FAULT DETECTION IN INDUCTION MOTORS USING VIBRATION PATTERNS AND ELM NEURAL NETWORK

被引：0

作者：

Ramalho, G. L. B. ^{[1
]}

Pereira, A. H. ^{[1
]}

Reboucas Filho, P. P. ^{[1
]}

Medeiros, C. M. S. ^{[1
]}

机构：

[1] Inst Fed Ceara, Limoeiro Do Norte, Brazil

来源：

HOLOS | 2014年 / 30卷 / 04期

关键词：

Fault detection; MEMS sensors; ELM neural network;

D O I：

10.15628/holos.2014.1925

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The condition monitoring of industrial electric motors provides information to help planning maintenance interventions before the occurrence of failures. This paper proposes a new approach for monitoring the operational condition of three-phase induction motors based on the extraction of characteristics of a signal obtained with MEMS accelerometers. The data extracted from the decomposition of the vibration signal using Haar Transform and the fractal dimension are used to train a ELM neural network. The results of our experiments demonstrated the feasibility of the proposed methodology in detection and identification of mechanical and electrical failures

引用

页码：185 / 194

页数：10

共 50 条

[31] Fault detection in distillation column using NARX neural network [J].

Taqvi, Syed A. ;

Tufa, Lemma Dendana ;

Zabiri, Haslinda ;

Maulud, Abdulhalim Shah ;

Uddin, Fahim .

NEURAL COMPUTING & APPLICATIONS, 2020, 32 (08) :3503-3519

[32] Fault detection in distillation column using NARX neural network [J].

Syed A. Taqvi ;

Lemma Dendana Tufa ;

Haslinda Zabiri ;

Abdulhalim Shah Maulud ;

Fahim Uddin .

Neural Computing and Applications, 2020, 32 :3503-3519

[33] Fault Detection of Brahmanbaria Gas Plant using Neural Network [J].

Sowgath, M. T. ;

Ahmed, S. .

2014 INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (ICECE), 2014, :733-736

[34] Fault Detection in Photovoltaic Systems Using Optimized Neural Network [J].

Kayal P. ;

Abdul Vasih T. V .

Applied Solar Energy (English translation of Geliotekhnika), 2023, 59 (03) :269-282

[35] Optimal Rotor Fault Detection in Induction Motor Using Particle-Swarm Optimization Optimized Neural Network [J].

Yektaniroumand, T. ;

Azari, M. Niaz ;

Gholami, M. .

INTERNATIONAL JOURNAL OF ENGINEERING, 2018, 31 (11) :1876-1882

[36] Induction machine fault detection using stray flux EMF measurement and neural network-based decision [J].

Bacha, Khmais ;

Henao, Humberto ;

Gossa, Moncef ;

Capolino, Gerard-Andre .

ELECTRIC POWER SYSTEMS RESEARCH, 2008, 78 (07) :1247-1255

[37] Vibration signal analysis for electrical fault detection of induction [J].

Su, Hua ;

Xi, Wang ;

Chong, Kil To .

2007 INTERNATIONAL SYMPOSIUM ON INFORMATION TECHNOLOGY CONVERGENCE, PROCEEDINGS, 2007, :188-+

[38] Robust Stator Fault Detection Under Load Variation in Induction Motors Using AI Techniques [J].

Lashkari, Negin ;

Azgomi, Hamid Fekri ;

Poshtan, Javad ;

Poshtan, Majid .

2015 IEEE INTERNATIONAL ELECTRIC MACHINES & DRIVES CONFERENCE (IEMDC), 2015, :1446-1451

[39] Modeling and Detection of Inter-Turn Fault in Induction Motors Using Wavelet Entropy Estimation [J].

Jagadanand, G. ;

Gopi, Lalgy ;

George, Saly ;

Jacob, Jeevamma .

INTERNATIONAL REVIEW OF ELECTRICAL ENGINEERING-IREE, 2012, 7 (01) :3342-3352

[40] Optimal MLP neural network classifier for fault detection of three phase induction motor [J].

Ghate, Vilas N. ;

Dudul, Sanjay V. .

EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (04) :3468-3481

← 1 2 3 4 5 →