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The data fusion of radar and automatic dependent surveillance-broadcast(ADS-B) is the effective method to surveille the 'black flights' and flying birds. However, the tracking performance of the two sensors has large differences and is easy to be fluctuated, which will bring a decline in fusion accuracy. A data fusion method of radar and ADS-B based on track quality assessment is proposed. Firstly, the effects of local track accuracy, data update times and sensor measurement errors on local track quality on corresponding assessment factors are analyzed and quantified. And then, these assessment factors are combined to calculate the quality weighting factors of the local track, and the asynchronous track fusion processing of radar and ADS-B is completed based on the distributed fusion structure. Finally, the feasibility and effectiveness of the proposed method is verified with simulation experiment and application. The results show that the proposed fusion method can effectively improve the fusion accuracy, and the tracking errors are better than the traditional algorithms when the sensor tracking performance fluctuates.

This work aims at investigating how variations in measured stresses are affected by track conditions and, if possible, extract information on track conditions from onboard measurements. Axle bending strains measured in extensive field tests are employed to evaluate axle stress spectra. Correlation between stress spectra and parameters describing track design and condition for three sections of the Swedish mainline "Västra stambanan" have been investigated. The study shows how switches and other discontinuities in the track running surface increase the scatter of the stress spectra and increase the number of overloads. Circular and transition curves mainly increase stress amplitudes with magnitudes close to quasistatic conditions load. A decrease in track quality leads to both a shift of stress spectra towards higher values and a higher number of overloads. The influence of bridges/tunnels and decreased track stiffness were found to be difficult to distinguish from effects of curves, switches and crossings and track quality. If effects exist, they are likely to be small. Results from the study aids future track condition monitoring, maintenance planning of track and running gear, and the estimation of stress spectra for track stretches with known characteristics. [ABSTRACT FROM AUTHOR]

Locomotives and trains—as well as the tracks on which they run—emit noise and vibrations. Vibrations are transmitted through the subsurface to the nearby building, where they can be felt directly or are heard as secondary airborne noise. Recurring vibrations can impact the health of people living and working in the nearby areas. This article describes the application of under-ballast mats (UBM), an elastic spring installed under the railway ballast, as an effective measure for vibration mitigation. The particular novelty is the use of UBMs for vibration mitigation with heavy-haul trains, which have high axle loads of about 33 t. This article firstly presents the process of assessing the specific conditions of the customers site in Mexico. Secondly, it looks at the steps in choosing a suitable UBM and performing design calculations. Finally, the vibration measurements are discussed to assess the performance after UBM installation. The measurements show a vibration reduction of 15.5 dB at 63 Hz and 19.9 dB at 125 Hz. The perceptible vibration peaks inside the building were reduced by 44%. The result confirms the suitability of UBM for vibration mitigation on heavy-haul lines and thereby reducing the impact of vibrations on people's health. This consequently fosters acceptance among railroad operators and developers. [ABSTRACT FROM AUTHOR]

Today's railway transport is built upon high-performance infrastructure. Cost-effective yet sustainable infrastructure presumes tracks with a precise and durable geometry. At ballasted tracks, the geometry is created and restored through tamping machines, which position the track panel and compact the ballast beneath the sleepers. It is commonly agreed that the ballast compaction plays an important role in the long-term stability of the track. Yet, there is no method available which allows a direct correlation between the compactness of the ballast and the stability of the track geometry. Available studies either model track behaviour without considering the bedding, or analyse ballast compactness locally while disregarding its influence on the track geometry. This paper presents a new methodology which establishes a relation between these two topics—ballast compaction during tamping and subsequent track behaviour. A state-of-the-art tamping machine has been equipped with an experimental measurement setup, constantly recording relevant data during every tamping process. These data can be used to derive an indication for the achieved compaction under every sleeper. Utilising the tamping machine's internal measuring system for track geometry documentation, every tamping process (every sleeper) is assigned to the precise position along the track. The data set is merged and synchronised with regular track geometry measurements of the infrastructure manager. The result is a comprehensive data set which allows precise analyses between tamping machine measurements and track behaviour. This data set provides the foundation for future research, aiming towards a better understanding of the tamping process and its influence on the quality and durability of the established track geometry. [ABSTRACT FROM AUTHOR]

