Classification of Wear Debris Using Weighted Fuzzy Cluster Method
The analysis and identification of wear particles for machine condition monitoring is usually very time-consuming by experienced inspectors. In order to remedy the limitation, automation of the analysis procedure appears to be necessary. A novel weighted fuzzy c-means algorithm for wear particle classification is proposed in this paper. The algorithm uses the variation of the pixel intensities of a region to choose strong resembling area. Then, the spatial relationships of the membership function are constructed to regulate the pixel membership obtained from the FCM object function. Finally, wear debris are classified based on the fuzzy membership. The example shows that the method is briefly and effectively.
Dunwen Zuo, Hun Guo, Hongli Xu, Chun Su, Chunjie Liu and Weidong Jin
D. Q. Peng and F. Xu, "Classification of Wear Debris Using Weighted Fuzzy Cluster Method", Applied Mechanics and Materials, Vol. 33, pp. 70-73, 2010