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1	Maintenance scheduling for railway tracks under limited possession time Dao, Cuong, Basten, R., Hartmann, A. 06 August 2020 (has links) Yes / Maintenance planning for busy railway systems is challenging because there is growing pressure on increasing operation time, which reduces the infrastructure-accessible time for maintenance. This paper proposes an optimization model that is aimed at finding the best maintenance schedule for multiple components in a railway track to minimize the total cost in the planning horizon. One distinct and practical feature of the model is that the track accessible time for maintenance is limited. We formulate all relevant costs in the component's life cycle, including maintenance cost, fixed track-closure (possession) cost, social-economic cost related to the effects of maintenance time on the train operation, and service-life shortening cost due to the shifting of activities. Generally, it is beneficial to cluster and maintain several components in a single possession because this helps reduce the cost by occupying the track only once. However, the decision must depend on the available possession time. A sensitivity analysis is performed to highlight the effects of available possession time on the number of required possessions as well as the total cost incurred. Railway maintenance Scheduling Accessibility Track-closure
2	Non-destructive evaluation of railway trackbed ballast De Bold, Robert Paul January 2011 (has links) The “green agenda” combined with highway congestion has accelerated the demand for increased freight and passenger travel on the world’s railways. These increases have driven demand for more efficient and rapid investigation of trackbed ballast. Network Rail and other rail infrastructure operators spend significant financial sums on inspecting, tamping, adjusting, cleaning, and replacing trackbed ballast. Such maintenance is often to the detriment of normal network operation. Industry requires a method of ballast evaluation that is non-intrusive, cheap, can appraise long stretches of track in a short period of time, and give a fingerprinting result from which time-to-maintenance can be calculated and planned. Thus, the aim was to develop evaluation methods using non-destructive testing techniques. A 10-year old full-scale trackbed composed of variously fouled ballast was re-visited and used for experimentation. The condition of the ballast was calculated using the Ionescu Fouling Index. Earlier research at the University of Edinburgh enabled researchers worldwide to characterise ballast using ground penetrating radar (GPR). This research was repeated, validated and taken forward in a series of GPR experiments on the trackbed using a range of antennas from 500MHz to 2.6GHz. New "scatter" metrics were developed to determine ballast condition from the GPR waveforms. These metrics were then used to predict the Ionescu Fouling Index with a correlation coefficient greater than 0.9. One of the current approaches to evaluating the stiffness of railway ballast is to use a Falling Weight Deflectometer (FWD). The viability of using a Prima 100 mini-FWD on railways to measure stiffness was determined and deemed to be ineffective on ballast. The applicability of the impulse response technique on railways was determined. An instrumented hammer was used to excite the ballast, with a geophone measuring the response. The Frequency Response Function of this was successfully correlated with the Ionescu Fouling Index with a correlation coefficient also greater than 0.9. Finally, using GPR data and measured stiffness data collected by Banverket, Sweden, a numerical model to successfully relate radar responses to stiffness was developed. 620.110287
3	Estimating marginal costs for the Austrian railway system Munduch, Gerhard, Pfister, Alexander, Sögner, Leopold, Stiassny, Alfred January 2002 (has links) (PDF) This article presents an econometric analysis of the maintenance costs for the Austrian railway system. The data contain observations of track maintenance costs from 1998 to 2000. Our analysis identifies the cost driving factors in order to determine estimates of marginal costs, as required by the infrastructure provision principles of the European Union. The analysis identifies the variables "track length" and "transported gross-tons" as the principal cost determinants. Furthermore, we observe that total costs as well as marginal costs increase with (i) a high proportion of the track occupied by train stations, (ii) the number of switches within a track, (iii) narrow bends, and (iv) considerable slopes. Moreover average as well as marginal costs for secondary lines are significantly higher than for main lines. (author's abstract) / Series: Department of Economics Working Paper Series JEL C51, L92
