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Готові списки джерел за темами / Rail area detection / Статті в журналах

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Статті в журналах з теми "Rail area detection"

Автор: Grafiati

Опубліковано: 7 червня 2025

Оновлено: 2 серпня 2025

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1

Fang, Zhongbin, Xiaojie Huang, Kangquan Ye, et al. "An algorithm for extracting groove rail area based on improved Hough transform." MATEC Web of Conferences 336 (2021): 02025. http://dx.doi.org/10.1051/matecconf/202133602025.

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In order to improve the accuracy and real-time performance of the automatic cleaning of groove rails in modern trams, this paper proposes a groove rail region extraction algorithm based on improved Hough transform. First, in order to speed up the detection and remove noise, the algorithm performs a series of pre-processing on the images collected by the camera, and then use the Canny edge detection method to extract the edge feature information of the groove rail. Finally, the algorithm is improved on the basis of the traditional Hough transform method according to the actual environment. The

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2

Choi, Jung-Youl, and Jae-Min Han. "Deep Learning (Fast R-CNN)-Based Evaluation of Rail Surface Defects." Applied Sciences 14, no. 5 (2024): 1874. http://dx.doi.org/10.3390/app14051874.

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In current railway rails, trains are propelled by the rolling contact between iron wheels and iron rails, and the high frequency of train repetition on rails results in a significant load exertion on a very small area where the wheel and rail come into contact. Furthermore, a contact stress beyond the allowable stress of the rail may lead to cracks due to plastic deformation. The railway rail, which is the primary contact surface between the wheel and the rail, is prone to rolling contact fatigue cracks. Therefore, a thorough inspection and diagnosis of the condition of the cracks is necessary

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3

di Scalea, Francesco Lanza, Ivan Bartoli, Piervincenzo Rizzo, and Mahmood Fateh. "High-Speed Defect Detection in Rails by Noncontact Guided Ultrasonic Testing." Transportation Research Record: Journal of the Transportation Research Board 1916, no. 1 (2005): 66–77. http://dx.doi.org/10.1177/0361198105191600110.

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Recent train accidents have reaffirmed the need to develop rail defect detection systems that are more effective than those used today. This paper proposes new inspection systems for detecting transverse-type cracks in the rail head, notoriously the most dangerous flaws in rails. In principle these systems can be applied to both continuous welded rail and jointed tracks because bidirectional inspection can be implemented. However, the systems may fail to detect defects located close to a joint. The proposed technology uses ultrasonic guided waves that are detected by remote sensors positioned

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4

Wang, Zhangyu, Xinkai Wu, Guizhen Yu, and Mingxing Li. "Efficient Rail Area Detection Using Convolutional Neural Network." IEEE Access 6 (2018): 77656–64. http://dx.doi.org/10.1109/access.2018.2883704.

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5

Tverdomed, Volodymyr, Anatoliy Gorban, and Lesia Kushmar. "Image segmentation method of rail head defects and area measurement of selected segments." MATEC Web of Conferences 390 (2024): 04008. http://dx.doi.org/10.1051/matecconf/202439004008.

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The operation safety of railway transport, which is the most important economic and social factor, is largely determined by the technical condition of the rail track and measures to maintain the quality of its track management system. One of the system elements for ensuring the accident-free operation of the track is the technical diagnosis of rails using a method complex of non-destructive control of rails, such as acoustic (ultrasonic), magnetic, combined, etc., and monitoring of the track using methods of measuring the geometry of the rail track and its disturbances. When the wheel interact

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6

Li, Liming, Rui Sun, Shuguang Zhao, Xiaodong Chai, Shubin Zheng, and Ruichao Shen. "Semantic-Segmentation-Based Rail Fastener State Recognition Algorithm." Mathematical Problems in Engineering 2021 (March 2, 2021): 1–15. http://dx.doi.org/10.1155/2021/8956164.

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Rail fastener status recognition and detection are key steps in the inspection of the rail area status and function of real engineering projects. With the development of and widespread interest in image processing techniques and deep learning theory, detection methods that combine the two have yielded promising results in practical detection applications. In this paper, a semantic-segmentation-based algorithm for the state recognition of rail fasteners is proposed. On the one hand, we propose a functional area location and annotation method based on a salient detection model and construct a no

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7

Shen, Tuo, Jinhuang Zhou, Tengfei Yuan, Yuanxiang Xie, and Xuanxiong Zhang. "LiDAR-Based Urban Three-Dimensional Rail Area Extraction for Improved Train Collision Warnings." Sensors 24, no. 15 (2024): 4963. http://dx.doi.org/10.3390/s24154963.

