Classification of Wear Debris Using Weighted Fuzzy Cluster Method

Dai Qiang Peng; Feng Xu

doi:10.4028/www.scientific.net/AMM.33.70

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The Friction and Wear Properties of VC Coating by TD Process
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Study and Application on Automatic Welding of Bellows Based on Laser Measurement
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Classification of Wear Debris Using Weighted Fuzzy Cluster Method
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Design and Testing of the Copper Pipe and Aluminum Pipe Welding Control System
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Analysis of the Milling Distortion due to Residual Stress Based on Analytical Method
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 33Classification of Wear Debris Using Weighted Fuzzy...

Classification of Wear Debris Using Weighted Fuzzy Cluster Method

Abstract:

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.