Condition Of Railway Infrastructure Research Articles

Identification of optimal accelerometer placement on trains for railway switch wear monitoring via multibody simulation

Accelerometers play a crucial role in the railway industry, especially in track monitoring. Traditionally, they are placed on the railway tracks or often on bridges to monitor the health and condition of the infrastructure. Recently, there has been an increased focus on using regular trains to monitor the condition of railway infrastructure. Often, the sensors are placed based on certain assumptions without much scientific evidence or support. This paper utilizes the multibody simulation software GENSYS to identify the optimal placement of accelerometers on a passenger train for monitoring railway switch wear. Switch wear profiles were generated systematically and used as input for the simulations, studying acceleration at a total of 93 locations distributed among the wheelsets, bogies, and carbody. Based on both time and frequency domain analyses, optimal sensor locations were identified, generally close to the first bogie or wheelset at the leading carbody. Accelerations generated by the wheelset passing the switch can also be captured in the carbody, but it is important to note that these are several orders lower in magnitude compared to the acceleration on the wheelset. If accelerometers are to be placed in the carbody, correct sensitivity must be chosen, and a high-pass filter should be applied to capture the acceleration signals associated with switch wear. The study confirms that there is a direct correlation between the depth of switch wear and the magnitude of the acceleration. It remains effective even under various curve radii and train speeds.

Improvement of Machine Vision Video Signal Processing Algorithm for Higher Accuracy in Extended Object Speed Measurements

Machine vision systems are widely used for monitoring of the railway infrastructure condition. High reliability of machine vision systems allows using them not only for video recording but also for automation of technological processes. One of the important tasks in the process automation is measurement of an extended object speed (rail-road cars, electric locomotives and rolling stock). Some systems have a requirement to estimate speed in real time (braking of cars at a shunting yard). In this case the speed is calculated by two adjacent frames to ensure the minimum delay for measurement. However, the image of an extended object can be uninformative (image fragments are uniform in brightness), the weather can cause interference. It leads to high speed estimation error. This article describes the improvement for the existing real-time algorithm which allows for higher accuracy in speed measurements. The improvement implies selection of an informative image area corresponding to an extended object. A comparative analysis of the existing and improved algorithm showed a significant reduction in the estimation error in speed measurements.

Risk Assessment of Using a Contactless Method for Railway Surface Inspection as Alternative for Staff Inspection of Infrastructure

Railway infrastructure managers are obliged to check technical condition of infrastructure in order to maintain safe traffic. Usually this is done using conventional methods and tools or directly through the inspections made by the technical staff. Technological development which is currently being experienced indicates the availability of new measurement methods that can be used to monitor the condition of railway infrastructure. However, the introduction of new methods for monitoring the infrastructure is usually a change affecting safety, which requires an assessment of the significance of the change for the maintenance of the required level of railway traffic safety. The authors assessed the significance of the change in the method of infrastructure monitoring and related risk assessment as a result of the use of the contactless method of checking the railway surface as an alternative method to staff inspections. Additional control measures or preventive measures for potential threats have also been indicated.

Machine learning approach for wheel flat detection of railway train wheels

Nowadays, monitoring the condition of railway infrastructure has become necessary and led railway companies to take advantage of artificial intelligence (AI) technologies to improve safety and reduce operating costs. This paper aims to present an unsupervised methodology to detect railway wheel flats. The automatic damage detection algorithm is based on the acceleration evaluated on the rails for the passage of traffic loads. The results of this research study show that only one sensor is enough to detect wheel flat automatically, which enables the development of a low-cost monitoring system that can be easily implemented in actual operating conditions.

EFFECTIVE RAILROAD FRAGMENTATION AND INFRASTRUCTURE RECOGNITION BASED ON DENSE LIDAR POINT CLOUDS

Abstract. Monitoring the condition of railway infrastructure is essential for maintaining safety standards and preventing accidents. The regular inspections required for this task are still typically carried out in many countries with costly and time-consuming on-site human inspections. LiDAR point clouds collected by mobile laser scanning (MLS) already proved to be suitable for recognizing important railroad infrastructure elements, such as cables and the rail tracks. However, the computational requirement for processing large data sets like these often extremely dense point clouds is still a challenge nowadays, resulting in longer execution time than practically applicable. In our research, we have implemented and comparatively analyzed railroad fragmentation and object segmentation algorithms with the focus on robustness and high effectiveness: prioritizing automation and prerequisite reduction (e.g. the spatial relationship between the position of the railway track and the overhead contact line). These aspects also enable the easy parallelization for the processing of larger railroad segments.