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The intrusion of objects into track areas is a significant issue affecting the safety of urban rail transit systems. In recent years, obstacle detection technology based on LiDAR has been developed to identify potential issues, in which accurately extracting the track area is critical for segmentation and collision avoidance. However, because of the sparsity limitations inherent in LiDAR data, existing methods can only segment track regions over short distances, which are often insufficient given the speed and braking distance of urban rail trains. As such, a new approach is developed in this

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8

Cao, Jinghao, Yang Li, and Sidan Du. "Robust Artificial Intelligence-Aided Multimodal Rail-Obstacle Detection Method by Rail Track Topology Reconstruction." Applied Sciences 14, no. 7 (2024): 2795. http://dx.doi.org/10.3390/app14072795.

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Detecting obstacles in the rail track area is crucial for ensuring the safe operation of trains. However, this task presents numerous challenges, including the diverse nature of intrusions, and the complexity of the driving environment. This paper presents a multimodal fusion rail-obstacle detection approach by key points processing and rail track topology reconstruction. The core idea is to leverage the rich semantic information provided by images to design algorithms for reconstructing the topological structure of railway tracks. Additionally, it combines the effective geometric information

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9

Zheng, Danyang, Liming Li, Shubin Zheng, et al. "A Defect Detection Method for Rail Surface and Fasteners Based on Deep Convolutional Neural Network." Computational Intelligence and Neuroscience 2021 (July 29, 2021): 1–15. http://dx.doi.org/10.1155/2021/2565500.

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Анотація:

As a result of long-term pressure from train operations and direct exposure to the natural environment, rails, fasteners, and other components of railway track lines inevitably produce defects, which have a direct impact on the safety of train operations. In this study, a multiobject detection method based on deep convolutional neural network that can achieve nondestructive detection of rail surface and fastener defects is proposed. First, rails and fasteners on the railway track image are localized by the improved YOLOv5 framework. Then, the defect detection model based on Mask R-CNN is utili

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10

Signore, James M., Mohamed G. Abdel-Maksoud, and Barry J. Dempsey. "Fiber-Optic Sensing Technology for Rail-Buckling Detection." Transportation Research Record: Journal of the Transportation Research Board 1584, no. 1 (1997): 41–45. http://dx.doi.org/10.3141/1584-06.

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Buckling and cracking of steel rails is a contributing factor in accidents on railroads today. Detection and notification of buckled track sections before a train reaches these locations will significantly increase rail safety. A fiber-optic-based sensing system, with the fiber affixed to a beam, was developed and evaluated to detect buckled regions. The purpose of this research is to evaluate the sensitivity of the fiber-optic sensing system to buckling of a long structural member. Numerous facets of fiber-optic sensing have been explored. Fiber-to-steel bonding techniques were examined and t

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11

Ji, Guoyi, Wen Chen, Jinbai Zou, and Shiyan Wei. "Research on foreign object detection method in track area based on Mask-RCNN." Journal of Physics: Conference Series 2365, no. 1 (2022): 012005. http://dx.doi.org/10.1088/1742-6596/2365/1/012005.

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Abstract As the train speeds up, the damage caused by the collisions between trains and foreign objects are becoming more and more severe. Therefore, it is of great significance to monitor the intrusion of foreign objects in the track environment. In this paper, transfer learning is introduced into Mask-RCNN deep learning model. And the data set of rail image is used to train the model, which improves the effect of rail segmentation. The trained model is used to segment the rail in the picture, and the rail vulnerable area is divided based on the segmentation results. The sliding window ORB fe

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12

Hsu, Wei-Lun, and Chia-Ming Chang. "Rail Corrugation Index Development by Sound-Field Excitation on the Carriage Floor of In-Service Train." Sensors 23, no. 17 (2023): 7539. http://dx.doi.org/10.3390/s23177539.

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The steel rail and wheel in the railway system offer a high precision and smooth-running surface. Nevertheless, the point of contact between the rail and wheel presents a critical area that can give rise to rail corrugation. This phenomenon can potentially elevate sound and vibration levels in the vicinity considerably, necessitating advanced monitoring and assessment measures. Recently, many efforts have been directed towards utilizing in-service trains for evaluating rail corrugation, and the evaluation has primarily relied on axle-box acceleration (ABA). However, the ABA measurements requir

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13

Ragala, Z., A. Retbi, and S. Bennani. "RAILWAY TRACK FAULTS DETECTION BASED ON IMAGE PROCESSING USING MOBILENET." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W3-2022 (December 2, 2022): 135–41. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w3-2022-135-2022.

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Abstract. The use of rail transport is increasing. Damaged rails interrupt traffic to carry out repairs. In fact, when a conductor or railway operator reports a damaged rail that interrupted the traffic in the affected area. A team of specialized agents dispatch to the site and carries out the repairs. Hence, the importance of automation of railway track faults detection to ensure track safety and reduce maintenance costs. In this work, we propose a method using image processing technologies and deep learning networks. We have studied the correlation effects of MobileNetV2 and optimization alg

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14

Mauz, Florian, Remo Wigger, Alexandru-Elisiu Gota, and Michal Kuffa. "Automatic Detection of the Running Surface of Railway Tracks Based on Laser Profilometer Data and Supervised Machine Learning." Sensors 24, no. 8 (2024): 2638. http://dx.doi.org/10.3390/s24082638.

