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  Published Paper Details:

  Paper Title

IOT BASED TRANSMISSION LINE MULTIPLE FAULT DETECTION AND INDICATION TO EB

  Authors

  SANKAR S,  D NAVEENKUMAR,  K VIGNESH,  S PALRAJ

  Keywords

Global System for Mobile Communication.

  Abstract


The Electric Power System is divided into many different sections. One of which is the transmission system, where power is transmitted from generating stations and substations via transmission lines into consumers. A smart GSM based fault detection and location system was used to adequately and accurately indicate and locate the fault had occurred. This will ensure a shorter response time for technical crew to rectify these faults and thus help save transformers from damage and disasters. The system automatically detects faults, analyses and classifies these faults and then, calculates the fault distance from the control room using an impedance-based algorithm method. Finally, the fault information is transmitted to the control room. In conclusion, the time required to locate a fault is drastically reduced, as the system automatically and accurately provides accurate fault location information. By using this project, we can detect the faults of three phase transmission lines one can monitor the Temperature, Voltage, Current by means of GSM modem by sending message.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2105228

  Paper ID - 206920

  Page Number(s) - c193-c204

  Pubished in - Volume 9 | Issue 5 | May 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  SANKAR S,  D NAVEENKUMAR,  K VIGNESH,  S PALRAJ,   "IOT BASED TRANSMISSION LINE MULTIPLE FAULT DETECTION AND INDICATION TO EB", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 5, pp.c193-c204, May 2021, Available at :http://www.ijcrt.org/papers/IJCRT2105228.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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