Abstract
This paper addresses the application of six different optimal sensor placement (OSP) techniques in buildings. These techniques are the EFfective Independence (EFI), Optimal Driving Point (ODP), Non-Optimal Driving Point (NODP), Effective Independence Driving Point Residue (EFI-DPR), Singular Value Decomposition (SVD) and the Sensor Set Expansion (SSE) methods. A toolbox OPTISEP is developed by the author for this purpose within the context of this paper. The techniques are compared among themselves by using various criteria. The overall results show that the SSE Technique is the best. First, the technique results in a dramatic reduction in the computational effort. Second, it allows a civil engineer to specify a set of locations that they absolutely want to keep in the final sensor configuration. Mozst importantly, while the sensor distribution estimated by other techniques is mainly concentrated in a certain storey of the building, SSE gives a homogeneous sensor distribution throughout the building. Finally, it is shown that the technique i s also robust against noise in the measurements.
Highlights
The sensor location problem is a key issue for on-orbit modal identification and correlation of large space structures (LSS) in aerospace industry
2.2 Optimum Driving Point (ODP) Based Method In order to identify the nodal points of mode shapes, modal constants for all chosen modes at each degree of freedom are multiplied and the result is a coefficient called the Optimal Driving Point (ODP) parameter which can be expressed as: (11) The candidate sensor locations are reduced to the number of available sensors using the ODP parameter
If a choice has to be made between the EFfective Independence (EFI) and Sensor Set Expansion (SSE), SSE would always be preferable due to the fact that a more homogeneous sensor configuration is obtained with the SSE
Summary
The sensor location problem is a key issue for on-orbit modal identification and correlation of large space structures (LSS) in aerospace industry. This paper addresses the application of different OSP techniques in stiff buildings. The OSP Techniques were first developed for aerospace structures where the stiffness and the mass distributions are homogeneous throughout the structure. The optimal sensor locations for a stiff building are determined based on the different OSP techniques in the toolbox and are compared with each other using various criteria in this paper. The best estimate in placing sensors within the candidate locations implies that the covariance matrix of the estimate errors will be a minimum. Within this context, the output must be modified as:. The FIM can be simplified from Eq(5) as [1]: The following eigenvalue problem is solved: The eigenvalues of Ao are real and positive and the eigenvectors resulting in the relations: ΨTAoΨ λ
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