Abstract

The health of trackside equipment often seriously affects the safe driving of the train, while manually checking their status is an indispensably laborious task. In order to automate the task, this paper addresses the problem of automatically and accurately detecting anomalies of equipment located along the track through GPS and image calibration techniques. Considering the unnoticeable changes in equipment, including screws missing and cable corrosion, detection by classification-based machine learning methods is difficult to implement, thus in this paper we propose and conduct a novel detection mechanism by an efficient way of image subtraction. Especially, our method consists of four steps. The first step is to collect images of the trackside equipment and their corresponding mileage in the same route several times through cameras and GPS devices installed in the inspection train. Then, by introducing an improved RANSAC algorithm, the GPS data is further corrected. Secondly, we define one pass of the collected image data along with GPS information as template, and for the rest passes that need to be detected, the first frame alignment operation is operated through GPS and image information. For the third step, the SURF algorithm is implemented for image matching, and then the subtraction operation is conducted between each matched image pairs. Finally, we use empirical filtering mechanism to remove false positives that we have detected. Experimental results demonstrate the efficiency and effectiveness of our proposed method for anomalies detection of trackside equipment.

Highlights

  • In recent years, as the foundation and an important transportation medium of the rapid development of economy and technology, the construction of Chinese railways has been greatly improved, and the latest high-speed railways have been serving the public life gradually

  • We propose an anomaly detection method for trackside equipment based on GPS and image matching

  • EXPERIMENTAL RESULTS we will show our anomaly detection results on trackside equipment image data from Beijing to Taiyuan section provided by the Ministry of Railways of China

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Summary

Introduction

As the foundation and an important transportation medium of the rapid development of economy and technology, the construction of Chinese railways has been greatly improved, and the latest high-speed railways have been serving the public life gradually. More people choose to travel by train, and the safety of railway trackside equipment has attracted attention from the government and society. Under the complicated operating conditions of Chinese railways and high-intensity transportation load, the task of ensuring transportation safety is very arduous. The rapid development of high-speed railways has put forward new and higher requirements for driving safety. The necessity of safety monitoring and early warning has become more prominent and significant.

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