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Content Provider | IEEE Xplore Digital Library |
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Author | Khan, M.A.S. Rahman, M.A. |
Copyright Year | 2007 |
Description | Author affiliation: Memorial Univ. of Newfoundland, St. John's (Khan, M.A.S.; Rahman, M.A.) |
Abstract | This paper presents an on-line protection scheme for three-phase interior permanent magnet (IPM) motors using artificial neural network. The proposed protection scheme is developed and implemented in real-time using the DS1102 digital signal processor (DSP) board. In this work, a two-layer feed-forward neural network (FFNN) with sixteen inputs and single output is designed and trained off-line with experimental data using the back-propagation algorithm. An experimental setup is developed to accommodate the on-line testing and to carry out the protection of IPM motors. Three types of faults such as single line to ground (L-G) fault, line-to-line (L-L) fault, and single phasing fault are investigated. The technique is evaluated and tested on-line on the laboratory 1-hp and 5-hp IPM motors using the DSP board. The laboratory results show that the proposed technique is able to detect the faulted conditions with high accuracy. |
Starting Page | 1021 |
Ending Page | 1026 |
File Size | 4887287 |
Page Count | 6 |
File Format | |
ISBN | 1424407834 |
ISSN | 1553572X |
DOI | 10.1109/IECON.2007.4459936 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-11-05 |
Publisher Place | Taiwan |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Protection Artificial neural networks Permanent magnet motors Digital signal processing Testing Laboratories Digital signal processors Feedforward systems Neural networks Feedforward neural networks Real-Time implementation Digital signal processor Fault detection Feed-forward neural network Interior permanent magnet motor |
Content Type | Text |
Resource Type | Article |
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