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Enhanced Identification of Damage Evolution in Two-Dimensional Woven Laminated Materials Through Multimodal Information Fusion of Acousto-Optic-Force Data

https://doi.org/10.2139/ssrn.4753504
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A waveform-based clustering and machine learning method for damage mode identification in CFRP laminates
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Nonlinear progressive damage model for woven patch-repaired laminate composites
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Fatigue damage monitoring of composite laminates based on acoustic emission and digital image correlation techniques
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Failure characterisation of sandwich beams using integrated acoustic emission and digital image correlation techniques
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A novel damage evaluation of CFRPs under mode-I loading by using multi-instrument structural health monitoring methods
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Study of post-impact behaviour of thin carbon/epoxy laminates subject to fatigue tensile loading
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Identifying damage mechanisms of composites by acoustic emission and supervised machine learning
inferredcites →https://doi.org/10.1016/j.measurement.2018.11.027openalex-extracted
Identification of mechanical parameters of composites in tensile tests using mixed numerical-experimental method
inferredcites →https://doi.org/10.1016/j.ndteint.2023.102815openalex-extracted
Miniaturized multi-modality field-ready sensing system for defect detection of CFRP materials
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Transverse indentation response and residual axial compressive characteristics of metal-composites hybrid tubes by deep learning-based acoustic emission and micro-CT
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State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission
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A Review on Acoustic Emission Testing for Structural Health Monitoring of Polymer-Based Composites
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