Automatic Detection of Track Length Defects

Abstract Ensuring the safety of railway transport operation requires constant monitoring of the technical condition of individual elements of railway infrastructure. The necessary activities that contribute to maintaining good operational condition of the railway transport line also include the diagnostics of track length. Diagnostics of railway tracks is most often performed by means of regular visual inspection (in the conditions of the infrastructure manager – ŽSR). The objective of the article is to provide information on the application of a new approach to diagnostics of the technical condition of railway infrastructure. The new approach to defect identification on railway infrastructure uses non-invasive diagnostic methods based on the latest knowledge in the field of information and communication technologies. These facts resulted in investigating the possibilities of automatic detection of the technical condition of the track length using neural networks. The article is part of the following scientific research task: ‘Research into new knowledge and observational experience of a new generation of diagnostic systems in industrial production and transport industry – research into the physical nature of an automated track length video inspection system’, supported by the Ministry of Education, Science, Research and Sport of the Slovak Republic.

A Literature Review of WSN based Railway Infrastructure Condition and Traffic Monitoring and Controlling Systems

A Literature Review of WSN based Railway Infrastructure Condition and Traffic Monitoring and Controlling Systems

A Hybrid Multi-Criteria Decision Making Model for Defect-Based Condition Assessment of Railway Infrastructure

The condition of railway infrastructure, such as rails, ballasts and sleepers, should always be monitored and analyzed to ensure ride safety and quality for both passengers and freight. It is hard to assess the condition of railway infrastructure due to the existence of various components. The existing condition assessment models are mostly limited to only assess track geometry conditions and structural condition of the railway infrastructure. Therefore, the present research develops a defect-based structural and geometrical condition model of railway infrastructure. The defects of each component are identified and examined through literature and experts in the field. Two main inputs are used to develop the model: (1) the relative weight of importance for components, defects and their categories and (2) defects severities. To obtain the relative weights, the analytic network process (ANP) technique is adopted. Fuzzy logic is used to unify all the different defect criteria and to interpret the linguistic condition assessment grading scale to a numerical score. Hence, the technique for order preference by similarity to ideal Solution (TOPSIS) is used to integrate both weights and severities to determine the railway infrastructure condition. The developed model gives a detailed condition of the railway infrastructure by representing a three-level condition state, for defect categories, components and an overall railway infrastructure. The developed model is implemented to five case studies from Ontario, Canada. The developed model is validated by comparing its results with the real case studies results, which shows similar results, indicating the robustness of the developed model. This model helps in minimizing the inaccuracy of railway condition assessment through the application of severity, uncertainty mitigation and robust aggregation

Analysis of Passenger Commuter Train Services Surabaya – Sidoarjo

This study is intended to measure the level of satisfaction and expectations of service users on the Surabaya - Sidoarjo Commuter Train service with the benchmarks used, namely the Minimum Service Standard Ministerial Transportation Degree number PM 65 of 2019. The study was conducted by conducting a field survey of the condition of railway infrastructure. The survey stated preference for the Surabaya - Sidorajo commuter train users through a questionnaire. The method to be used is Importance Performance Analysis (IPA). The results of the analysis using the IPA method are expected to identify the level of satisfaction and expectations of service users on the Surabaya - Sidoarjo Commuter train service and will be able to provide service improvement suggestions to PT. Kereta Api Indonesia (KAI) as a commuter transport operator in the Gerbang Kertasusila area. In this case the research is in line with the Technology Readiness Level (TKT) point 9 which has criteria, namely the real application (application) of technology in its final form and under the intended (planned) conditions as in operational testing and evaluation. In general, this is the last part / aspect of the bug fixing effort in actual system development. Examples include for example the use of the system in operational mission conditions.

Optical Fibres for Condition Monitoring of Railway Infrastructure—Encouraging Data Source or Errant Effort?

The condition of railway infrastructure is currently assessed by track recording cars, wayside equipment, onboard monitoring techniques and visual inspections. These data sources deliver valuable information for infrastructure managers on the asset’s condition but are mostly carried out in time-based intervals. This paper examines the potential of fibre optic cables, which are already installed in cable troughs alongside railway tracks, to monitor railway infrastructure conditions. The sensing technique, known as distributed acoustic/vibration sensing (DAS/DVS), relies on the effect of Rayleigh scattering and transforms the optical fibre into an array of “virtual microphones” in the thousands. This sensing method has the ability to be used over long distances and thus provide information about the events taking place in the proximity of the monitored asset in real-time. This study outlines the potential of DAS for the identification of different track conditions and isolated track defects. The results are linked to asset data of the infrastructure manager to identify the root cause of the detected signal anomalies and pattern. A methodology such as this allows for condition-based and component-specific maintenance planning and execution and avoids the installation of additional sensors. DAS can pave the way toward a permanent and holistic assessment of railway tracks.

