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发表刊物：Infrared Physics and Technology

摘要：The carbon fiber reinforced polymer (CFRP) is widely used in aircraft and wind turbine blades. The common type of CFRP defect is debond. Optical pulse thermographic nondestructive evaluation (OPTNDE) and relevant thermal feature extraction algorithms are generally used to detect the debond. However, the resolution of detection performance remain as challenges. In this paper, the ensemble variational Bayes tensor factorization has been proposed to conduct super resolution of the debond detection. The algorithm is based on the framework of variational Bayes tensor factorization

备注：Code is attached

全部作者：Peng Lu, Qizhi Feng, Yang Yang, Wai Lok Woo, Gui Yun Tian

论文类型：应用研究

通讯作者：Bin Gao

学科门类：工学

一级学科：控制科学与工程

卷号：85

页面范围：335-346

是否译文：否

发表时间：2017-08-15