Condition monitoring and fault detection systems are becoming increasingly important in rail vehicles maintenance and operation, ensuring safety and reliability improvement. Light rail systems are not the main target for this trend, because of low operational speed and lower safety factors. Nevertheless public transport operators begin to pay a closer attention to the technical state monitoring of vehicle and track, in order to reduce maintenance cost and increase safety and ride comfort for passengers, which is an important challenge for public transport competitiveness in XXI century. The paper describes the main concept of the innovative on-board condition monitoring system for light rail vehicle and track. Functional requirements, assumptions and procedures are described, as well as the on-board data acquisition unit with necessary transducers, which number, function and technical parameters were optimized during the research phase of the project. The prototype of the presented system is now being tested in normal operating conditions.
The article concerns the developed methodology for assessing the technical condition of a tramway track. Thanks to the data
collected from multiple tram journeys equipped with an on-board vibration recording system, it was possible to create profiles of
crossings through track sections in different technical condition. In order to identify the track condition, an algorithm based on the
gray-scale modeling was proposed, and a similarity comparison between the obtained track profiles. A new measure of similarity has been proposed that has not been used so far in gray-scale modeling. The obtained results confirm the applicability of the
proposed methodology
In tram operations, flange wear is predominant due to the low-radius curves and inappropriate technical conditions of the infrastructure; hence, investigations should be focused on the interaction between the wheel flange and the rail gauge corner. Moreover, the calculation methods based on the Hertzian model (elliptic contact patch) provide less accurate results due to the contact occurrence in the wheel flange region. This paper presents a methodology of a finite element method to predict the tram wheel wear in complex motions. The new procedure is based on the Abaqus software and several other sub-procedures written in Python and Fortran. Multibody simulations were used to determine the wheel–rail alignment. In this method, accuracy was chosen at the expense of the computational effort. The main steps are: preparation of models and ride scenarios, multibody simulation for calculating the wheel–rail alignment for different track scenarios and multiple runs of finite element method analysis to determine the wear magnitude. The proposed methodology presents a good agreement with the measurements and can be considered as guidelines for a proper configuration of the flange-designing experimental setup where the influence of the technical conditions of the infrastructure should be introduced adequately.
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