Dual-Modality-Integrated Planar Sensor of ECT and EMT for CFRPs Damage Detection
In this article, an electrical capacitance tomography (ECT)/electromagnetic tomography (EMT) dual-modality planar sensor for damage detection of carbon fiber-reinforced plastics (CFRPs) is proposed. When CFRP has different damages, the dielectric constant and conductivity will undergo different slight changes, so it is difficult for a single-modality electrical sensor to accurately detect multiple damages. The design of the ECT/EMT dual-modality planar sensor aims to overcome the limitations of single-modality sensors in detecting small-area damage and subtle changes in electrical parameters. The ECT modality is used to detect the change in dielectric constant, and the EMT modality is used to detect the change in conductivity. The two modalities are integrated in the same sensor to obtain more comprehensive damage information in a single detection. In order to use the sensor to detect damage more accurately, CFRP is simulated and modeled at the mesoscopic level to quantify the changes in its dielectric constant and conductivity when it is damaged. The image reconstruction of the measurement data of the dual-modality planar sensor is carried out by using the Iterative Method with Adaptive Thresholding for Compressed Sensing (IMATCS) based on L2 regularization method. Since the area of CFRP damage is small, the matrix reconstructed by IMATCS is a sparse matrix, which can better determine the damage range and location. The results show that the method proposed in this article can accurately detect the fracture, delamination of CFRP samples, and impact damage and their locations. Compared to other traditional algorithms, the correlation coefficient (CC) of L2-IMATCS is approximately 4.8% higher. Compared to single-modal sensors ECT and EMT, the CC of dual-modal sensors is approximately 50% and 36% higher, respectively.
Authors
- Shidong Jia (ORCID: https://orcid.org/0009-0006-3823-8227)
- Xuefeng Bai (ORCID: https://orcid.org/0000-0002-9973-5247)
- Wenying Fu (ORCID: https://orcid.org/0009-0003-9647-7240)
- Jialing Le (ORCID: https://orcid.org/0009-0007-0762-5336)
- Wuliang Yin (ORCID: https://orcid.org/0000-0001-5927-3052)
- Boyang Li (ORCID: https://orcid.org/0000-0002-6230-2376)
- Ronghua Zhang (ORCID: https://orcid.org/0000-0002-4758-4061)
Institutions
- Tiangong University (CN)
- University of Manchester (GB)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1109/jsen.2025.3531651
- Primary Topic
- Non-Destructive Testing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China