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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhao Juan |
| Copyright Year | 2010 |
| Description | Author affiliation: Institute of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, Hebei, China, 050000 (Zhao Juan) |
| Abstract | The inter turn short-circuit in rotor windings take the induced electromotive force, which is detected by detecting coil, as a study object. And a method of fault diagnosis based on Wavelet analysis and neural network is presented. The induced electromotive force is analyzed by wavelet packet, which can decompose and construct the energy eigenvectors. Then set up the neural network and use the energy eigenvectors as the input vector of neural network. The method can correctly locate singularity that appears on the measured potential signal to diagnose faulting slot correspondingly. The simulated experimental results show that the artificial intelligence method combining detection coil can detect the inter-turn shorted-circuit fault. |
| Starting Page | 617 |
| Ending Page | 620 |
| File Size | 349653 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424469277 |
| e-ISBN | 9781424469284 |
| DOI | 10.1109/ICIFE.2010.5609433 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-09-17 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Coils Windings Rotors motor rotor Artificial neural networks Wavelet analysis Wavelet packets Circuit faults turn-to-turn short circuit neural network |
| Content Type | Text |
| Resource Type | Article |
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