Integrating structural control, health monitoring, and energy harvesting for smart cities
S Javadinasab Hormozabad, M Gutierrez Soto… - Expert …, 2021 - Wiley Online Library
Cities that are adopting innovative and technology‐driven solutions to improve the city's
efficiency are considered smart cities. With the increased attention on smart cities with self …
efficiency are considered smart cities. With the increased attention on smart cities with self …
Auto-regressive model based input and parameter estimation for nonlinear finite element models
A novel framework to accurately estimate nonlinear structural model parameters and
unknown external inputs (ie, loads) using sparse sensor networks is proposed and …
unknown external inputs (ie, loads) using sparse sensor networks is proposed and …
Switching Kalman filter for damage estimation in the presence of sensor faults
Bayesian filtering based approaches for diagnosis of structural damage have been widely
employed in structural health monitoring (SHM) research. The approach however may lead …
employed in structural health monitoring (SHM) research. The approach however may lead …
Estimation of local failure in tensegrity using Interacting Particle-Ensemble Kalman Filter
Tensegrities form a special case of truss, wherein compression members (struts/bars) float
within a network of tension members (cables). Tensegrities are characterized by the …
within a network of tension members (cables). Tensegrities are characterized by the …
A generalized extended Kalman particle filter with unknown input for nonlinear system‐input identification under non‐Gaussian measurement noises
Y Lei, J Lai, J Huang, C Qi - Structural Control and Health …, 2022 - Wiley Online Library
It is necessary to investigate the identification of structural systems and unknown inputs
under non‐Gaussian measurement noises. In recent years, a few scholars have proposed …
under non‐Gaussian measurement noises. In recent years, a few scholars have proposed …
Structural health monitoring with non-linear sensor measurements robust to unknown non-stationary input forcing
Bayesian filtering based structural health monitoring algorithms typically assume stationary
white Gaussian noise models to represent an unknown input forcing. However, typical …
white Gaussian noise models to represent an unknown input forcing. However, typical …
Multimetric event-driven system for long-term wireless sensor operation for SHM applications
Wireless sensor networks (WSNs) are promising solutions for large infrastructure monitoring
because of their ease of installation, computing and communication capability, and cost …
because of their ease of installation, computing and communication capability, and cost …
Zero-shot knowledge transfer for seismic damage diagnosis through multi-channel 1D CNN integrated with autoencoder-based domain adaptation
Accurate and timely structural damage diagnosis is crucial to efficient disaster response and
city renovation in post-earthquake events. The scarcity of labeled data hinders the powerful …
city renovation in post-earthquake events. The scarcity of labeled data hinders the powerful …
Strain‐based joint damage estimation approach robust to unknown non‐stationary input force
To avert catastrophic failure in the structures, joints are typically designed to yield, but not
fail, so that energy accumulated under cyclic loading is dissipated. Eventually, this renders …
fail, so that energy accumulated under cyclic loading is dissipated. Eventually, this renders …
Online decentralized parameter estimation of structural systems using asynchronous data
K Huang, KV Yuen - Mechanical Systems and Signal Processing, 2020 - Elsevier
This paper presents an online decentralized parameter estimation approach for structural
systems using asynchronous data. This is motivated by the problems encountered in …
systems using asynchronous data. This is motivated by the problems encountered in …