A comparison of track model formulations for simulation of dynamic vehicle–track interaction in switches and crossings

This paper compares different track model formulations for the simulation of dynamic vehicle–track interaction in switches and crossings (S&C, turnouts) in a multi-body simulation (MBS) environment. The investigations are an extension of the S&C simulation Benchmark with the addition of a finite element model of a 60E1-760-1:15 turnout. This model constitutes a common reference from which four different track formulations are derived: co-running, modal superposition, finite element incorporated into the MBS model and finite element coupled to MBS using a co-simulation approach. For the different track models, the difference in modelling technique, results, simulation time, and suitability for different simulation tasks is compared. A good agreement is found between the different track model formulations for wheel–rail contact forces and rail displacements. This study found a better agreement between co-running and structural track models compared to previous studies in the prediction of wheel–rail contact forces. This appears to be due to the increased complexity of co-running track model used in this study together with a tuning of the co-running track model to the reference model in a wider frequency range. For the reader interested to reproduce the results in this paper, the reference track model is available for download

Sensitivity enriched multi-criterion decision making process for novel railway switches and crossings - a case study

Background: Despite their important role in railway operations, switches and crossings (S&C) have changed little since their conception over a century ago. It stands now that the existing designs for S&C are reaching their maximum point of incremental performance improvement, and only a radical redesign can overcome the constraints that current designs are imposing on railway network capacity. This paper describes the process of producing novel designs for next generation switches and crossings, as part of the S-CODE project. Methods: Given the many aspects that govern a successful S&C design, it is critical to adopt multi criteria decision making (MCDM) processes to identify a specific solution for the next generation of switches and crossings. However, a common shortcoming of these methods is that their results can be heavily influenced by external factors, such as uncertainty in criterium weighting or bias of the evaluators, for example. This paper therefore proposes a process based on the Pugh Matrix method to reduce such biases by using sensitivity analysis to investigate them and improve the reliability of decision making. Results: In this paper, we analysed the influences of three different external factors, measuring the sensitivity of ranking due to (a) weightings, (b) organisational and (c) discipline bias. The order of preference of the results was disturbed only to a minimum while small influences of bias were detected. Conclusions: Through this case study, we believe that the paper demonstrates an effective case study for a quantitative process that can improve the reliability of decision making

Model-based fault diagnosis in rotor systems with self-sensing piezoelectric actuators

Machines which are developed today are highly automated due to increased use of mechatronic systems. Fault detection and isolation are important features to ensure their reliable operation. This research work aims to achieve an integrated control and fault detection functionality with minimum number of components. Piezomaterials can be used both as sensors and actuators due to their inherent coupling between electrical and mechanical properties. In this thesis, piezoelectric actuators which are being researched for active vibration control on flexible rotors, are also used as sensors. These self-sensing actuators reconstruct their mechanical deflection from the measured voltage and current signals. The systems under investigation are a numerical aircraft engine model and its scaled representation in a rotor test bench. Since the actuators are mounted in rotor bearings, their displacement represent the bearing deflection directly. In this research work, the virtual sensor signals are utilised for model-based fault diagnosis in rotor systems, with focus on unbalances in rotors. Unbalance magnitude and phase were estimated in frequency domain using a parameter estimation method by least squares optimisation. The robustness of the estimates against signal outliers is improved by method of M-estimators. Identifying the fault location is also explored using the hypothesis of localization of faults. In simulation, models of both systems (aircraft engine and test bench) were used to detect unbalance faults. In the former system, the influence of actuator placements in fault detection ability is examined. The fault detection method is also validated at the real test bench, as a first step. The unbalance detected using the measured virtual sensor signals is compared against results using available physical sensors. They are found to be in good agreement which proves sensing capability of the actuators. This sensor-minimal approach could be favoured in systems with space constraints. As a further step, unbalances are detected with self-sensing piezoelectric actuators in closed loop with an adaptive algorithm for vibration minimisation. This combined control effort and fault detection as a strategy, is suitable to augment level of automation in a machine

Self-sensing techniques of piezoelectric actuators in detecting unbalance faults in a rotating machine

AbstractSensors are inevitable components in a machine or in a mechatronic system, to measure physical quantities. Due to the inherent property of a piezoelectric material, it can be used as an actuator to bring in a displacement in the system by applying an actuator voltage or it can be used as a sensor where a force applied on it is translated as voltage. This property called as self-sensing, is one way to reduce the number of sensors needed in an active system. In the present application, piezoelectric actuators are mounted at the bearings of a rotor. The bearing displacement can be determined from the deflection of the piezos. This deflection can be reconstructed from the current and voltage. By feeding the reconstructed deflection to a finite element (FE) model, faults such as unbalance can be detected. The modal expansion theory helps to determine the deflection at any degree of freedom from few measured signals such as the bearing displacements. Moreover, the forces at each node can be calculated and detected for presence of unbalance faults. With the help of least squares minimization, the magnitude and phase of the unbalance can be determined