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The measurement of the longitudinal rail profile is relevant to the condition monitoring of the rail infrastructure. The running surface is recognizable as a shiny metallic area on top of the rail head. The detection of the running surface is crucial for vehicle-based rail profile measurements, as well as for defect detection. This paper presents a methodology for the automatic detection of the running surface based on a laser profilometer. The detection of the running surface is performed based on the light reflected from the rail surface. Three rail surfaces with different surface conditions

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15

Seavers, Connor, Guiherme Caselato Gandia, Jackson Winn, James Mathias, Tsuchin Chu, and Anish Poudel. "Line Scanning Thermography for Rail Base Defect Detection." Materials Evaluation 82, no. 11 (2024): 30–40. http://dx.doi.org/10.32548/2024.me-04445.

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Rail base defects present significant maintenance challenges within the railway industry, as they are difficult to detect before they lead to failure. While various in-motion nondestructive evaluation (NDE) methods exist for inspecting rail, none of the existing NDE methods can inspect the rail base area reliably and efficiently. This paper presents finite element analysis (FEA) and experimental results applying a line scanning thermography (LST) approach developed for rail base area inspection. This work demonstrates the LST approach for dynamic inspection of thick steel components containing

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16

Wang, Chensong, Wei Cui, Xingguang Li, and Xinrou Liu. "Foreign Body Detection in the Electrified Area of Urban Rail Trains Using Improved Yolov3 Algorithm." Tobacco Regulatory Science 7, no. 5 (2021): 1059–66. http://dx.doi.org/10.18001/trs.7.5.23.

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Foreign body invade the electric receiving area of urban rail train, interfere with the operation of electric equipment on the roof, and affect the normal operation of urban rail traffic. Aiming at the problems of the traditional non-contact foreign body detection in the electric area of urban rail train, such as slow detection speed and poor detection accuracy of small target foreign body, An improved YOLOV3 (You Only Look Once) network model based on PAN feature pyramid structure and adaptive spatial feature fusion is proposed. By improving the main body of the YOLOv3 network model, it can a

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17

Najya, Hilma, and Ari Purno Wahyu Wibowo. "TECHNOLOGY THE FIRE DETECTION SYSTEM ON THE RAILWAY LINE IS BASED ON IMAGE PROCESSING WITH THE COMPUTER VISION METHOD." Jurnal Darma Agung 31, no. 1 (2023): 65. http://dx.doi.org/10.46930/ojsuda.v31i1.2939.

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The rail transportation system plays a role important as a medium of transportation for the movement of goods and people in large quantities and is one of the modes of cheap transportation, this transportation model evolved from a steam train until it evolves to become more sophisticated using electric and magnetic technology, trains system works well with support from several the first factor is human resources, supporting technology and facilities. The problem with the rail system is that damage to the rails can cause result in the transportation route being blocked and can cause a very fata

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18

Guo, Long, Jun Zhang, Zhe Chen, et al. "Automatic Detection for Defects of Railroad Track Surface." Applied Mechanics and Materials 278-280 (January 2013): 856–60. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.856.

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Rail track surface defects detection is an important part of the monitoring of railroad safety. In this paper, rail track images obtained by detection system of rail track surface image are processed. Firstly, the Hough transform is applied to process the images of the track surface to locate and extract the image of the track surface, which overcomes the influence of incline and unfixed width of track surface images caused by vehicle vibration. Secondly, improved Sobel operator and area filter are used together to extract track surface defects from the original images. Finally, the defects im

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19

Bersenev, S. P., and E. M. Slobtsova. "Status of nondestructive control of transport function metal products at JSC EVRAZ NTMK." Ferrous Metallurgy. Bulletin of Scientific , Technical and Economic Information 76, no. 6 (2020): 586–90. http://dx.doi.org/10.32339/0135-5910-2020-6-586-590.

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Achievements in the area of automated ultrasonic control of quality of rails, solid-rolled wheels and tyres, wheels magnetic powder crack detection, carried out at JSC EVRAZ NTMK. The 100% nondestructive control is accomplished by automated control in series at two ultrasonic facilities RWI-01 and four facilities УМКК-1 of magnetic powder control, installed into the exit control line in the wheel-tyre shop. Diagram of location, converters displacement and control operations in the process of control at the facility RWI-01 presented, as well as the structural diagram of the facility УМКК-1. The

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20

Zhang, Qiang, Fei Yan, Weina Song, Rui Wang, and Gen Li. "Automatic Obstacle Detection Method for the Train Based on Deep Learning." Sustainability 15, no. 2 (2023): 1184. http://dx.doi.org/10.3390/su15021184.

