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发表刊物：IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

摘要：This paper proposes an unsupervised method for diagnosing and monitoring defects in inductive thermography imaging system. The proposed method is fully automated and does not require manual selection from the user of the specific thermal frame images for defect diagnosis. The core of the method is a hybrid of physics-based inductive thermal mechanism with signal processing-based pattern extraction algorithm using sparse greedy based Principal Component Analysis (SGPCA). An internal functionality is built into the proposed algorithm to control the sparsity of SGPCA.

全部作者：Wai Lok Woo,Yunze He,Guiyun Tian

通讯作者：Bin Gao

学科门类：工学

卷号：12

期号：1

页面范围：371-383

是否译文：否

发表时间：2016-02-02