Survey methods in eliminate the effect of temperature on the damage detection by machine learning

This leads to a large number of false alarms if the detection method cannot isolate the various impacts due to changing environmental conditions or damage. To address this issue, there are many methods that are proposed to detect the damage of bridges under environmental temperature changes. In this paper, some machine learning methods that eliminates the effect of temperature on the damage detection are explored.