An Implementation of Artificial Neural Network based on IMU sensor for Train Detection - Saputro, Anton Cahyo; Sudarsono, Amang; Yuliana, Mike (International Conference on Sciences Development and Technology, 2022)
The purpose of train detection systems is to check the clearness-relation in track section of vehicles before a train passes through a route. A train detection system has an important role in ensuring the safety of train traffic. There are mainly 2 commercially used train detection systems. They consist of an axle counter and a track circuit. The problem with both systems is the high-cost installations and related equipment management. Several solutions have already been presented either on previous research with various methods, such as using Infrared and computer vision/image processing. Most of them want to make the system more effective and less cost maintenance than commercial use. To solve the issues, we propose a new method for train detection based on the usage of an Inertia Measurement Unit (IMU) with embedded artificial neural network module mounted on the sleeper's train in the following section. We utilize the method of train detection by involving an appropriate data acquisition method and a convolution operator as a time series processing algorithm. This idea equips the system to recognize the difference between train and gangway at the speed of 30 km/h. Several experiments conducted on actual rails demonstrate the method's dependability, suggesting its adoption in an automatic track warning system. So, in this proposed train detection system, we propose the train detection system using IMU with Artificial Neural Network Algorithm.