Railway track support condition assessment—Initial developments on a vehicle-based monitoring solution through modal analysis

Nowadays, there are multiple initiatives showing a renewed interest on railway transport of goods and passengers around the world. Thus, an efficient management of railway infrastructures, both at the operational level and in terms of economic profitability, is not only desirable but also corresponds to an area of ongoing research. In order to contribute to these efforts, an alternative and novel methodology to evaluate railway track support conditions is presented here, based on modal analysis of the characteristic frequencies of the multi-element system composed by a railway infrastructure and an instrumented vehicle moving over it. This methodology belongs to the group of vibration-based structural damage identification methods, and is focused on observing the characteristic frequencies of this multi-element system, which can be correlated with changes in the physical properties of the railway infrastructure under analysis. An important feature of the proposed methodology is that it should enable the collection of information regarding the conditions of the substructure of a railway infrastructure. By performing this assessment of a railway infrastructure over its length, and over time by comparing different rides over the same railway stretch, important information can be gathered regarding the support conditions of the track. This paper presents a complete description on the current stage of development of the proposed methodology, along with the theoretical model that serves as the basis to interpret the collected data. Preliminary verification of this methodology is performed through the analysis of two case studies regarding the passage of an instrumented vehicle over two underpasses. The results obtained so far show that the proposed methodology can provide relevant information regarding the support conditions of railway tracks.

Effects of the highway live load on the additional forces of the continuously welded rails of a long-span suspension bridge

High-speed running trains have higher regularity requirements for rail tracks. The track-bridge interaction of long-span bridges for high-speed railways has become a key factor for engineers and researchers in the last decade. However, studies on the track-bridge interaction of long-span bridges are rare because the bridges constructed for high-speed railways are mainly short- or moderate-span bridges, and the effects of the highway live load on the additional forces of continuously welded rails (CWRs) have not been reported. In the present study, the effects of the highway live load on the additional forces of a CWR of a long-span suspension bridge are investigated through numerical simulations. A track-bridge spatial analysis model was established using the principle of the double-layer spring model and the bilinear resistance model. The additional stress and displacement of the rail are calculated, and the effects of the highway live load are analyzed and compared with those without a highway live load. The results show that the highway live load has an obvious effect on the additional forces of a CWR. Under a temperature force, the highway live load increases the maximum tensile stress and compressive stress by 10 and 13%, respectively. Under a bending force, the highway live load increases the maximum compressive rail stress and maximum displacement by 50 and 54%, respectively. Under a rail breaking force, when the highway live load is taken into consideration, the rail displacement at both sides of the broken rail varies by 50 and 42%, respectively. The highway live load must be taken into consideration when calculating the additional forces of rails on highway-railway long-span bridges.

A hybrid fault diagnosis scheme for railway point machines by motor current signal analysis

Proper analysis of point machine current signal provides pervasive information of health status of their internal components. Point machines are subjected to several failure modes during their operation. “Gearbox,” “ball bearing,” “lead screw,” and “sliding chair” faults are among common mechanical failure modes. In this article, a two-stage prediction innovative process is proposed using Fault Detection based Decision Tree strategy (FDDT) where the healthy and faulty modes are first determined, followed by classifying the types of mechanical faults based on Parallel Neural Network Architecture and Fuzzy System (PNNFS). To differentiate between faulty and healthy point machines, some relevant features are extracted from the motors’ current signals which are used as input data for the proposed FDDT_PNNFS method. Feature selection has been performed using the ReliefF to select the dominant predictors in the point machine. Firstly, the Decision Tree (DT) algorithm is used to obtain a classifier model based on the offline training method for fault detection. The performance of DT is compared with the support vector machine algorithm. In the second stage, faulty data is fed to a bank of Neural Networks, designed in Parallel Neural Network Architecture (PNNA), which is used for identifying the type of failures. Each Neural Network Algorithm (NNA) is responsible for detecting only one type of failure and assessment of the NNA outputs shows the final failure of the point machine. If there is a discrepancy between the outputs of the NNAs, fuzzy logic plays the role of modifier and judges among outputs of NNAs and determines the more probable fault type.

