Lightning Fault Classification for Transmission Line Using Support Vector Machine

• Main Authors: Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.
• Other Authors: 57194493395
• Format: Conference Paper
• Published: Institute of Electrical and Electronics Engineers Inc. 2024
• Subjects: accuracy; computational time; k-Nearest Neighbor (k-NN); lightning fault; Support Vector Machine (SVM); Electric lines; Electric power transmission; Learning algorithms; MATLAB; Motion compensation; Nearest neighbor search; Transmissions; Accuracy; Computational time; Failure trees; Fault classification; K-near neighbor; Lightning faults; Lightning strikes; Support vector machine; Support vectors machine; Transmission-line; Support vector machines

Transmission lines are susceptible to a variety of phenomena that can cause system faults. The most prevalent cause of faults in the power system is lightning strikes, while other causes may include insulator failure, tree or crane encroachment. In this study, two machine learning algorithms, Suppor...