A novel machine learning‐based algorithm to detect damage in high‐rise building structures
A novel model is presented for global health monitoring of large structures such as high‐rise
building structures through adroit integration of 2 signal processing techniques …
building structures through adroit integration of 2 signal processing techniques …
Vision‐based multipoint displacement measurement for structural health monitoring
A novel noncontact vision sensor for simultaneous measurement of structural displacements
at multiple points using one camera is developed based on two advanced template …
at multiple points using one camera is developed based on two advanced template …
A novel methodology for modal parameters identification of large smart structures using MUSIC, empirical wavelet transform, and Hilbert transform
A key issue in health monitoring of smart structures is the estimation of modal parameters
such as natural frequencies and damping ratios from acquired dynamic signals. In this …
such as natural frequencies and damping ratios from acquired dynamic signals. In this …
New method for modal identification of super high‐rise building structures using discretized synchrosqueezed wavelet and Hilbert transforms
Measured signals obtained by sensors during dynamic events such as earthquake, wind,
and wave contain nonlinear, nonstationary, and noisy properties. In this paper, a new …
and wave contain nonlinear, nonstationary, and noisy properties. In this paper, a new …
Identification of structural stiffness and excitation forces in time domain using noncontact vision-based displacement measurement
The emerging noncontact vision-based displacement sensor system offers a promising
alternative to the conventional sensors for quantitative structural integrity assessment …
alternative to the conventional sensors for quantitative structural integrity assessment …
Incremental Bayesian matrix/tensor learning for structural monitoring data imputation and response forecasting
There has been increased interest in missing sensor data imputation, which is ubiquitous in
the field of structural health monitoring (SHM) due to discontinuous sensing caused by …
the field of structural health monitoring (SHM) due to discontinuous sensing caused by …
New fundamental period formulae for soil-reinforced concrete structures interaction using machine learning algorithms and ANNs
The importance of designing safe and economic structures in seismically active areas is of
great importance. Thus, developing tools that would help in accurately predicting the …
great importance. Thus, developing tools that would help in accurately predicting the …
Impact force reconstruction and localization using nonconvex overlapping group sparsity
Although extensively studied, impact force identification is still a challenging task. When the
location of the impact force is unknown, an under-determined problem is usually required to …
location of the impact force is unknown, an under-determined problem is usually required to …
Probabilistic updating of building models using incomplete modal data
H Sun, O Büyüköztürk - Mechanical Systems and Signal Processing, 2016 - Elsevier
This paper investigates a new probabilistic strategy for Bayesian model updating using
incomplete modal data. Direct mode matching between the measured and the predicted …
incomplete modal data. Direct mode matching between the measured and the predicted …
Sparse Bayesian learning for structural damage identification
Identification of structural parameters can be cast as the process of solving an inverse
problem, in which regularization may be required when the problem is ill-posed. Bayesian …
problem, in which regularization may be required when the problem is ill-posed. Bayesian …