scholarly journals Semi-Supervised Deep Learning in High-Speed Railway Track Detection Based on Distributed Fiber Acoustic Sensing

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 413
Author(s):  
Shulun Wang ◽  
Feng Liu ◽  
Bin Liu
Keyword(s):  
Deep Learning ◽  
Optical Sensors ◽  
High Speed ◽  
Railway Track ◽  
Detection Methods ◽  
High Speed Railway ◽  
Safety Risks ◽  
Data Driven Approach ◽  
Distributed Optical Fiber ◽  
Selection Of

High deployment costs, safety risks, and time delays restrict traditional track detection methods in high-speed railways. Therefore, approaches based on optical sensors have become the most remarkable strategy in terms of deployment cost and real-time performance. Owing to the large amount of data obtained by sensors, it has been proven that deep learning, as a powerful data-driven approach, can perform effectively in the field of track detection. However, it is difficult and expensive to obtain labeled data from railways during operation. In this study, we used a segment of a high-speed railway track as the experimental object and deployed a distributed optical fiber acoustic system (DAS). We propose a track detection method that innovatively leverages semi-supervised deep learning based on image recognition, with a particular pre-processing for the dataset and a greedy algorithm for the selection of hyper-parameters. The superiority of the method was verified in both experiments and actual applications.

Selection of the Optimal Type of Bored-Injection Piles Strengthening of Weak Bases of High-Speed Railway Lines

2019 ◽  
pp. 40-44
Author(s):  
N.S. SOKOLOV ◽  
◽  
S.S. VIKTOROVA ◽  
I.P. FEDOSEEVA ◽  
G.M. SMIRNOVA ◽  
...  
Keyword(s):  
High Speed ◽  
High Speed Railway ◽  
Weak Bases ◽  
Selection Of ◽  
Optimal Type

A deep learning forecasting method for frost heave deformation of high-speed railway subgrade

2021 ◽  
pp. 103265
Author(s):  
Jing Chen ◽  
Anyuan Li ◽  
Chunyan Bao ◽  
Yanhua Dai ◽  
Minghao Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Speed ◽  
Frost Heave ◽  
High Speed Railway ◽  
Forecasting Method

scholarly journals The Design and Implementation of an Inertial GNSS Odometer Integrated Navigation System Based on a Federated Kalman Filter for High-Speed Railway Track Inspection

2021 ◽  
Vol 11 (11) ◽  
pp. 5244
Author(s):  
Xinchun Zhang ◽  
Ximin Cui ◽  
Bo Huang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
High Speed ◽  
Measurement Accuracy ◽  
Railway Track ◽  
Filter Method ◽  
Integrated Navigation ◽  
High Speed Railway ◽  
Track Geometry ◽  
Integrated Navigation System

The detection of track geometry parameters is essential for the safety of high-speed railway operation. To improve the accuracy and efficiency of the state detector of track geometry parameters, in this study we propose an inertial GNSS odometer integrated navigation system based on the federated Kalman, and a corresponding inertial track measurement system was also developed. This paper systematically introduces the construction process for the Kalman filter and data smoothing algorithm based on forward filtering and reverse smoothing. The engineering results show that the measurement accuracy of the track geometry parameters was better than 0.2 mm, and the detection speed was about 3 km/h. Thus, compared with the traditional Kalman filter method, the proposed design improved the measurement accuracy and met the requirements for the detection of geometric parameters of high-speed railway tracks.

Risk Assessment Method for High-Speed Railway Track Based on Dynamically Weighted Acceleration

2021 ◽  
Vol 27 (4) ◽  
pp. 04021030
Author(s):  
Xiaohui Wang ◽  
Jianwei Yang ◽  
Jinhai Wang ◽  
Yanxue Wang ◽  
Fu Liu
Keyword(s):  
Risk Assessment ◽  
High Speed ◽  
Assessment Method ◽  
Railway Track ◽  
High Speed Railway ◽  
Risk Assessment Method

scholarly journals Application of Mastic Asphalt Waterproofing Layer in High-Speed Railway Track in Cold Regions

