Importance Sampling and Feature Fusion Paradigm-Boosted Multi-Modal Convolutional Neural Networks: Deployment in Composite Curing Process Monitored by Electro-Mechanical Impedance

Importance Sampling and Feature Fusion Paradigm-Boosted Multi-Modal Convolutional Neural Networks: Deployment in Composite Curing Process Monitored by Electro-Mechanical Impedance

The increasing application of composite materials in various industrial sectors is driven by their lightweight nature, high strength-to-stiffness ratio, and corrosion resistance. Effective monitoring of the curing process is crucial for ensuring quality and performance. Electro-Mechanical Impedance...

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Bibliographic Details
Main Authors: Xin Zhao, Zeyuan Gao, Meng Li, Zhibin Han, Jianjian Zhu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Composite curing
convolutional neural networks
electro-mechanical impedance
importance sampling algorithm
multi-modal learning
Online Access:https://ieeexplore.ieee.org/document/10930734/
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