In India, Rail mode of transport serves as frequently preferrable transit systems operating with the optimal cost. Typically, the Indian Railways transport thousands of people on a day-to-day basis in addition to transporting large consignment of goods. Therefore, it is important for the trains to ensure that they run on quality tracks. At times, these tracks are challenged by the friction generated by continuous passage of trains in addition to over corrosions that occur due to their environmental imbalance. Preventive Track Maintenances (PTMs) have been recently introduced by railways for enhancing the quality of railway tracks, but on the contrary, it was failed to focus on the actual needs or emergencies of railway tracks. Moreover, none of the existing methods have been tested with real time datasets. Specifically, holding only two class labels are being considered resulting in the reduction of classification performances. But the major challenging task is that the real-time datasets fall under the category of multi-variant data. Hence, this study aims to provide a Decision Support System (DSS) that predicts the Railway Track Quality (RTQ) from the real time datasets available on the track inspection data of the Indian metro rail system. The proposed research uses clustering and classification processes for achieving Predictive Track maintenance (PTM). Furthermore, the proposed method of RPTMs includes five steps namely data collection, data transformations, clustering of data, preventive maintenances, and evaluations. The undertaken datasets are transformed into numeric formats for the creation of clusters using Kernel Mean Weight Fuzzy Local Information C Means (KMWFLICMs). The resultant clusters from the data have five major types of clusters such as Normal, Low risks, Medium, High, and Emergency Risks based on the parameters of gauge, cross level attributes, turnouts and versine of mainline. From the inferred cluster results, the dataset was further classified to choose maintenance status from four major classes namely No Actions, Fixed Maintenances, Investigate Maintenances, and Emergency Maintenance pertinent to the outcomes of FWCNNs (Fuzzy Weight Convolution Neural Networks). The proposed system was experimented on MATLAB and evaluated against various machine learning approaches. Therefore, the obtained statistical results confirmed that the proposed FWCNN model had afforded higher accuracy in predicting the maintenance interventions based on relevant risk category. [ABSTRACT FROM AUTHOR]

The positive effects of under sleeper pads have already been proven by track and laboratory tests worldwide. In Austria, padded concrete sleepers reduce track deterioration by 50 percent and have therefore been used as standard components since 2010. As the pads increase material costs, many infrastructure managers have discussed the idea of covering costs by reducing the ballast bed thickness. Technically, this approach (less ballast) is feasible, as the pads increase the track elasticity and protect the ballast. Further, pads lead to higher rail deflection and distribution of the load to more sleepers, and the stresses in sleepers are therefore relieved. Here, we compared Austrian test sections with padded and unpadded concrete sleepers and with a difference in the ballast bed thickness: standard thickness of 30 cm against 20 cm below the sleeper. Fractal analyses and standard deviations of the track's longitudinal level provided information about the sections' long-term track behaviour over 20 years. We found that the standard solution with 30 cm ballast performed better in the long term compared to 20 cm. Additionally, the test section with padded sleepers on a reduced ballast bed thickness showed a lower maintenance demand than the unpadded concrete sleeper track on a 30 cm ballast bed. [ABSTRACT FROM AUTHOR]

Today’s railway transport is built upon high-performance infrastructure. Cost-effective yet sustainable infrastructure presumes tracks with a precise and durable geometry. At ballasted tracks, the geometry is created and restored through tamping machines, which position the track panel and compact the ballast beneath the sleepers. It is commonly agreed that the ballast compaction plays an important role in the long-term stability of the track. Yet, there is no method available which allows a direct correlation between the compactness of the ballast and the stability of the track geometry. Available studies either model track behaviour without considering the bedding, or analyse ballast compactness locally while disregarding its influence on the track geometry. This paper presents a new methodology which establishes a relation between these two topics—ballast compaction during tamping and subsequent track behaviour. A state-of-the-art tamping machine has been equipped with an experimental measurement setup, constantly recording relevant data during every tamping process. These data can be used to derive an indication for the achieved compaction under every sleeper. Utilising the tamping machine’s internal measuring system for track geometry documentation, every tamping process (every sleeper) is assigned to the precise position along the track. The data set is merged and synchronised with regular track geometry measurements of the infrastructure manager. The result is a comprehensive data set which allows precise analyses between tamping machine measurements and track behaviour. This data set provides the foundation for future research, aiming towards a better understanding of the tamping process and its influence on the quality and durability of the established track geometry.

