Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights

A Malekloo, E Ozer, M AlHamaydeh… - Structural Health …, 2022 - journals.sagepub.com
Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …

Fracture mode identification in cementitious materials using supervised pattern recognition of acoustic emission features

A Farhidzadeh, AC Mpalaskas, TE Matikas… - … and building materials, 2014 - Elsevier
Cracking in concrete as a ubiquitous cementitious material in civil structures has been a
worldwide critical issue in the field of engineering. Acoustic emission (AE) has demonstrated …

Rock crack type identification by Gaussian process learning on acoustic emission

J Jiang, G Su, Z Yan, Z Zheng, X Hu - Applied Acoustics, 2022 - Elsevier
A good understanding of crack development helps reveal the mechanism of different rock
failures. Identification of crack types (tensile or shear) can be a useful tool for characterizing …

Unsupervised learning for classification of acoustic emission events from tensile and bending experiments with open-hole carbon fiber composite samples

HA Sawan, ME Walter, B Marquette - Composites Science and Technology, 2015 - Elsevier
Widespread use of composites for structural applications is hindered by the inability to fully
understand and predict the materials response. The uncertainty in composite materials …

Damage evolution of polymer matrix composites reinforced by nanoparticles modified under the three-point bending test by acoustic emission methods

S Shayanfar, M Nikkhah… - Journal of …, 2023 - journals.sagepub.com
This study aimed to investigate the behavior, and failure resistance of composite materials,
and the effect of nanoparticles on their flexural properties. Nanoparticles with different …

Quantitative investigation of acoustic emission waveform parameters from crack opening in a rail section using clustering algorithms and advanced signal processing

H Mahajan, S Banerjee - Sensors, 2022 - mdpi.com
Acoustic emission (AE) is an emerging technology for real-time non-destructive testing of
structures. While research on a simulated AE source in rail and testing on rail material using …

An entropy-based probabilistic model for acoustic emission RA-value-average‎ frequency data

P Bazrafshan… - Health Monitoring of …, 2024 - spiedigitallibrary.org
This study presents an innovative method for probabilistic modeling of acoustic emission by
applying the principles of maximum entropy and utilizing a non-Gaussian probability …

[PDF][PDF] Support vector machine procedure and gaussian mixture modelling of acoustic emission signals to study crack classification in reinforced concrete structures

RV Sagar - Proceedings of the 10th International Conference on …, 2019 - framcos.org
Four point bending tests on reinforced concrete (RC) beam specimens were carried out and
simultaneously released Acoustic Emissions (AE) were recorded in laboratory. This study …

Aspects temporels dans l'interprétation des données d'émission acoustique: importance de critères de validation adaptés et pertinence de méthodes variationnelles …

MM Nkogo - 2022 - theses.hal.science
La technique de l'émission acoustique est une méthode passive et non destructive
d'évaluation de l'état de santé des structures. Sous contrainte, les structures libèrent de …

[PDF][PDF] Application of Clustering System in Acoustic Emission Monitoring of Reinforced concrete structures: A Preliminary Study

P Mirgal, H Mahajan, S Banerjee - researchgate.net
The Acoustic Emission (AE) technique has gained popularity over the last two decades as a
monitoring methodology and assessment tool for evaluating the safety and reliability of …