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ANOMALY IMAGING FOR STRUCTURAL HEALTH MONITORING EXPLOITING CLUSTERED SPARSITY

Citation Author(s):
Geethu Joseph, Ahmad B. Zoubi, Chandra R. Murthy, V. John Mathews
Submitted by:
Geethu Joseph
Last updated:
9 May 2019 - 12:55am
Document Type:
Poster
Document Year:
2019
Event:
Presenters:
Geethu Joseph
Paper Code:
2573
 

We present 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 confirm that the algorithm of this paper outperforms two competing methods in terms of reconstruction accuracy.

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