Defect Identification on The Underside of a Flat Plate using Moving Heat Source raft item

2017-02-15T03:50:46Z (GMT) by Yi Chin Tan
The causes of rail line accidents are apparent over the years, and there is a need to address this situation. One of the common factors is the lack of knowledge on rail base defects. Current technologies and methodologies on the inspection of rail track health are limited, and often require extended hours of inspection and labour effort. To enhance the detectability and efficiency of defect detection on rail systems, a heat source mounted on a moving platform was proposed and tested with computational modelling. <br>    A flat plate model with underside defect was used for the investigation to simulate and represent a complex rail base structure. The presence of defects was determined by analysing surface temperature responses. The second order peak derivative method estimated the defect depth while the Full Width Half Maximum (FWHM) method predicted the actual size of the defect located at the underside of test plate. <br>    The results on stationary heating showed that the prediction of underside defect size and depth location were most accurate when investigating for a case where a large size defect is positioned near the inspection surface. When defect depth is increased, this prediction ability deteriorates. For a defect at 7 mm depth, the predicted defect size is not justified. The results on stationary test were used as a reference for moving heat source test. The moving heat source was set up by creating sequential stationary heating of small segments separated by a constant delay. It was found that when this time delay was removed, the prediction of defect depth and size was similar to the test results on stationary heating. In fact, due to the high-speed heating, lateral heat diffusion can be assumed negligible, resulting in similar outcome as stationary test. The minimum heating speed for this to be true is 18km/hr. The tests in this thesis were validated with mathematical model and previously established findings. <br>    Edge effects are one of the main factors in affecting the prediction accuracy of defect size and depth location. A small defect size will experience earlier occurrence and significant edge effect whereas a large defect size will behave oppositely. In this study, other factors such as maximum achievable temperature and temperature contrast were also considered. <br>    The use of high-speed moving heat source for defect detection and measurement is feasible given that it is approximated to stationary heating. It allows the moving heat source test method to determine minimum detectable defect size and maximum detectable defect depth.