Railway Track Crack Detection

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Railway Track crack Detection

Railway Track Crack Detection

Abstract

In this Railway Track Crack Detection paper, we presented a railway track crack detection patrolling vehicle. Indian railway has one of  the world’s largest railway networks comprising 92,081 km (57,216 mi) of track over a route of 66,687 km (41,437 mi) and 7,216 stations.So,manualinspection and detecting a crack on these railways tracks is very tedious process and consumes lot of time and human resource. This Railway Track crack Detection paper proposes a cost effective solution to the problem of railway track crack detection utilizing IR sensor array assembly which tracks the exact location of faulty track, then inform to nearby railway station through short messaging application, so that many lives will be saved.

System Configuration

H/W System Configuration
Speed                   : 1.1 GHz
RAM                      : 256 MB(min)
Hard Disk              : 20 GB
Floppy Drive          : 1.44 MB
Key Board             : Standard Windows Keyboard
Mouse                  : Two or Three Button Mouse
Monitor                : SVGA
S/W System Configuration

Platform                     :  IOT

Operating system       : Windows Xp,7,
Server                       : WAMP/Apache
Working on                : Browser Like Firefox, IE

Conclusion

In this crack Detection Management by using this Autonomous patrolling vehicle for purpose of railway track inspection and crack detection, it will have a great impact in the maintenance of the tracks which will help in preventing train accidents to a very large extent. The regions where manual inspection is not possible, like in deep coal mines, mountain regions and dense thick forest regions can be easily done using this vehicle. Cracks in rails have been identified to be the main cause of derailments in the past. Recently on 28th of December,2016 Train no-12987 named Ajmer- Sealdah Express had derailed near Rura , around 70km from Kanpur. Fifteen Coaches were derailed in this accident and reported death of 2 people with 48 people was injured. Hence, owing to the crucial solution of this problem, we have worked on implementing an efficient and cost effective solution suitable for this application.