Πλοήγηση ανά Θέμα "Optimal sensor placement"
Αποτελέσματα 1-13 από 13
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Bayesian optimal sensor placement for crack identification in structures using strain measurements
(2018)A Bayesian framework is presented for finding the optimal locations of strain sensors in a plate with a crack with the goal of identifying the crack properties, such as crack location, size, and orientation. Sensor grids ... -
The effect of prediction error correlation on optimal sensor placement in structural dynamics
(2012)The problem of estimating the optimal sensor locations for parameter estimation in structural dynamics is re-visited. The effect of spatially correlated prediction errors on the optimal sensor placement is investigated. ... -
Information-driven modeling of structures using a Bayesian framework
(2018)This work presents a comprehensive Bayesian framework for integrating information from data and models of civil infrastructure systems. In the proposed framework, modeling uncertainties are quantified and propagated through ... -
Optimal experimental design for structural health monitoring applications
(2008)Successful structural health monitoring and condition assessment depends to a large extent on the sensor and actuator networks place on the structure as well as the excitation characteristics. An optimal experimental design ... -
Optimal Experimental Design Methodology for Parameter Estimation of Nonlinear Models
(2021)Experimental data are used to improve structural models and model-based predictions of output quantities of interest (QoI), that are crucial in making decisions regarding structural health, safety and performance. The ... -
Optimal sensor placement for artificialA swimmers
(2019)Natural swimmers rely for their survival on sensors that gather information from the environment and guide their actions. The spatial organization of these sensors, such as the visual fish system and lateral line, suggests ... -
Optimal sensor placement for multi-setup modal analysis of structures
(2017)Modal tests on large structures are often performed in multiple setups for practical reasons. Several sensors are kept fixed as reference sensors over all setups, while the other, so called roving sensors, are moved from ... -
Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost
(2022)This paper proposes an optimal sensor placement (OSP) framework for parameter estimation, virtual sensing, and condition monitoring using information theory. The framework uses a Bayesian OSP method combined with modal ... -
Optimal sensor placement for reliable virtual sensing using modal expansion and information theory
(2021)A framework for optimal sensor placement (OSP) for virtual sensing using the modal expansion technique and taking into account uncertainties is presented based on information and utility theory. The framework is developed ... -
Optimal sensor placement for response predictions using local and global methods
(2020)A Bayesian framework for model-based optimal sensor placement for response predictions is presented. Our interest lies in determining the parameters of the model in order to make predictions about a particular response ... -
Robust Bayesian optimal sensor placement for model parameter estimation and response predictions
(2020)Optimal sensor placement (OSP) in complex systems implies a configuration that maximizes the information gain by the sensors. This configuration is identified by maximizing, with respect to the location of the sensors, an ... -
Robust optimal sensor placement for response reconstruction using output-only vibration measurements
(2020)Vibration measurements taken from various locations in a structure are used to improve models and model-based predictions of output quantities of interest (QoI). Such improved models and predictions can be used to update ... -
A unified sampling-based framework for optimal sensor placement considering parameter and prediction inference
(2021)We present a Bayesian framework for model-based optimal sensor placement. Our interest lies in minimizing the uncertainty on predictions of a particular response quantity of interest, with parameter estimation being an ...