Non-contact determination of Rail Neutral Temperature (RNT) and state of stress in continuously welded steel railway rail using robust dot-peen displacement tagging

Abstract

It is well-known that stresses induced by temperature extremes can lead to buckling and breakage of Continuously Welded Steel Railway Rail (CWR). Furthermore, there is currently no proven non-contact technology for accurately assessing and monitoring the state of rail stress. CWR can be subjected to very high stress levels when the temperature of the rail differs from the installation temperature, referred as the “Rail Neutral Temperature (RNT),” corresponding to zero stress in the rail. The objective of this research is to develop and demonstrate a new approach using non-contact technology for monitoring the rail neutral temperature and the state of rail stress. This is achieved through simultaneous non-contact measurement of rail axial displacement and temperature. A new prototype sensor has been developed by the Technology Development Institute (TDI) at Kansas State University (KSU) based on existing robust field-hardened non-contact strain-measurement technology. Steel rail displacement (strain) tagging is attained using a robust dot-peen pattern with commercially available portable dot-peen equipment.

The capability of the prototype sensor system to accurately assess the mechanical stress in steel rail is first demonstrated using a special-purpose laboratory testbed. This facility is capable of imposing mechanical loading in excess of 150,000lbf, while also subjecting the section of steel railroad rail to controlled thermal strain conditions. The viability of monitoring the state of rail stress is demonstrated under mechanical and thermal laboratory conditions representing extremes of what might be encountered in a field environment. Such conditions correspond to significant departures from a given baseline (rail neutral) strain condition in the testbed.

The unique application of this new technology represents a completely new paradigm for assessment of rail stress in track. It is based on the concept that whenever track is cut/replaced for maintenance, the baseline conditions of the rail will be assessed and “tagged” to this section of rail. Over time, a growing network of these baseline sections of track will develop, allowing an ever-increasing database of measurement stations that can be accessed for periodic monitoring of the state of rail stress using the new sensor technology. The results presented in this dissertation represent the first steps in proving the capability of the method, prior to actual application in the field environment.