Ensemble Joint Sparse Low Rank Matrix Decomposition for Thermography Diagnosis System

Ahmedtl, Junaid, Gao, Bin, Woo, Wai Lok and Zhu, Yuyu (2020) Ensemble Joint Sparse Low Rank Matrix Decomposition for Thermography Diagnosis System. IEEE Transactions on Industrial Electronics. p. 1. ISSN 0278-0046 (In Press)

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Official URL: https://doi.org/10.1109/tie.2020.2975484

Abstract

Composite is widely used in the aircraft industry and it is essential for manufacturers to monitor its health and quality. The most commonly found defects of composite are debonds and delamination. Different inner defects with complex irregular shape is difficult to be diagnosed by using conventional thermal imaging methods. In this paper, an ensemble joint sparse low rank matrix decomposition (EJSLRMD) algorithm is proposed by applying the optical pulse thermography (OPT) diagnosis system. The proposed algorithm jointly models the low rank and sparse pattern by using concatenated feature space. In particular, the weak defects information can be separated from strong noise and the resolution contrast of the defects has significantly been improved. Ensemble iterative sparse modelling are conducted to further enhance the weak information as well as reducing the computational cost. In order to show the robustness and efficacy of the model, experiments are conducted to detect the inner debond on multiple carbon fiber reinforced polymer (CFRP) composites. A comparative analysis is presented with general OPT algorithms. Not withstand above, the proposed model has been evaluated on synthetic data and compared with other low rank and sparse matrix decomposition algorithms.

Item Type: Article
Uncontrolled Keywords: CFRP composites, optical thermography, eigen decomposition, low rank sparse decomposition, concatenated matrix factorization, weak signal detection
Subjects: F200 Materials Science
G400 Computer Science
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 28 May 2020 09:48
Last Modified: 29 May 2020 10:30
URI: http://nrl.northumbria.ac.uk/id/eprint/43260

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