Degradation Prediction of Rail Tracks: A Review of the Existing Literature

Elkhoury, N.; Hitihamillage, L.; Moridpour, Sara; Robert, Dilan

doi:10.2174/1874447801812010088

Cited by 33 publications

(34 citation statements)

References 37 publications

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“…Additionally, in empirical modeling, a modern approach called Artificial Intelligence -AI (i.e., Artificial Neural Networks -ANNs and Neuro-Fuzzy Logic -NFL, a combination between ANN and fuzzy logic) is increasingly used among scientists, as discussed by Elkhoury et al (2018). These methods are recognized to have high predictive accuracy.…”

Section: Introductionmentioning

confidence: 99%

Methods to Monitor and Evaluate the Deterioration of Track and Its Components in a Railway In-Service: A Systemic Review

Melo

Kaewunruen

Papaelias

et al. 2020

Front. Built Environ.

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When planning a new track or improving a track that is currently in-service, it is important to predict the probable rate of track deterioration as a function of the variables related to the train and its periodicity. This literature review reveals that there are currently no track deterioration methods available analyze the condition of a railway track. A prediction of deterioration requires accurate quantification of each track component and track geometry behavior and a better knowledge of interactions between components and geometry. This extended survey found more than 100 methods (or studies) related to track deterioration, including other literature reviews, but very few of these methods work when several track deterioration issues occur. This paper aims to build upon these, adopting a methodology for a systematic critical literature review that identifies, evaluates, and classifies these primary studies to predict the track deterioration according to criteria of assessment. Finally, it establishes the gaps and the challenges that will need to be overcome in future research.

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Section: Introductionmentioning

confidence: 99%

Methods to Monitor and Evaluate the Deterioration of Track and Its Components in a Railway In-Service: A Systemic Review

Melo

Kaewunruen

Papaelias

et al. 2020

Front. Built Environ.

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“…Sol-Sánchez [16] conducted a literature review focusing on the effectiveness of the major conventional techniques and materials for track design and maintenance, as well as innovative solutions being developed to reduce track degradation. Other survey articles on the application of data analytics in a specific aspect of railway track can be found in the literature [17][18][19][20]. To the best of the authors' knowledge, the literature in this field suffers from the lack of a holistic survey covering all of the data-driven solutions in both railway track defects detection, prediction, and maintenance decision-making.…”

Section: High Noisementioning

confidence: 99%

“…Table 3 discusses the advantages and disadvantages of classical data-driven models and how they are employed in the predictive maintenance of railway track. More details about these models can be found in Reference [14,18,33]. 3.5.…”

Section: Classical Data-driven Models In Railway Predictive Maintenancementioning

confidence: 99%

Systematic Literature Review on Data-Driven Models for Predictive Maintenance of Railway Track: Implications in Geotechnical Engineering

et al. 2020

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Conventional planning of maintenance and renewal work for railway track is based on heuristics and simple scheduling. The railway industry is now collecting a large amount of data with the fast-paced development of sensor technologies. These data sets carry information about the conditions of various components in railway track. Since just before the beginning of the 21st century, data-driven models have been used in the predictive maintenance of railway track. This study presents a systematic literature review of data-driven models applied in the predictive maintenance of railway track. A taxonomy to classify the existing literature based on types of models and types of applications is provided. It is found that applying the deep learning methods, unsupervised methods, and ensemble methods are the new trends for predictive maintenance of railway track. Rail geometry irregularity, rail head defect, and missing rail components detection were the top three most commonly considered issues within the application of data-driven models. Prediction of rail breaks has received increasing attention in the last four years. Among these data-driven model applications, the collected data types are the most critical factors which affect selecting suitable models. Finally, this study discusses upcoming challenges in the predictive maintenance of railway track.

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“…Na revisão bibliométrica, procurou-se analisar e destacar os principais modelos utilizados na literatura internacional. Dentre os modelos destacados por (ELKHOURY et al 2018), notou-se a utilização dos modelos determinísticos, probabilísticos (Bayesiano e Markov) e estocásticos (Figura 1).…”

Section: Modelo De Degradação Da Viaunclassified

Modelos de degradação no pavimento ferroviário a partir de uma revisão sistemática

Fonte

Donato

2020

RICA

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Um dos principais fatores que acelera a degradação do pavimento ferroviário nos últimos anos é o aumento da movimentação de cargas, ocasionado pelas novas demandas exigidas pelo mercado nacional e internacional. Consequentemente, as intervenções de manutenção para correção da geometria da via são desafiadas, exigindo novas técnicas capazes de proporcionar reduções de custos em manutenção e renovação. As empresas ferroviárias no Brasil apresentam valores elevados em gastos com intervenções de manutenções ao longo do trecho concessionado, chegando de 12,4% na superestrutura e 18,9% no material rodante. Portanto, o objetivo deste trabalho está voltado em identificar os artigos que apresentem o uso dos modelos de degradação no pavimento ferroviário na literatura científica utilizando a técnica de análise bibliométrica e revisão sistemática, sendo possível verificar o tipo de degradação (geométrico ou estrutural), parâmetros geométricos e os resultados obtidos em cada pesquisa. Observou-se que os modelos de degradação proporcionam a identificação do momento de exigência para aplicação intervenções de manutenção e renovação da via, utilizando as normas técnicas internacionais de índices de qualidade de via ou estado dos componentes ferroviário.

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Degradation Prediction of Rail Tracks: A Review of the Existing Literature

Cited by 33 publications

References 37 publications

Methods to Monitor and Evaluate the Deterioration of Track and Its Components in a Railway In-Service: A Systemic Review

Methods to Monitor and Evaluate the Deterioration of Track and Its Components in a Railway In-Service: A Systemic Review

Systematic Literature Review on Data-Driven Models for Predictive Maintenance of Railway Track: Implications in Geotechnical Engineering

Modelos de degradação no pavimento ferroviário a partir de uma revisão sistemática

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