Embedded Sensors for In-Situ Strain Monitoring in Composite Structure
Randjbaran, Elias, Khaksari, Darya, AHMAD MEHRABI, HAMID, Zahari, Rizal, Majid, Dayang L., Sultan, Mohamed T.H. and Mazlan, Norkhairunnisa (2025) Embedded Sensors for In-Situ Strain Monitoring in Composite Structure. New Environmentally Friendly Materials, 2 (4). ISSN 2538-3744
| Item Type: | Article |
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Abstract
Continuous in-situ strain monitoring is vital for assessing the structural integrity and in-service performance of
large-scale composite structures in sectors like aerospace and wind energy. This review provides a comprehensive
analysis of methodologies for integrating sensor technologies to facilitate such monitoring. It encompasses established
and emerging approaches, including Fibre Bragg Gratings (FBGs), piezoelectric transducers, and novel solutions like
graphene-based sensors and MXene fibres. Beyond their operating principles, the review pays particular attention
to vibration-based techniques that exploit nonlinear dynamic responses induced by damage. A critical appraisal is presented of the challenges of embedding these technologies, addressing manufacturing integration and the preservation
of functional reliability under operational stressors. The article also considers key system-level requirements, including
robust data acquisition, effective signal processing, and long-term durability. A central finding is the inherent trade�off between sensor performance and structural integrity; FBGs offer high precision but can reduce interlaminar shear
strength, whilst emerging solutions like MXene fibres show exceptional sensitivity but face durability challenges. The
synthesis underscores significant advancements—from high-accuracy sensor localisation and nanotechnology in sensor
fabrication, to autonomous, self-powered frameworks—alongside persistent, multidisciplinary challenges in creating
validated and scalable systems. We conclude that the convergence of advanced sensing materials with intelligent data
analytics is decisively transforming composites into intelligent, self-diagnosing systems.
Keywords: Composite SHM; In-Situ Strain Monitoring; Vibration Monitoring; Sensor Integration; Smart Structures;
Machine Learning Applications
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| Uncontrolled Keywords: Composite SHM, In-Situ Strain Monitoring, Vibration Monitoring, Sensor IntegrationS, Smart Structures, Machine Learning Applications |
| Depositing User: Hamid Ahmad Mehrabi |
Identifiers
| Item ID: 19770 |
| Identification Number: 10.55121/nefm.v4i2.510 |
| ISSN: 2538-3744 |
| URI: https://sure.sunderland.ac.uk/id/eprint/19770 | Official URL: https://ojs.bilpub.com/index.php/nefm/article/view... |
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Catalogue record
| Date Deposited: 22 Dec 2025 12:18 |
| Last Modified: 22 Dec 2025 12:18 |
| Author: |
HAMID AHMAD MEHRABI
|
| Author: | Elias Randjbaran |
| Author: | Darya Khaksari |
| Author: | Rizal Zahari |
| Author: | Dayang L. Majid |
| Author: | Mohamed T.H. Sultan |
| Author: | Norkhairunnisa Mazlan |
University Divisions
Faculty of Business and TechnologySubjects
Engineering > Mechanical EngineeringEngineering
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