Research on Fault Detection Algorithm of Pantograph Based on Edge Computing Image Processing

Hongsheng Li

doi:10.1109/access.2020.2988286

Abstract

Traditional pantograph detection technology has installed a large number of various types of sensors on the pantograph, which is not conducive to the flow characteristics of the pantograph. Traditional detection technology can neither monitor the operation status of the pantograph in real time, nor guarantee the safe operation of the entire train. The existing schemes are only manual solutions, and intelligent real-time monitoring is performed without error, and a lot of labor costs are required. Focusing on the shortcomings of traditional pantographs in sliding plate wear and sliding plate crack detection, an improved mean filtering algorithm is proposed to optimize the image of pantograph, and the adaptive Canny edge detection technology is used to accurately calculate the skateboard wear. Firstly, the improved image algorithm is used to pre-treat the pantograph slide wear and crack length, then the improved mean filtering algorithm is combined with adaptive Canny operator for image optimization detection, and finally the edge calculation is used for crack identification. An optimized real-time on-line detection technology is proposed, which can accurately measure the wear and tear of skateboards and cracks. For different experimental environments, the optimization algorithm proposed in this paper is used to detect pantographs in real time. The experimental results show that, compared with the traditional detection algorithm, the detection accuracy of sliding plate wear can reach 0.5 mm, and and that of sliding plate cracks can reach 0.4 mm. The crack recognition accuracy of skates is as high as 93%.

Highlights

With the rapid development of urban traffic track technology, safe and comfortable traffic has become a hot spot of concern [1]
OPTIMIZED FILTERING ALGORITHM In the filtering technique of pantograph image detection, this paper proposes an optimized filtering algorithm, which is mainly based on advanced boundary distinguishing noise detection algorithm (ABDND) and mean filtering algorithm, as well as processing the pantograph image with ABDND algorithm
For the Gaussian noise of the pantograph image, this paper proposes an optimized mean filtering algorithm based on the local depolarization weighted mean filtering algorithm

Summary

Introduction

With the rapid development of urban traffic track technology, safe and comfortable traffic has become a hot spot of concern [1]. The emergence of high-speed electrified trains has met people’s needs to a certain extent. In order to ensure the safety and reliability of electrified trains, each train has zero. Realtime monitoring of components becomes very important [2]. The pantograph component is the only way for the train to obtain electrical energy [3]. The state of the pantograph during operation determines the safety and reliability of the train operation. During the operation of the pantograph, it is necessary to consider the influence of its own structure, running path, train speed and weather conditions. The crack and loss of the pantograph slide is a common phe-

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Conclusion