Segmented infrared image analysis for rotating machinery fault diagnosis

被引:41
作者
Duan, Lixiang [1 ]
Yao, Mingchao [1 ]
Wang, Jinjiang [1 ]
Bai, Tangbo [1 ]
Zhang, Laibin [1 ]
机构
[1] China Univ Petr, Sch Mech & Transportat Engn, Beijing 102249, Peoples R China
基金
美国国家科学基金会;
关键词
Infrared image analysis; Feature enhancement; Region selection; Machinery fault diagnosis; EMPIRICAL MODE DECOMPOSITION; THERMAL IMAGE; VECTOR MACHINE; THERMOGRAPHY;
D O I
10.1016/j.infrared.2016.06.011
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
As a noncontact and non-intrusive technique, infrared image analysis becomes promising for machinery defect diagnosis. However, the insignificant information and strong noise in infrared image limit its performance. To address this issue, this paper presents an image segmentation approach to enhance the feature extraction in infrared image analysis. A region selection criterion named dispersion degree is also formulated to discriminate fault representative regions from unrelated background information. Feature extraction and fusion methods are then applied to obtain features from selected regions for further diagnosis. Experimental studies on a rotor fault simulator demonstrate that the presented segmented feature enhancement approach outperforms the one from the original image using both Naive Bayes classifier and support vector machine. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:267 / 276
页数:10
相关论文
共 27 条
[1]   Automated diagnosis of dry eye using infrared thermography images [J].
Acharya, U. Rajendra ;
Tan, Jen Hong ;
Koh, Joel E. W. ;
Sudarshan, Vidya K. ;
Yee, Sharon ;
Too, Cheah Loon ;
Chua, Chua Kuang ;
Ng, E. Y. K. ;
Tong, Louis .
INFRARED PHYSICS & TECHNOLOGY, 2015, 71 :263-271
[2]   Infrared thermography for condition monitoring - A review [J].
Bagavathiappan, S. ;
Lahiri, B. B. ;
Saravanan, T. ;
Philip, John ;
Jayakumar, T. .
INFRARED PHYSICS & TECHNOLOGY, 2013, 60 :35-55
[3]   Surface crack detection in welds using thermography [J].
Broberg, Patrik .
NDT & E INTERNATIONAL, 2013, 57 :69-73
[4]   Recent progress in diagnosing the reliability of electrical equipment by using infrared thermography [J].
Jadin, Mohd Shawal ;
Taib, Soib .
INFRARED PHYSICS & TECHNOLOGY, 2012, 55 (04) :236-245
[5]   A review on machinery diagnostics and prognostics implementing condition-based maintenance [J].
Jardine, Andrew K. S. ;
Lin, Daming ;
Banjevic, Dragan .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2006, 20 (07) :1483-1510
[6]   A comprehensive method of contour extraction for industrial computed tomography images [J].
Jiang, Haina ;
Zeng, Li ;
Bi, Bi .
OPTICS AND LASERS IN ENGINEERING, 2013, 51 (03) :286-293
[7]   A reappraisal of the use of infrared thermal image analysis in medicine [J].
Jones, BF .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 1998, 17 (06) :1019-1027
[8]   Infrared thermography (IRT) applications for building diagnostics: A review [J].
Kylili, Angeliki ;
Fokaides, Paris A. ;
Christou, Petros ;
Kalogirou, Soteris A. .
APPLIED ENERGY, 2014, 134 :531-549
[9]   Infrared thermography based defect detection in ferromagnetic specimens using a low frequency alternating magnetic field [J].
Lahiri, B. B. ;
Bagavathiappan, S. ;
Soumya, C. ;
Mahendran, V. ;
Pillai, V. P. M. ;
Philip, John ;
Jayakumar, T. .
INFRARED PHYSICS & TECHNOLOGY, 2014, 64 :125-133
[10]   Measurement of annular air-gap using active infrared thermography [J].
Lahiri, B. B. ;
Bagavathiappan, S. ;
Shunmugasundaram, R. ;
Philip, John ;
Jayakumar, T. .
INFRARED PHYSICS & TECHNOLOGY, 2013, 61 :192-199