Helsingborg, Sweden
Helsingborg, Sweden

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Trehag J.,Interfleet Technology AB | Handel P.,KTH Royal Institute of Technology | Ogren M.,Interfleet Technology AB
IEEE Transactions on Instrumentation and Measurement | Year: 2010

When performing tests on a rail vehicle, it is often necessary to categorize the target data according to the characteristics of the railroad plane geometry. In this paper, a method to classify and identify the railroad plane geometry is considered, employing railroad curvature readings formed by onboard sensor data. The aim is to extract the characteristics of the railroad track to identify and categorize different segments of the track. The railroad curvature is modeled as a first-order piecewise linear polynomial representing sections of straight tracks, transition curves, and circular curves along the railroad. The sensor data are preprocessed in a Global Positioning System-aided dead reckoning navigation system to debias the curvature readings. Subsequently, the noise in the curvature readings is suppressed by nonlinear filtering techniques. Furthermore, the observed curvatures are processed with a linear filter by minimizing a discounted least-squares criterion, yielding the final estimate of the railroad curvature and its rate of change, which further on are utilized to form a detector where the position of a trend change in curvature measurements is located. The result from the presented method has been compared against database values on plane geometry from Banverkets Information Systema system belonging to the Swedish Rail Administration office. The reported accuracy of detecting a change in the railroad curvature has varied in the range of ±7 m in difference between the position entries in the curvature database and the positions found with the developed method. © 2009 IEEE.


Gullers P.,Interfleet Technology AB | Dreik P.,Dreik Ingenjorskonst AB | Nielsen J.C.O.,Chalmers University of Technology | Ekberg A.,Chalmers University of Technology | Andersson L.,Interfleet Technology AB
Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit | Year: 2011

Vertical wheel-rail contact forces with high magnitudes are generated in vehicle operation on track sections with periodic (rail corrugation) or discrete (rail joints, crossings) surface defects and/or in operations with out-of-round wheels. This may result in severe wheel damage, such as subsurface rolling contact fatigue and deep shelling. Based on input data in the form of contact forces measured by an instrumented wheelset, including contributions with frequencies up to about 2 kHz, a track condition analyser (TCA) has been developed. The dominating and most frequently occurring types of rail rolling surface defects can be detected, their location along the line can be determined, and their detrimental effect on the fatigue life of wheels can be estimated. This means that the TCA can be used as a tool to assess the current track quality and determine the need for immediate and planned track maintenance. Using the instrumented wheelset on a Swedish passenger train, the 450 km line Stockholm-Gothenburg can be measured in both directions during an 8 h test campaign.


Persson I.,AB DEsolver | Nilsson R.,AB Storstockholms Lokaltrafik | Bik U.,AB Storstockholms Lokaltrafik | Lundgren M.,Interfleet Technology AB | Iwnicki S.,Manchester Metropolitan University
Vehicle System Dynamics | Year: 2010

In this paper, a genetic algorithm optimisation method has been used to develop an improved rail profile for Stockholm underground. An inverted penalty index based on a number of key performance parameters was generated as a fitness function and vehicle dynamics simulations were carried out with the multibody simulation package Gensys. The effectiveness of each profile produced by the genetic algorithm was assessed using the roulette wheel method. The method has been applied to the rail profile on the Stockholm underground, where problems with rolling contact fatigue on wheels and rails are currently managed by grinding. From a starting point of the original BV50 and the UIC60 rail profiles, an optimised rail profile with some shoulder relief has been produced. The optimised profile seems similar to measured rail profiles on the Stockholm underground network and although initial grinding is required, maintenance of the profile will probably not require further grinding. © 2010 Taylor & Francis.


Lindfeldt E.,Chalmers University of Technology | Ekh M.,Chalmers University of Technology | Cvetskovski K.,Interfleet Technology AB | Schilke M.,Interfleet Technology AB
Experimental Mechanics | Year: 2014

Digital Image Correlation (DIC) is used to analyze in-situ obtained SEM images of a pearlitic steel. Rather than using a synthetic speckle the microstructure of the material (cementite lamellae embedded in a ferrite matrix) is used as a natural speckle. The impact of the DIC method parameters on the identified motion (displacements and strains) is studied and it is shown that the method is robust, in the sense of being insensitive to the subset size, when it comes to determining the local subset displacements. However, a sufficiently large subset size is required in order for the local subset strains to converge. © 2014, Society for Experimental Mechanics.


Patent
Interfleet Technology AB | Date: 2010-01-06

The invention relates to a method for determining a plurality of load components (F) on a wheel, comprising the steps of providing on the wheel a plurality of sensors (g) with which it is possible to detect strains or stresses, and measuring essentially simultaneously sensor values () of at least some of the sensors (g). The invention is characterised in that the number of sensors (g), sensor values (j) of which are measured essentially simultaneously, is at least three, and in that the method comprises the step of determining a plurality of load components (F) at least partly based on the measured sensor values ().

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