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ToolsSingh, Shishir K., Sikdar, Shirsendu and Malinowski, Pawel H. (2021) An optimized data fusion strategy for structural damage assessment using electromechanical impedance. Smart Materials and Structures, 30 (3). ISSN 0964-1726
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Abstract
This paper proposes a new sensor network optimized data fusion approach for structural health monitoring of metallic structures using electromechanical impedance (EMI) signals. The integrated approach used to fuse common healthy state baseline model based damage detection, quantification and classification in EMI technique. Towards this, the principal component analysis (PCA) is carried out and corresponding the root mean square deviation (RMSD) index is calculated to study the information of piezoelectric transducer’s impedance (|Z|), admittance (|Y|), resistance (R), and conductance (G) in the frequency domain. A new optimized data fusion approach is proposed which was realized at the sensor level using the PCA as well as at the variable level using self-organizing maps (SOMs). The SOM comparative studies are performed using the Q-statistics (Q index) and the Hotelling’s T2 statistic (T index). The proposed methodology is tested and validated for an aluminum plate with multiple drilled holes with variable size and locations. In the process, a centralized data-fused baseline eigenvector is prepared from a healthy structure and the damage responses are projected on this baseline model. The statistical, data-driven damage matrices are calculated and compared with the RMSD index and used in a fusion based data classification using SOM. The proposed method shows robust damage sensitivity for hole locations and hole enlargement irrespective of the wide frequency range selection, and the selected frequency range contains the resonant frequency range.
| Item Type: | Article |
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| Additional Information: | Acknowledgements: The authors acknowledge the funding support provided by National Science Center, Poland under SONATA BIS project entitled: Study of piezoelectric sensors placement and their interaction with structural elements (2016/22/E/ST8/00068). Shirsendu Sikdar would like to acknowledge the support by the Research Foundation-Flanders (FWO), Belgium under grant agreement no. FWO.3E0.2019.0102.01. The authors are also grateful to TASK-CI for allowing the use of their computational resources. |
| Uncontrolled Keywords: | data fusion,electromechanical impedance,principal component analysis,self-organizing map,sensor network,structural health monitoring,signal processing,civil and structural engineering,atomic and molecular physics, and optics,materials science(all),condensed matter physics,mechanics of materials,electrical and electronic engineering ,/dk/atira/pure/subjectarea/asjc/1700/1711 |
| Faculty \ School: | Faculty of Science > School of Engineering (former - to 2024) |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 13 Oct 2021 02:17 |
| Last Modified: | 25 Sep 2024 15:53 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/81677 |
| DOI: | 10.1088/1361-665X/abdc07 |
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