A dual Kalman filter approach for state estimation via output-only acceleration measurements
A dual implementation of the Kalman filter is proposed for estimating the unknown input and
states of a linear state-space model by using sparse noisy acceleration measurements. The …
states of a linear state-space model by using sparse noisy acceleration measurements. The …
Fault detection, isolation and quantification from Gaussian residuals with application to structural damage diagnosis
Despite the general acknowledgment in the Fault Detection and Isolation (FDI) literature that
FDI are typically accomplished in two steps, namely residual generation and residual …
FDI are typically accomplished in two steps, namely residual generation and residual …
Vibration-based structural health monitoring under changing environmental conditions using Kalman filtering
A Kalman filtering based framework for structural damage assessment under changing
environmental conditions is presented. The approach is based on the well-known property …
environmental conditions is presented. The approach is based on the well-known property …
Subspace-based damage detection under changes in the ambient excitation statistics
In the last ten years, monitoring the integrity of the civil infrastructure has been an active
research topic, including in connected areas as automatic control. It is common practice to …
research topic, including in connected areas as automatic control. It is common practice to …
Sequential Bayesian estimation of state and input in dynamical systems using output-only measurements
The problem of joint estimation of the state and input in linear time-invariant dynamical
systems is revisited proposing novel sequential Bayesian formulations. An appealing feature …
systems is revisited proposing novel sequential Bayesian formulations. An appealing feature …
An adaptive unscented Kalman filter for tracking sudden stiffness changes
The paper presents an approach to track sudden changes in stiffness of structural systems
exposed to earthquake induced base excitations. Such sudden changes in the stiffness …
exposed to earthquake induced base excitations. Such sudden changes in the stiffness …
Input-state-parameter-noise identification and virtual sensing in dynamical systems: A Bayesian expectation-maximization (BEM) perspective
Structural identification and damage detection can be generalized as the simultaneous
estimation of input forces, physical parameters, and dynamical states. Although Kalman-type …
estimation of input forces, physical parameters, and dynamical states. Although Kalman-type …
Real-time simultaneous input-state-parameter estimation with modulated colored noise excitation
This paper introduces a novel method for real-time simultaneous input-state-parameter
estimation with modulated colored noise excitation. In this method, the unknown inputs are …
estimation with modulated colored noise excitation. In this method, the unknown inputs are …
Adaptive constrained unscented Kalman filtering for real‐time nonlinear structural system identification
The unscented Kalman filter (UKF) is often used for nonlinear system identification in civil
engineering; nevertheless, the application of the UKF to highly nonlinear structures could …
engineering; nevertheless, the application of the UKF to highly nonlinear structures could …
Generalized minimum variance unbiased joint input-state estimation and its unscented scheme for dynamic systems with direct feedthrough
W Song - Mechanical Systems and Signal Processing, 2018 - Elsevier
This paper proposes a joint input-state estimation technique that can estimate unknown
inputs, states and parameters of dynamic systems with direct feedthrough. The estimation is …
inputs, states and parameters of dynamic systems with direct feedthrough. The estimation is …