Abstract
The paper investigates the role of model errors and parametric uncertainties in optimal or near optimal sensor placements for structural health monitoring (SHM) and modal testing. The near optimal set of measurement locations is obtained by the Information Entropy theory; the results of placement process considerably depend on the so-called covariance matrix of prediction error as well as on the definition of the correlation function. A constant and an exponential correlation function depending on the distance between sensors are firstly assumed; then a proposal depending on both distance and modal vectors is presented. With reference to a simple case-study, the effect of model uncertainties on results is described and the reliability and the robustness of the proposed correlation function in the case of model errors are tested with reference to 2D and 3D benchmark case studies. A measure of the quality of the obtained sensor configuration is considered through the use of independent assessment criteria. In conclusion, the results obtained by applying the proposed procedure on a real 5-spans steel footbridge are described. The proposed method also allows to better estimate higher modes when the number of sensors is greater than the number of modes of interest. In addition, the results show a smaller variation in the sensor position when uncertainties occur.
Highlights
Modern technologies for structural safety, system identification, and damage detection require control systems to monitor the structural behaviour during the whole operating life
In the subsections two simple numerical case studies are presented to investigate the role played by the covariance matrix of the prediction error and how uncertainties in the structural model could modify results of the sensor placement
The paper investigates the role of the covariance matrix and the correlation function in optimal or near optimal sensor placement for structural health monitoring and modal testing
Summary
Modern technologies for structural safety, system identification, and damage detection require control systems to monitor the structural behaviour during the whole operating life. In a general sensor placement procedure, the estimate of the optimal position is sensitive to errors and uncertainties of the numerical model They can alter the optimal locations of sensors and limit the efficiency of the monitoring systems. The role of the covariance matrix and the correlation function in optimal sensor placement is investigated considering at first a simple case-study without uncertainties. The investigation of the model errors (model form uncertainties and parametric uncertainties) in optimal sensor placement and a new proposal for the correlation function are the main contributions of this paper; it will show that the proposed correlation function allows to take into account the spatial correlation in 3D structures and it could reduce the variability of results in the case of model uncertainties
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