Practical identification of favorable time windows for infrared thermography for concrete bridge evaluation
Abstract
Infrared Thermography (IRT) is one of the nondestructive inspection techniques to detect delaminations in concrete bridge decks. These defects are identified by capturing the temperature gradient of concrete surfaces. In order for this technique to be effective in damage detection, IRT inspections should be conducted at certain time windows with favorable temperature conditions to get clear temperature gradients on inspected surfaces. This study is an experimental work examining the effects of ambient environmental conditions at different times of a day to locate subsurface delaminations and voids at a shallow depth, which is an additional influencing factor. This study also attempts to figure out a relationship between ambient environmental conditions and the temperature values of concrete surfaces to estimate the best time window with appropriate environmental conditions for IRT inspections. To this end, specially designed reusable concrete test plates with different thicknesses were manufactured to collect thermocouple sensor readings. Multiple regression analyses were employed to generate prediction models that seek a relationship between environmental conditions and temperature gradients on the test plates attached to a target bridge. Regression models also utilized sensor data collected at another location different than the target bridge location. It was found out that the most important aspect of sensor data collection was to accomplish a perfect contact of test plates with concrete bridge deck surfaces to get discernible temperature gradients. When this condition is not met, data analyses yield spurious results leading to futile conclusions. On the other hand, it was also observed that prediction models generated by regression analyses followed the same pattern as that of sensor readings. This makes it possible to have prediction equations based on sensor readings to determine suitable time window for conducting IRT inspections. (C) 2015 Elsevier Ltd. All rights reserved.