4	Automating condition monitoring of vegetation on railway trackbeds and embankments Nyberg, Roger Gote January 2015 (has links) Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, aswell as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of (human) raters' visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithmwhich quantifies the vegetation cover was able to process 98% of the image data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%. Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance. A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust mo nitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed formthe foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections. 388
5	[pt] METODOLOGIAS DE GERENCIAMENTO DE PROJETOS APLICADAS À RENOVAÇÃO DE LINHA FERROVIÁRIA / [en] PROJECT MANAGEMENT METHODOLOGIES APPLIED TO RAILWAY TRACK RENEWAL RAMON FREITAS MENDES 07 October 2021 (has links) [pt] Projetos de renovação ferroviária apresentam características de projetos complexos e repetitivos, dado seu grande número de recursos e fatores de influência e atividades repetitivas para determinadas unidades de produção. Neste contexto o presente trabalho buscou aplicar conceitos relativos a gerenciamento de projetos desse nicho e desenvolver uma forma integrada de trabalhar com a incerteza nesse ambiente. Foi aplicada a metodologia de planejamento de projetos chamada Linha de Balanço, utilizando informações do projeto em fase de concepção em uma empresa ferroviária. Em sequência foi desenvolvido um protocolo para obtenção da opinião de especialistas em informações críticas para o processo e obtidas as distribuições betas que melhor representam as informações elicitadas. A partir dessas entradas, foi desenvolvido um modelo de simulação das atividades do projeto para analisar o seu funcionamento em um ambiente virtual e livre de riscos e usar como ferramenta para aprimorar seu planejamento. Como resultados são apresentadas e analisadas as principais saídas do modelo e propostas formas de controle que possam auxiliar na retroalimentação do planejamento com informações do andamento do projeto após iniciado. / [en] Project Planning known as Line of Balance (LoB) was applied, using information from a project in the conception stage of a railway company. Next, a protocol was developed to obtain expert opinion on critical information for the process and beta distributions that best represent the elicited information. From these inputs, it was developed a simulation model of the project activities in order to analyze their operation in a virtual and risk-free environment and optimize their scheduling. As a result, the main outputs of the model are presented and analyzed, in addition with the suggestion of methods of control that can assist in the feedback of the planning process with status information of the ongoing project. [pt] SIMULACAO [pt] MANUTENCAO FERROVIARIA [pt] OPINIAO DE ESPECIALISTAS [pt] LINHA DE BALANCO [pt] GERENCIAMENTO DE PROJETOS [en] SIMULATION [en] RAILWAY MAINTENANCE [en] EXPERT ELICITATION [en] LINE OF BALANCE [en] PROJECT MANAGEMENT
6	Railway Fastener Fault Detection using YOLOv5 Efraimsson, Alva, Lemón, Elin January 2022 (has links) The railway system is an important part of the sociotechnical society, as it enables efficient, reliable, and sustainable transportation of both people and goods. Despite increasing investments, the Swedish railway has encountered structural and technical problems due to worn-out infrastructure as a result of insufficient maintenance. Two important technical aspects of the rail are the stability and robustness. To prevent transversal and longitudinal deviations, the rail is attached to sleepers by fasteners. The fasteners’ conditions are therefore crucial for the stability of the track and the safeness of the railway. Automatic fastener inspections enable efficient and objective inspections which are a prerequisite for a more adequate maintenance of the railway. This master thesis aims to investigate how machine learning can be applied to the problem of automatic fastener fault detection. The master thesis includes the complete process of applying and evaluating machine learning algorithms to the given problem, including data gathering, data preprocessing, model training, and model evaluation. The chosen model was the state-of-the-art object detector YOLOv5s. To assess the model’s performance and robustness to the given problem, different settings regarding both the dataset and the model’s architecture in terms of transfer learning and hyperparameters were tested. The results indicate that YOLOv5s is an appropriate machine learning algorithm for fastener fault detection. The models that achieved the highest performance reached an mAP[0.5:0.95] above 0.744 during training and 0.692 during testing. Furthermore, several combinations of different settings had a positive effect