Effect of polygon-shaped wheels on fatigue fracture of fastener clips in high-speed railway lines

This paper studies the effect of wheel polygonalization and material properties on the fatigue failure of fastener clips in high-speed railway lines and puts forward the corresponding inhibition measures. Vibration frequencies excited by 24th-order wheel out-of-roundness (OOR) were analysed by on-site tests of the axle box vertical vibration acceleration. A finite element modelling method of polygon-shaped wheels was proposed, which was verified by comparing the field measurement with the dynamic simulation. The dynamic response of the fastener clip was simulated by using a rigid–flexible coupled model of the wheelset-track system. The effect of amplitudes as well as typical wavelengths of wheel OOR on the fracture of the clip was analysed based on the Miner fatigue damage accumulation ruler. The results show that when the wheelset ran at 237 km/h on the track, the 24th-order wheel OOR had no obvious effect on the Mises equivalent stress of the clip. When the amplitude of the 24th-order wheel OOR reached 0.225 mm and above, excited vibrations of about 1172 Hz were transmitted from the wheelset-rail system to the fastener systems, thus reducing the safe operating life of the clips. This phenomenon can be inhibited by setting a reasonable amplitude threshold for wheel re-profiling. Wheel eccentric wear (first-order OOR) and 12th-order OOR had lesser effects on the fatigue failure of the clip. The decrease of Poisson’s ratio or the increase of Young’s modulus of the material could cause the maximum Mises equivalent stress at the clip to increase, which might induce cracks, thus leading to the fracture of the clip. Therefore, during the production process, the Poisson’s ratio and Young’s modulus of fastener clips should be strictly controlled to ensure that they are within the permitted range.

Efficient time–frequency approach for prediction of subway train-induced tunnel and ground vibrations

In this paper, an efficient time–frequency approach is presented for the prediction of subway train-induced tunnel and ground vibrations. The proposed approach involves two steps. In the first step, a time domain simulation of the vehicle–track subsystem is used to determine the track–tunnel interaction forces and, in the second step, the resulting forces are then applied to a 2.5 D FEM–PML model of the tunnel–soil system. There are two main aspects to the novelty and contribution of this work: First, the errors of the linearized Hertzian wheel–rail contact models in the calculation of the track–tunnel interaction forces are quantified by a comparison with the nonlinear Hertzian contact model. The results show that the relative errors are less than 2%. Second, an efficient time–frequency analysis framework is proposed, including the use of a strongly coupled model in the time domain solution and a 2.5 D FEM–PML model in the frequency–wavenumber domain solution. Finally, the accuracy and efficiency of the proposed approach are verified by comparison with a time-dependent 3 D approach, where three types of soil, i.e. soft, medium, and hard, are considered.

Design optimization of hopper cars employing functionally graded honeycomb sandwich panels

In this paper, a novel multiscale and multi-stage structural design optimization procedure is developed for the weight minimization of hopper cars. The procedure is tested under various loading conditions according to guidelines established by regulatory bodies, as well as a novel load case that considers fluid-structure interaction by means of explicit finite elements employing Smoothed Particle Hydrodynamics. The first stage in the design procedure involves topology optimization whereby optimal beam locations are determined within the design space of the hopper car wall structure. This is followed by cross-sectional sizing of the frame to concentrate mass in critical regions of the hopper car. In the second stage, hexagonal honeycomb sandwich panels are considered in lower load regions, and are optimized by means of Multiscale Design Optimization (MSDO). The MSDO drew upon the Kreisselmeier–Steinhausser equations to calculate a penalized cost function for the mass and compliance of a hopper car Finite Element Model (FEM) at the mesoscale. For each iteration in the MSDO, the FEM was updated with homogenized sandwich composite properties according to four design variables of interest at the microscale. A cost penalty is summed with the base cost by comparing results of the FEM with the imposed constraints. Efficacy of the novel design methodology is compared according to a baseline design employing conventional materials. By invoking the proposed methodology in a case study, it is demonstrated that a mass savings as high as 16.36% can be yielded for a single hopper car, which translates into a reduction in greenhouse gas emissions of 13.09% per car based on available literature.

