TY  - JOUR
T1  - 3D Wavelet Network and Wavelet Transform Used for Transmission Lines Fault
Detection and Their Classification
AU - Hussein Zayer, Wael 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 18
SP  - 7732
EP  - 7738
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.7732.7738
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.7732.7738
KW  - Transmission line
KW  -fault detection
KW  -classification
KW  -WT
KW  -3DWN
KW  -decompositions
AB  - Accurate detection and classification of transmission line faults for permanent protection in avoiding
costly maintenance remain challenging to power system engineers. To resolve this issue, we used Wavelet
Transform (WT) and 3D-Wavelet Network (3DWN) to detect and classify various types of faults in
transmission lines depending on the emanating waves from the power system. First, the WT was used to extract
the vector features for each type of faults. Next, these features were analyzed using three level decompositions.
The wavelet toolbox in MATLAB/Simulink was utilized to calculate the maximum norm values, maximum detail
coefficients and energy of the current signals. Furthermore, 3DWN was employed to classify the single line to
ground faults, line-to-line faults, double line to ground faults and three lines faults. Result obtained using WT
and 3DWN confirmed the possibility of developing an accurate fault classification scheme useful for reliable
transient-based protection approaches where this applicable for each case of faults.
ER  -