k nearest neighbor algorithm. A set of 15 types of non destructive faults has been tested, reaching a high degree of early fault detection and fault type recognition. Moreover, taking into account the neuro-fuzzy nature of the FasArt model, a set of fuzzy rules, containing the knowledge learnt by the system, has been extracted. These rules permit a transfer of the knowledge from a numerical to a symbolic level where the fuzzy rules describe the fault in linguistic terms that can be interpreted by humans in an easier way.
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