Artificial-neural-network-based surrogate models for structural health monitoring of civil structures: a literature review

A Dadras Eslamlou, S Huang - Buildings, 2022 - mdpi.com
It is often computationally expensive to monitor structural health using computer models.
This time-consuming process can be relieved using surrogate models, which provide cheap …

Combined two-level damage identification strategy using ultrasonic guided waves and physical knowledge assisted machine learning

M Rautela, J Senthilnath, J Moll, S Gopalakrishnan - Ultrasonics, 2021 - Elsevier
Abstract Structural Health Monitoring of composite structures is one of the significant
challenges faced by the aerospace industry. A combined two-level damage identification viz …

Damage characterization using CNN and SAE of broadband Lamb waves

F Gao, J Hua - Ultrasonics, 2022 - Elsevier
The method based on Lamb wave shows great potential for structural health monitoring
(SHM) and nondestructive testing (NDT). Deep learning algorithms including convolutional …

[HTML][HTML] Elastic constants identification of fibre-reinforced composites by using guided wave dispersion curves and genetic algorithm for improved simulations

P Kudela, M Radzienski, P Fiborek, T Wandowski - Composite Structures, 2021 - Elsevier
There is a great potential for model-based approaches in which guided waves are utilised
for damage detection, localisation and size estimation. However, to be effective, the model …

Inverse characterization of composites using guided waves and convolutional neural networks with dual-branch feature fusion

M Rautela, A Huber, J Senthilnath… - … of Advanced Materials …, 2022 - Taylor & Francis
In this work, ultrasonic guided waves and a dual-branch version of convolutional neural
networks are used to solve two different but related inverse problems, ie, finding layup …

Real-time determination of elastic constants of composites via ultrasonic guided waves and deep learning

S Wang, Z Luo, J **g, Z Su, X Wu, Z Ni, H Zhang - Measurement, 2022 - Elsevier
An immediate and convenient report of mechanical properties of composites with full
automation is crucial for timely characterizing the time-dependent degradation of material …

[HTML][HTML] A probabilistic machine learning framework for stiffness tensor estimation of carbon composite laminate

NMM Kalimullah, S Ojha, M Radzieński… - … Systems and Signal …, 2025 - Elsevier
The potential uses of carbon composite material are vast, particularly in the civil, mechanical
and aero-structures. Nonetheless, the practical utilization of carbon composite faces …

Neural-network-based ultrasonic inspection of offshore coated concrete specimens

AKU Malikov, YH Kim, JH Yi, J Kim, J Zhang, Y Cho - Coatings, 2022 - mdpi.com
A thin layer of protective coating material is applied on the surface of offshore concrete
structures to prevent its degradation, thereby extending the useful life of the structures. The …

Machine learning-based orthotropic stiffness identification using guided wavefield data

AH Orta, J De Boer, M Kersemans, C Vens… - Measurement, 2023 - Elsevier
The characterization of the full set of elastic parameters for an orthotropic material is a
complex non-linear inversion problem that requires sophisticated optimization algorithms …

Diagnosis of interior damage with a convolutional neural network using simulation and measurement data

Y Bao, S Mahadevan - Structural Health Monitoring, 2022 - journals.sagepub.com
Current deep learning applications in structural health monitoring (SHM) are mostly related
to surface damage such as cracks and rust. Methods using traditional image processing …