MerMec (Italy)

This paper describes an algorithm based on fuzzy logic for the real-time detection and removal of impulsive spike noise from measures of track geometry in railway infrastructures. Spike noise is caused by random events, including anomalous reflections of external lights, detection or transmission errors within the measuring systems, and singular parts of tracks (switches, level crossings) hiding the rail profile. Its effects are extremely undesirable because they can generate erroneous alerts about inexistent railway defects. The real-time detection of spike noise is generally difficult, as the inspected tracks have extremely variable characteristics, and the measurement is performed in dynamic and turbulent conditions. By incorporating in a fuzzy system the typical rules used for offline analysis of the measured data, we develop a filtering algorithm that is able to perform spike removal in real time. Moreover, we also propose a variant of the fuzzy filter that improves the reconstruction of the corrupted measures. The proposed algorithm is validated on an extensive set of experimental investigations, which include a comparison with other algorithms selected from recent literature. The results confirm the effectiveness of the filtering algorithm, which has been recently implemented on some measuring vehicles for high-speed lines

Damage mechanisms such as surface cracks, plastic deformation and wear can significantly reduce the service life of railway tracks and rolling stock. They also have a negative impact on the rolling noise as well as on the riding comfort. In the study of the interaction forces which act in the wheel-rail contact point and the oscillatory motions to which the vehicle is subject during the running, different parameters have been introduced to quantify the vehicle safety against derailment, its aggressiveness toward the track and the passenger's comfort. For each of these parameters, associated to the vehicle or track status, a threshold value has been defined according to the experience and the statistical distribution of the faults, more than to a strict analysis. If all the parameters exceed their threshold value, the vehicle safety can't be guaranteed. Therefore, it is advisable to develop test methods that consider the simultaneous faults on the railway track and on the vehicle axle. The opportunity to employ diagnostic vehicles able to measure simultaneously all the parameters related to the track and wheel geometry allows us to characterize the real wheel-rail interaction, rather than simulate this interaction using computer-based models. In this paper we will introduce the equivalent conicity parameter, defined in the UIC 518. This parameter will be able to quantify the wheel-rail interaction, collecting all the information related to the wheel and rail parameters. A method to calculate this parameter by means of a diagnostic vehicle will be introduced, validating its accuracy according to the testing procedures defined in the UIC 519.

DYNROT is a code based on the finite element method which is intended to perform a complete study of the dynamic behaviour of rotors. Although initially designed to solve the basic linear rotordynamic problems (Campbell diagram for damped or undamped systems, unbalance response, critical speeds, static loading), it can be used for the study of non‐stationary motions of nonlinear rotating systems and for the torsional analysis of rotors and reciprocating machines. Explains that one of the distinctive features of the code is the use of complex co‐ordinates, both for isotropic and non‐symmetric systems. Makes extensive use of complex arithmetics in all parts of the analysis. Applies the modal approach in some of the solution routines to increase the efficiency of the computation or to compute an equivalent viscous damping in those cases where hysteretic damping cannot be introduced directly to the model. The dynamics of bladed discs is included in the code.