Smart Maintenance of Railway Infrastructure Using Wireless Sensor Networks
Journal Title: International Journal of Experimental Research and Review - Year 2024, Vol 46, Issue 10
Abstract
The railway infrastructure is a perfect blend of all branches of engineering. Technology has drastically increased, mainly in the Signalling, Civil, Electrical and Mechanical engineering streams. In the field of Signalling, it has leaped from Mechanical to Electronics Interlocking. Civil engineering has gone from manual track maintenance to high-end mechanized tools. In the field of mechanical engineering, it has progressed from wooden coaches to modern designed (LHB)coaches. In electrical engineering, the technology changed from steam loco to diesel and later electrically powered loco design. Nowadays, the loco is powered by nonconventional sources (like solar or wind). Hence, the maintenance of rail infrastructure with traditional methods of physical supervision is sluggish and prone to frequent failures. However, condition monitoring through manual verification by railwaymen helps in the upkeep of railway assets, but it is prone to human errors and subsequent failure of systems, which may result in disasters like derailments or head-on collisions. Signalling components (Point, Tracks, Signals, OFC, DNS, Dataloggers, EI, Block-working instruments etc.), Mechanical rolling stock (Carriage and Wagon), Electrical fitments (OHE, AT, DG, TSS/SP/SSP, locomotive etc.) and Civil Structures (Bridges, Culverts, rail-tracks, rail beds) all require regular maintenance. This paper introduces a “condition monitoring method Enhanced with Wireless Sensor Network” for railway infrastructure. It also clearly distinguishes the typical category of sensors, which are best suitable for condition monitoring of various types of railway assets. The proposed WSN-based technology will improve railway subsystem reliability, effectively reducing failure time and improving the operating ratio.
Authors and Affiliations
Rajev Kumar Sharma, Ajay Sharma, Sandeep Kanaujia
Keywords
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- EP ID EP754332
- DOI 10.52756/ijerr.2024.v46.009
- Views 24
- Downloads 0
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