Fault Diagnosis of Motor Rotor Based on Fuzzy C-Means Clustering Analysis

Yu Xiang Cao; Xue Jun Li; Ling Li Jiang

doi:10.4028/www.scientific.net/AMM.273.409

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Fault Diagnosis of Motor Rotor Based on Fuzzy C-Means Clustering Analysis

Abstract:

For the fuzziness of the fault symptoms in motor rotor, this paper proposes a fault diagnostic method which based on the time-domain statistical features and the fuzzy c-means clustering analysis (FCM). This method is to extract the characteristic features of time-domain signal via time-domain statistics and to import the extracted characteristic vector to classifier. And then the fuzzy c-means realizes the classification by confirming the distance among samples, which is based on the degree of membership between the sample and the clustering center. The fault diagnostic cases of motor rotor show that the method which bases on the time-domain statistical features-FCM can detect the rotor fault effectively and distinguish the different types of fault correctly. Therefore, it can be used as an important means of rotor fault identification.