A feature extraction & selection benchmark for structural health monitoring
T Buckley, B Ghosh, V Pakrashi - Structural Health …, 2023 - journals.sagepub.com
There are a large number of time domain, frequency domain and time-frequency signal
processing methods available for univariate feature extraction. However, there is no …
processing methods available for univariate feature extraction. However, there is no …
Structural damage identification using improved Jaya algorithm based on sparse regularization and Bayesian inference
Structural damage identification can be considered as an optimization problem, by defining
an appropriate objective function relevant to structural parameters to be identified with …
an appropriate objective function relevant to structural parameters to be identified with …
Time-frequency domain methods for the identification of breathing cracks in beam-like structures
Breathing cracks in beam-like structures are common types of damage that occur due to
long-term cyclic loading, which makes the identification and assessment of breathing cracks …
long-term cyclic loading, which makes the identification and assessment of breathing cracks …
Damage quantification using transfer component analysis combined with Gaussian process regression
M Omori Yano, S da Silva… - Structural Health …, 2023 - journals.sagepub.com
Machine learning methods used in Structural Health Monitoring applications still have
generalization difficulties among structures, even when structures are nominally and …
generalization difficulties among structures, even when structures are nominally and …
The dual Fourier transform spectra (DFTS): a new nonlinear damage indicator for identification of breathing cracks in beam-like structures
Fatigue damage is a common type of structural damage associated with long-term cyclic
loading operating on engineering structures. Within the fatigue damage phenomenon, the …
loading operating on engineering structures. Within the fatigue damage phenomenon, the …
Decoding electroencephalography signal response by stacking ensemble learning and adaptive differential evolution
Electroencephalography (EEG) is an exam widely adopted to monitor cerebral activities
regarding external stimuli, and its signals compose a nonlinear dynamical system. There are …
regarding external stimuli, and its signals compose a nonlinear dynamical system. There are …
Damage detection of nonlinear structures using probability density ratio estimation
Y Zhang, JHG Macdonald, S Liu… - Computer‐Aided Civil …, 2022 - Wiley Online Library
This study focuses on vibration‐based damage detection for a structure that has nonlinear
behavior even in the undamaged state. Based on the vibration responses of a single sensor …
behavior even in the undamaged state. Based on the vibration responses of a single sensor …
A novel DISTINCT method for characterizing breathing features of nonlinear damage in structures
The detection of breathing cracks in in-service structures is an intractable issue due to the
distinctive dynamic behavior, typically the opening and closing of the crack subjected to …
distinctive dynamic behavior, typically the opening and closing of the crack subjected to …
Structural damage identification considering uncertainties in nonuniform measurement conditions based on convolution neural networks
S Zhu, T Xiang - Structural Control and Health Monitoring, 2023 - Wiley Online Library
Dynamic‐vibration‐based structural damage identification (SDI) represents the main target
for structural health monitoring (SHM). It is significant to consider the unavoidable …
for structural health monitoring (SHM). It is significant to consider the unavoidable …
Damage detection in an uncertain nonlinear beam based on stochastic Volterra series: an experimental application
The damage detection problem becomes a more difficult task when the intrinsically
nonlinear behavior of the structures and the natural data variation are considered in the …
nonlinear behavior of the structures and the natural data variation are considered in the …