Wayside detection monitors critical parameters relating to the condition of in-service railway vehicles. Economic decisions about the maintenance of vehicles can be made, and servicing can occur when a particular vehicle is likely to cause even small amounts of damage to the track, to itself, or when the cost of damage is significant, such as in catastrophic failure. Vehicles with poorly performing axle bearings, out-of-round (skidded or spalled) wheels, vehicles which exhibit transient lateral motion (‘hunting’), and vehicles with poorly performing brakes are all likely to fall into the category of requiring maintenance, in order to save the track and the vehicle owner's money. In the present paper, the parameters that define vehicle condition and their measurable effects are stated. There are frequently a number of wayside detection methods of inspecting a vehicle for the same vehicle condition and each of these is described in detail. This investigation reveals the need for further research to enable rollingstock owners to make better decisions about the cost of operating their vehicles, based on the output from wayside detectors and the observed trends in wheel impact.

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Out-of-round rollingstock wheels are caused by skidding or spalling of the wheel tread and by dynamic motion of wheels and wheelsets in service. Out-of-round wheels generate impact forces at the wheel-rail interface, which are transferred to train and to track components including rail and both bolted and welded rail joints, prestressed concrete sleepers, ballast, wheels, and bearings. To make a rational decision about removing out-of-round wheels from service, estimation of the damage caused by an individual wheel is required. Previous studies have used analytical and numerical models to illustrate the distribution of impact into track and rolling stock components. These models are compared here. The review details mathematical models and studies of the lives of the earlier-listed components, which would provide a means of determining the damage caused by impacting wheels. In addition, studies have found that impacting wheels increase fuel consumption and increase pass-by noise levels, which are also discussed here. Further study of the effect of impacting wheels on axle bearing lives, parent rail, and bridges would improve this decision-making tool. It is envisaged that these models would be combined to determine the total cost of operating rolling stock with impacting wheels. This could be offset against the cost of wheelset maintenance to determine when an impacting wheel should be reprofiled.

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SUMMARYDistributed fiber optic sensors have been shown to be promising when used to monitor the structural health of pipes. The body of work thus far has only considered pipes whose cross sections are assumed to remain circular under load. In some applications, the cross section of the pipe has been known to deform when loaded. Subsequent loading on a deformed pipe then generates additional stresses that may have been unaccounted for when designing the pipe. This paper addresses the effects of the initial non-circular cross section of a pipe under internal pressure and its detection with a distributed fiber optic sensor based on Brillouin Optical Time Domain Analysis. This ability of the Brillouin Optical Time Domain Analysis sensor to detect local stiffness irregularities on an out-of-round pipe subjected to internal pressures is also demonstrated.