A Review of The Effectiveness of Different Types of Railway Sleepers

Jabu, Mbatha Abednigo; Aa, Alugongo; Maube, O; Nz, Nkomo

doi:10.14445/22315381/ijett-v69i10p224

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…2 Furthermore, The U.S. uses 2% out of 700 million wooden crossties for replacement and for maintenance. 3 Therefore, the applications of implementing nondestructive testing and evaluation techniques (NDT/E) for condition assessment of railroad structures for early defect detection become even more crucial than ever. While saving time, money, energy, and manpower, the use of NDT/E devices allows us to detect potentially growing structural deficiencies earlier than with conventional and/or destructive methods used in the past.…”

Section: Introductionmentioning

confidence: 99%

“…The failure of a railway tie can lead to train derailments, potentially resulting in severe accidents. [3][4][5] Thus, it is recognized that railway crossties play a significant role in ensuring operational efficiency and safety. Wooden crossties have a good past of reliable performance and are effective in the railway industry.…”

Section: Introductionmentioning

confidence: 99%

“…Fungal decay is also a noticeable problem due to moisture absorption, which causes failure in wooden crossties. 3,[6][7][8] End splitting in wooden crossties is another challenge that has been identified due to aggressive traverse shear loading 3,8,9 Electromagnetic (EM) techniques are a popular, emerging, but less-researched NDT approach. The working principles of these methods stem from the EM theory and the material constitutive relationships, and they rely on the use of radar technology.…”

Section: Introductionmentioning

confidence: 99%

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Application of remote ground-penetrating radar for condition assessment of wooden crossties

Raisi,

Abazarsa,

2024

Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVIII

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Wooden crossties are an important component in railroad infrastructure as a load-bearing member connecting rail tracks and the ballast. Their internal failures (e.g., flexural cracks, delamination, and railroad crosstie-ballast failures) could be left undetected for years from routine inspection. Subsurface nondestructive testing/evaluation (NDT/E) techniques are required for effective routine inspections. In this paper, the feasibility of a 1.6 GHz ground-penetrating radar (GPR) was assessed for condition assessment of wooden crossties in both contact and remote setups. Two wooden crossties (one intact with length = 100 ", width = 7", depth = 9"), and one damaged with (length = 100", width = 6", depth = 9", with two symmetrical wedge-shaped cracks due to end-splitting on both sides) were considered. A height-adjustable Styrofoam slab was created and used for controlling the separation distance to different values (0, 1"/2.5 cm, 2.6"/6.6 cm, 4.2"/10.7 cm, and 5.8"/14.7 cm). The crossties were scanned along their length and multi-dimensional amplitude, and dielectric mapping analyses were performed to detect and map the locations of crack boundaries for each separation distance. From our results, it was found that GPR scan parameters such as dielectric analysis and A-scan comparison can detect and map defects in railroad crossties. Moreover, it was found that an increasing separation distance reduces the GPR signal amplitude as well as damage detectability for condition assessment of wooden crossties in railroad infrastructure.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of remote ground-penetrating radar for condition assessment of wooden crossties

Raisi,

Abazarsa,

2024

Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVIII

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“…A systematic problem of worn ballast are increased forces for sleepers and rail fastening systems. Sleepers, together with the rail fastening system, need to secure the rail position and to distribute loads towards the ballast bed [19]. A poor sleeper condition means that these tasks can no longer be fulfilled.…”

Section: Introductionmentioning

confidence: 99%

Quality Behaviour of Turnouts: Comparison, Problem Specification and Recommendation of Measures

Loidolt,

Marschnig,

Bürgler

et al. 2023

Applied Sciences

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For future requirements, asset management of turnouts needs to rely on data-based assessment tools. These tools must enable the quantification of quality behaviour of turnouts and identify causes of poor behaviour. In this paper, we provide a toolbox addressing these requirements. We use track geometry as the main criterion for quality behaviour in combination with additional indicators, each associated with a different component, to understand turnout performance. The toolbox is applied to five similar turnouts to compare their performance. It is revealed that one of the turnouts performs significantly worse than the others. A deeper analysis can identify worn ballast in several areas of the turnout as the cause of poor performance. Problems in the ballast bed can be attributed to worn insulated rail joints as well as to stiffness changes in the transition areas of the turnout.

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AI-based technology to prognose and diagnose complex crack characteristics of railway concrete sleepers

Kaewunruen,

Adesope,

Huang

et al. 2024

Discov Appl Sci

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Railway concrete sleepers are key safety-critical components in ballasted railway tracks. Due to frequent high-intensity impact loadings from train-track interaction over irregularities together with hostile environmental conditions, complicated characteristics of various crack patterns can incur on railway concrete sleepers, which will decrease their durability and service life overtime. Early warning of those cracks can help railway engineers to plan and schedule for renewal and maintenance timely and effectively. This study thus explores the artificial intelligence application of YOLOv5OBB (YOLOv5 with Oriented Bounding Box output) in the identification and classification of cracks in railway sleepers into three distinct types: longitudinal, transverse, and inclined, based on their specific crack angles, which have not been investigated in the past. The identification of crack angles is the novelty of this study. Recognising the various types of cracks is critical, given their varying causes and degrees of severity. Current corrective maintenance methods pose considerable safety risks to workers and exhibit low efficiency, underscoring the need for a more autonomous and efficient solution. This study marks a significant stride towards revolutionising railway maintenance, evidenced by an impressive mAP (Mean Average Precision) of 0.72 for crack detection and a 92% accuracy rate for angle detection. These promising results substantiate our study's potential to pioneer advancements in railway infrastructure maintenance.

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A Review of The Effectiveness of Different Types of Railway Sleepers

Cited by 3 publications

References 13 publications

Application of remote ground-penetrating radar for condition assessment of wooden crossties

Application of remote ground-penetrating radar for condition assessment of wooden crossties

Quality Behaviour of Turnouts: Comparison, Problem Specification and Recommendation of Measures

AI-based technology to prognose and diagnose complex crack characteristics of railway concrete sleepers

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