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Vision-based technique for bolt-loosening detection in wind turbine tower
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  • Journal title : Wind and Structures
  • Volume 21, Issue 6,  2015, pp.709-726
  • Publisher : Techno-Press
  • DOI : 10.12989/was.2015.21.6.709
 Title & Authors
Vision-based technique for bolt-loosening detection in wind turbine tower
Park, Jae-Hyung; Huynh, Thanh-Canh; Choi, Sang-Hoon; Kim, Jeong-Tae;
 Abstract
In this study, a novel vision-based bolt-loosening monitoring technique is proposed for bolted joints connecting tubular steel segments of the wind turbine tower (WTT) structure. Firstly, a bolt-loosening detection algorithm based on image processing techniques is developed. The algorithm consists of five steps: image acquisition, segmentation of each nut, line detection of each nut, nut angle estimation, and bolt-loosening detection. Secondly, experimental tests are conducted on a lab-scale bolted joint model under various bolt-loosening scenarios. The bolted joint model, which is consisted of a ring flange and 32 sets of bolt and nut, is used for simulating the real bolted joint connecting steel tower segments in the WTT. Finally, the feasibility of the proposed vision-based technique is evaluated by bolt-loosening monitoring in the lab-scale bolted joint model.
 Keywords
bolted joint;bolt loosening;vision;image processing;steel structure;wind turbine tower;
 Language
English
 Cited by
1.
Recent R&D activities on structural health monitoring in Korea, Structural Monitoring and Maintenance, 2016, 3, 1, 91  crossref(new windwow)
2.
A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications, Journal of Sensors, 2016, 2016, 1  crossref(new windwow)
 References
1.
Abdel-Qader, I., Abudayyeh, O. and Kelly, M.E. (2003), "Analysis of edge-detection techniques for crack identification in bridges", J. Comput. Civil Eng. - ASCE, 17(4), 255-263. crossref(new window)

2.
Basava, S. and Hess, D.P. (1998), "Bolted joint clamping force variation due to axial vibration", J. Sound Vib., 210(2), 255-265. crossref(new window)

3.
Canny, J.F. (1986), "A computational approach to edge detection", IEEE T. Pattern Anal., 8(6), 679-698.

4.
Choi, K.Y. and Kim, S.S. (2005), "Morphological analysis and classification of types of surface corrosion damage by digital image processing", Corros. Sci., 47(1), 1-15. crossref(new window)

5.
Ciang, C.C., Lee, J.R. and Bang, H.J. (2008), "Structural health monitoring for wind turbine system: a review of damage detection methods", Meas. Sci. Technol., 19(12), 1-20.

6.
Fukuda, Y., Feng, M.Q., Narita, Y., Kaneko, S. and Tanaka, T. (2013), "Vision-based displacement sensor for monitoring dynamic response using robust object search algorithm", IEEE Sensor J., 13(12), 4725-4732. crossref(new window)

7.
Ho, H.N., Kim, K.D., Park, Y.S. and Lee, J.J. (2013), "An efficient image-based damage detection for cable surface in cable-stayed bridges", NDT&E Int., 58, 18-23. crossref(new window)

8.
Ho, H.N., Lee, J.H., Park, Y.S. and Lee, J.J. (2012), "A synchronized multipoint vision-based system for displacement measurement of civil infra structures", The Scientific World J., 2012, Article ID 519146, 1-9.

9.
Hough, P.V.C. (1959), "Machine analysis of bubble chamber pictures", Proceedings of the 2nd International Conference on High-Energy Accelerations and Instrumentation, Genova, Switzerland, September.

10.
Hutchinson, T.C. and Chen, Z. (2006), "Improved image analysis for evaluating concrete damage", J. Comput. Civil Eng., 20(3), 200-216.

11.
Huynh, T.C., Lee, K.S. and Kim, J.T. (2015), "Local dynamic characteristics of PZT impedance interface on tendon anchorage under prestress force variation", Smart Struct. Syst., 15(2), 375-393. crossref(new window)

12.
Hyun, S.H. (2013), The study on inspection for relaxation of bolted joins by electric potential drop method, Master Dissertation, Chung-Ang University, Seoul.

13.
Izumi, S., Yokoyama, T., Iwasaki, A. and Sakai, S. (2005), "Threedimensional finite element analysis of tightening and loosening mechanism of threaded fastener", Eng. Fail. Anal., 12(4), 604-615. crossref(new window)

14.
Kim, J.T., Park, J.H., Hong, D.S. and Ho, D.D. (2011), "Hybrid acceleration-impedance sensor nodes on Imote2-platform for damage monitoring in steel girder connections", Smart Struct. Syst., 7(5), 393-416. crossref(new window)

15.
Kim, N. and Hong, M. (2009), "Measurement of axial stress using mode-converted ultrasound", NDT & E Int., 42(3), 164-169. crossref(new window)

16.
Korea Expressway Corporation (2006), Performance optimization of steel bridge coating diagnosing system for field application, Research Report, Korea.

17.
Lee, S., Chang, L.M. and Skibniewski, M. (2006), "Automated recognition of surface defects using digital color image processing", Automat. Constr., 15(4), 540-549. crossref(new window)

18.
McAndrew, A. (2004), An introduction to digital image processing with matlab, Course Technology Press, Boston, MA, USA.

19.
Park, G., Sohn, H., Farrar, C.R. and Inman, D.J. (2003), "Overview of piezoelectric impedance-based health monitoring and path forward", Shock Vib. Digest, 35(6), 451-463. crossref(new window)

20.
Park, S.H., Yun, C.B. and Roh, Y. (2006) "Active sensing-based real-time nondestructive evaluations for steel bridge members", J. Civil Eng.- KSCE, 10(1), 33-39.

21.
Subirats, P., Dumoulin, J., Legeay, V. and Barba, D. (2006), "Automation of pavement surface crack detection using the continuous wavelet transform", Proceeding of the 2006 IEEE International Conference on Image Processing, Atlanta, USA, October.

22.
Wang, T., Song, G., Liu, S., Li, Y. and Xiao, H. (2013a), "Review of bolted connection monitoring", Int. J. Distrib. Sens. N., 2013, Article ID 871213, 1-8.

23.
Wang, T., Song, G., Wang, Z.G. and Li, Y.R. (2013b), "Proof-of-concept study of monitoring bolt connection status using a piezoelectric based active sensing method", Smart Mater. Struct., 22(8), Article ID 087001.

24.
Wikipedia, https://en.wikipedia.org/.

25.
Yamaguchi, T. and Hashimoto, S. (2010), "Fast crack detection method for large-size concrete surface images using percolation-based image processing", Mach. Vision Appl., 21(5), 797-809. crossref(new window)

26.
You, Y.J., Park, K.T., Lee, W.S. and Han, S.H. (2010), "Development of information detection unit on the loosening of bolted joints using USN technology", Proceeding of the Korea Society of Civil Engineers (KSCE) Conference & Expo 2010, Incheon, Korea, October.

27.
Zou, Q., Cao, Y., Li, Q., Mao, Q. and Wang. S. (2012), "CrackTree: automatic crack detection from pavement images", Pattern Recogn. Lett., 33(3), 227-238. crossref(new window)