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Анотація:

Automatic obstacle detection is of great significance for improving the safety of train operation. However, the existing autonomous operation of trains mainly depends on the signaling control system and lacks the extra equipment to perceive the environment. To further enhance the efficiency and safety of the widely deployed fully automatic operation (FAO) systems of the train, this study proposes an intelligent obstacle detection system based on deep learning. It collects perceptual information from industrial cameras and light detection and ranging (LiDAR), and mainly implements the functiona

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21

Savitha, AC, Kumar KM Madhu, V. Prathap, et al. "Automatic Detection of Obstacle in Railway Track." Journal of Scholastic Engineering Science and Management (JSESM), A Peer Reviewed Universities Refereed Multidisciplinary Research Journal 4, no. 5 (2025): 1–5. https://doi.org/10.5281/zenodo.15385583.

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Анотація:

The main aim of the work is to  enhance the safety and efficiency of train operations. The system focuses on detecting obstacles on the railway track and automatically applying the train's brakes to prevent accidents. With the growing concerns over train collisions and safety incidents, the introduction of an automated system that can detect obstructions and take immediate corrective actions is crucial. The proposed work  utilizes sensors like ultrasonic sensors, cameras, and advanced algorithms for obstacle detection, coupled with automated braking mechanisms.

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22

Kou, Lei, Mykola Sysyn, and Jianxing Liu. "INFLUENCE OF CROSSING WEAR ON ROLLING CONTACT FATIGUE DAMAGE OF FROG RAIL." Facta Universitatis, Series: Mechanical Engineering 22, no. 1 (2024): 025. http://dx.doi.org/10.22190/fume220106024k.

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The damage of the frog rail significantly affects the wear of the crossing rail and restricts the passing speed of the train. A geometric 3D modeling of the vehicle passing through the crossing center is particularly concerned with the cumulative wheel-rail contact of the traffic volume. The frog rail wear is simulated to obtain the dynamic change of the impact force of the wheel on the frog rail as the rail wears. By summarizing the existing experimental results of other scholars, it is clear that the important factors, that cause the damage of the frog rail, are vehicle load, friction coeffi

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23

Lü, Kun Lin, Jun Zhang, Guang Yu Dai, et al. "Track Surface Image Collecting System Base on Area-Array Camera." Applied Mechanics and Materials 321-324 (June 2013): 1145–49. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1145.

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The first step of track surface detection based on contactless optical detection is to obtain the surface image. This paper introduces a vehicle-mounted image collecting system base on area-array camera. This system avoids image morphing and edge deformation of system base on linear-array camera.Camera could works in both frequently flash and persistent bright without influence image collecting and will not miss information of the rail track surface when vehicle keeps the speed of 342Km/h. The exposure time should be chosen according to railcar speed and maximum speed.

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24

Phrommahakul, Nichapa, Manwika Kongpuang, Suhaidee Sani, Anas Katib, and Fittriya Sulong. "Detection of Rail Defects Using Phased Array Ultrasonic Technique." E3S Web of Conferences 602 (2025): 01009. https://doi.org/10.1051/e3sconf/202560201009.

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The Phased Array Ultrasonic Technique (PAUT) is an advanced non-destructive inspection method that utilizes an array of ultrasonic testing (UT) probes consisting of several small elements. The laboratory used an artificial crack on the rail steel grade 900A/ R260 test block to study the principles of PAUT and how to measure the defect’s reliability and accuracy. On-site studies were done on railroad tracks with different structures. Rail steel grade 900A/ R260, Hadfield steel, and thermite welded joints. No defects were found during the inspection at the crossing nose of the two positions. Onl

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25

Fang, Bo, Cheng Qiu, Ming Feng, Wei Liang, and Ximing Zhang. "Collision Avoidance Strategy for Multivehicle Conflict on Common Rail." Mathematical Problems in Engineering 2022 (May 3, 2022): 1–14. http://dx.doi.org/10.1155/2022/9388092.

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With the rapid expansion and application of bright logistics technology in the field of metallurgical production, in recent years, a type of intermediate granary storage and transportation system, signified by multiple child-parent rail car system, has gradually looked in steel plants, which effectively solves the drawbacks of crane craning in the intermediate warehouse area and improves the transportation competence of shop-level logistics. However, there are not many studies on conflict avoidance strategies for such multivehicle cooperative common rail transportation system in order to impro

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26

Zhang, Ziwen, Mangui Liang, and Zhiyu Liu. "A Novel Decomposition Model for Visual Rail Surface Inspection." Electronics 10, no. 11 (2021): 1271. http://dx.doi.org/10.3390/electronics10111271.

