Vibration analysis for slab track at different train speeds using Bayes wavelet denoising

Yue, Guodong; Xu, Zheng; Wang, Liding; Liu, Chong; Zhou, Wenjing

doi:10.1177/0954409716647417

Cited by 7 publications

(3 citation statements)

References 21 publications

(26 reference statements)

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“…To emphasise the impact events in the acceleration signal and to reduce noise, wavelet denoising was performed. Wavelets have been applied as a denoising technology for vibration data [ 30 , 31 ] ever since it was first introduced by Donoho and Johnstone [ 32 ]. The wavelet transform is a very powerful tool for time–frequency analysis and the cornerstone of wavelet denoising.…”

Section: Methodsmentioning

confidence: 99%

Squat Detection of Railway Switches and Crossings Using Point Machine Vibration Measurements

Zuo

Lundberg

Najeh

et al. 2023

Sensors

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Railway switches and crossings (S&C) are among the most important high-value components in a railway network and a failure of such an asset could result in severe network disturbance. Therefore, potential defects need to be detected at an early stage to prevent traffic-disturbing downtime or even severe accidents. A squat is a common defect of S&Cs that has to be monitored and repaired to reduce such risks. In this study, a testbed including a full-scale S&C and a bogie wagon was developed. Vibrations were measured for different squat sizes by an accelerometer mounted at the point machine. A method of processing the vibration data and the speed data is proposed to investigate the possibility of detecting and quantifying the severity of a squat. One key technology used is wavelet denoising. The study shows that it is possible to monitor the development of the squat size on the rail up to around 13 m from the point machine. The relationships between the normalised peak-to-peak amplitude of the vibration signal and the squat depth were also estimated.

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Section: Methodsmentioning

confidence: 99%

Squat Detection of Railway Switches and Crossings Using Point Machine Vibration Measurements

Zuo

Lundberg

Najeh

et al. 2023

Sensors

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“…Track vibrations are excited by wheel‐rail contact forces, including quasi‐static components due to moving loads and dynamic components due to track irregularities (Milne et al., 2017). As the train speed increases, wheel passage and sleeper passage frequencies increase linearly, and the corresponding track response first increases and then may decrease after resonance (Auersch, 2006; Le Pen et al., 2016; Yue et al., 2017). For the dynamic response due to irregularities, its frequencies increase linearly with the increasing train speed, while the track vibration amplitude increases first fast and then slowly (Bian et al., 2015).…”

Section: Introductionmentioning

confidence: 99%

Railway sleeper vibration measurement by train‐borne laser Doppler vibrometer and its speed‐dependent characteristics

Zeng,

Núñez,

2024

Computer aided Civil Eng

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A train‐borne laser Doppler vibrometer (LDV) directly measures the dynamic response of railway track components from a moving train, which has the potential to complement existing train‐borne technologies for railway track monitoring. This paper proposes a holistic methodology to characterize train‐borne LDV measurements by combining computer‐aided approaches and real‐life measurements. The focus is on the speed‐dependent characteristics because the train speed affects the intensity of railway sleeper vibrations and the intensity of speckle noise, which further affects the quality and usability of the measured signals. First, numerical models are established and validated to simulate sleeper vibrations and speckle noise separately. Then, a vibration–noise separation method is proposed to effectively extract speckle noise and structural vibrations from LDV signals measured at different speeds. The parameters of the separation method are tuned using simulation signals. The method is then validated using laboratory measurements in a vehicle‐track test rig and applied to field measurements on a railway track in Rotterdam, the Netherlands. Further, the speed‐dependent characteristics of train‐borne LDV measurement are determined by analyzing the competition between sleeper vibrations and speckle noise at different speeds. Simulation and measurement results show that an optimal speed range yields the highest signal‐to‐noise ratio, which varies for different track structures, measurement configurations, and operational conditions. The findings demonstrate the potential of train‐borne LDV for large‐scale rail infrastructure monitoring.

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“…Currently, various slab tracks are implemented in the world. erefore, the frequency response and noise resulting from the train movement on the rail are significant in identifying the railway track's dynamic behavior [15]. us, the potential decay of rail tracks can be reduced by identifying these two factors.…”

Section: Introductionmentioning

confidence: 99%

Modeling Dynamic Frequency Response on Slab Track of Shinkansen Railway Based on Finite Element Method

Gholizadeh

Aghayan

Hadadi

2022

Advances in Civil Engineering

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The use of slab tracks in lieu of ballast tracks has introduced new dimensions in track dynamics in high-speed railways. To improve the performance of slab tracks under dynamic frequency responses caused by loads on the Shinkansen railway, the present study aimed to investigate the effect of mechanical properties of track components, including the elasticity modulus and thickness on the resonance frequency of the vertical dynamic responses using the finite element method. Such responses included receptance and decay rate in the asphalt bearing layer (ABL), hydraulically bonded layer (HBL), and concrete bearing layer (CBL). In addition, the study sought to select the optimal layer as an effective layer in the view of reducing the resonance frequency of dynamic responses in comparison with the general model. Based on the data regarding the effects of elasticity modulus and thickness of slab track layers on the resonance of the dynamic frequency responses under the amplitude loads, by changing the load from 20 to 25 tons over the slab track, the receptance under the modulus and thickness change increased up to 34 and 29%. Moreover, the decay rate under the modulus and thickness change increased up to 31 and 37%. Accordingly, by increasing the load amplitude, the CBL and HBL showed lower dynamic responses than other layers. Thus, CBL and HBL were selected as the optimum layers for improving the performance of the slab track of the Shinkansen railway.

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Vibration analysis for slab track at different train speeds using Bayes wavelet denoising

Cited by 7 publications

References 21 publications

Squat Detection of Railway Switches and Crossings Using Point Machine Vibration Measurements

Squat Detection of Railway Switches and Crossings Using Point Machine Vibration Measurements

Railway sleeper vibration measurement by train‐borne laser Doppler vibrometer and its speed‐dependent characteristics

Modeling Dynamic Frequency Response on Slab Track of Shinkansen Railway Based on Finite Element Method

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