Structural dynamic properties such as natural frequency depend not only on damage but also environmental condition (i.e., Temperature). Without removing the variation of environmental condition in the damage detection, false-positive or negative damage diagnosis may occur so that structural health monitoring becomes unreliable. One of methods used to solve this problem is to construct regression model based on structural responses with the environmental factors. However, it is difficult to determine where and which environmental variables to measure. One alternative is to remove the variability due to environmental variation without measurement of environmental variables. However, the performance of this method is depending on how to define the reference data set. Generally, there is no prior information on reference condition (i.e., healthy condition) during data mining. Reference condition is determined based on subjective perspective with human-intervention. To overcome the drawback of current methods, this paper investigates adaptive PCA technique for the monitoring of structural damage detection under environmental change. This method is not required to determine the reference condition and measure the environmental variables. Proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation.