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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM23011

Automatic Crack Detection in Railway Track

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM23011

Volume:

7 |

6 |

Jun 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SB

Shivani Bandgar

SB

Shraddha Byale

VS

Vaishnavi Shelke

VG

Vikas Ghuge

PPL

Prof. P. Lone

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Abstract

In India, rail transport occupies a prominent position in quenching the ever barge owing needs of rapidly growing economy. However, in terms of the reliability and safety parameters, global standards have not yet been truly reached. Though rail transport in India is growing at a rapid pace, the associated safety infrastructure facilities have not kept up with the mentioned prolife ration. The principal problem is the lack of efficient and cost-effective technology to detect the problems in the rail tracks and the lack of proper maintenance. Monitoring the inspection methods like are visual inspection, ultrasonic inspection, The main cause of the accidents happened in railways are railway track crossing and unrevealed crack in railway tracks. Therefore, there is a need to have new technology which will be robust, efficient and stable for both crack detection in railway tracks as well as object detection. This project discusses a Railway track crack detection using sensors and is a dynamic approach which combines the use of GPS tracking system to send alert messages and the geographical coordinate of location. Arduino Microcontrollers used to control and coordinate the activities of this device. Cracks in rails have been identified to be the main cause of derailments in the past, yet there have been no cheap automated solutions available for testing purposes.

KEYWORDS

Ultra sonic Sensor Motor Driver GPS system.

Cite This Article

Shivani Bandgar, Shraddha Byale, Vaishnavi Shelke, Vikas Ghuge, Prof. P. Lone, "Automatic Crack Detection in Railway Track," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 6, Jun 2023.

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Publication Date

7/5/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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