In this article, numerical and experimental investigations are carried out to assess the possible use of vibration measurements to identify the presence of a fatigue crack in railway axles, detecting components of axle vibration occurring at frequencies that are integer multiples of the axle’s frequency of revolution (N×Rev components). A model of a cracked axle is defined using the Timoshenko beam finite elements incorporating an equivalent beam element having cross-sectional area and moments which are periodically changing with the angular position of the axle turn to reflect the crack breathing mechanics. Two levels of validation are considered for this model: first, verification with numerical results from a solid model of railway cracked axle (solid model was built before using the solid finite element model) and, second, validation against experimental results obtained from full-scale tests performed on cracked axles using a rotating bending fatigue test rig available at the labs of Politecnico di Milano. To consider the effect of disturbances arising from train–track interaction, track irregularity and wheel out-of-roundness, a multi-body model of a complete railway vehicle is defined, incorporating one axle modelled as a flexible cracked axle. This model is used to evaluate the N×Rev components of axle vibration occurring in the presence of axle cracks having different positions along the axle and different depths, in combination with different sources of disturbance. The results show that the 2×Rev and 3×Rev components of the horizontal axle-box acceleration are well correlated to the size of the crack and are almost insensitive to the effect of all disturbances considered in this study. Hence, they can be used for the continuous monitoring of axel integrity. Finally, a criterion for crack detection is defined and applied to the experimental and numerical results, showing the possibility of detecting cracks with sizes in the order of 8% of the total section area.

How to save wheels and influence train performance  Overview of severe wheel issues on Greater Anglia Routes  Proposed solution by using on-board monitoring of wheel condition  Plans for improving fleet performance  Use of on-board monitoring for other components and on other fleets David Pearce, Fleet Performance and Planning Engineer, Abellio Greater Anglia Alan Stewart, Commercial Manager, Perpetuum 11:00 Refreshments, networking and exhibition Session 1a: Hardware, communications and data standards from RCM applications Session 1b: monitoring systems for systems and vehicles 11:30 1.a.1 An automated data-driven toolset for predictive analytics K Pipe, B Culkin, Humanware, UK 1.b.1 Crack detection in railway axle using horizontal and vertical vibration measurements

This paper presents the performance of a new, floating, mono-hull wind turbine installation vessel (Nordic Wind) in the installation process. The vessel can transport pre-assembled wind turbines from the marshalling port to the offshore installation site. Each assembled turbine will be positioned over the pre-installed floating spar structure. The primary difficulty lies in examining the multibody system’s reactions when subjected to combined wind, current, and wave forces. Time-domain simulations are utilized to model the interconnected system, incorporating mechanical coupling between components, the mooring system for the spar, and the installation vessel. The primary objective is to focus on the monitoring and connection stages preceding the mating operations between the turbine and the floating spar. Additionally, it involves examining the impacts of wind, current, and wave conditions on the motion responses of the installation vessel and the spar, as well as the relative motions at the mating point, gripper forces, and mooring forces. The simulations show that the resulting gripper forces are reasonable to compensate. The relative motion at the mating point is not significantly affected by the orientations of the turbine blades, but it is influenced by the prevailing wave conditions. In addition, vessel heading optimization can minimize the relative motions at the mating point and gripper forces. Given the examined environmental conditions, the presented installation concept exhibits a commendable performance.

Abstract-Suspension bridges are an important and widely used element of regional and urban infrastructure for traffic and transportation. One of the elements of the system to ensure their safety and security is the geodetic monitoring by using GNSS technologies. Displacement of the bridges points depend not only on time, the impact of traffic capacity and wind on the naturaltechnical system of suspension bridge should be taken into consideration. This makes the task of constructing a predictive model difficult. The most significant effects are the temperature change, the impact of wind and vehicle movement. Here is some analysis of these effects on the dynamics of a suspension bridge using real experimental data. Two analytical methods, namely Neural Networks (NN) and Least Square (LS), were used for the prediction of the effects on the behavior of suspension bridges. The results of the Neural Networks give better picture than the results of Least Square.

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