A Novel Online Detection System for Wheelset Size in Railway Transportation

Cheng, Xiaoqing; Chen, Yuejian; Xing, Zongyi; Li, Yifan; Qin, Yong

doi:10.1155/2016/9507213

Cited by 17 publications

(6 citation statements)

References 15 publications

(32 reference statements)

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“…Among them, there is a digital image processing based trackside system that takes image of wheel tread and flange as the wheel passes across its lightening devices [10]. There is also an online detection system based on laser displacement sensor (LDS) [28] installed on the trackside. The wheel profile (wheel diameter, wheel flange width and height) was able to be measured.…”

Section: Wheel Flange Wear Measurement Techniquesmentioning

confidence: 99%

Development of an On-Board Measurement System for Railway Vehicle Wheel Flange Wear

Turabimana

Nkundineza

2020

Sensors

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The maintenance of railway systems is critical for their safe operation. However some landscape geographical features force the track line to have sharp curves with small radii. Sharp curves are known to be the main source of wheel flange wear. The reduction of wheel flange thickness to an extreme level increases the probability of train accidents. To avoid the unsafe operation of a rail vehicle, it is important to stay continuously up to date on the status of the wheel flange thickness dimensions by using precise and accurate measurement tools. The wheel wear measurement tools that are based on laser and vision technology are quite expensive to implement in railway lines of developing countries. Alternatively significant measurement errors can result from using imprecise measurement tools such as the hand tools, which are currently utilized by the railway companies such as Addis Ababa Light Rail Transit Service (AALRTS). Thus, the objective of this research is to propose and test a new measurement tool that uses an inductive displacement sensor. The proposed system works in both static and dynamic state of the railway vehicle and it is able to save the historical records of the wheel flange thickness for further analysis. The measurement system is fixed on the bogie frame. The fixture was designed using dimensions of the bogie and wheelset structure of the trains currently used by AALRTS. Laboratory experiments and computer simulations for of the electronic system were carried out to assess the feasibility of the data acquisition and analysis method. The noises and unwanted signals due to the dynamics of the system are filtered out from the sensor readings. The results show that the implementation of the proposed measurement system can accurately measure the wheel flange wear. Also, the faulty track section can be identified using the system recorded data and the operational control center data.

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Section: Wheel Flange Wear Measurement Techniquesmentioning

confidence: 99%

Development of an On-Board Measurement System for Railway Vehicle Wheel Flange Wear

Turabimana

Nkundineza

2020

Sensors

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“…Polynomial and B-spline are commonly used forms to fit a curve. Reference [19] adopted polynomial fitting with the least square method to detect the wheel set size in the railway transportation system. The polynomial surface was also considered to approximate concrete structures with gentle surfaces [20][21][22][23].…”

Section: Curve Fitting With Mathematical Functionsmentioning

confidence: 99%

TLS-Based Feature Extraction and 3D Modeling for Arch Structures

Zhao

Yang

et al. 2017

Journal of Sensors

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Terrestrial laser scanning (TLS) technology is one of the most efficient and accurate tools for 3D measurement which can reveal surface-based characteristics of objects with the aid of computer vision and programming. Thus, it plays an increasingly important role in deformation monitoring and analysis. Automatic data extraction and high efficiency and accuracy modeling from scattered point clouds are challenging issues during the TLS data processing. This paper presents a data extraction method considering the partial and statistical distribution of the point clouds scanned, called the window-neighborhood method. Based on the point clouds extracted, 3D modeling of the boundary of an arched structure was carried out. The ideal modeling strategy should be fast, accurate, and less complex regarding its application to large amounts of data. The paper discusses the accuracy of fittings in four cases between whole curve, segmentation, polynomial, and B-spline. A similar number of parameters was set for polynomial and B-spline because the number of unknown parameters is essential for the accuracy of the fittings. The uncertainties of the scanned raw point clouds and the modeling are discussed. This process is considered a prerequisite step for 3D deformation analysis with TLS.

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“…In addition, two extra 2D-LDSs were arranged to measure the wheel diameter by the three-point fitting method. Cheng [18] replaced one of the 2D-LDSs with a 1D-LDS to obtain a higher measurement accuracy and lower costs. Since the measurement frequency of 2D-LDSs is much lower than that of 1D-LDSs, a very low speed while the train passes the sensors is required to obtain a good wheel diameter result.…”

Section: Introductionmentioning

confidence: 99%

High-Accuracy On-Site Measurement of Wheel Tread Geometric Parameters by Line-Structured Light Vision Sensor

Ran

Feng

et al. 2021

IEEE Access

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Railway wheels are one of the important parts of railway vehicles, and it is necessary to inspect their status frequently. To measure the wheel tread geometric parameters dynamically and accurately in a train running environment, a line-structured light vision sensor-based measurement system was demonstrated in this paper. In the system, a subpixel laser stripe centre extraction algorithm based on skeleton extraction, which can significantly reduce the interference of complex lighting environments in the field and greatly improve the extraction accuracy, was proposed. To further improve the measurement accuracy and stability, the influence of the eccentricity error caused by the dynamic measurement on the results was analyzed, a mathematical model was established, and the deformed profile was corrected. The system has been successfully applied to railway maintenance sections and has become a part of train safety inspection systems. Field tests were conducted to verify the performance of the system, and the results showed that the measurement accuracy and stability are marked improved after eccentric error correction, especially for the flange height and QR value.

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A Novel Online Detection System for Wheelset Size in Railway Transportation

Cited by 17 publications

References 15 publications

Development of an On-Board Measurement System for Railway Vehicle Wheel Flange Wear

Development of an On-Board Measurement System for Railway Vehicle Wheel Flange Wear

TLS-Based Feature Extraction and 3D Modeling for Arch Structures

High-Accuracy On-Site Measurement of Wheel Tread Geometric Parameters by Line-Structured Light Vision Sensor

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