Damage detection of civil structures has been carried out by mainly analysing the vibration properties of the structures which change when damages occur. However, these properties are also affected by the changing environmental conditions the structures are face with, and these conditions usually produce nonlinear effects on the vibration properties. Hence, a method is proposed in this paper to analyse structures subjected to nonlinear effects of environmental conditions. The method first applies Principal Component Analysis (PCA) on a bank of damage sensitivity features, followed by applying Gaussian Mixture Model on the obtained first principal component scores to cluster the data into several linear regions. By creating a baseline for each linear region using two extreme and opposite environmental conditions, and adding new measurements to the baseline one at a time followed by applying PCA, damage detection can be achieved. The method is validated on a numerical truss structure model and on the Z24 Bridge. The results demonstrate the ability of the method to analyse structures under nonlinear environmental effects.
- Principal Component Analysis (PCA)
- Gaussian mixture model
- Environmental conditions
- Damage detection