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Numerical Simulations of Railroad Track Damage Characterization Using Non-Contact Tomography



The progress in the development of sciences pertaining to structural health monitoring has witnessed tremendous growth. Significant progress has been made in finding and locating defects in plate-like and in built-up structures. This paper shall present a potential “what next†in the field of structural health monitoring. It will illustrate this with work performed on the wayside monitoring of rail infrastructure. The application of wheel impact load detection or WILD systems to monitor train wheel health condition has generated significant savings and an increasing database of knowledge regarding wheel performance and behaviour. Applications of the WILD systems have so far been limited to assessing wheel health and determining which wheels are too hazardous to be in operation. This paper will show how a defective wheel can be identified by wayside monitoring. Once these defective wheels are identified, it is then important to determine if we can leave this defective wheel to continue operation. This decision can be assisted by integrating the engineering data into an economic model. The application of an economic feasibility study on the wheel removal protocol showed the relative savings obtained from timely removal of train wheels with defects. This is an alternative approach to the current wheel removal protocol which employs a three stage wheel monitoring and maintenance procedure dependent on the impact load levels.

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