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Анотація:

Rail surface inspection plays a pivotal role in large-scale railway construction and development. However, accurately identifying possible defects involving a large variety of visual appearances and their dynamic illuminations remains challenging. In this paper, we fully explore and use the essential attributes of our defect structure data and the inherent temporal and spatial characteristics of the track to establish a general theoretical framework for practical applications. As such, our framework can overcome the bottleneck associated with machine vision inspection technology in complex rai

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27

Kuzmin, Egor V., Oleg E. Gorbunov, Petr O. Plotnikov, Vadim A. Tyukin, and Vladimir A. Bashkin. "Application of Neural Networks for Recognizing Rail Structural Elements in Magnetic and Eddy Current Defectograms." Modeling and Analysis of Information Systems 25, no. 6 (2018): 667–79. http://dx.doi.org/10.18255/1818-1015-2018-6-667-679.

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To ensure traffic safety of railway transport, non-destructive test of rails is regularly carried out by using various approaches and methods, including magnetic and eddy current flaw detection methods. An automatic analysis of large data sets (defectgrams) that come from the corresponding equipment is an actual problem. The analysis means a process of determining the presence of defective sections along with identifying structural elements of railway tracks on defectograms. This article is devoted to the problem of recognition of rail structural element images in magnetic and eddy current def

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28

Sakthivel, V. "Advanced IoT Solution for Early Detection of Railway Hazards." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 4873–76. https://doi.org/10.22214/ijraset.2025.69363.

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Анотація:

The expanded development in the railroad area has brought about an expansion in the train activity thickness over the world. This has brought about the expansion in the quantity of mischances including trains. In this paper, the proposed framework which deals with the problems related to the railways this system monitors the track, platforms and trains regularly This framework makes utilization of Ultrasonic sensors IR sensors, fire sensor, GSM, GPS and other inserted frameworks Rail mischances have been expanded because of the surge streaming over the Railway tracks. We are proposing a system

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29

Chandran, Praneeth, Johnny Asber, Florian Thiery, Johan Odelius, and Matti Rantatalo. "An Investigation of Railway Fastener Detection Using Image Processing and Augmented Deep Learning." Sustainability 13, no. 21 (2021): 12051. http://dx.doi.org/10.3390/su132112051.

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Анотація:

The rail fastening system forms an indispensable part of the rail tracks and needs to be periodically inspected to ensure safe, reliable and sustainable rail operations. Automated visual inspection has gained significant importance for fastener inspection in recent years. Position accuracy, robustness, and practical limitations due to the complex environment are some of the major concerns associated with this method. This study investigates the combined use of image processing and deep learning algorithms for detecting missing clamps within a rail fastening system. The images used for this stu

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30

Simonović, Miloš, Milan Banić, Dušan Stamenković, et al. "Toward the Enhancement of Rail Sustainability: Demonstration of a Holistic Approach to Obstacle Detection in Operational Railway Environments." Sustainability 16, no. 7 (2024): 2613. http://dx.doi.org/10.3390/su16072613.

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Анотація:

Rail transport plays a crucial role in promoting sustainability and reducing the environmental impact of transport. Ongoing efforts to improve the sustainability of rail transport through technological advancements and operational improvements are further enhancing its reputation as a sustainable mode of transport. Autonomous obstacle detection in railways is a critical aspect of railway safety and operation. While the widespread deployment of autonomous obstacle detection systems is still under consideration, the ongoing advancements in technology and infrastructure are paving the way for the

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31

Cao, Xiangang, Mengzhen Zuo, Guoyin Chen, Xudong Wu, Peng Wang, and Yizhe Liu. "Visual Localization Method for Fastener-Nut Disassembly and Assembly Robot Based on Improved Canny and HOG-SED." Applied Sciences 15, no. 3 (2025): 1645. https://doi.org/10.3390/app15031645.

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Visual positioning accuracy is crucial for ensuring the successful execution of nut disassembly and assembly tasks by a fastener-nut disassembly and assembly robot. However, disturbances such as on-site lighting changes, abnormal surface conditions of nuts, and complex backgrounds formed by ballast in complex railway environments can lead to poor visual positioning accuracy of the fastener nuts, thereby affecting the success rate of the robot’s continuous disassembly and assembly operations. Additionally, the existing method of detecting fasteners first and then positioning nuts has poor appli

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32

Hanum, Arrosida, Susanto Agus, Ciptaningrum Adiratna, Rudianti Tyan, Nazar Surya Kencana Masayu, and Mahmud Rizal. "Rail Line Surfaces Defect Monitoring using YOLO Architecture: Case Study on Madiun-Magetan Track, East Java." Rail Line Surfaces Defect Monitoring using YOLO Architecture: Case Study on Madiun-Magetan Track, East Java 8, no. 12 (2023): 15. https://doi.org/10.5281/zenodo.10432573.

