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Title: Decentralized structural damage detection methods under earthquake and ambient excitations
Authors: Ni, Pinghe
Degree: Ph.D.
Issue Date: 2018
Abstract: The structural health monitoring (SHM) technology has been developed and applied to numerous large-scale structures. Structural damage identification using the vibration data of the SHM systems has gained much attention during the past three decades. However, condition assessment and damage detection of large-scale structures are still challenging due to the slow convergence in the inverse problem with a large number of unknowns and limitation in computational resources. This thesis aims to develop a decentralized damage detection framework for large-scale structures, which would be used to evaluate the structural condition under seismic loading and ambient excitations. The study contributes to following aspects. First, a parallel, decentralized damage detection method is developed for large-scale structures. A large-scale structure is divided into several smaller zones according to its finite element configuration. Each zone is dynamically tested with the sensors in the zone. The dynamic responses in the zone are then used to update the corresponding structural parameters in that zone based on the assumption that the structural damage has more significant effects on the responses of the zone than other zones. The structural parameters in each zone are updated using the Newton Successive Over-Relaxation method. Parallel computing is used in the model updating process. The decentralized damage detection under seismic and ambient excitations is then studied. Under the earthquake excitation, the nonlinear behaviors of the structure are studied and two kinds of nonlinear models are addressed. One is the simplified mass-spring-dashpot model, and the other is the nonlinear finite element model. In the case of the simplified nonlinear model, an output only decentralized damage detection method is developed, in which the nonlinear structural parameters and the unknown input force are identified iteratively. In the case of a large-scale structure modelled by nonlinear finite elements, a decentralized nonlinear finite element model updating is developed and the parameters of the nonlinear constitutive material laws (such as compressive strength of concrete, the yield stress of reinforcement, etc.) are identified. Structural damage detection under ambient excitations is then addressed, in which the ambient excitations are considered as white noise processes. Two damage detection methods are proposed based on correlation functions. In the first method, a two-stage model updating technique is developed to identify the structural damage with the correlation function. In the second method, the correlation function is treated as the free vibration response based on the natural excitation technique. The proposed decentralized technique is used to determine the structural damage. The measured correlation functions are divided into several subsets according to its finite element configuration. Each subset of correlation functions is used to identify the corresponding structural parameters in the zone. Besides the theoretical development, numerical and experimental investigations are conducted to verify the effectiveness of the proposed methods.
Subjects: Hong Kong Polytechnic University -- Dissertations
Structural health monitoring
Structural failures
Pages: xxvii, 207 pages : color illustrations
Appears in Collections:Thesis

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