| Summary: | 碩士 === 中原大學 === 機械工程研究所 === 93 === This paper applies fuzzy neural network (FNN) in the fault diagnosis of the gear-rotor system. According to the document and experiment data, the relationship between fault and frequency spectrum is built up as the rule of approximate reasoning diagnosis and the training data of NN. In this paper, gears which have the four typical faults will be taking into vibrating examining : (1)Gear skew (2)Shaft not parallel (3) Tooth breakage (4)wear. Picking up the characteristic signals by using the technique of analysing spectrums . After classifing by membership function, and detect this classified data in NN. Comparing with the detect result of FNN, NN, and approximate reasoning. Verifying that FNN could make rational and accurate diagnosis from the complicated spectrum.
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