ST‐17AB: optimal sensor placement for non-linear dynamic model updating and response prediction of civil engineering structures subjected to future uncertain dynamic loadings - Kang, Teng Wee (2016)
The focus of this study is on the selection of ideal sensor location through computational and hypothetical methods. A statistical approach is used to acquire the optimal sensor locations in a building. This will allow the selection of measured parameters which illustrates the structural behaviour. The methodology can also be used for model updating, identifying structural damages and response prediction. Information entropy from a nominal model analysis generates a data, which is reviewed for the choosing of ideal locations for sensors placement. Thus, this methodology will account for the unavoidable uncertainties in model parameters. This methodology also increases the reliability of this study and its prediction. Prediction errors and parameter uncertainties will hinder the identification of statistical system. The errors and uncertainties can be determined by applying probability models. This assignment focuses on a building model with five storeys and degree of freedom (DOF). The optimal sensor configurations will be identified through the measurement of information entropy and Monte Carlo simulation.