Design method of worn rail grinding profile based on Frechet distance method

Due to the large volume and high running density of railway freight lines, rail deterioration occur frequently. Thus, it is necessary to grind the rail in time to improve the wheel-rail relationship. The profile data of the worn rail were measured at different measuring points in a section, and the Frechet distance method was adopted to analyze the data. The representative profile reflecting the overall condition of rail wear in this section is obtained. Combined with NURBS curve theory, a fitting algorithm in which the rail profile with certain discrete points was established. Taking the reduction of the amount of grinding material removed as the objective function, setting wheel-rail matching characteristics, and the reduction of rail wear as the constraint conditions, a calculation model for rail grinding profile was established. The dynamic characteristics of standard profile CN75 and g grinding profile OP75 were analyzed by the vehicle track dynamics model. The results showed that compared with the standard profile CN75, the amount of grinding material removed of the grinding profile OP75 is reduced by 44.7%, and the height reduction of the rail top is reduced by 0.39 mm. After [Formula: see text] km of running, the wear amounts of grinding profile OP75 is about 36.1%–36.5% less than that of standard profile CN75.In the small curve section, the derailment coefficient of grinding profile OP75 is reduced by 11.7% compared with that of standard profile CN75. The dynamic performance is improved. The grinding target profile has better dynamic characteristics and is beneficial to reduce wheel-rail wear.

An efficient physical-based method for predicting the long-term evolution of vertical railway track geometries

The dynamic wheel-rail contact forces resulting from the interaction between vehicle and track are responsible for the local track settlement. If these local settlements vary along the track, geometric irregularities develop further amplifying the dynamic loading of the track caused by the interaction between the vehicle and track. In this work, an efficient vehicle-track interaction (VTI) model is presented for predicting the long-term evolution of vertical track settlement during operation. The VTI model has two interacting components – vehicle and track. The vehicle model describes the vertical dynamics of an 8th of a car. The track model considers an elastic rail on discrete (sleeper) supports. Each sleeper location can have its own stiffness, relative height and settlement characteristics. Dependent on the distribution of stiffness and settlement behaviour along the track together with the initial track geometry, each sleeper settles dependent on the number of load cycles (vehicle passes). The track model is initialized with measured vertical track geometry data and static track deflection data at the beginning (day 0) for two types of track sections in the field, a track section where concrete sleepers with Under Sleeper Pads (USP) are used and a track section where only concrete sleepers are used. Using the same settlement model parameters (constant along the track) for the two tracks, the physical-based VTI model can predict the different track geometry quality evolution for both tracks over 350 days. Finally, the VTI model is used to assess the track geometry deterioration when the track/vehicle properties are changed. The prediction strength of the fast VTI model based on the physical understanding can assist in designing and optimizing tracks and in supporting of maintenance activities.

Sensitivity analysis for operating loads in fatigue design of railway vehicles

For the reliable simulation-based fatigue design of railway vehicles, the operation conditions and resulting loads over the lifespan of the vehicle have to be considered. After introducing the relevant fatigue loads on the vehicle and the methods for modelling the fatigue damage, this work aims at analysing the influence of the operating conditions and loads on the damage using sensitivity analysis. Two approaches are studied: the variance-based sensitivity analysis of the loads acting on the car body and the influence of different operating conditions using statistical values per track section. The loads are obtained from multi-body simulations and the damage is estimated using both physical FE-models and meta-models. The performances of linear regression models and polynomial chaos models are evaluated. The proposed sensitivity analysis is applied to the highspeed train being developed in the Next Generation Train (NGT) project at DLR and will serve as a basis for the virtual design and reliability analysis.