Advanced Deep Learning Methods for Vibration-based Structural Damage Identification
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Vibration-based damage identification has been a challenging task in structural health monitoring. The main difficulty lies on the reliable correlation between the measured vibration characteristics and the damage states of structures. However, the measured vibration signals are often high-dimensional and noise-contaminated, and sometimes in multiple scales or have multiple physical meanings. In this thesis, we propose advanced deep learning models for effective and efficient structural damage identification.
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Hao, Hong; Li, Jun (2017)© 2017 International Society for Structural Health Monitoring of Intelligent Infrastrucure. All rights reserved. Many sources of uncertainties, which could be introduced into the structure during their construction and ...
Long-term monitoring of vibration properties of structures with different materials and boundary conditionsHao, Hong (2013)Different methods have been developed for structural conditions monitoring. Among them, vibration-based methods have been receiving a lot of attentions because any change in structural conditions will result in a change ...
Hao, Hong; Deeks, A. (2017)Structural damage will cause changes in structural vibration properties such as vibration frequency, mode shape and damping ratio. Therefore the structural vibration properties are commonly used in structural condition ...