Title of Paper:Unsupervised Sparse Pattern Diagnostic of Defects with Inductive Thermography Imaging System

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Journal:IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

Abstract: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.

All the Authors:Wai Lok Woo,Yunze He,Guiyun Tian

Correspondence Author:Bin Gao

Discipline:Engineering

Volume:12

Issue:1

Page Number:371-383

Translation or Not:no

Date of Publication:2016-02-02