A High Accuracy and High Speed Imaging and Measurement System for Rail Corrugation Inspection

Gazafrudi, Sayed Mohammad Mousavi; Younesian, Davood; Torabi, Mehran

doi:10.1109/tie.2020.3013748

Cited by 21 publications

(7 citation statements)

References 36 publications

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“…Three parallel light planes intersect with the rail to form three laser stripes of the rail profile, respectively. For other rail-corrugation-detection methods, Mmg et al [63] proposed a machine-vision-based corrugation measurement system for rail damage evaluation. The system uses a robust laser peak detection algorithm with sub-pixel accuracy to measure the amplitude of rail corrugation with an accuracy of up to 4 microns.…”

Section: Computer-vision-based Methods For Corrugation Automatic Dete...mentioning

confidence: 99%

Concise Historic Overview of Rail Corrugation Studies: From Formation Mechanisms to Detection Methods

Wang,

Huang,

Wang

et al. 2024

Buildings

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Rail corrugation is a serious problem in a railway transportation system, aggravating the operational risk and shortening the lifetime of train–track system. In order to ensure the safety and reliability of the railway system, the detection of rail corrugation is very important. Thus, this study systematically summarizes the recent research progress of rail corrugation. First, this study introduces the definition of rail corrugation and the classification criteria. Then, the formation mechanism of rail corrugation is analyzed in detail, and its adverse consequences are investigated. Further, this study summarizes several main detection methods, which are corrugation-detection methods based on acceleration measurements, wavelet transform methods for corrugation evaluation, computer-vision-based methods for corrugation automatic detection, digital filtering algorithms for rail corrugation detection, and others. In this study, the formation mechanism and detection methods of rail corrugation are systematically described, and various corrugation-detection methods are also introduced in detail. This study not only provides a scientific basis for railway maintenance, but also lays a solid foundation for future experimental design and data analysis. This study can also guide engineering practice to improve the reliability and safety of railway systems. It also provides useful experience for future railway-engineering design and planning, as well as safer and more reliable operation. In general, this study can provide technical support for the detection of rail corrugation to ensure the safety of the rail–track system.

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Section: Computer-vision-based Methods For Corrugation Automatic Dete...mentioning

confidence: 99%

Concise Historic Overview of Rail Corrugation Studies: From Formation Mechanisms to Detection Methods

Wang,

Huang,

Wang

et al. 2024

Buildings

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“…The proposed system can detect corrugation and discrete types of faults with 93.1% and 80.41%, respectively, and with lower accuracy at 72.78% and 81%. Corrugation fault is detected by [21] with imaging and laser triangulation method with an amplitude accuracy of 4 um. A prototype is presented in [22] for the Electro Magnetic Acoustic Transducer (EMAT) phased array probe.…”

Section: Related Workmentioning

confidence: 99%

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

Memon¹,

Memon²,

Kalwar³

et al. 2023

Computers, Materials &Amp; Continua

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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 year. For this purpose, a proper condition monitoring system is essential to avoid accidents and heavy losses. Generally, 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 environment. Therefore, in this paper, we present the development of a novel embedded system prototype for condition monitoring of railway track. The 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 process. The 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 regions. It 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 color. We have used the multiprocessing technique to overcome the massive processing and memory issues. This 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/h. The functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faults. An unhealthy frame's onsite detection processing time was recorded at approximately 25.6 ms. The proposed system can synchronize the acceleration data on specific railway track deformation. The proposed novel embedded system may be beneficial for detecting faults to overcome the conventional manual railway track condition monitoring, which is still being practiced in various developing or underdeveloped countries.

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“…Light-section vision systems are widely used in many applications for their adaptability, high accuracy, and effective cost [ 1 , 2 , 3 ], such as rail traffic monitoring [ 4 ], medical imaging [ 5 ], robotics [ 6 ], and industrial production [ 7 ]. Such systems typically comprise a camera, laser projector, and mechanical scanning platform.…”

Section: Introductionmentioning

confidence: 99%

A Novel Dynamic Light-Section 3D Reconstruction Method for Wide-Range Sensing

Chen,

Li,

Shimasaki

et al. 2024

Sensors

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Existing galvanometer-based laser-scanning systems are challenging to apply in multi-scale 3D reconstruction because of the difficulty in achieving a balance between a high reconstruction accuracy and a wide reconstruction range. This paper presents a novel method that synchronizes laser scanning by switching the field-of-view (FOV) of a camera using multi-galvanometers. Beyond the advanced hardware setup, we establish a comprehensive geometric model of the system by modeling dynamic camera, dynamic laser, and their combined interaction. Furthermore, since existing calibration methods mainly focus on either dynamic lasers or dynamic cameras and have certain limitations, we propose a novel high-precision and flexible calibration method by constructing an error model and minimizing the objective function. The performance of the proposed method was evaluated by scanning standard components. The results show that the proposed 3D reconstruction system achieves an accuracy of 0.3 mm when the measurement range is extended to 1100 mm × 1300 mm × 650 mm. This demonstrates that for meter-scale reconstruction ranges, a sub-millimeter measurement accuracy is achieved, indicating that the proposed method realizes multi-scale 3D reconstruction and simultaneously allows for high-precision and wide-range 3D reconstruction in industrial applications.

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A High Accuracy and High Speed Imaging and Measurement System for Rail Corrugation Inspection

Cited by 21 publications

References 36 publications

Concise Historic Overview of Rail Corrugation Studies: From Formation Mechanisms to Detection Methods

Concise Historic Overview of Rail Corrugation Studies: From Formation Mechanisms to Detection Methods

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

A Novel Dynamic Light-Section 3D Reconstruction Method for Wide-Range Sensing

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