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Real-time detection using wavelet transform and neural network of short-circuit faults within a train in DC transit systems

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4 Author(s)
C. S. Chang ; Centre for Wavelets Approximation & Inf. Processing, Nat. Univ. of Singapore, Singapore ; S. Kumar ; B. Liu ; A. Khambadkone

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 third-rail 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

Published in:

IEE Proceedings - Electric Power Applications  (Volume:148 ,  Issue: 3 )