Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties
Civil Engineering and Engineering Mechanics, The University of Arizona, Tucson, AZ 85721, USA
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Sensors 2017, 17(11), 2656; https://doi.org/10.3390/s17112656
Received: 31 August 2017 / Revised: 2 November 2017 / Accepted: 6 November 2017 / Published: 17 November 2017
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications 2017)
Direct measurements of external forces acting on a structure are infeasible in many cases. The Augmented Kalman Filter (AKF) has several attractive features that can be utilized to solve the inverse problem of identifying applied forces, as it requires the dynamic model and the measured responses of structure at only a few locations. But, the AKF intrinsically suffers from numerical instabilities when accelerations, which are the most common response measurements in structural dynamics, are the only measured responses. Although displacement measurements can be used to overcome the instability issue, the absolute displacement measurements are challenging and expensive for full-scale dynamic structures. In this paper, a reliable model-based data fusion approach to reconstruct dynamic forces applied to structures using heterogeneous structural measurements (i.e., strains and accelerations) in combination with AKF is investigated. The way of incorporating multi-sensor measurements in the AKF is formulated. Then the formulation is implemented and validated through numerical examples considering possible uncertainties in numerical modeling and sensor measurement. A planar truss example was chosen to clearly explain the formulation, while the method and formulation are applicable to other structures as well.
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Keywords:
force estimation; heterogeneous sensor network; Kalman filtering; multi-metric measurements; structural dynamics
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MDPI and ACS Style
Khodabandeloo, B.; Melvin, D.; Jo, H. Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties. Sensors 2017, 17, 2656. https://doi.org/10.3390/s17112656
AMA Style
Khodabandeloo B, Melvin D, Jo H. Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties. Sensors. 2017; 17(11):2656. https://doi.org/10.3390/s17112656
Chicago/Turabian StyleKhodabandeloo, Babak; Melvin, Dyan; Jo, Hongki. 2017. "Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties" Sensors 17, no. 11: 2656. https://doi.org/10.3390/s17112656
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