Winding Function Approach to Simulate Induction Motors under Sleeve Bearing Fault

被引:0
|
作者
Ojaghi, Mansour [1 ]
Yazdandoost, Nasser [1 ]
机构
[1] Univ Zanjan, Dept Elect Engn, Zanjan, Iran
关键词
Induction motor; Sleeve bearing; Oil whirl fault; Modeling and simulation;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes dynamic modeling and simulation of squirrel cage induction motors under oil whirl fault within their sleeve bearings. Previous experimental results are used for defining an appropriate air gap function under the fault. This function is used in the winding function approach for the modeling and simulation purpose. Analytic approach and simulation results show presence of the same frequency components on the stator line current of the faulty motor. Some of these frequency components can be appropriate indices for diagnosing the fault.
引用
收藏
页码:158 / 163
页数:6
相关论文
共 50 条
  • [41] Inter-turn stator winding fault diagnosis in three-phase induction motors, by Park's vector approach
    Cardoso, AJM
    Cruz, SMA
    Fonseca, DSB
    [J]. IEEE TRANSACTIONS ON ENERGY CONVERSION, 1999, 14 (03) : 595 - 598
  • [42] Inter-turn stator winding fault diagnosis in three-phase induction motors, by Park's vector approach
    Cardoso, AJM
    Cruz, SMA
    Fonseca, DSB
    [J]. 1997 IEEE INTERNATIONAL ELECTRIC MACHINES AND DRIVES CONFERENCE RECORD, 1997, : MB151 - MB153
  • [43] DESIGN OF DUAL SPEED SINGLE WINDING INDUCTION-MOTORS, A UNIFIED APPROACH
    PARIMELALAGAN, R
    SUBBIAH, M
    KRISHNAMURTHY, MR
    [J]. IEEE TRANSACTIONS ON POWER APPARATUS AND SYSTEMS, 1977, 96 (04): : 1060 - 1060
  • [44] A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing
    Si-Yu Shao
    Wen-Jun Sun
    Ru-Qiang Yan
    Peng Wang
    Robert X Gao
    [J]. Chinese Journal of Mechanical Engineering, 2017, 30 : 1347 - 1356
  • [45] A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing
    Shao, Si-Yu
    Sun, Wen-Jun
    Yan, Ru-Qiang
    Wang, Peng
    Gao, Robert X.
    [J]. CHINESE JOURNAL OF MECHANICAL ENGINEERING, 2017, 30 (06) : 1347 - 1356
  • [46] A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing
    Si-Yu Shao
    Wen-Jun Sun
    Ru-Qiang Yan
    Peng Wang
    Robert X Gao
    [J]. Chinese Journal of Mechanical Engineering, 2017, 30 (06) : 1347 - 1356
  • [47] Low-Cost Thermographic Analysis for Bearing Fault Detection on Induction Motors
    Nunez, J. A. R.
    Velazquez, L. M.
    Hernandez, L. A. M.
    Troncoso, R. J. R.
    Osornio-Rios, R. A.
    [J]. JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH, 2016, 75 (07): : 412 - 415
  • [48] Vibration analysis as useful domain for detection of bearing fault signals in induction motors
    Tabasi, M.
    Ojaghi, M.
    Mostafavi, M.
    [J]. International Journal of Engineering, Transactions B: Applications, 2021, 34 (08): : 2010 - 2020
  • [49] Application of Generalized Demodulation in Bearing Fault Diagnosis of Inverter Fed Induction Motors
    Li, Cui
    Liu, Zhenxing
    Zhou, Fengxing
    Gong, Cheng
    [J]. 2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2014, : 2328 - 2333
  • [50] Fuzzy model based on-line stator winding turn fault detection for induction motors
    Wang Xu-hong
    He Yi-gang
    [J]. ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 1, 2006, : 838 - 843