Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/16086
Title: Statistical structural health monitoring: Methodologies and Applications
Authors: WANG ZENGRONG
Keywords: Damage assessment; Monitoring; Statistical models; Time series analysis; Data analysis; Methodology.
Issue Date: 15-Oct-2008
Source: WANG ZENGRONG (2008-10-15). Statistical structural health monitoring: Methodologies and Applications. ScholarBank@NUS Repository.
Abstract: Innovative methodologies of statistical structural health monitoring (SHM) and their applications are presented in this thesis. First, Hotelling's T2 control chart is used to construct a multivariate extension of a time series based SHM scheme. The sensitivity of the defined damage indicator is further improved by invoking multivariate exponentially weighted moving average (MEWMA) control chart analysis. Based on this MEWMA control chart analysis and the vibration responses representation by sample principal component coefficients (PCCs), structural damage detection is then addressed via a multivariate statistical approach. Finally, a nonparametric statistical SHM framework is formulated. The efficacy of the methodologies is demonstrated by a series of applications including numerical examples of a progressively damaged reinforced concrete (RC) frame, a five-story shear frame, a shear wall, a twenty-degree-of-freedom system and a hyperbolic paraboloid roof shell as well as the experimental example of the I-40 Bridge benchmark.
URI: http://scholarbank.nus.edu.sg/handle/10635/16086
Appears in Collections:Ph.D Theses (Open)

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