The optimal morlet wavelet and its application on mechanical fault detection
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
A boltzmann theory based dynamic agglomerative hierarchical clustering
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
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A new method of fault diagnosis based on feature weighted FCM is presented. Feature-weight assigned to a feature indicates the importance of the feature. This paper shows that an appropriate assignment of feature-weight can improve the performance of fuzzy c-means clustering. Feature evaluation based on class separability criterion is discussed in this paper. Experiment shows that the algorithm is able to reliably recognize not only different fault categories but also fault severities. Therefore, it is a promising approach to fault diagnosis of rotating machinery.