Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)

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Structural Health Monitoring Technology: Advances in Multi-Modal Sensing and Data Fusion

Authors
Xin Sui1, *
1Process Equipment and Control Engineering, Dalian University of Technology, Dalian, Liaoning, 116000, China
*Corresponding author. Email: xs151@student.le.ac.uk
Corresponding Author
Xin Sui
Available Online 23 October 2025.
DOI
10.2991/978-94-6463-864-6_80How to use a DOI?
Keywords
Shm; Multi-Modal Sensing; Ifem; Data Fusion
Abstract

Structural Health Monitoring (SHM) plays a vital role in ensuring the safety and longevity of engineering systems, especially in aerospace applications. However, the anisotropy and concealed damage mechanisms of composite materials present significant challenges to conventional monitoring techniques. Recent advancements have focused on multi-modal sensing technologies, such as fiber optic sensors (e.g., distributed gratings) and piezoelectric sensor networks, which offer high sensitivity, real-time capability, and multiplexing benefits. In parallel, the inverse finite element method (iFEM) has emerged as a powerful tool for reconstructing structural displacements from distributed strain data, though its computational load calls for data-driven optimization strategies. Multi-sensor fusion approaches enable more accurate, hierarchical damage detection in composite aircraft structures. Despite these advancements, challenges remain in adapting to harsh environments, ensuring sensor durability, and achieving real-time data processing. Future directions include self-powered smart sensor networks, digital twin integration, and transfer learning for improved generalization under data-scarce conditions, paving the way for intelligent, lightweight SHM systems.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)
Series
Advances in Engineering Research
Publication Date
23 October 2025
ISBN
978-94-6463-864-6
ISSN
2352-5401
DOI
10.2991/978-94-6463-864-6_80How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Xin Sui
PY  - 2025
DA  - 2025/10/23
TI  - Structural Health Monitoring Technology: Advances in Multi-Modal Sensing and Data Fusion
BT  - Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)
PB  - Atlantis Press
SP  - 924
EP  - 941
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-864-6_80
DO  - 10.2991/978-94-6463-864-6_80
ID  - Sui2025
ER  -