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...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Published: |
International Academy Publishing (IAP)
2012
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/30514/ http://dx.doi.org/10.7763/IJCEE.2012.V4.536 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Malaysia |