Hybrid modelling of doubly fed induction generators with inter-turn stator fault and its detection method using wavelet analysis
Stator faults contribute to 38% of all electrical machine failures. The detection of inter-turn stator fault has therefore been the focus of research for many years. The aim of this research is to provide new condition monitoring technique for doubly fed induction generator during inter-turn fault....
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| Published in | IET generation, transmission & distribution Vol. 7; no. 9; pp. 982 - 990 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Stevenage
The Institution of Engineering and Technology
01.09.2013
Institution of Engineering and Technology The Institution of Engineering & Technology |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1751-8687 1751-8695 |
| DOI | 10.1049/iet-gtd.2012.0491 |
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| Abstract | Stator faults contribute to 38% of all electrical machine failures. The detection of inter-turn stator fault has therefore been the focus of research for many years. The aim of this research is to provide new condition monitoring technique for doubly fed induction generator during inter-turn fault. The contribution of this research is to formulate a method of doubly-fed induction generator (DFIG) inter-turn stator fault detection that is applicable when this machine operates during steady-state condition. New proposed hybrid model (ABC/dq) has been presented for modelling of DFIG with inter-turn stator fault. Finally a new index has been defined for the detection of inter-turn stator fault in DFIG that employs wavelet analysis of the stator currents and energy of a signal which has been called fault detection index. Proposed index is robust to variation of operating point, percentage of turn fault, stator and rotor resistance and sampling frequency. |
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| AbstractList | Stator faults contribute to 38% of all electrical machine failures. The detection of inter‐turn stator fault has therefore been the focus of research for many years. The aim of this research is to provide new condition monitoring technique for doubly fed induction generator during inter‐turn fault. The contribution of this research is to formulate a method of doubly‐fed induction generator (DFIG) inter‐turn stator fault detection that is applicable when this machine operates during steady‐state condition. New proposed hybrid model (ABC/dq) has been presented for modelling of DFIG with inter‐turn stator fault. Finally a new index has been defined for the detection of inter‐turn stator fault in DFIG that employs wavelet analysis of the stator currents and energy of a signal which has been called fault detection index. Proposed index is robust to variation of operating point, percentage of turn fault, stator and rotor resistance and sampling frequency. Stator faults contribute 38% of electrical machine failures. The detection of inter-turn stator fault has, therefore, been the focus of research for many years. The aim of this research is to provide new condition monitoring technique for doubly fed induction generator during inter-turn fault. The contribution of this research is to formulate a method of doubly-fed induction generator (DFIG) inter-turn stator fault detection that is applicable when this machine operates during steady-state condition. New proposed hybrid model (ABC/dq) has been presented for modelling of DFIG with inter-turn stator fault. Finally, a new index has been defined for the detection of inter-turn stator fault in DFIG that employs wavelet analysis of the stator currents and energy of a signal which has been called fault detection index. Proposed index is robust to variation of operating point, percentage of turn fault, stator and rotor resistance, and sampling frequency. |
| Author | Yousefi kia, Mohammad Najafi, Hamid Reza Shamsi Nejad, Mohammad Ali Khedri, Mostafa |
| Author_xml | – sequence: 1 givenname: Mohammad surname: Yousefi kia fullname: Yousefi kia, Mohammad email: yoosefi.mohammad@yahoo.com organization: Department of Power Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran – sequence: 2 givenname: Mostafa surname: Khedri fullname: Khedri, Mostafa organization: Department of Power Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran – sequence: 3 givenname: Hamid Reza surname: Najafi fullname: Najafi, Hamid Reza organization: Department of Power Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran – sequence: 4 givenname: Mohammad Ali surname: Shamsi Nejad fullname: Shamsi Nejad, Mohammad Ali organization: Department of Power Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran |
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| Copyright | The Institution of Engineering and Technology 2013 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons, Ltd. on behalf of The Institution of Engineering and Technology 2014 INIST-CNRS Copyright The Institution of Engineering & Technology 2013 |
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| Keywords | doubly fed induction generator power generation reliability rotors electrical machine failure wavelet transforms fault detection index interturn stator fault detection asynchronous generators steady-state condition sampling frequency failure analysis rotor resistance stators hybrid modelling wavelet analysis signal sampling condition monitoring power generation faults DFIG Asynchronous generators Stator Absorbing boundary condition Failures Modeling Rotor Steady state Sampling frequency Wavelet transformation Electric machine Double supply machine Hybrid model Signal analysis Monitoring Defect detection |
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| Snippet | Stator faults contribute to 38% of all electrical machine failures. The detection of inter-turn stator fault has therefore been the focus of research for many... Stator faults contribute to 38% of all electrical machine failures. The detection of inter‐turn stator fault has therefore been the focus of research for many... Stator faults contribute 38% of electrical machine failures. The detection of inter-turn stator fault has, therefore, been the focus of research for many... |
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| SubjectTerms | Applied sciences asynchronous generators condition monitoring DFIG doubly fed induction generator Electrical engineering. Electrical power engineering electrical machine failure Electrical machines Exact sciences and technology failure analysis Fault detection fault detection index Faults High voltage or high current generators hybrid modelling Induction generators interturn stator fault detection Miscellaneous Modelling power generation faults power generation reliability rotor resistance rotors Sampling sampling frequency signal sampling Stators steady‐state condition Testing. Reliability. Quality control Various equipment and components Wavelet analysis wavelet transforms |
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| Title | Hybrid modelling of doubly fed induction generators with inter-turn stator fault and its detection method using wavelet analysis |
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