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UBC Theses and Dissertations

Optimal sensor placement for structural health monitoring Segeja, Martin

Abstract

Optimal sensor placement (OSP) is a crucial subject in structural health monitoring. It becomes even more important for large structures like bridges since it is not economical, and most times impossible, to cover the entire structure with sensors. On account of that, there are several methods used in civil engineering to determine optimal sensor placement. In this thesis three methods of OSP are discussed: the effective independence (EFI) method, the modal kinetic energy (MKE) method, and the damage diagnosability (DD) method. The EFI method has additional subtypes based on including sensor noise statistics and the driving point residue, these are also discussed. The three OSP methods are implemented for a hollow steel structure (HSS) beam and the S101 bridge. The methods are coded in MATLAB and make use of SAP2000 models. Furthermore, the HSS beam model is created in SAP2000 and calibrated to match the frequencies obtained through operational modal analysis (OMA). While a calibrated S101 bridge model was developed during a previous study. Additionally, an interface is created in MATLAB to connect SAP2000 to MATLAB in order to carry out the sensor placement methods. Finally, the results from the three methods are presented and validated by confirming whether the performance criterion is maximized. The EFI method is validated by the condition number of the mode shape matrix. The MKE method is validated by the kinetic energy at degrees of freedom (DOF). The DD method is validated by comparing the predicted mean test response and the empirical mean test response. Also, by the relationship between the minimum measurement duration and the mean test response. The results of the HSS case study demonstrate that the DD method maximizes damage detectability by calculating the minimum measurement duration to detect the intended damage. Therefore, it is the only method used for the S101 case study. In the scope of this thesis, the most effective method is determined to be the DD method because it is the only OSP method that maximized its performance criterion.

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