Actual utilisation of maximum line speed - Polish and Ukrainian experience

The overall condition of the Polish railway infrastructure has been recently improved. The condition of railway infrastructure and the level of its technical equipment are reflected in the maximum train speeds allowed on particular sections of railway lines. The analysis covers the utilisation of the maximum line speed by the long-distance trains in Poland in the 2018/2019 timetable. The database has been prepared, covering start-to-stop runs of Express Intercity Premium (EIP) trains). The analysis shows that typical value of speed utilisation ratio for EIP trains operated with ED250 EMU is approximately 0.82-0.83. The correlation ratio between the average maximum line speed and the train commercial (startto-stop) speed is rather good. The data from the Polish railways have been compared with Ukrainian ones. The results of the research show clearly, that the selection of passenger rolling stock for particular route can have significant impact on its day-to-day operation.

Method of railway line audit in terms of the condition of railway infrastructure

The most important problems concerning the organization of railway traffic is continuous provision and systematic improvement the level of safety of services provided by railway transport enterprises. This safety results from many factors – including condition of the infrastructure, state of superstructure or the way of conducting railway traffic. This article covers railway infrastructure within its scope. In this regard include, among others take appropriate actions to monitor its condition. One of the methods may be the audit of the railway line in terms of infrastructure condition. The purpose of the article is to present the method of railway line audit in the area of infrastructure. The concept of railway line audit from the point of view of infrastructure status was defined in the paper. The audit method was presented along with the identification of problems that may occur as a result of the audit and suggestions for solutions to these problems. The presented method was verified for a selected railway line in Poland railway line No. 12 Skierniewice – Łuków. The possibilities of improving the condition of this line were proposed together with the estimation of the amount of expenditures necessary to make therefore and time gains achieved through improvement.

The influence of the projects led by PKP Polskie Linie Kolejowe S.A. that are included in the national railway program until the year 2023 on the transport infrastructurein Poland

The National Railway Programme (NRP) until the year 2023 assumes the execution of investments worth PLN 66 billion in total, and it is assumed that 220 projects will be completed within the scope of these investments. The projects include work on 9,000 km of tracks. The rehabilitation work will enable PLK to create better connections between various voivodships and regions, along with faster and more comfortable travelling within agglomerations. The improvement of the railway infrastructure condition will ensure higher comfort of customer service at railway stations and train stops. Thanks to the modernization of the tracks, it will also be possible to limit the harmful impact of the infrastructure on the environment and to ensure a higher level of safety. The authors discuss the current stage of NRP and present the most important projects to be done as part of this enterprise. Additionally, the way in which similar investments were accomplished by PKP Polskie Linie Kolejowe S.A. as part of earlier initiatives was analysed. The authors discuss the influence of the execution of these projects on the global transport infrastructure in Poland.

A New Methodology for Assessment of Railway Infrastructure Condition

The majority of the railway infrastructure in Croatia is over one hundred years old. In common with many other EU member states, a lack of investment in maintenance and renewal projects in over the last 30 years has resulted in generally poor track conditions. As a result traffic speeds are often restricted with some important operating with speeds limited up to only 20km/h.This work describes a joint initiative between researchers and infrastructure managers (IM's) to revitalize risk assessment associated on ageing infrastructure, with the aim of increasing safety and reducing the costs of remediation. In order to achieve this, a new methodology for assessment of railway condition is developed. In this paper the use of phased investigation involving electromagnetic ground penetrating radar (GPR), seismic refraction, drones and in-situ geotechnical investigation to determine parameters affecting the track performance are presented. The features considered include ballast fouling, anomalies in railway embankments (including burrows), boundaries between layers, substructure condition, the water content of the soil, the slope geometry and drainage condition. The work constitutes the first step in a Decision Support Framework for IM's, being developed through the Horizon 2020 Project Destination Rail which will help to identify potential hot-spots on the rail network. By early identification of these locations low-cost remediation can be applied and thus costs can be reduced and failures avoided.In this paper the use of custom-made cart which allows acquisition of data along the three axes of railway rail cross-section and an innovative interpretation methodology is described. Based on GPR data, visual assessment and on photogrammetry images made using an unmanned aerial vehicle (UAV), a categorization of critical infrastructure data is collected to a quantitative risk assessment procedure. This provides a basis for preliminary design solutions as well as for establishment of detailed programme of investigation works and monitoring on sections where it was shown as necessary. A next step is implementation of this methodology into geographic information system (GIS) which would additionally fulfil the needs of decision-makers in railway sector.

Failure analysis and diagnostics for railway trackside equipment

In the future, the dependability of the railway system must be improved to accommodate higher train speeds, greater axle loads, and increased service frequency. One way of increasing the dependability is through improved maintenance and failure management. The collection and processing of information to ascertain the condition of railway infrastructure allows remedial action to be undertaken in a more efficient manner. This paper describes the development of a condition monitoring system based on pattern recognition for detecting and diagnosing point machine failures. It is shown that initially, when data is acquired from a point machine, it is difficult to detect faults. However, upon the application of a moving average filter, fault conditions can be more straightforwardly detected and diagnosed. Using data collected from a set of points under test it is shown that all potentially tested failure modes can be successfully detected and diagnosed.