Indian railways are one of the largest railway networks of the world. Despite the huge size, the rampant negligence and lack of maintenance have created a number of problems. The main problem being that, frequent cracks are found in the rail lines which cause derailments leading to huge loss of life and property. In fact, the year 2010 alone, reports around 21 train crashes leading to around 450 deaths. Having researched about the conventional methods of railway crack detection includes ultrasonic and eddy current based approaches, we find that their expensive nature does not warrant their use in the current scenario. Hence, we aim to create a new LED-LDR based simple technique to detect cracks in rails that will be cheap enough, so that it can be put to mass usage. Our scheme consists of a robot which will traverse the railway line looking for cracks during night time when local railways don't operate. This mobile robot will be powered by a DC to motor traverse the railway line. It will be equipped with a LED(Light Dependent Resistor) and LDR arrangement. When a crack is present in the railway line the light falls on the LDR and its resistance decreases. This is detected by a microcontroller which then stops the motor. Navigation in robotics usually requires solving two major problems, one is position of the robot and the other is motion control mechanism. In case, no prior information in the motion environment can be obtained, the challenge becomes worst. This problem happens due to the lack of mobility information in its surroundings. In this particular method controlling is finished dependent upon the feedback offered by the sensor. In this present work, different modules like controlling module and Wireless unit module Sensing are introduced. In the sensing module, whenever the micro controller is powered along the high speed DC motors. Sensor is connected to the robot. Encoder connected to the robot, which transmit the comprehensive data continuously. Here the robot is comprised of transmitter and receiver. Here the repetitiveness used is 433 kHz.
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