• Patel Sana Fatima
• Anuja R. Tungar

While supplying power, transmission and distribution are crucial. Any flaw in these systems may prevent the delivery of energy, which would be quite problematic in today's society. Hence, fault diagnosis has become crucial for providing a consistent supply of electricity. This essay offers an examination of several systems for categorizing transmission line failures. Any disruption in the power system will be discovered by strategically situating the relay medium inside the network. Often, fault detection in the distribution system is the main problem. The fault diagnosis is time-consuming if it occurs during the power swing. In order to guarantee the efficiency of the distributed system, early fault identification is crucial. The complexity and ambiguity of system observations must be managed in order to perform an accurate detection, despite the fact that there are various techniques for fault detection. Fault classification is more crucial for a dependable, high-speed protective relay that is followed by digital distance safety. It is a quick overview of transmission line problems and an evaluation of the applicability of several previous methods to this problem. In this article, we examine research on machine learning algorithms for defect detection. It provides a succinct summary of all prevalent and hybrid methodologies. This study also discusses the necessity for creative fault categorization methods.

Feature selection, feature ranking, redundancy minimization, Radial Basis Function,Kernel

"Cable Fault Detection using Deep Learning Kernel Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.e452-e462, March-2023, Available :http://www.jetir.org/papers/JETIR2303456.pdf

"Cable Fault Detection using Deep Learning Kernel Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppe452-e462, March-2023, Available at : http://www.jetir.org/papers/JETIR2303456.pdf