Application of an optimal wavelet transformation for rail-fastening system identification in different preloads

Valikhani, Mohammad; Younesian, Davood

doi:10.1016/j.measurement.2015.12.039

Cited by 20 publications

(6 citation statements)

References 19 publications

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“…The passage of wheels on such damaged rail sections causes vertical and horizontal high-frequency and large-amplitude dynamic forces (greater than 100 g) [5,70]. Therefore, it is important to know not only the static but also the dynamic parameters of the fastening system, such as modal shapes, natural frequencies, dynamic stiffness, and the damping factor, which are significantly influenced by the fastening force and clip stiffness [71][72][73].…”

Section: Dynamic Strength Assessment Of the Clipsmentioning

confidence: 99%

“…However, a study on the dynamic parameters of the clip from the frequency domain perspective states that the frequency range in which the natural frequencies of the clip should be investigated is 0-1000 Hz [14,74], and the study [19] indicates up to 2000 Hz. Previous research studies that analysed the fastening system, including all components, if noise is ignored, were performed in the range of 100-1000 Hz [71,73,76]. Therefore, the relationship between the clip's and rail's natural frequencies in response to the dynamic forces generated during rail-wheel contact must be understood.…”

Section: Dynamic Strength Assessment Of the Clipsmentioning

confidence: 99%

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Development of a new and modification of existing elastic clips for rails fastening

Lakušić¹

2022

JCE

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One of the problems of railway fastening systems (fastening system) that occurs due to the development of railways is the damage of the elastic clips, which leads to the loss of structural integrity between the rail and the base. Therefore, there is a need to develop new clips or improve existing ones. The paper describes the contribution and role of each component of the fastening system in different loading cases. As a tool whose parameters can affect the efficiency of the fastening system, special attention is given to the clips. Finally, an example is briefly described for creating numerical models that can be used to perform parametric analyses in order to develop new clips or improve existing ones.

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Section: Dynamic Strength Assessment Of the Clipsmentioning

confidence: 99%

Section: Dynamic Strength Assessment Of the Clipsmentioning

confidence: 99%

Development of a new and modification of existing elastic clips for rails fastening

Lakušić¹

2022

JCE

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“…Inspired by vibration-based structural damage inspection method, some scholars have carried out fastener inspection method based on vibration. Valikhani and Younesian [16] proposed a fastener inspection method based on vibration, an accelerometer is installed on the rail track and its vibration signal is aroused by hitting a hammer to the track, the looseness of fasteners is inspected by conditional entropy criterion and the Morlet wavelet transformation. Wei et al [17] developed a vibration-based fastener inspection system, the acceleration signals are analyzed by wavelet packet analysis and the location and severity of loose fastener can be worked out.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Inspection System for Ballast Railway Fasteners Based on Point Cloud Deep Learning

Cui

et al. 2020

IEEE Access

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Rail fasteners are the most numerous components in railways and they should be inspected periodically. Manual inspection is currently a common solution, which is laborious and low-efficient. Some automatic inspection approaches are proposed. But for ballast railway fasteners inspection, debris, especially ballast along tracks may cover the fasteners, which is still a tricky problem. In this paper, a real-time inspection system for ballast railway fasteners based on point cloud deep learning is developed. Dense and precise point cloud of fastener is obtained from the structured light sensors in the system. The point cloud of fastener is segmented into different parts to avoid the interference of debris on fasteners. A ballast fastener point cloud semantic segmentation dataset is created based on automatic annotation method. Several deep learning point cloud segmentation models are tested in this dataset and PointNet++ is selected to be deployed in the real-time deep learning module of the system. Field tests on ballast railways show excellent accuracy and efficiency of this system.INDEX TERMS Ballast railway fasteners, fastener inspection, deep learning, neural network, point cloud semantic segmentation.

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“…At present, high-speed railway is developing rapidly in China. By the end of October 2019, the operating mileage of China's high-speed railway has reached 30,000 kilometers, accounting for 66 percent of the total mileage of the world's high-speed railway, and it still grows at a speed of about 3,000 kilometers per year (Zhao, 2018;Antonio et al, 2010;Valikhani and Younesian, 2016;Hyoung, 2016;Xu and Zhai, 2018). A large number of high-speed railways have been built and put into operation.…”

Section: Introductionmentioning

confidence: 99%

Study on fatigue life of ballastless track fastener springs based on a fatigue test

Xiao

et al. 2020

IJSI

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Purpose Fastener technology is one of the key technologies of the ballastless track structure, and the spring strip is the key component to realize the fastener function. Based on the fatigue test of the WJ-7 type fastener of the ballastless track in China, it is concluded that the fatigue damage of an elastic strip is the main reason for the decline of service performance of the fastener. The purpose of this paper is to discuss the fatigue life of the fastener. Design/methodology/approach First, a DH3818 static strain tester is used to measure the static strain signal in the elastic strip fatigue test, and then the fatigue limit of the WJ-7 elastic strip is calculated. Finally, the fatigue life of the fastener strip is estimated. Findings The findings of the paper are as follows: first, the lowest fatigue life with a survival rate of 99 percent should be taken as a reference for the service times of WJ-7; second, the fatigue life of the modified formula found to be short under the same stress amplitude. Originality/value The fatigue test is processed by the authors and the results of elastic strip are obtained based on the test. Meanwhile, the corresponding limit value of the fatigue stress amplitude is calculated based on the tested results.

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Application of an optimal wavelet transformation for rail-fastening system identification in different preloads

Cited by 20 publications

References 19 publications

Development of a new and modification of existing elastic clips for rails fastening

Development of a new and modification of existing elastic clips for rails fastening

Real-Time Inspection System for Ballast Railway Fasteners Based on Point Cloud Deep Learning

Study on fatigue life of ballastless track fastener springs based on a fatigue test

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