A Fuzzy C-Means Algorithm to Analyze Current Waveform for Determining the Motor’s Quality Types

• Main Authors: Chia-Yi Lin, 林佳儀
• Other Authors: Chiung-Chou Liao
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/yfppfs

碩士 === 健行科技大學 === 電子工程系碩士班 === 106 === This dissertation proposes a novel Fuzzy C-Means (FCM) algorithm for determining the motors’ quality types by analyzing their current waveforms. The determining process of motors’ quality types are listed as follows: (i) Obtaining input current signals of sample motors with well-known distinct classes and then calculating their feature values of qualitative features; (ii) Computing centroid values of each quality class; (iii) Computing Euclidean distances of their feature values and centroid values of classes; and (iv) Determining motors’ quality types using obtained Euclidean distances. A motor belongs to a class-z if it and class-z has the minimum Euclidean distance. Experimental results show that the proposed FSM algorithm is an effective quality determining method for motors.