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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM31792

Railway Track Fault Detection and Automation System

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM31792

Volume:

8 |

4 |

Apr 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM31792

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

MBM

Ms. Bidave M.S

MGV

Ms. Ghule V.S

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Abstract

The Railway Track Fault Detection and Automation System (RTFDAS) represents a significant leap forward in the realm of railway infrastructure maintenance and management. Traditional methods of track inspection often suffer from limitations such as manual labor, periodic assessments, and the potential for human error, leading to safety hazards and operational disruptions. In response, the RTFDAS leverages cutting-edge technology, sophisticated algorithms, and automation capabilities to enable proactive fault detection and streamlined maintenance processes. This paper presents a comprehensive overview of the RTFDAS, highlighting its key components, functionalities, and benefits. The system comprises a network of sensors strategically deployed along railway tracks to capture data on various parameters. Through advanced data processing and analysis, fault detection algorithms identify anomalies indicative of track faults, such as cracks, misalignments, and wear, enabling prompt intervention and maintenance.

KEYWORDS

railway track automation fault detection

Cite This Article

Ms. Bidave M.S, Ms. Ghule V.S, "Railway Track Fault Detection and Automation System," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 4, Apr 2024. https://doi.org/10.55041/IJSREM31792

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Publication Date

12/31/45413

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Double-Blind Peer Review

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

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