A spatiotemporal dual kalman filter for the estimation of states and distributed inputs in dynamical systems
Abstract
The fusion of Gaussian Process (GP) models with the Dual Kalman Filter (DKF) is proposed in this contribution, with the aim of recursively estimating the state and distributed input in dynamical systems using a limited number of vibration response measurements. To do so, the distributed system excitation is represented by a GP model, enabling thus the implementation of a space-time filtering approach for the input process, which is then coupled with a Kalman filter for the state estimation of system dynamics. The proposed approach is assessed in terms of a simulated case study on the finite element model of a wind turbine blade under operational conditions, which is excited by a distributed drag and lift load along the length of the blade. Show more
Publication status
publishedBook title
International Conference on Noise and Vibration Engineering (ISMA 2020) and International Conference on Uncertainty in Structural Dynamics (USD 2020)Pages / Article No.
Publisher
CurranEvent
Organisational unit
03890 - Chatzi, Eleni / Chatzi, Eleni
Notes
Conference lecture held on September 7, 2020. Due to the Coronavirus (COVID-19) the conference was conducted virtually.More
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