ARCHIVES
VOL. 11, ISSUE 1 (2025)
High-speed rail track inspection (HSRTI) system
Authors
Sairaj Mangesh Shinde, Rohit Dilip Solanki, Ayushi Dinesh Pandey, Chhaya Shamrao Patil
Abstract
Train derailments pose a significant threat to
the safety and efficiency of railway networks, particularly in India, where
frequent incidents cause substantial loss of life, operational delays, and
economic damage. Existing inspection systems like the Integrated Track
Monitoring System (ITMS) are limited by high costs, dependency on specialized
vehicles, and inability to detect internal faults in real time. To address
these limitations, this research presents the development and implementation of
a High-Speed Rail Track Inspection (HSRTI) System that enables real-time
monitoring of track health while operating at speeds between 15 km/h and 120
km/h. The proposed system, mounted on the bogie of a moving train, uses
ultrasonic acoustic sensors and machine learning algorithms to detect internal
and surface defects such as cracks, misalignments, and weld failures. Data is
transmitted to a cloud server via ThingSpeak, analyzed by a predictive ML model,
and visualized in a mobile application built with Flutter and Firebase. The
system achieved a fault detection accuracy of 90%, significantly reducing
inspection time, operational disruptions, and maintenance costs. The HSRTI
system represents a scalable, cost-effective, and intelligent solution to
enhance railway safety and support preventive maintenance.
Download
Pages:14-22
How to cite this article:
Sairaj Mangesh Shinde, Rohit Dilip Solanki, Ayushi Dinesh Pandey, Chhaya Shamrao Patil "High-speed rail track inspection (HSRTI) system". International Journal of Research in Advanced Engineering and Technology, Vol 11, Issue 1, 2025, Pages 14-22
Download Author Certificate
Please enter the email address corresponding to this article submission to download your certificate.