Dynamics of railway freight vehicles

This paper summarises the historical development of railway freight vehicles and how vehicle designers have tackled the difficult challenges of producing running gear which can accommodate the very high tare to laden mass of typical freight wagons whilst maintaining stable running at the maximum required speed and good curving performance. The most common current freight bogies are described in detail and recent improvements in techniques used to simulate the dynamic behaviour of railway vehicles are summarised and examples of how these have been used to improve freight vehicle dynamic behaviour are included. A number of recent developments and innovative components and sub systems are outlined and finally two new developments are presented in more detail: the LEILA bogie and the SUSTRAIL bogie

The role and work of forensic nurses:an international comparative approach

This paper presents a model for simulating vehicle–track interaction at high frequencies for investigations of rail roughness growth. The dynamic interaction model developed employs a substructuring technique and the whole system consists of a number of substructures that can be modelled independently. The systems are coupled through the forces at the wheel–rail contact and the railpad. A coupled, rotating flexible wheelset, a flexible track model and a non-Hertzian/non-steady contact model have been implemented and results are presented here for a free wheelset on a symmetrical track system with initial random and sinusoidal roughness. Both rigid and flexible wheelsets are considered

Application of Power Spectrum, Cepstrum, Higher Order Spectrum and Neural Network Analyses for Induction Motor Fault Diagnosis

The power spectrum is defined as the square of the magnitude of the Fourier transform (FT) of a signal. The advantage of FT analysis is that it allows the decomposition of a signal into individual periodic frequency components and establishes the relative intensity of each component. It is the most commonly used signal processing technique today. If the same principle is applied for the detection of periodicity components in a Fourier spectrum, the process is called the cepstrum analysis. Cepstrum analysis is a very useful tool for detection families of harmonics with uniform spacing or the families of sidebands commonly found in gearbox, bearing and engine vibration fault spectra. Higher order spectra (HOS) (also known as polyspectra) consist of higher order moment of spectra which are able to detect non-linear interactions between frequency components. For HOS, the most common used is the bisoectrum. The bispectrum is the third-order frequency domain measure, which contains information that standard power spectral analysis techniques cannot provide. It is well known that neural networks can represent complex non-linear relationships, and therefore they are extremely useful for fault identification and classification. This paper presents an application of power spectrum, cepstrum, bispectrum and neural network for fault pattern extraction of induction motors. The potential for using the power spectrum, cetstrum, bispectrum and neural network as means for differentiating between healthy and faulty induction motor operation is examined. A series of experiments are done and the advantages and disadvantages between them are discussed

Simulations of roughness growth on rails – results from a 2D non-Hertzian, non-steady contact model

A new model for simulating rail roughness growth on tangent track is presented in this paper. The model consists of three relatively independent components: (1) a time-domain vehicle/track interaction model; (2) a 2D non-Hertzian and non-steady wheel/rail contact model; and (3) a wear model. Wheel/rail contact forces for a given initial roughness obtained from the vehicle/track interaction model are used by the contact model to calculate the contact patch size, normal pressure and tangential stresses with material removal assumed to be linearly proportional to the friction work in the contact patch. The roughness profile is updated and fed back into vehicle/track interaction model. The 2D contact model is initially compared with a 3D model for various wavelength of initial sinusoidal roughness. Long term roughness growth is then simulated with the 2D contact model. Simulation shows that all initial sinusoidal roughness of wavelengths between 20–100 mm are levelled out. The wavelength-fixing mechanism, that has previously been used to explain the cause of corrugation, is not found in the present investigations

Experimental and theoretical investigation of railway wheel squeal

The tangential contact forces that arise at the interface between the wheel of a railway vehicle and the rail provide all the traction, braking, and guidance required by the vehicle. These forces are the result of microslip or creepage and can become unstable exciting vibration of the wheel, particularly at frequencies corresponding to the wheel's axial (and radial) modes

Simulations of roughness growth on railway rails

A model for the prediction of the initiation and growth of roughness on the rail is presented. The vertical interaction between a train and the track is calculated as a time history for single or multiple wheels moving on periodically supported rails, using a wavenumber-based approach. This vertical dynamic wheel/rail force arises from the varying stiffness due to discrete supports (i.e. parametric excitation) and the roughness excitation on the railhead. The tangential contact problem between the wheel and rail is modelled using an unsteady two-dimensional approach and also using the three-dimensional contact model, FASTSIM. This enables the slip and stick regions in the contact patch to be identified from the input geometry and creepage between the wheel and rail. The long-term wear growth is then predicted by applying repeated passages of the vehicle wheelsets, as part of an iterative solution

The introduction of falling friction coefficients into curving calculations for studying curve squeal noise

In this paper, a method of introducing falling friction coefficients into curving simulations for studying curve squeal noise is presented. Generation of squeal at the wheel of a railway vehicle in a curve is caused by unstable vibration, caused in turn by a lateral wheel/rail force which reduces with increasing lateral creepage. To model vehicle curve squeal, the wheel/rail tangential force in the curving simulation is calculated by a modified version of FASTSIM, which uses a sliding velocity-dependent friction characteristic. Using the falling friction characteristics, a UK passenger vehicle is modelled with SIMPACK. Curving behaviour is simulated for a range of curve radii and cant deficiencies. The wheel/rail contact properties are then obtained to study the possibility of the occurrence of squeal using a frequency-domain method. The methodology in this paper allows various curves, wheel/rail profiles, vehicle speeds and friction characteristics to be taken into account