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Adaptive Regression for Damage Detection in Bridges Under Environmental Influence



Many of Vibration-based structural health monitoring (SHM) often uses vibration characteristics to detect damage. It has been acknowledged that changes in vibration characteristics can also happen due to environmental factors. Especially for civil structures it is impossible to test in isolation from natural environment. These environmental factors are seen to significantly affect modal frequencies and can easily mask changes caused by damage. In this study we propose a technique that treats temperature variations as embedded parameter and helps to define a correlation structure between modal frequencies. The proposed method utilizes the correlation between structural frequencies to represent the healthy state of the structure. Damage is detected by measuring deviation of the recorded frequency from the healthy state. The proposed damage detection strategy is tested using simulation result for a simply supported T-beam section bridges.

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