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Embedded System Development for Detection of railway Track Surface Deformation Using Contour Feature Algorithm

Computers, Materials & Continua 2023年第5期75卷 2461-2477页

作者： Tarique Rafique Memon Tayab Din Memon Imtiaz Hussain Kalwar Bhawani Shankar Chowdhry NCRA-HHCMS Lab Mehran University of Engineering&Technology Jamshoro76062Pakistan Department of Electronic Engineering Quaid-e-Awam University of EngineeringScience&Technology Nawabshah67480Pakistan Design and Creative Technology Torrens University Australia196 Flinders StreetMelbourneVIC 3000Australia Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76062Pakistan Department of Electronics and Power Engineering Pakistan Navy Engineering CollegeNUST Karachi75350Pakistan

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each *** this purpose,a proper condition monitoring system is essential to avoid accidents and heavy ***,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy ***,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway *** proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition *** contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy *** works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black *** have used the multiprocessing technique to overcome the massive processing and memory *** embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a railway Inspection Trolley(RIT),which runs at an average speed of 15 km/*** functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faul

关键词： railway track surface faults condition monitoring system fault detection contour detection deep learning image processing rail wheel impact

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