A New Approach for Inspection of Selected Geometric Parameters of a Railway Track Using Image-Based Point Clouds

Gabara, Grzegorz; Sawicki, Piotr

doi:10.3390/s18030791

Cited by 34 publications

(15 citation statements)

References 28 publications

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“…Safa et al [27] introduced a three-dimensional imaging-based correlation analysis method for dense point cloud information on rail corrosion damage; Zhan et al [28] outlines the research progress in three-dimensional dynamic detection of tunnels a railway based on multi-camera and structured light vision systems; Zhou et al [29] proposed a three dimensional point cloud tunnel crack detection method based on mobile laser scanning system (MLS) with an accuracy of 0.03 m, which can effectively calculate the differences among various crack types; Rikhotso et al [30] proposed a method for acquiring rail condition and detecting surface defects using 3D image acquisition and modeling; Gabara et al [31] proposed an image-based point cloud measurement method for the determination of geometrical parameters of railway tracks; Xiong et al [32] proposed a new type of three-dimensional laser profiling system, which acquires the rail surface profile data using laser scanners, odometers, inertial measurement units (IMUs), and global positioning systems (GPS), and combines all measurement profiles to form a rail surface. Yi et al [33] proposed a new profile registration method for sparse iterative nearest neighbors for 3D track measurements, and introduced the distance between the Hausdorff distance measurement wear model and the reference model; Mao et al [34] proposed a high-speed railway fastener detection method based on structured light sensor, which uses the structured light sensor to obtain high-precision, high-density fastener point cloud, and uses the decision tree classifier to defect the fastener and carry out the detailed classification; Cui et al [35] proposed a real-time measurement system for high-speed railway fastener geometric parameters based on 3D laser profilometer, which obtained a dense and accurate 3D point cloud of high-speed rail fasteners.…”

Section: Introductionmentioning

confidence: 99%

A Rail Fastener Tightness Detection Approach Using Multi-source Visual Sensor

Han

Wang

Fang

et al. 2020

Sensors

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At present, the method of two-dimensional image recognition is mainly used to detect the abnormal fastener in the rail-track inspection system. However, the too-tight-or-too-loose fastener condition may cause the clip of the fastener to break or loose due to the high frequency vibration shock, which is difficult to detect from the two-dimensional image. In this practical application background, 3D visual detection technology provides a feasible solution. In this paper, we propose a fundamental multi-source visual data detection method, as well as an accurate and robust fastener location and nut or bolt segmentation algorithm. By combining two-dimensional intensity information and three-dimensional depth information generated by the projection of line structural light, the locating of nut or bolt position and accurate perception of height information can be realized in the dynamic running environment of railway. The experimental results show that the static measurement accuracy in the vertical direction using the structural light vision sensor is 0.1 mm under the laboratory condition, and the dynamic measurement accuracy is 0.5 mm under the dynamic train running environment. We use dynamic template matching algorithm to locate fasteners from 2D intensity map, which achieves 99.4% accuracy, then use the watershed algorithm to segment the nut and bolt from the corresponding depth image of located fastener. Finally, the 3D shape of the nut and bolt is analyzed to determine whether the nut or bolt height meets the local statistical threshold requirements, so as to detect the hidden danger of railway transportation caused by too loose or too tight fasteners.

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Section: Introductionmentioning

confidence: 99%

A Rail Fastener Tightness Detection Approach Using Multi-source Visual Sensor

Han

Wang

Fang

et al. 2020

Sensors

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“…Gabara and Sawicki presented a method for measuring image-based point clouds for the determination of the geometric parameters of a railway track. (4) Their study was performed using digital images and a reference control network. Jwa and Sohn suggested a solution for the automatic reconstruction of a 3D power line model from airborne laser scanning (ALS) data.…”

Section: Introductionmentioning

confidence: 99%

Automated Reconstruction of Railroad Rail Using Helicopter-borne Light Detection and Ranging in a Train Station

Jeon¹,

Kim²

2019

Sensors and Materials

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A coordinate-based 3D model of a railroad rail is essential for the maintenance of railway services. However, automated processing to reconstruct objects from light detection and ranging (LiDAR) data in areas where such facilities are installed in a complex manner is still a challenge. In this study, our objective is to develop a method for the automated reconstruction of rails from LiDAR data in a complex area. Unlike the running sections of a train where one or two rails are present, many rails are installed by joining or branching in a railway station. Three factors, namely, height difference, spatial relationship with other objects, and point density difference, were considered in detecting the rails in this complicated area. For tracking and modeling rails, an iterative random sample consensus (RANSAC) and singular value decomposition (SVD) algorithms were used. The results showed that about 90% of the rail tracks were extracted, and the precision rate was about 99%. All processes were fully automated, and the method proposed in this study was developed to be applicable to various line-type facilities as well as rails.

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“…Existing railway reconstruction is an important research topic in the fields of railway engineering [3], surveying and mapping engineering [4], reverse engineering [5], and computing science [6]. In recent years, scientists have conducted extensive investigations in the field of existing railway reconstruction based on the coordinate method.…”

Section: Introductionmentioning

confidence: 99%

Methodology for Existing Railway Reconstruction with Constrained Optimization Based on Point Cloud Data

Ren²,

Luo

et al. 2018

Applied Sciences

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The reconstruction of an existing railway is important for railway reformation or double-track design. Obtaining the curve parameters of the railway and the location of the main stake accurately and rapidly is the key issue for existing railway reconstruction. A new method based on point cloud data is proposed in this paper. The issue of reconstruction was transformed into an optimization problem by constructing the objective function and introducing the constraint. With consideration of the slope of the curves’ chord, the robust local weighted moving average method was used for de-noising. The time complexity was reduced greatly after separating the curve unit. The proposed method can obtain the coordinates of the main stake and the parameters of the railway by particle swarm optimization using a full direction search, combining the design requirements and geometric relations of the railway. Finally, some experiments on the design data and measured data were conducted to verify the validity of the proposed method. The results also show that the proposed method is very effective and useful for existing railway reconstruction.

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A New Approach for Inspection of Selected Geometric Parameters of a Railway Track Using Image-Based Point Clouds

Cited by 34 publications

References 28 publications

A Rail Fastener Tightness Detection Approach Using Multi-source Visual Sensor

A Rail Fastener Tightness Detection Approach Using Multi-source Visual Sensor

Automated Reconstruction of Railroad Rail Using Helicopter-borne Light Detection and Ranging in a Train Station

Methodology for Existing Railway Reconstruction with Constrained Optimization Based on Point Cloud Data

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