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In Indonesia, trains are one of the most popular means of transportation for Indonesians to help with the mobility of passengers and goods. However, train derailment is also something that happens quite frequently. The train derailment was caused by several factors, the rail line damage is one of the biggest possible causes. For this reason, it is necessary to carry out inspections on it to detect and find defects on the rails for subsequent repairs. Manual inspections, as is still often done by officers in Indonesia, have shortcomings such as low efficiency, human error, and danger. Automatic

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33

Wang, Yi, Yuhui Wang, Ping Wang, et al. "Rail Magnetic Flux Leakage Detection and Data Analysis Based on Double-Track Flaw Detection Vehicle." Processes 11, no. 4 (2023): 1024. http://dx.doi.org/10.3390/pr11041024.

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The rapid development of the railway industry has brought convenience to people’s lives. However, with the high speed, high frequency and heavy load characteristics of rail use, the safety of rail is seriously threatened. In this paper, a magnetic flux leakage testing (MFL) detection technology of rail based on a double-track flaw detection vehicle is introduced in detail, which can effectively detect the damage of rail top surface, which is the blind area of ultrasonic detection. The magnetic dipole model is used to analyze that the leakage magnetic field in the direction of Bx and Bz above t

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34

Bai, Tangbo, Jialin Gao, Jianwei Yang, and Dechen Yao. "A Study on Railway Surface Defects Detection Based on Machine Vision." Entropy 23, no. 11 (2021): 1437. http://dx.doi.org/10.3390/e23111437.

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The detection of rail surface defects is an important tool to ensure the safe operation of rail transit. Due to the complex diversity of track surface defect features and the small size of the defect area, it is difficult to obtain satisfying detection results by traditional machine vision methods. The existing deep learning-based methods have the problems of large model sizes, excessive parameters, low accuracy and slow speed. Therefore, this paper proposes a new method based on an improved YOLOv4 (You Only Look Once, YOLO) for railway surface defect detection. In this method, MobileNetv3 is

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35

Wang, Nan, Tao Hou, and Tianming Zhang. "Research on railway track edge detection based on BM3D and Zernike moments." Archives of Transport 68, no. 4 (2023): 7–20. http://dx.doi.org/10.61089/aot2023.fz9g6c16.

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With the rapid development of intelligent rail transportation, the realization of intelligent detection of railroad foreign body intrusion has become an important topic of current research. Accurate detection of rail edge location, and then delineate the danger area is the premise and basis for railroad track foreign object intrusion detection. The application of a single edge detection algorithm in the process of rail identification is likely to cause the problem of missing important edges and weak gradient change edges of railroad tracks. It will affect the subsequent detection of track fore

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36

Ye, Xuan-Yu, Yan-Yun Luo, Zai-Wei Li, and Xiao-Zhou Liu. "A Quantitative Detection Method for Surface Cracks on Slab Track Based on Infrared Thermography." Applied Sciences 13, no. 11 (2023): 6681. http://dx.doi.org/10.3390/app13116681.

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Surface cracks are typical defects in high-speed rail (HSR) slab tracks, which can cause structural deterioration and reduce the service reliability of the track system. However, the question of how to effectively detect and quantify the surface cracks remains unsolved at present. In this paper, a novel crack-detection method based on infrared thermography is adopted to quantify surface cracks on rail-track slabs. In this method, the thermogram of a track slab acquired by an infrared camera is first processed with the non-subsampled contourlet transform (NSCT)-based image-enhancement algorithm

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37

Esteves, Gonçalo, Filipe Fidalgo, Nuno Cruz, and José Simão. "Long-Range Wide Area Network Intrusion Detection at the Edge." IoT 5, no. 4 (2024): 871–900. https://doi.org/10.3390/iot5040040.

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Internet of Things (IoT) devices are ubiquitous in various applications, such as smart homes, asset and people tracking, and city management systems. However, their deployment in adverse conditions, including unstable internet connectivity and power sources, present new cybersecurity challenges through new attack vectors. The LoRaWAN protocol, with its open and distributed network architecture, has gained prominence as a leading LPWAN solution, presenting novel security challenges. This paper proposes the implementation of machine learning algorithms, specifically the K-Nearest Neighbours (KNN

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38

Pan, Yucheng, Jiasi Chen, Peiwen Wu, Hongsheng Zhong, Zihao Deng, and Daozong Sun. "Enhanced Rail Surface Defect Segmentation Using Polarization Imaging and Dual-Stream Feature Fusion." Sensors 25, no. 11 (2025): 3546. https://doi.org/10.3390/s25113546.