2018 ◽  
Vol 8 (5) ◽  
pp. 667 ◽  
Author(s):  
Song Liu ◽  
Jun Yang ◽  
Xianhua Chen ◽  
Guotao Yang ◽  
Degou Cai
Keyword(s):  
High Speed ◽  
Railway Track ◽  
High Speed Railway ◽  
Cold Regions ◽  
Mastic Asphalt

Nonlinear random seismic analysis of 3D high-speed railway track-bridge system based on OpenSEES

Structures ◽  
2020 ◽  
Vol 24 ◽  
pp. 87-98
Author(s):  
Haiyan Li ◽  
Zhiwu Yu ◽  
Jianfeng Mao ◽  
Lizhong Jiang
Keyword(s):  
High Speed ◽  
Seismic Analysis ◽  
Railway Track ◽  
High Speed Railway ◽  
Track Bridge ◽  
Bridge System

scholarly journals An Innovative Detection Method of High-Speed Railway Track Slab Supporting Block Plane Based on Point Cloud Data from 3D Scanning Technology

2019 ◽  
Vol 9 (16) ◽  
pp. 3345 ◽  
Author(s):  
Chen ◽  
Qin ◽  
Xia ◽  
Bao ◽  
Huang ◽  
...  
Keyword(s):  
Point Cloud ◽  
High Speed ◽  
Detection Method ◽  
Railway Track ◽  
Point Cloud Data ◽  
3D Scanner ◽  
High Speed Railway ◽  
Cloud Data ◽  
Plane Point ◽  
Track Slab

The dimension detection of high-speed railway track slabs is one of the most important tasks before the track slabs delivery. Based on the characteristics of a 3D scanner which can acquire a large amount of measurement data continuously and rapidly in a short time, this paper uses the integration of 3D scanner and the intelligent robot to detect the CRTSIII (China Railway Track System) track slab supporting block plane, then the dense and accurate supporting block plane point cloud data is obtained, and the point cloud data is registered with the established model. An improved Random Sample Consensus (RANSAC) plane fitting algorithm is also proposed to extract the data of supporting block plane point cloud in this paper. The detection method is verified and the quality analysis of the detection results is assessed by a lot of real point cloud data obtained on site. The results show that the method can meet the quality control of CRTSIII finished track slab and the detection standard. Compared with the traditional detection methods, the detection method proposed in this paper can complete the detection of a track slab in 7 min, which greatly improves the detection efficiency, and has better reliability. The method has wide application prospects in the field of railway component detection.

scholarly journals Experimental Study of the Temperature Distribution in CRTS-II Ballastless Tracks on a High-Speed Railway Bridge

2020 ◽  
Vol 10 (6) ◽  
pp. 1980 ◽  
Author(s):  
Lei Zhao ◽  
Ling-Yu Zhou ◽  
Guang-Chao Zhang ◽  
Tian-Yu Wei ◽  
Akim D. Mahunon ◽  
...  
Keyword(s):  
High Temperature ◽  
Temperature Distribution ◽  
Temperature Gradient ◽  
High Speed ◽  
Railway Track ◽  
Vertical Temperature ◽  
High Speed Railway ◽  
Extreme High Temperature ◽  
Transverse Temperature ◽  
Temperature Test

To study the temperature distribution in the China Railway Track System Type II ballastless slab track on a high-speed railway (HSR) bridge, a 1:4 scaled specimen of a simply-supported concrete box girder bridge with a ballastless track was constructed in laboratory. Through a rapid, extreme high temperature test in winter and a conventional high temperature test in summer, the temperature distribution laws in the track on the HSR bridge were studied, and the vertical and transverse temperature distribution trend was suggested for the track. Firstly, the extreme high temperature test results showed that the vertical temperature and the vertical temperature difference distribution in the track on HSR bridge were all nonlinear with three stages. Secondly, the extreme high temperature test showed that the transverse temperature distribution in the track was of quadratic parabolic nonlinear form, and the transverse temperature gradient in the bottom base was significantly higher than that of the other layers of the track. Thirdly, the three-dimensional temperature distribution in the track on HSR bridge was a nonlinear, three-stage surface. Furthermore, similar regularities were also obtained in the conventional high temperature test, in which the temperature span ranges were different from those of the extreme high temperature test. In addition, the conventional high temperature test also showed that under the natural environment conditions, the internal temperature gradient in the track layers changed periodically (over a period of 24 h).

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