Abstract
Accurate and efficient damage detection in long-term health monitoring for structures still encounters many difficulties due to the effect of environment. Furthermore, recorded big data requires efficient damage detection algorithm. In this study, an efficient and effective damage detection algorithm is proposed using transmissibility along with Mahalanobis distance and Hotelling T-square. A numerically simulated beam and an experimentally tested laboratory structure are used to validate the proposed algorithm. Results demonstrate good performance of the proposed technique in damage detection.
Highlights
Structural health monitoring (SHM) has been a research focus in the past years, and transmissibility has attracted a lot of attention due to its characteristic in avoiding the requirement of measuring excitation
This study developed an output based dual-step damage detection procedure using transmissibility incorporated with Mahalanobis distance and Hotelling T square for detecting structural damages in a fast manner at an early stage
At a second stage, Mahalanobis distance based damage detection procedure guarantees the detection of damage
Summary
Structural health monitoring (SHM) has been a research focus in the past years, and transmissibility has attracted a lot of attention due to its characteristic in avoiding the requirement of measuring excitation. Even numerous research outputs have been developed, early damage alarming and detection still encounters difficulty in long-term SHM for real engineering applications. This is because minor damage does not cause large changes in structural dynamic responses. For long-term SHM, previous researches concentrated on the outlier detection by using several models such as statistical models, discriminant analysis and so on [6,7,8], while few works paid attention to the efficiency, especially in transmissibility based SHM. A dual-step damage detection procedure based on using Mahalanobis distance and Hotelling T square is developed. The main contribution of this study is to introduce a less time-consuming damage detection methodology by illustrating the differences between Mahalanobis distance and T-square from an efficiency perspective
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