Modern Condition Monitoring Systems for Railway Wheel-Set Dynamics: Performance Analysis and Limitations of Existing Techniques

Mal, Khakoo; Hussain, Imtiaz; Memon, Tayab Din; Soother, Dileep Kumar; Chowdhry, Bhawani Shankar

doi:10.33317/ssurj.419

Cited by 3 publications

(3 citation statements)

References 30 publications

(75 reference statements)

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“…There are manual caliper measurements, non-contact laser equipment * Authors to whom any correspondence should be addressed. measurements, and measurements by automated measuring instruments mounted on the ground [10].…”

Section: Introductionmentioning

confidence: 99%

Rapid measurement method for key dimensions of train wheelset based on improved image processing algorithm

Fang,

Wang,

Zhu

et al. 2024

Meas. Sci. Technol.

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The key dimensions of train wheelsets change with the increase of running time. To ensure the safe operation of the train, the key dimensions should meet the relevant technical requirements. Maintenance of wheelsets and measurement of key dimensions are important part of the daily maintenance work. A rapid measurement method for key dimensions of hand-held wheelsets integrating multiple parameter measurements is studied. The general framework of the system is examined and the roles of the modules are described. A rapid measurement algorithm for key dimensions of wheelsets based on image processing algorithms is studied. The optical center for the initial position of the continuous line spot is searched. The continuous line spot center extraction algorithm during tread measurement is optimized. A three-dimensional model is reconstructed using point cloud data, then key dimensions are measured and calculated from the model. In order to verify the feasibility of the method, traditional measurement methods are used for comparison tests. The results show that the method is effective in the daily maintenance of trains.

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Section: Introductionmentioning

confidence: 99%

Rapid measurement method for key dimensions of train wheelset based on improved image processing algorithm

Fang,

Wang,

Zhu

et al. 2024

Meas. Sci. Technol.

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“…The point of the installation could be either on the rolling stock or track mounted. Track-mounted sensors are usually used to detect wheel faults and on-board sensors are used for infrastructure monitoring [4], [5]. Railway infrastructure management is driven by data acquired via inspection devices.…”

Section: Introductionmentioning

confidence: 99%

State-of-the-Art Wayside Condition Monitoring Systems for Railway Wheels: A Comprehensive Review

et al. 2023

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In recent decades, there has been a constant demand for faster, longer, and safer railway networks. This also brings challenges for condition monitoring systems in modern railway vehicles. More specifically, critical parts of railway vehicles like wheels degrade over time due to various operational and environmental reasons. Different dynamic effects such as skidding/sliding over the track and the presence of contamination between wheel-rail cause various wheel defects. Faulty wheels ultimately lead to the derailment of railway vehicles. To avoid worst situations like railway derailments, various research has been conducted for developing efficient condition monitoring systems for railway wheels. In addition, there have been some commercial condition monitoring products that can be deployed with railway vehicles. These systems incorporate various sensors such as strain gauges and vision sensors to collect data for diagnosis and prognosis. Various methods have been explored but yet there is a broad research gap in terms of developing advanced onboard condition monitoring systems. With the progress in technology, advanced systems with Machine Learning/Deep Learning methods can provide more efficient and robust condition monitoring of dynamic railway systems. Considering the need for advancement in condition monitoring systems for railway vehicles, a comprehensive review of existing condition monitoring systems for railway wheels is conducted in this paper. The review is aimed at understanding the feasibility and potential of new methods for modern railways. This paper provides a detailed overview of studies on the existing wayside systems and reports their advantages and disadvantages concerning its recently emerging counterpart on-board monitoring systems. Data acquisition systems and analysis methods are critically reviewed which could assist in developing more efficient and reliable condition monitoring systems for railway wheels. This article also reviews the current progress of wayside systems and their limitations. The article is targeted at the researchers and engineers working in this domain, who can pave the way for developing advanced and cost-effective condition monitoring systems for railway wheels using modern technologies.

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“…However, the creep curves for different types of contaminated rails not clear enough, so systematic work on the influence of creep curves for all conditions is required. A lot of research is being carried out for the estimation of wheel-track contact conditions mainly scholars use model-based techniques [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

FPGA Implementation of Extended Kalman Filter for Parameters Estimation of Railway Wheelset

Mal¹,

Memon²,

Kalwar³

et al. 2023

Computers, Materials &Amp; Continua

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It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad vehicle. The proper estimation of adhesion conditions and their real-time implementation is considered a challenge for scholars. In this paper, the development of simulation model of extended Kalman filter (EKF) in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of track. Due to concurrent in nature, the Xilinx ® System-on-Chip Zynq Field Programmable Gate Array (FPGA) device is chosen to check the onboard estimation of wheel-rail interaction parameters by using the National Instruments (NI) myRIO ® development board. The NI myRIO ® development board is flexible to deal with nonlinearities, uncertain changes, and fastchanging dynamics in real-time occurring in wheel-rail contact conditions during vehicle operation. The simulated dataset of the railway nonlinear wheelset model is tested on FPGA-based EKF with different track conditions and with accelerating and decelerating operations of the vehicle. The proposed model-based estimation of railway wheelset parameters is synthesized on FPGA and its simulation is carried out for functional verification on FPGA. The obtained simulation results are aligned with the simulation results obtained through MATLAB. To the best of our knowledge, this is the first time study that presents the implementation of a model-based estimation of railway wheelset parameters on FPGA and its functional verification. The functional behavior of the FPGA-based estimator shows that these results are the addition of current knowledge in the field of the railway.

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Modern Condition Monitoring Systems for Railway Wheel-Set Dynamics: Performance Analysis and Limitations of Existing Techniques

Cited by 3 publications

References 30 publications

Rapid measurement method for key dimensions of train wheelset based on improved image processing algorithm

Rapid measurement method for key dimensions of train wheelset based on improved image processing algorithm

State-of-the-Art Wayside Condition Monitoring Systems for Railway Wheels: A Comprehensive Review

FPGA Implementation of Extended Kalman Filter for Parameters Estimation of Railway Wheelset

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