on the different models’ performances. In conclusion, YOLOv5s is in general a suitable model for detecting fasteners. By closer analysis of the result, the models failed when both fasteners and missing fasteners were partly visible in the lower and upper parts of the image. These cases were not annotated in the dataset and therefore resulted in misclassification. In production, the cropped fasteners can be reduced by accurately synchronizing the frequency of capturing data with the distance between the sleepers, in such a way that only one sleeper and corresponding fasteners are visible per image leading to more accurate results. To conclude, machine learning can be applied as an effective and robust technique to the problem of automatic fastener fault detection. Fastener Fault Detection Object Detection YOLOv5 Machine Learning Railway Maintenance Proactive Maintenance
7	Desarrollo de técnicas avanzadas en la auscultación dinámica para la optimización del mantenimiento de vías férreas Salvador Zuriaga, Pablo 25 July 2014 (has links) El mantenimiento de la vía se ha convertido en los últimos años en un tema verdaderamente relevante para la ingeniería ferroviaria debido a la necesidad de conseguir mejores niveles de calidad a menores costes. Para ello, no hay más remedio que incorporar a las filosofías y procedimientos tradicionales del mantenimiento y la auscultación de la vía nuevas técnicas, que en muchos casos están ampliamente desarrolladas en otros campos de la ingeniería. Así, este trabajo profundiza en las técnicas de adquisición y procesado de datos para su aplicación a la auscultación de la vía. Para ello, se han realizado varias pruebas en la red de Metro de Valencia, registrando las aceleraciones producidas en las cajas de grasa durante la circulación de los vehículos por las vías. Dichas aceleraciones se han registrado y analizado de diferentes maneras, variando la frecuencia de muestreo, la frecuencia de filtrado, el emplazamiento de los acelerómetros y los diferentes parámetros que definen las representaciones tiempo-frecuencia. Los resultados muestran los valores óptimos de los parámetros que determinan la auscultación dinámica y el mejor emplazamiento para los acelerómetros. Además, mediante el análisis espectral y los diagramas tiempo-frecuencia es posible identificar y clasificar los diferentes defectos, puntos singulares y modos de vibración de la vía. De este modo, pueden sentarse las bases para la aplicación de técnicas de procesado digital de imágenes al mantenimiento de la vía. / Salvador Zuriaga, P. (2014). Desarrollo de técnicas avanzadas en la auscultación dinámica para la optimización del mantenimiento de vías férreas [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39003 Mantenimiento ferroviario Auscultación de vía Aceleraciones en caja de grasa Señales digitales Representación tiempo-frecuencia Railway maintenance Track surveying Axlebox acceleration Digital signals Time-frequency representatio TEORIA DE LA SEÑAL Y COMUNICACIONES
8	Railway curve squeal: Statistical analysis of train speed impact on squeal noise Asplund, Ruben January 2024 (has links) No description available. ml operation maintenance railway maintenance railway curve machine learning statistics railway train passenger train x60 squeal noise curve squeal squealing noise squeal wheel squeal squealing programming system development computer engineering data visualization data preprocessing industrial computer systems matlab python vibration vibrations vibration signals signals and systems filtering signal processing computer systems communication system infrastructure technology infrastructure track t-test z-test random forest xgboost feature importance speed detection band-pass filter script yaw angle angle of attack decision tree gbdt filter temperature humidity dew point curve radius cloud accelerometers sensors track rail statistical analysis acoustics sound ai artificial intelligence gradient boosting decision trees curve software development drift underhåll järnvägsunderhåll järnvägskurva maskininlärning statistik järnväg tåg x60 skrikljud snäva kurvor kurvradie kurvskrik hjulskrik programmering systemutveckling datateknik data industriella datorsystem matlab python vibration signaler vibrations signaler signaler och system filtrering signalbehandling datorsystem kommunikationssystem infrastrukturteknik infrastruktur spår t-test z-test random forest Södertälje band-pass filter hastighets detektion attackvinkeln anfallsvinkel IMx SKF temperatur fuktighet daggpunkt accelerometer järnvägskurvskrik tåg hastighetens statistisk analys akustik ljud ai kurva kurvor mjukvaruutveckling artificiell intelligens Infrastructure Engineering Infrastrukturteknik Signal Processing Signalbehandling Communication Systems Kommunikationssystem Computer Systems Datorsystem

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