Fault Detection and Fault Classification In Transmission Line Using Neural Network

Rashika Rajput; Amit Gupta

Fault Detection and Fault Classification In Transmission Line Using Neural Network

Authors: Rashika Rajput, Amit Gupta

Unique Paper ID: 146671
Volume: 5
Issue: 1
PageNo: 748-760

Keywords: Transmission line blame recognition blame arrangement neural network feed forward networks Back propagation.

Abstract:
Transmission lines, among the other electrical power framework segments, experience the ill effects of startling disappointments because of different arbitrary causes. These mistakes meddle with the unfaltering nature of the errand of the power structure. Right when unpredicted inadequacies happen protective systems are required to keep the causing of these lacks and shield the structure against the sporadic movement coming to fruition as a result of them. The objective of the paper is detecting and classifying the power system transmission line faults. Fault detection and fault classification have been achieved by using artificial neural networks in fitting tools. Feed forward networks have been employed along with back propagation algorithm for each of the three phases in the Fault location process.

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Cite This Article

ISSN: 2349-6002
Volume: 5
Issue: 1
PageNo: 748-760

Fault Detection and Fault Classification In Transmission Line Using Neural Network

Available:https://ijirt.org/Article?manuscript=146671

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UGC Approved
Journal no 47859

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