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|Title:||Real-time detection using wavelet transform and neural network of short-circuit faults within a train in DC transit systems|
|Authors:||Chang, C.S. |
|Citation:||Chang, C.S., Kumar, S., Liu, B., Khambadkone, A. (2001-05). Real-time detection using wavelet transform and neural network of short-circuit faults within a train in DC transit systems. IEE Proceedings: Electric Power Applications 148 (3) : 251-256. ScholarBank@NUS Repository. https://doi.org/10.1049/ip-epa:20010350|
|Abstract:||A method is proposed for the real-time detection of DC-link short-circuit faults in DC transit systems. The discrete wavelet transform is implemented to detect any surges in the DC thirdrail current waveform. In the event of a surge the wavelet transform extracts a feature vector from the current waveform and feeds it to a self-organising neural network. The neural network determines whether the feature vector belongs to a normal or a fault current surge.|
|Source Title:||IEE Proceedings: Electric Power Applications|
|Appears in Collections:||Staff Publications|
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