Identification and extraction of surface discharge acoustic emission signals using wavelet neural network
A hybrid model incorporating wavelet and feed forward back propagation neural network (WFFB-NN) is presented which is used to detect, identify and characterize the acoustic signals due to surface discharge (SD) activity and hence differentiate abnormal operating conditions from the normal ones. The...
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| Main Authors: | , |
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| Format: | Article |
| Published: |
International Academy Publishing (IAP)
2012
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/30514/ http://dx.doi.org/10.7763/IJCEE.2012.V4.536 |
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