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Rail surface defects pose significant risks to the operational efficiency and safety of industrial equipment. Traditional visual defect detection methods typically rely on high-quality RGB images; however, they struggle in low-light conditions due to small, low-contrast defects that blend into complex backgrounds. Therefore, this paper proposes a novel defect segmentation method leveraging a dual-stream feature fusion network that combines polarization images with DeepLabV3+. The approach utilizes the pruned MobileNetV3 as the backbone network, incorporating a coordinate attention mechanism fo

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39

Mogyla, V. I., M. O. Morneva, and M. V. Kovtanets. "The use of the multivariate antiskid sensor to gain maximum trailed load of the rolling stock." Вісник Східноукраїнського національного університету імені Володимира Даля, no. 5 (275) (December 10, 2022): 55–57. http://dx.doi.org/10.33216/1998-7927-2022-275-5-55-57.

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The article examines the use of the antiskid sensor to gain maximum trailed load.Skidding means the slip of wheels of a vehicle (tram, railway carriage) along the bearing surface (road, rails) where the linear speed of the wheel surface is lower than the speed of the bearing surface towards the vehicle. The wheel slip occurs during braking. It is caused by the excess braking force over the traction with the bearing surface. Skidding of rail vehicles leads to the wear-out of locked wheels in the place of their contact with the rail and to the flat area on the wheel tire.  To prevent

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40

Chudzikiewicz, Andrzej, Jozef Drozdziel, and Bogdan Sowinski. "Practical Solution of Rail Vehicle and Track Dynamics Monitoring System." Key Engineering Materials 518 (July 2012): 271–80. http://dx.doi.org/10.4028/www.scientific.net/kem.518.271.

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The improvement of traveller comfort and safety, in parallel to an increase of passenger train speed, is a reason to implement monitoring systems. These systems are more often used to monitor components of railway infrastructure and vehicles. Studies in this area must be preceded by identification and a complex analysis of the railway vehicle - track system. This allows us to recognise the dynamic properties of the system and then select the appropriate place to install sensors on board the vehicle. This paper presents the results of model studies and a prototype monitoring system which is ins

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41

Liu, Shuai, Yu-Hao Shi, Tian-Yu Lin, Yong-Peng Zhang, Zhi-Jian Lu, and Lan-Jun Yang. "Influence of operating parameters on discharge mode of parallel-rail accelerator." Acta Physica Sinica 70, no. 20 (2021): 205205. http://dx.doi.org/10.7498/aps.70.20210484.

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Electromagnetic plasma accelerators which can generate hypervelocity and high density plasma jets have been widely used in the fields of nuclear physics and astrophysics. In this paper, an experimental platform of parallel-rail accelerator electromagnetically driven plasma is established, and the discharge modes under different discharge currents and gas injection conditions are studied through using magnetic probes, a spectrometer and an ICCD. A fast gas valve is used to inject argon into the rail electrode area. The time delay between the fast valve discharge and the parallel-rail accelerato

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42

Liu, Shuai, Yu-Hao Shi, Tian-Yu Lin, Yong-Peng Zhang, Zhi-Jian Lu, and Lan-Jun Yang. "Influence of operating parameters on discharge mode of parallel-rail accelerator." Acta Physica Sinica 70, no. 20 (2021): 205205. http://dx.doi.org/10.7498/aps.70.20210484.

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Анотація:

Electromagnetic plasma accelerators which can generate hypervelocity and high density plasma jets have been widely used in the fields of nuclear physics and astrophysics. In this paper, an experimental platform of parallel-rail accelerator electromagnetically driven plasma is established, and the discharge modes under different discharge currents and gas injection conditions are studied through using magnetic probes, a spectrometer and an ICCD. A fast gas valve is used to inject argon into the rail electrode area. The time delay between the fast valve discharge and the parallel-rail accelerato

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43

Xiao, Tianwen, Yongneng Xu, and Huimin Yu. "Research on Obstacle Detection Method of Urban Rail Transit Based on Multisensor Technology." Journal of Artificial Intelligence and Technology 1, no. 1 (2021): 61–67. http://dx.doi.org/10.37965/jait.2020.0027.

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With the rapid development of urban rail transit, passenger traffic is increasing, and obstacle violations are more frequent, and the safety of train operation under high-density traffic conditions is becoming more and more thought-provoking. In order to monitor the train operating environment in real time, this paper first adopts multi-sensing technology based on machine vision and lidar, which is used to collect video images and ranging data of the track area in real time, and then it performs image preprocessing and division of regions of interest on the collected video. Then, the obstacles

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44

Yuan, Cheng, and Xin Chen. "Research on collision avoidance method based on millimeter wave radar." Highlights in Science, Engineering and Technology 37 (March 18, 2023): 137–41. http://dx.doi.org/10.54097/hset.v37i.6068.

