Damage detection and reliability assessment of building structures using stochastic approaches

Vibration-based structural damage detection methods have attracted considerable attention for assessment of functionality and safety of civil structures. Nevertheless, the damage detection of civil structures still remains as a challenging task. One of the main obstacles is that the current damage detection methods are either insensitive to local structural damage or sensitive to measurement noise. In addition, a significant amount of uncertainties are inherently and inescapably associated with structural damage detection of civil structures, which limits the successful application of most deterministic damage detection methods. In this regard, this thesis focuses on the establishment of a framework in which novel stochastic approaches in consideration of the uncertainties involved in measurements, structures and external excitations are proposed to detect damage of building structures and assess their reliability effectively.;Firstly, this thesis proposes a novel structural damage detection method using a new damage index based on the statistical moments of dynamic responses of a building structure under random excitation. Then, the statistical moment-based damage detection (SMBDD) method is advanced in the frequency domain for its practical application. In addition, the feasibility and effectiveness of the generalized SMBDD method are also explored in the time domain for the building structures under non-Gaussian and non-stationary excitations. After that, this thesis presents an experimental investigation on the SMBDD method through shaking table tests. Extensive numerical and experimental investigations have demonstrated that the SMBDD method is not only sensitive to local structural damage but also insensitive to measurement noise. The research work on structural damage detection then makes further progress by proposing a new stochastic damage detection method based on the SMBDD method in consideration of random parameters or uncertainties which are inescapable for civil structures. The stochastic damage detection method enables the identification of damage locations and damage severities of building structures with uncertainties or random parameters. The last piece of work described in this thesis is concerned with reliability assessment of instrumented building structures. Two integrated methods are proposed to respectively evaluate structural component reliability and system reliability by directly using limited measurement responses.