Selective Laser Melting (SLM) is a manufacturing process that involves layer-by-layer fusion of metal powder material using a laser beam. AlSi10Mg alloy, a hypoeutectic aluminum-silicon alloy, is known for its favorable mechanical properties, low density, and corrosion resistance, making it widely used in various industries. While traditionally used for casting, the unique properties of AlSi10Mg alloy have opened up opportunities for additive manufacturing, including SLM technology. This paper explores the tracks quality and preferable parameter interval for production via SLM. SLM products exhibit unique microstructures with distinct advantages and limitations. This study underscores the importance of careful parameter selection during SLM and the need for effective quality control in achieving desired mechanical properties.

The provision of safe, efficient, reliable and affordable railway transport requires the railway track infrastructure to be maintained to an appropriate condition. Given the constrained budgets under which the infrastructure is managed, maintenance needs to be predicted in advance of track failure, prioritized and identified risks and uncertainties need to be considered within the decision-making process. This paper describes a risk-informed approach that can be used to economically justify railway track infrastructure conditions by comparing on a life-cycle basis infrastructure maintenance costs, train operating costs, travel time costs, safety, social and environmental impacts. The approach represents a step-change for the railway industry as it will enable economic maintenance standards to be derived which considers the needs of the infrastructure operator, but also those of users, train operating companies and the environment. Further, the risk-informed capability of the tool enables asset managers to deal with uncertainties associated with forecasting costs and the effects of track maintenance, and unavailability of data. The Monte Carlo simulation technique and a Fuzzy reasoning approach are used to address safety data uncertainties through probabilistic risk assessment allied to expert opinion. The approach is illustrated using data from three routes on the UK mainline railway network. The results demonstrate that the approach can be used to support strategic and tactical levels of railway asset management to inform plausible design and maintenance strategies that realise the maximum benefit for the available budget. [ABSTRACT FROM AUTHOR]

The positive effects of under sleeper pads have already been proven by track and laboratory tests worldwide. In Austria, padded concrete sleepers reduce track deterioration by 50 percent and have therefore been used as standard components since 2010. As the pads increase material costs, many infrastructure managers have discussed the idea of covering costs by reducing the ballast bed thickness. Technically, this approach (less ballast) is feasible, as the pads increase the track elasticity and protect the ballast. Further, pads lead to higher rail deflection and distribution of the load to more sleepers, and the stresses in sleepers are therefore relieved. Here, we compared Austrian test sections with padded and unpadded concrete sleepers and with a difference in the ballast bed thickness: standard thickness of 30 cm against 20 cm below the sleeper. Fractal analyses and standard deviations of the track’s longitudinal level provided information about the sections’ long-term track behaviour over 20 years. We found that the standard solution with 30 cm ballast performed better in the long term compared to 20 cm. Additionally, the test section with padded sleepers on a reduced ballast bed thickness showed a lower maintenance demand than the unpadded concrete sleeper track on a 30 cm ballast bed.

Polyurethane-reinforced ballasted track (PRBT) can improve the integrity of ballasted track structures and satisfy the high-stability requirements of high-speed railways. In this study, the quality evolution law of PRBT structures after being launched into train service was analyzed, and a reference for structural optimization and maintenance operation was provided. The track geometric state of the PRBT test section of a high-speed railway was measured and monitored for nearly one year after it was launched into operation, and the ballastless track of the adjacent section was selected as a reference. The geometric states of the tracks were evaluated and compared using various parameters, including sliding standard deviation, average standard deviation, and track irregularity spectrum density. Results show that the track quality indexes of the test section, which were in operation for nearly one year, were slightly over the limit. Moreover, the fastener can be finely adjusted for the high-value index sections to further improve the ride comfort. The application effect of PRBT in the subgrade fracture zone was good, which could satisfy the requirements of high-quality transportation as well as the normal operation and maintenance of high-speed railway. [ABSTRACT FROM AUTHOR]

Adequate railway track condition is a prerequisite for safe and reliable railway operation. Many track quality indices (TQIs) have been developed with the aim of assessing the track condition holistically. These indices combine measurement signals of some or all relevant geometry parameters with different mathematical models. In this paper, a selection of important TQIs is evaluated. Using measurement data of a five kilometer track section, the indices are calculated and their properties are discussed. This study reveals that all indices exhibit drawbacks to varying degrees. As a consequence, a new index has been developed—the track quality index of Graz University of Technology (TUG_TQI). Its favorable characteristics are presented by means of the above-mentioned test section. The TUG_TQI combines all relevant track geometry parameters, which are normalized beforehand to eliminate over or underrepresentation of different parameters. Thus, the index reliably describes the overall geometrical track quality. [ABSTRACT FROM AUTHOR]

