Development of smart sensors system for machine fault diagnosis

被引:43
作者
Son, Jong-Duk [1 ]
Niu, Gang [1 ]
Yang, Bo-Suk [1 ]
Hwang, Don-Ha [2 ]
Kang, Dong-Sik [2 ]
机构
[1] Pukyong Natl Univ, Sch Mech Engn, Pusan 608739, South Korea
[2] Korea Electrotechnol Res Inst, Power Facil Diag Res Grp, Chang Won 641120, Gyungnam, South Korea
关键词
Smart sensors; Fault diagnosis; Induction motor; Performance comparison; SUPPORT VECTOR MACHINES;
D O I
10.1016/j.eswa.2009.03.069
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
Machine fault diagnosis is a traditional maintenance problem. In the past, the maintenance using tradition sensors is money-cost, which limits wide application in industry. To develop a cost-effective maintenance technique, this paper presents a novel research using smart sensor systems for machine fault diagnosis. In this paper, a smart sensors system is developed which acquires three types of signals involving vibration, current, and flux from induction motors. And then, support vector machine, linear discriminant analysis, k-nearest neighbors, and random forests algorithm are employed as classifiers for fault diagnosis. The parameters of these classifiers are optimized by using cross-validation method. The experimental results show that smart sensor system has the similar performance for applying in intelligent machine fault diagnosis with reduced product cost. Developed smart sensors have feasibility to apply for intelligent fault diagnosis. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:11981 / 11991
页数:11
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