Diagnosis of stator faults of the single-phase induction motor using acoustic signals

被引:95
作者
Glowacz, Adam [1 ]
Glowacz, Zygfryd [2 ]
机构
[1] AGH Univ Sci & Technol, Fac Elect Engn Automat Comp Sci & Biomed Engn, Dept Automat & Biomed Engn, Al A Mickiewicza 30, PL-30059 Krakow, Poland
[2] AGH Univ Sci & Technol, Fac Elect Engn Automat Comp Sci & Biomed Engn, Dept Power Elect & Energy Control Syst, Al A Mickiewicza 30, PL-30059 Krakow, Poland
关键词
Fault; Acoustic signal; Single phase induction motor; Diagnosis; Recognition; SUPPORT VECTOR MACHINE; ELECTRICAL MACHINES; TECHNICAL CONDITION; COMBUSTION ENGINE; BEARING; VIBRATION; GEAR; IDENTIFICATION; CLASSIFIERS; CLASSIFICATION;
D O I
10.1016/j.apacoust.2016.10.012
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
An early diagnosis of faults prevents financial loss and downtimes in the industry. In this paper the authors presented the early fault diagnostic technique of stator faults of the single-phase induction motor. The proposed technique was based on recognition of acoustic signals. The authors measured and analysed 3 states of the single-phase induction motor: a healthy single-phase induction motor, a single-phase induction motor with shorted coils of auxiliary winding, a single-phase induction motor with shorted coils of auxiliary winding and main winding. In this paper an original method of feature extraction called MSAF-RATIO30-MULTIEXPANDED (Method of Selection of Amplitudes of Frequency Ratio 30% of maximum of amplitude Multiexpanded) was described. This method was used to form feature vectors. A classification of obtained vectors was performed by the KNN (K-Nearest Neighbour classifier), the K-Means clustering and the Linear Perceptron. The early fault diagnostic technique can find application for protection of the single-phase induction motors. It can be also used for other rotating electrical machines. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:20 / 27
页数:8
相关论文
共 51 条
[1]   Comparative Study of Time-Frequency Decomposition Techniques for Fault Detection in Induction Motors Using Vibration Analysis during Startup Transient [J].
Antonio Delgado-Arredondo, Paulo ;
Garcia-Perez, Arturo ;
Morinigo-Sotelo, Daniel ;
Alfredo Osornio-Rios, Roque ;
Gabriel Avina-Cervantes, Juan ;
Rostro-Gonzalez, Horacio ;
de Jesus Romero-Troncoso, Rene .
SHOCK AND VIBRATION, 2015, 2015
[2]  
Arthur D, 2007, PROCEEDINGS OF THE EIGHTEENTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, P1027
[3]  
Baranski M, 2015, AER ADV ENG RES, V13, P472
[4]   THE INNOVATIVE DESIGN CONCEPT OF THERMAL MODEL FOR THE CALCULATION OF THE ELECTROMAGNETIC CIRCUIT OF ROTATING ELECTRICAL MACHINES [J].
Bedkowski, Bartlomiej ;
Madej, Jerzy .
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 2015, 17 (04) :481-486
[5]   Acoustic emission-based condition monitoring methods: Review and application for low speed slew bearing [J].
Caesarendra, Wahyu ;
Kosasih, Buyung ;
Tieu, Anh Kiet ;
Zhu, Hongtao ;
Moodie, Craig A. S. ;
Zhu, Qiang .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2016, 72-73 :134-159
[6]   Vibroacoustic Measurements and Simulations Applied to External Gear Pumps. An Integrated Simplified Approach [J].
Carletti, Eleonora ;
Miccoli, Giuseppe ;
Pedrielli, Francesca ;
Parise, Giorgio .
ARCHIVES OF ACOUSTICS, 2016, 41 (02) :285-296
[7]   Current-based higher-order spectral covariance as a bearing diagnostic feature for induction motors [J].
Ciszewski, T. ;
Gelman, L. ;
Swedrowski, L. .
INSIGHT, 2016, 58 (08) :431-434
[8]   A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors [J].
Cunha Palacios, Rodrigo H. ;
da Silva, Ivan Nunes ;
Goedtel, Alessandro ;
Godoy, Wagner F. .
ELECTRIC POWER SYSTEMS RESEARCH, 2015, 127 :249-258
[9]  
da Costa C, 2015, INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE (ICCSAI 2014), P109
[10]   Decision Support System for Identifying Technical Condition of Combustion Engine [J].
Deptula, Adam ;
Osinski, Piotr ;
Radziwanowska, Urszula .
ARCHIVES OF ACOUSTICS, 2016, 41 (03) :449-460