Joseph, G and Zoubi, AB and Murthy, CR and Mathews, VJ (2019) Anomaly Imaging for Structural Health Monitoring Exploiting Clustered Sparsity. In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 12 - 17 May 2019, Brighton, pp. 4255-4259.
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Abstract
This paper presents a new tomography-based anomaly mapping algorithm for composite structures. The system consists of an array of piezoelectric transducers which sequentially excites the structure and collects the resulting waveform at the remaining transducers. Anomaly indices computed from the sensor waveforms are fed as input to the mapping algorithm. The output of the algorithm is a color map indicating the outline of damage on the structure when present. Unlike prior work on this topic, the algorithm of this paper explicitly accounts for both sparsity and cluster pattern structures that are typical of structural anomalies. Hence, the algorithm of this paper provides excellent reconstruction accuracy by incorporating the available prior information on the anomaly map. Experimental results on a unidirectional composite plate confirms that the algorithm of this paper outperforms two competing methods in terms of reconstruction accuracy.
Item Type: | Conference Paper |
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Publication: | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Additional Information: | The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc. |
Keywords: | Audio signal processing; Composite structures; Conformal mapping; Speech communication; Structural health monitoring; Transducers, Bayesian learning; Cluster patterns; Mapping algorithms; Prior information; Reconstruction accuracy; Structural anomaly; Structured sparsities; Unidirectional composites, Clustering algorithms |
Department/Centre: | Division of Electrical Sciences > Electrical Communication Engineering |
Date Deposited: | 30 Nov 2022 05:50 |
Last Modified: | 30 Nov 2022 05:50 |
URI: | https://eprints.iisc.ac.in/id/eprint/78390 |
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