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Fisher information‐based optimal sensor locations for output‐only structural identification under base excitation
A method is developed to determine optimal sensor locations for output‐only identification of modal and stiffness parameters under a class of non‐stationary base excitation. These optimal locations are obtained by maximizing the determinant of the associated Fisher information matrix (FIM), such that the optimally located sensors would contain the maximum information about the parameters of interest. To obtain the FIM, the input‐output relation is formulated in a random vibration framework. The input base excitation, modeled as a uniformly modulated random process, is characterized through an evolutionary power spectrum. Under such motions, the sum of eigenvalues of the output power spectrum, considered as measurement parameter, is shown to follow an exponential distribution. The FIM is then shown to comprise of the sum of these eigenvalues along with the sensitivities of the output power spectrum to the parameters of interest. Analytical expressions are derived for the different response sensitivities. The approach is illustrated through numerical simulations using a laterally‐torsionally coupled building, and experimental data from shake table tests. The effect of unobserved modes is discussed. It is seen that, while stiffness depending on unobservable modes are not identified or have high estimation uncertainty, the optimal sensor set‐ups for identifying a stiffness and for identifying the modes most sensitive to that stiffness are not necessarily the same. The importance of optimal sensor locations in damage detection is also highlighted through the shake table tests. It is shown that the estimation uncertainties in structural parameters and damage severities are least for optimally located sensors.
Fisher information‐based optimal sensor locations for output‐only structural identification under base excitation
A method is developed to determine optimal sensor locations for output‐only identification of modal and stiffness parameters under a class of non‐stationary base excitation. These optimal locations are obtained by maximizing the determinant of the associated Fisher information matrix (FIM), such that the optimally located sensors would contain the maximum information about the parameters of interest. To obtain the FIM, the input‐output relation is formulated in a random vibration framework. The input base excitation, modeled as a uniformly modulated random process, is characterized through an evolutionary power spectrum. Under such motions, the sum of eigenvalues of the output power spectrum, considered as measurement parameter, is shown to follow an exponential distribution. The FIM is then shown to comprise of the sum of these eigenvalues along with the sensitivities of the output power spectrum to the parameters of interest. Analytical expressions are derived for the different response sensitivities. The approach is illustrated through numerical simulations using a laterally‐torsionally coupled building, and experimental data from shake table tests. The effect of unobserved modes is discussed. It is seen that, while stiffness depending on unobservable modes are not identified or have high estimation uncertainty, the optimal sensor set‐ups for identifying a stiffness and for identifying the modes most sensitive to that stiffness are not necessarily the same. The importance of optimal sensor locations in damage detection is also highlighted through the shake table tests. It is shown that the estimation uncertainties in structural parameters and damage severities are least for optimally located sensors.
Fisher information‐based optimal sensor locations for output‐only structural identification under base excitation
Ghosh, Dhiraj (author) / Mukhopadhyay, Suparno (author)
2022-10-01
27 pages
Article (Journal)
Electronic Resource
English
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