Improving visibility of rear surface cracks during inductive thermography of metal plates using Autoencoder

被引:29
作者
Xie, Jing [1 ,2 ]
Xu, Changhang [2 ]
Chen, Guoming [2 ]
Huang, Weiping [1 ]
机构
[1] Ocean Univ China, Coll Engn, Qingdao 266071, Peoples R China
[2] China Univ Petr East China, Coll Mech & Elect Engn, Changjiang West Rd 66, Qingdao 266580, Shandong, Peoples R China
关键词
Infrared thermography; Inductive thermography; Real surface cracks; Autoencoder; FATIGUE CRACKS; INSPECTION; STEEL; ENHANCEMENT;
D O I
10.1016/j.infrared.2018.04.016
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
Inductive thermography is one kind of infrared thermography (IRT) technique, which is effective in detection of front surface cracks in metal plates. However, rear surface cracks are usually missed due to their weak indications during inductive thermography. Here we propose a novel approach (AET: AE Thermography) to improve the visibility of rear surface cracks during inductive thermography by employing the Autoencoder (AE) algorithm, which is an important block to construct deep learning architectures. We construct an integrated framework for processing the raw inspection data of inductive thermography using the AE algorithm. Through this framework, underlying features of rear surface cracks are efficiently extracted and new clearer images are constructed. Experiments of inductive thermography were conducted on steel specimens to verify the efficacy of the proposed approach. We visually compare the raw thermograms, the empirical orthogonal functions (EOFs) of the prominent component thermography (PCT) technique and the results of AET. We further quantitatively evaluated AET by calculating crack contrast and signal-to-noise ratio (SNR). The results demonstrate that the proposed AET approach can remarkably improve the visibility of rear surface cracks and then improve the capability of inductive thermography in detecting rear surface cracks in metal plates (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:233 / 242
页数:10
相关论文
共 32 条
[1]  
Alain G, 2014, J MACH LEARN RES, V15, P3563
[2]  
[Anonymous], 2013, INT C MACHINE LEARNI
[3]  
[Anonymous], 2011, INT C ART INT STAT
[4]  
[Anonymous], 2012, PREDICTION CANDIDATE
[5]  
Bishop Christopher M, 2006, PATTERN RECOGNITION, DOI DOI 10.18637/JSS.V017.B05
[6]   Autoencoder-based Unsupervised Domain Adaptation for Speech Emotion Recognition [J].
Deng, Jun ;
Zhang, Zixing ;
Eyben, Florian ;
Schuller, Bjoern .
IEEE SIGNAL PROCESSING LETTERS, 2014, 21 (09) :1068-1072
[7]   Context-Aware Saliency Detection [J].
Goferman, Stas ;
Zelnik-Manor, Lihi ;
Tal, Ayellet .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 34 (10) :1915-1926
[8]   Crack detection in aluminum parts by using ultrasound-excited infrared thermography [J].
Guo, Xingwang ;
Vavilov, Vladimir .
INFRARED PHYSICS & TECHNOLOGY, 2013, 61 :149-156
[9]   Eddy current pulsed phase thermography for subsurface defect quantitatively evaluation [J].
He, Yunze ;
Pan, Mengchun ;
Tian, GuiYun ;
Chen, Dixiang ;
Tang, Ying ;
Zhang, Hong .
APPLIED PHYSICS LETTERS, 2013, 103 (14)
[10]   Reducing the dimensionality of data with neural networks [J].
Hinton, G. E. ;
Salakhutdinov, R. R. .
SCIENCE, 2006, 313 (5786) :504-507