A review on guided-ultrasonic-wave-based structural health monitoring: From fundamental theory to machine learning techniques

Z Yang, H Yang, T Tian, D Deng, M Hu, J Ma, D Gao… - Ultrasonics, 2023 - Elsevier
The development of structural health monitoring (SHM) techniques is of great importance to
improve the structural efficiency and safety. With advantages of long propagation distances …

Advances in dynamic load identification based on data-driven techniques

D Fu, L Wang, G Lv, Z Shen, H Zhu, WD Zhu - Engineering Applications of …, 2023 - Elsevier
Dynamic loads on engineering structures are often difficult to measure directly. Therefore,
indirect identification methods based on dynamic responses are commonly used. However …

TanhExp: A smooth activation function with high convergence speed for lightweight neural networks

X Liu, X Di - IET Computer Vision, 2021 - Wiley Online Library
Lightweight or mobile neural networks used for real‐time computer vision tasks contain
fewer parameters than normal networks, which lead to a constrained performance. Herein, a …

A feature learning-based method for impact load reconstruction and localization of the plate-rib assembled structure

T Chen, L Guo, A Duan, H Gao… - Structural Health …, 2022 - journals.sagepub.com
Impact load is the load that machines frequently experienced in engineering applications. Its
time-history reconstruction and localization are crucial for structural health monitoring and …

Structural health monitoring impact classification method based on Bayesian neural network

H Yu, AH Seno, Z Sharif Khodaei, MHF Aliabadi - Polymers, 2022 - mdpi.com
This paper proposes a novel method for multi-class classification and uncertainty
quantification of impact events on a flat composite plate with a structural health monitoring …

Uncertainty quantification for impact location and force estimation in composite structures

AH Seno, MHF Aliabadi - Structural Health Monitoring, 2022 - journals.sagepub.com
Structural health monitoring of impact location and severity using Lamb waves has been
proven to be a reliable method under laboratory conditions. However, real-life operational …

Input estimation of nonlinear systems using probabilistic neural network

SS Eshkevari, L Cronin, SS Eshkevari… - Mechanical Systems and …, 2022 - Elsevier
Input estimation is an involved task with wide applications in nonlinear dynamic systems.
Model-based input estimation methods are not feasible solutions for problems in which the …

A non-negative Bayesian learning method for impact force reconstruction

G Yan, H Sun - Journal of Sound and Vibration, 2019 - Elsevier
Detecting and identifying impact events, which may cause severe damages, is important in
assessment of the integrity of many engineering structures. This paper presents a new …

Measurement and prediction of vibration displacement in micro-milling of nickel-based superalloy

X Lu, Z Jia, X Wang, Y Liu, M Liu, Y Feng, SY Liang - Measurement, 2019 - Elsevier
The relative vibration between the micro-milling cutter and workpiece influences the
processing quality and tool life. To solve the difficult problem of measurement of vibration …

[HTML][HTML] Impact force identification for composite structures using adaptive wavelet-regularised deconvolution

D Xiao, Z Sharif-Khodaei, MH Aliabadi - Mechanical Systems and Signal …, 2024 - Elsevier
Impact force identification (IFI) through deconvolution methods from measured structural
responses poses a challenge due to the ill-posed nature of the inversion problem …