Fault diagnosis of rotating machine by thermography method on support vector machine

Journal of Mechanical Science and Technology

Volumn 28, Issue 8, 2014, Pages 2947-2952

  Lim, Gang Min ^a   Bae, Dong Myung ^a   Kim, Joo Hyung ^b  

^a Pukyong National University   (South Korea)

^b Inha University   (South Korea)

Author keywords

Condition monitoring; Fault diagnosis; Rotating machine; Support vector machine (SVM); Thermal image

Indexed keywords

CONDITION MONITORING; FAILURE ANALYSIS; INFRARED IMAGING; ROTATING MACHINERY;

FAULT DIAGNOSTIC METHODS; FEATURE REPRESENTATION; FEATURE-BASED CLASSIFICATION; MEASUREMENT TECHNIQUES; NONCONTACT METHODS; REAL TIME CONDITION MONITORING; ROTATING MACHINE; THERMAL IMAGES;

SUPPORT VECTOR MACHINES;

EID: 84906236387     PISSN: 1738494X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s12206-014-0701-6     Document Type: Article

References (18)

1. Y. Lei, Z. He and Y. Zi, Application of an intelligent classification method to mechanical fault diagnosis, Expert System with Application, 36 (2009) 9941.
2. J. H Williams, A. Davies and P. R. Drake, Condition-based Maintenance and Machine Diagnostics, Chapman & Hall, London (1994).
3. th Ed., Elsevier Advanced Technology Publications, UK (1992).
4. thInternational Congress on COMADEM, Houston, USA (2000) 12-20.
5. A. K. S. Jardine, D. Lin and D. Banjevic, A review on machinery diagnostics and prognostics implementing conditionbased maintenance, Mechanical Systems and Signal Processing, 20 (2006) 1483.
6. A. Widodo and B. S. Yang, Support vector machine in condition monitoring and fault diagnosis, Mechanical System and Signal Processing, 21 (2007) 2560.
7. B. Samanta, Gear fault detection using artificial neural networks and support vector machines with genetic algorithms, Mechanical Systems and Signal Processing, 18 (3) (2004) 625.
8. S. B. Glavatskih, O. Uusitalo and D. Spohn, Simultaneous monitoring of oil film thickness and temperature in fluid film bearings, Tribology International, 34 (12) (2001) 853.
9. S. B. Glavatskih, A method of temperature monitoring in fluid film bearing, Tribology International, 37 (2) (2004) 143.
10. P. De Choudhury and E. W. Barth, A comparison of film temperature and oil discharge temperature for a tilting-pad jounal bearing, J. lubrication Technology, 103 (1) (1981) 115.
11. thInternational Conference on Quantitative Infrared Thermography, Krakow, Poland, July (2008).
12. A. M. Younus, A. Widodo and B. S. Yang, Evaluation of thermography image data for machine fault diagnosis, Nondestructive Testing and Evaluation, 25 (2009) 231.
13. A. M. Younus and B. S. Yang, Intelligent fault diagnosis of rotating machinery using infrared thermal image, Expert System with Applications, 39 (2011) 2082.
14. V. N. Vapnik, The nature of statistical learning theory, Springer, New York (1995).
15. C. Cortes and V. Vapnik, Support-vector networks, Machine Learning, 20 (1995) 273.
16. C. W. Hsu and C. J. Lin, A comparison of methods for multi-class support vector machines, IEEE Trans. Neural Networks, 13 (2002) 415.
17. Colour Theory: Understanding and modelling colour, (http://www. jiscdigitalmedia. ac. uk/stillimages/advice/colour-theory-understanding-and-modelling-colour/).
18. CIEL*a*b* Color Scale, Hunterlab application Notes, 8 7 (2008).