Multiple Faults Diagnosis of Induction Motor Using Artificial Neural Network

被引：9
|
作者：
Jigyasu, Rajvardhan [1 ]
Mathew, Lini [1 ]
Sharma, Amandeep [1 ]
机构：
[1] Natl Inst Tech Teachers Training & Res, Elect Engn Dept, Sect 26, Chandigarh 160019, India
来源：
ADVANCED INFORMATICS FOR COMPUTING RESEARCH, ICAICR 2018, PT I | 2019年 / 955卷
关键词：
Induction motor; Fault detection; Fault diagnosis; Artificial intelligence; ANN; Transfer functions; Time domain analysis;
D O I：
10.1007/978-981-13-3140-4_63
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents multiple fault diagnosis and detection using artificial neural feed forward network. In this work analysis is done on induction motor, as these motor are widely used in industries because of their robustness, easy maintenance etc. The current and vibration responses of healthy motor, motor with bearing, rotor and stator defects are analysed. The feature extraction process is done in time domain only. From the results it is cleared that among various transfer functions in ANN the trainlm performs best and traingdm performs worst for fault detection.
引用
收藏
页码：701 / 710
页数：10
相关论文
共 50 条
  • [1] Serial wound starter motor faults diagnosis using artificial neural network
    Bayir, R
    Bay, ÖF
    ICM '04: PROCEEDINGS OF THE IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS 2004, 2004, : 194 - 199
  • [2] Electric motor faults diagnosis using artificial neural networks
    Li, LX
    Mechefske, CK
    Li, WD
    INSIGHT, 2004, 46 (10) : 616 - 621
  • [3] Detection of Inter Turn Short Circuit Faults in Induction Motor using Artificial Neural Network
    Mohamed, Menshawy
    Mohamed, Essam
    Mohamed, Al-Attar
    Abdel-Nasser, Mohamed
    Hassan, Mohamed Moustafa
    PROCEEDINGS OF THE 26TH CONFERENCE OF OPEN INNOVATIONS ASSOCIATION FRUCT, 2020, : 297 - 304
  • [4] Monitoring and diagnosis of external faults in three phase induction motors using artificial neural network
    Eldin, ElSayed M. Tag
    Emara, Hassan R.
    Aboul-Zahab, Essam M.
    Refaat, Shady S.
    2007 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1-10, 2007, : 812 - +
  • [5] Control of Induction Motor Using Artificial Neural Network
    Kumar, Abhishek
    Singh, Rohit
    Mahodi, Chandan Singh
    Sahoo, Sarat Kumar
    ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2016, 2017, 517 : 791 - 804
  • [6] A Hybrid TSA-Neural Network Approach for Induction Motor Faults Diagnosis
    Khiam, Abdennabi
    Ouassaid, Mohammed
    Ngote, Nabil
    PROCEEDINGS OF 2017 INTERNATIONAL RENEWABLE & SUSTAINABLE ENERGY CONFERENCE (IRSEC' 17), 2017, : 629 - 634
  • [7] Neural networks application for induction motor faults diagnosis
    Kowalski, CT
    Orlowska-Kowalska, T
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2003, 63 (3-5) : 435 - 448
  • [8] Condition Monitoring of Induction Motor using Artificial Neural Network
    Bhavsar, Ravi C.
    Patel, Rakeshkumar A.
    Bhalja, B. R.
    2014 ANNUAL INTERNATIONAL CONFERENCE ON EMERGING RESEARCH AREAS: MAGNETICS, MACHINES AND DRIVES (AICERA/ICMMD), 2014,
  • [9] Identification of Induction Motor at Standstill Using Artificial Neural Network
    Bechouche, Ali
    Sediki, Hamid
    Abdeslam, Djaffar Ould
    Haddad, Salah
    IECON 2010 - 36TH ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2010,
  • [10] Performance Estimation of Induction Motor using Artificial Neural Network
    Lee, Ho-Young
    Lee, Jong-Il
    Kwon, Soon-O
    Lee, Su-Woong
    2018 25TH INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP), 2018,
12345