With rapid advances in sensor and condition monitoring technologies, railway infrastructure managers are turning their attention towards the promise that digital information and big data will help them understand and manage their assets more efficiently. In addition to the existing track geometry records, it is evident that track stiffness is a key physical quantity to help assess track quality and its long-term deterioration. The present paper analyses the role of track stiffness and its spatial variability through a set of computational experiments, varying other vehicle and track physical quantities such as vehicle unsprung mass, speed and track vertical irregularities. The support stiffness conditions are obtained using a sample procedure from an autoregressive integrated moving average model to generate a representative larger set of data from previously on-site measured data. A set of computational experiments is carefully designed, varying different physical variables, and a vehicle–track interaction model is used to estimate the track geometry deterioration rates. A series of log-linear regression models are then used to analyse the impact of the tested physical variables on the track deterioration. The main findings suggest that the spatial variability of track stiffness significantly contributes to the track deterioration rates, and thus it should be used in the future to better target the design and maintenance of railway track. Finally, a comparative study of some settlement models available in literature shows that they are very dependent on the test conditions under which they have been derived. [ABSTRACT FROM AUTHOR]

Adequate railway track condition is a prerequisite for safe and reliable railway operation. Many track quality indices (TQIs) have been developed with the aim of assessing the track condition holistically. These indices combine measurement signals of some or all relevant geometry parameters with different mathematical models. In this paper, a selection of important TQIs is evaluated. Using measurement data of a five kilometer track section, the indices are calculated and their properties are discussed. This study reveals that all indices exhibit drawbacks to varying degrees. As a consequence, a new index has been developed—the track quality index of Graz University of Technology (TUG_TQI). Its favorable characteristics are presented by means of the above-mentioned test section. The TUG_TQI combines all relevant track geometry parameters, which are normalized beforehand to eliminate over or underrepresentation of different parameters. Thus, the index reliably describes the overall geometrical track quality.

The cutting-edge engineering maintenance software systems of various objects are aimed at processing of geo-location data coming from the employees’ mobile devices in real time. To reduce the amount of transmitted data such systems, usually, use various filtration methods of geo-coordinates recorded directly on mobile devices.The paper identifies the reasons for errors of geo-data coming from different sources, and proposes an adaptive dynamic method to filter geo-location data. Compared with the static method previously described in the literature [1] the approach offers to align adaptively the filtering threshold with changing characteristics of coordinates from many sources of geo-location data.To evaluate the efficiency of the developed filter method have been involved about 400 thousand points, representing motion paths of different type (on foot, by car and high-speed train) and parking (indoors, outdoors, near high-rise buildings) to take data from different mobile devices. Analysis of results has shown that the benefits of the proposed method are the more precise location of long parking (up to 6 hours) and coordinates when user is in motion, the capability to provide steam-oriented filtering of data from different sources that allows to use the approach in geo-information systems, providing continuous monitoring of the location in streamoriented data processing in real time. The disadvantage is a little bit more computational complexity and increasing amount of points of the final track as compared to other filtration techniques.In general, the developed approach enables a significant quality improvement of displayed paths of moving mobile objects.

Under sleeper pads appear to be suitable measure to improve track quality as a consequence of ballast bed protection against extreme stress. The paper comprises experience of under sleeper pads applications in the Czech Republic in two test sections which were built in the Czech Republic in 2007. The tests sections were built with the aim to protect permanent way elements against extremely high dynamic loading. That is why all parameters which could be influenced by the application of USPs are assessed, especially track quality, deflection and vibration of sleepers and bearers. Some positive influence of under sleeper pads on the track quality was observed after six years of monitoring. Extension of the application of under sleeper pads is expected in the Czech Republic especially for switches and crossings.

The paper focuses on a method to synthesize the track vertical irregularities, with the possibility of application in the simulation of the dynamics in the railway vehicles. The basic elements of the method are the power spectral density of the track irregularities and the quantities describing the track geometry quality, as they have been adopted in compliance with the ORE B 176 report and UIC 518 leaflet. A major contribution of this method is the extension of the interval specific to the wavelength of the track vertical irregularities, so that this interval be representative for the frequency range of the vertical vibrations in the railway vehicle. The results of the numerical simulations of the dynamic behavior in a vehicle while running on a tangent track with vertical irregularities being synthesized as above demonstrate its efficiency.

