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 …
The unscented Kalman filter and particle filter methods for nonlinear structural system identification with non‐collocated heterogeneous sensing
The use of heterogeneous, non‐collocated measurements for nonlinear structural system
identification is explored herein. In particular, this paper considers the example of sensor …
identification is explored herein. In particular, this paper considers the example of sensor …
[HTML][HTML] An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
The establishment of a Digital Twin of an operating engineered system can increase the
potency of Structural Health Monitoring (SHM) tools, which are then bestowed with …
potency of Structural Health Monitoring (SHM) tools, which are then bestowed with …
A new Kalman filter approach for structural parameter tracking: Application to the monitoring of damaging structures tested on shaking-tables
In this paper, a new data assimilation framework for correcting finite element models from
datasets acquired on-the-fly in low-frequency dynamics is presented. An Unscented Kalman …
datasets acquired on-the-fly in low-frequency dynamics is presented. An Unscented Kalman …
Vehicle sideslip angle measurement based on sensor data fusion using an integrated ANFIS and an Unscented Kalman Filter algorithm
Abstract Most existing ESC (Electronic Stability Control) systems rely on the measurement of
both yaw rate and sideslip angle. However, one of the main issues is that the sideslip angle …
both yaw rate and sideslip angle. However, one of the main issues is that the sideslip angle …
A hybrid optimization algorithm with Bayesian inference for probabilistic model updating
A hybrid optimization methodology is presented for the probabilistic finite element model
updating of structural systems. The model updating process is formulated as an inverse …
updating of structural systems. The model updating process is formulated as an inverse …
Identification of structural models using a modified Artificial Bee Colony algorithm
A modified version of the Artificial Bee Colony (ABC) algorithm is presented to identify
structural systems. ABC is a heuristic algorithm with simple structure, ease of implementation …
structural systems. ABC is a heuristic algorithm with simple structure, ease of implementation …
Novel outlier-resistant extended Kalman filter for robust online structural identification
Structural health monitoring (SHM) using dynamic response measurement has received
tremendous attention over the last decades. In practical circumstances, outliers may exist in …
tremendous attention over the last decades. In practical circumstances, outliers may exist in …
Performance comparison of Kalman− based filters for nonlinear structural finite element model updating
Finite element (FE) model updating has emerged as a powerful technique for structural
health monitoring and damage identification of civil structures. Updating mechanics-based …
health monitoring and damage identification of civil structures. Updating mechanics-based …
Unscented Kalman filter with unknown input and weighted global iteration for health assessment of large structural systems
A Al‐Hussein, A Haldar - Structural Control and Health …, 2016 - Wiley Online Library
A novel concept denoted as unscented Kalman filter with unknown input and weighted
global iterations (UKF‐UI‐WGI) to assess health of large structural systems is proposed. It …
global iterations (UKF‐UI‐WGI) to assess health of large structural systems is proposed. It …