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发表刊物：IEEE Transactions on Industrial Informatics

摘要：This paper proposes a new system for the unsupervised diagnostic and monitoring of defects in waveguide imaging. The proposed method is automatic and does not require manual selection of specific frequencies for defect diagnostics. The core of the method is a computational intelligent machine learning algorithm based on sparse non-negative matrix factorization. An internal functionality is built into the machine learning algorithm to adaptively learn and control the sparsity of the factorization, and to render better accuracy in detecting defects. This is achieved by using Bayesian approach.

全部作者：Bin Gao,Wai Lok Woo,Guiyun Tian,Hong Zhang

学科门类：工学

卷号：12

期号：1

页面范围：405-416

是否译文：否

发表时间：2016-02-02