Sen, D and Nagarajaiah, S and Gopalakrishnan, S (2017) Harnessing sparsity in lamb wave-based damage detection for beams. In: Structural Monitoring and Maintenance, 4 (4). pp. 381-396.
Full text not available from this repository.Abstract
Structural health monitoring (SHM) is a necessity for reliable and efficient functioning of engineering systems. Damage detection (DD) is a crucial component of any SHM system. Lamb waves are a popular means to DD owing to their sensitivity to small damages over a substantial length. This typically involves an active sensing paradigm in a pitch-catch setting, that involves two piezo-sensors, a transmitter and a receiver. In this paper, we propose a data-intensive DD approach for beam structures using high frequency signals acquired from beams in a pitch-catch setting. The key idea is to develop a statistical learning-based approach, that harnesses the inherent sparsity in the problem. The proposed approach performs damage detection, localization in beams. In addition, quantification is possible too with prior calibration. We demonstrate numerically that the proposed approach achieves 100 accuracy in detection and localization even with a signal to noise ratio of 25 dB.
| Item Type: | Journal Article |
|---|---|
| Publication: | Structural Monitoring and Maintenance |
| Publisher: | Techno Press |
| Additional Information: | The copyright for this article belongs to the Techno Press. |
| Keywords: | Damage detection; Lamb waves; Sparsity; Statistical learning |
| Department/Centre: | Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering) |
| Date Deposited: | 15 Jul 2022 11:20 |
| Last Modified: | 15 Jul 2022 11:20 |
| URI: | https://eprints.iisc.ac.in/id/eprint/74451 |
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