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As one of the most essential technologies, wireless sensor networks (WSNs) integrate sensor technology, embedded computing technology, and modern network and communication technology, which have become research hotspots in recent years. The localization technique, one of the key techniques for WSN research, determines the application prospects of WSNs to a great extent. The positioning errors of wireless sensor networks are mainly caused by the non-line of sight (NLOS) propagation, occurring in complicated channel environments such as the indoor conditions. Traditional techniques such as the extended Kalman filter (EKF) perform unsatisfactorily in the case of NLOS. In contrast, the robust extended Kalman filter (REKF) acquires accurate position estimates by applying the robust techniques to the EKF in NLOS environments while losing efficiency in LOS. Therefore it is very hard to achieve high performance with a single filter in both LOS and NLOS environments. In this paper, a localization method using a robust extended Kalman filter and track-quality-based (REKF-TQ) fusion algorithm is proposed to mitigate the effect of NLOS errors. Firstly, the EKF and REKF are used in parallel to obtain the location estimates of mobile nodes. After that, we regard the position estimates as observation vectors, which can be implemented to calculate the residuals in the Kalman filter (KF) process. Then two KFs with a new observation vector and equation are used to further filter the estimates, respectively. At last, the acquired position estimates are combined by the fusion algorithm based on the track quality to get the final position vector of mobile node, which will serve as the state vector of both KFs at the next time step. Simulation results illustrate that the TQ-REKF algorithm yields better positioning accuracy than the EKF and REKF in the NLOS environment. Moreover, the proposed algorithm achieves higher accuracy than interacting multiple model algorithm (IMM) with EKF and REKF.

In the past, railway maintenance actions were usually planned based on the knowledge and experience of the infrastructure owner. The main goal was to provide a high level of safety, and there was little concern about economic and operational optimisation issues. Today, however, a deregulated competitive environment and budget limitations are forcing railway infrastructures to move from safety limits to cost-effective maintenance limits to optimise operation and maintenance procedures. By so doing, one widens the discussion to include both operational safety and cost-effectiveness for the whole railway transport system. In this study, a cost model is proposed to specify the cost-effective maintenance limits for track geometry maintenance. The proposed model considers the degradation rates of different track sections and takes into account the costs associated with inspection, tamping, delay time penalties, and risk of accidents due to poor track quality. It draws on track geometry data from the Iron Ore Line (Malmbanan) in northern Sweden, used by both passenger and freight trains, to estimate the geometrical degradation rate of each section. The methodology is based on reliability and cost analysis and facilitates the maintenance decision-making process to identify cost-effective maintenance thresholds. [ABSTRACT FROM AUTHOR]

As one of the most essential technologies, wireless sensor networks (WSNs) integrate sensor technology, embedded computing technology, and modern network and communication technology, which have become research hotspots in recent years. The localization technique, one of the key techniques for WSN research, determines the application prospects of WSNs to a great extent. The positioning errors of wireless sensor networks are mainly caused by the non-line of sight (NLOS) propagation, occurring in complicated channel environments such as the indoor conditions. Traditional techniques such as the extended Kalman filter (EKF) perform unsatisfactorily in the case of NLOS. In contrast, the robust extended Kalman filter (REKF) acquires accurate position estimates by applying the robust techniques to the EKF in NLOS environments while losing efficiency in LOS. Therefore it is very hard to achieve high performance with a single filter in both LOS and NLOS environments. In this paper, a localization method using a robust extended Kalman filter and track-quality-based (REKF-TQ) fusion algorithm is proposed to mitigate the effect of NLOS errors. Firstly, the EKF and REKF are used in parallel to obtain the location estimates of mobile nodes. After that, we regard the position estimates as observation vectors, which can be implemented to calculate the residuals in the Kalman filter (KF) process. Then two KFs with a new observation vector and equation are used to further filter the estimates, respectively. At last, the acquired position estimates are combined by the fusion algorithm based on the track quality to get the final position vector of mobile node, which will serve as the state vector of both KFs at the next time step. Simulation results illustrate that the TQ-REKF algorithm yields better positioning accuracy than the EKF and REKF in the NLOS environment. Moreover, the proposed algorithm achieves higher accuracy than interacting multiple model algorithm (IMM) with EKF and REKF. [ABSTRACT FROM AUTHOR]