Temporary Short Circuit Detection in Induction Motor Winding Using Second Level Haar-Wavelet Transform

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2011/09/01

タイトル(英語): Temporary Short Circuit Detection in Induction Motor Winding Using Second Level Haar-Wavelet Transform

著者名: Dimas Anton Asfani (Department of Computer Science and Electrical Engineering, Kumamoto University/Department of Electrical Engineering Intitut Teknologi Sepuluh Nopember), Syafaruddin (Department of Computer Science and Electrical Engineering, Kumamoto University), Mauridhi Heri Purnomo (Department of Electrical Engineering Intitut Teknologi Sepuluh Nopember), Takashi Hiyama (Department of Computer Science and Electrical Engineering, Kumamoto University)

著者名(英語): Dimas Anton Asfani (Department of Computer Science and Electrical Engineering, Kumamoto University/Department of Electrical Engineering Intitut Teknologi Sepuluh Nopember), Syafaruddin (Department of Computer Science and Electrical Engineering, Kumamoto University), Mauridhi Heri Purnomo (Department of Electrical Engineering Intitut Teknologi Sepuluh Nopember), Takashi Hiyama (Department of Computer Science and Electrical Engineering, Kumamoto University)

キーワード: early detection，induction motor，temporary fault，wavelet transform

要約(英語): Faults in induction motor winding can be successfully detected using different motor current signature analysis. However, there still remain some parts where the performance of conventional methods can be improved. In case of the fast Fourier transform (FFT) method, it can only identify the permanent fault, but not the temporary one because the method gives frequency content similar to the normal condition. Moreover, the FFT technique is unable to provide the exact timing information of the fault occurrence. On the other hand, the method based on the first level wavelet transform sometimes gives misleading information, especially in case of starting and ending points of temporary short circuit. For these reasons, this paper comes up with a new method for winding fault detection, which analyzes motor current spectrogram based on extension wavelet analysis, called the second level Haar wavelet transform. The proposed method is able to detect temporary fault with very short duration and low current level with more clear information than that of the first level. Several testing scenarios are presented to confirm the robustness of the proposed method including the provision of time of occurrence information for each case.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.131 No.9 （2011）

本誌掲載ページ: 1093-1102 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/131/9/131_9_1093/_article/-char/ja/