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In view of the current production environment in the mining area during the transportation of the minecart, the minecart driver's obstruction of vision and dim light during the driving process, which is easy to cause the minecart to collide and rear-end the collision. Various accidents such as injuries occur. Therefore, in order to improve the safety of mining area operation, it is necessary to apply the target detection technology of the rail travel area to the train to further realize unmanned driving. Millimeter wave radar has a series of advantages such as small size, light weight, narrow

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45

Pamuła, Teresa, and Wiesław Pamuła. "Detection of Safe Passage for Trains at Rail Level Crossings Using Deep Learning." Sensors 21, no. 18 (2021): 6281. http://dx.doi.org/10.3390/s21186281.

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The detection of obstacles at rail level crossings (RLC) is an important task for ensuring the safety of train traffic. Traffic control systems require reliable sensors for determining the state of anRLC. Fusion of information from a number of sensors located at the site increases the capability for reacting to dangerous situations. One such source is video from monitoring cameras. This paper presents a method for processing video data, using deep learning, for the determination of the state of the area (region of interest—ROI) vital for a safe passage of the train. The proposed approach is va

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46

Ma, Boyang, Shupeng Chen, Shulong Wang, et al. "A False Trigger-Strengthened and Area-Saving Power-Rail Clamp Circuit with High ESD Performance." Micromachines 14, no. 6 (2023): 1172. http://dx.doi.org/10.3390/mi14061172.

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A power clamp circuit, which has good immunity to false trigger under fast power-on conditions with a 20 ns rising edge, is proposed in this paper. The proposed circuit has a separate detection component and an on-time control component which enable it to distinguish between electrostatic discharge (ESD) events and fast power-on events. As opposed to other on-time control techniques, instead of large resistors or capacitors, which can cause a large occupation of the layout area, we use a capacitive voltage-biased p-channel MOSFET in the on-time control part of the proposed circuit. The capacit

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47

Jia, Yajuan, Jianbo Zheng, and Hongfang Zhou. "Research on Airborne Electromagnetic Whole-area Apparent Resistivity Imaging Algorithm in the Detection of Goaf in Rail Transit." Journal of Physics: Conference Series 2083, no. 4 (2021): 042072. http://dx.doi.org/10.1088/1742-6596/2083/4/042072.

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Abstract Depth apparent resistivity imaging is an important process of data processing and analysis in the aviation transient electromagnetic method. It can provide reference value of conductor depth, vertical extension, and other information, and can accurately provide the measurement of each aviation transient electromagnetic measurement system. The structural section of the apparent conductivity of the one-dimensional layered medium on the line. As an advanced geophysical exploration technology, the aerial transient electromagnetic method has been applied significantly in the exploration of

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48

Yaodong, Jiang. "Active Obstacle Detection System Based on Video Recognition and Lidar Information Fusion." New Metro 1, no. 1 (2020): 11–21. http://dx.doi.org/10.37819/nm.001.01.0073.

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In terms of the requirements for obstacle detection in the rail transit application field, an architecture and implementation method for active obstacle detection system based on the fusion of video recognition and lidar information is proposed. The studies on the video recognition algorithms based on deep learning neural network and lidar for orbit area recognition, pedestrian vehicle recognition, and small foreign object recognition are analyzed, and the necessity of the fusion of video recognition and lidar data and the related key technical points are discussed. Through the tests on domest

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49

Jiang, Aihui, Jie Dai, Sisi Yu, Baolei Zhang, Qiaoyun Xie, and Huanxue Zhang. "Unsupervised Change Detection around Subways Based on SAR Combined Difference Images." Remote Sensing 14, no. 17 (2022): 4419. http://dx.doi.org/10.3390/rs14174419.

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Prompt and precise acknowledgement of surface change around subways is of considerable significance in urban rail protection and local environmental management. Research has proven the considerable potential of synthetic aperture radar (SAR) images for detecting such information; however, previous studies have mostly focused on change intensity using single Difference images (DIs), e.g., difference value DI (DVDI) and mean value DI (MVDI). With the aim of more accurate information with respect to surface changes around subways, in this study, we proposed a novel SAR detection method that invol

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50

Beauchamp, A. J. "Banded rail (Gallirallus philippensis) detection at Ruakaka estuary before, during, and after mangrove (Avicennia marina) removal." Notornis 72, no. 3 (2025): 161. https://doi.org/10.63172/012836krmcgh.

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Banded rails (Hypotaenidia philippensis) were monitored using footprints before, during, and after the partial removal of 1.8 ha of mangroves (Avicennia marina) from a 2.4 ha area in the Ruakaka estuary. Mangrove removal occurred in two phases: adult trees in winter 2014 and juvenile plants and pneumatophores in winter 2015. Banded rails were only detected on the margins of mangroves during adult tree removal, and then throughout the cleared areas after seedling and pneumatophore removal. In 2016, 2018, and 2020, rails showed a similar use pattern in the uncleared and cleared areas to that use

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