Volume 19, Issue 2 (June 2023)                   IJEEE 2023, 19(2): 2594-2594 | Back to browse issues page

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Chennamsetty D P, Bali S K. A Novel Fault Detection and Classification Approach in Transmission Lines Based on Statistical Patterns. IJEEE 2023; 19 (2) :2594-2594
URL: http://ijeee.iust.ac.ir/article-1-2594-en.html
A Novel Fault Detection and Classification Approach in Transmission Lines Based on Statistical Patterns
Das P. Chennamsetty , Sravana K. Bali
Abstract:   (1364 Views)
Symmetrical nature of mean of electrical signals during normal operating conditions is used in the fault detection task for dependable, robust, and simple fault detector implementation is presented in this work. Every fourth cycle of the instantaneous current signal, the mean is computed and carried into the next cycle to discover nonlinearities in the signal. A fault detection task is completed using a comparison of two sub cycle means, and the same concept is extended to faulty phase classification. Under various fault and system operating situations, the suggested technique is assessed for regular faults, remote end faults, high resistive faults, and high impedance arcing faults. This paper's extensive case studies illustrate the suggested scheme's simplicity, computational flexibility, speed, and reliability. The suggested approach yields 100% consistent results in 4-8 msec detection time. 
Keywords: Shifting Window, Fault Detection, Remote End Fault.
Full-Text [PDF 625 kb]   (680 Downloads)    
Type of Study: Research Paper | Subject: Fault Location
Received: 2022/07/18 | Revised: 2023/06/06 | Accepted: 2023/06/11
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.