Vibration-Based Fault Diagnosis of Commutator Motor

被引:52
|
作者
Glowacz, Adam [1 ]
Glowacz, Witold [1 ]
机构
[1] AGH Univ Sci & Technol, Fac Elect Engn Automat Comp Sci & Biomed Engn, Dept Automat Control & Robot, Al A Mickiewicza 30, PL-30059 Krakow, Poland
关键词
INDUCTION-MOTORS; ROTOR BAR; CLASSIFICATION; IDENTIFICATION; SIGNALS;
D O I
10.1155/2018/7460419
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
This paper presents a study on vibration-based fault diagnosis techniques of a commutator motor (CM). Proposed techniques used vibration signals and signal processing methods. The authors analysed recognition efficiency for 3 states of the CM: healthy CM, CM with broken tooth on sprocket, CM with broken rotor coil. Feature extraction methods called MSAF-RATIO-50-SFC (method of selection of amplitudes of frequencies ratio 50 second frequency coefficient), MSAF-RATIO-50-SFC-EXPANDED were implemented and used for an analysis. Feature vectors were obtained using MSAF-RATIO-50-SFC, MSAF-RATIO-50-SFC-EXPANDED, and sum of RSoV. Classification methods such as nearest mean (NM) classifier, linear discriminant analysis (LDA), and backpropagation neural network (BNN) were used for the analysis. A total efficiency of recognition was in the range of 79.16%- 93.75% (T-V). The proposed methods have practical application in industries.
引用
收藏
页数:10
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