Damage Identification in a Laboratory Offshore Wind Turbine Demonstrator

Article Preview

Abstract:

This paper presents a method to detect and identify damage in a laboratory offshore wind turbine support structure. The structure consists of three different parts: the jacket, the tower and the nacelle. The jacket is a lattice structure joined with several bolts. The tower consists of three different sections joined by bolts. The nacelle is composed of a single piece. The different parts are also joined with bolts. The damage in the structure is simulated by loosening some of the bolts in the jacket. Two damage detection algorithms, namely AutoRegressive methods and NullSpace methods, have been tested in a primitive variation of this structure without the jacket, obtaining good results. In this paper we present the application of the last damage detection method to the new structure with the jacket and an extension to identification of the damage.

You might also be interested in these eBooks

Info:

Periodical:

Key Engineering Materials (Volumes 569-570)

Pages:

555-562

Citation:

Online since:

July 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] D.L. Balageas, C.P. Fritzen, A. Güemes, Structural Health Monitoring, London; Newport Beach, CA, (2006).

Google Scholar

[2] A. Rytter, Vibration based inspection of civil engineering structures, Ph D Thesis, Aalborg University, Denmark, (1993).

Google Scholar

[3] L. Wang, T.H.T. Chan, Review of Vibration-Based Damage Detection and Condition Assessment of Bridge Structures using Structural Health Monitoring, In: The Second Infrastructure Theme Postgraduate Conference : Rethinking Sustainable Development: Planning, Engineering, Design and Managing Urban Infrastructure (2009).

DOI: 10.4018/978-1-61692-022-7.ch016

Google Scholar

[4] C.C. Ciang, J.R. Lee, H.J. Bang, Structural health monitoring for a wind turbine system: a review of damage detection methods, Measurement Science and Technology, 19 (2008) 122001 (20pp).

DOI: 10.1088/0957-0233/19/12/122001

Google Scholar

[5] S. Doebling, C. Farrar, M. Prime, D. Shevitz, Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review, Technical Report LA-13070-MS, Los Alamos National Laboratory (1996).

DOI: 10.2172/249299

Google Scholar

[6] S.D. Fassois, J.S. Sakellariou, Time-series methods for fault detection and identification in vibrating structures. The Royal Society – Phylosophical Transactions: Mathematical Physical and Engineering Sciences, 365 (2007) 411–448.

DOI: 10.1098/rsta.2006.1929

Google Scholar

[7] P. Gudmundson. Eigenfrequency changes of structures due to cracks, notches or other geometrical changes, Journal of Mechanical Physics and Solids, 30 (1982), 339–353.

DOI: 10.1016/0022-5096(82)90004-7

Google Scholar

[8] R. Liang, J.I. Hu, Theoretical-study of crack-induced eigenfrequency changes on beam structures, Journal of Engineering Mechanics-ASCE, 118 (1992), 384–396.

DOI: 10.1061/(asce)0733-9399(1992)118:2(384)

Google Scholar

[9] R.J. Allemang, D.L. Brown, Correlation coefficient for modal vector analysis Proc. 1st Int. Modal Analysis Conf. (Orlando, FL) (1982) 110–116.

Google Scholar

[10] N.A.J. Lieven, D.J. Ewins Spatial correlation of modespaces: the coordinate modal assurance criterion (COMAC) Proc. 6th Int. Modal Analysis Conf. (Kissimmee, FL) (1988) 1063–1070.

Google Scholar

[11] J.T. Kim, Y.S. Ryu, H.M. Cho, N. Stubbs, Damage identification in beam-type structures: frequency-based method vs. mode-shape-based method Eng. Struct. 25 (2003) 57–67.

DOI: 10.1016/s0141-0296(02)00118-9

Google Scholar

[12] K. Worden, G. Manson, N.R.J. Fieller, Damage detection using outlier analysis J. Sound Vib. 229 (2000) 647–667.

DOI: 10.1006/jsvi.1999.2514

Google Scholar

[13] P. De Boe, J.C. Golinval, Principal component analysis of piezo-sensor array for damage localization Struct. Health Monit. 2 (2003) 137–144.

DOI: 10.1177/1475921703002002005

Google Scholar

[14] A.M. Yan, P. De Boe, J.C. Golinval, Structural diagnosis by Kalman model based on stochastic subspace identification Struct. Health Monit. 3 (2004) 103–119.

DOI: 10.1177/1475921704042545

Google Scholar

[15] S. Liberatore, G. Carman, Power spectral density analysis for damage identification and location J. Sound Vib. 274 (2004) 761–766.

DOI: 10.1016/s0022-460x(03)00785-5

Google Scholar

[16] D. Rizos, S.D. Fassois, Z. Marioli-Riga, A. Karanjka, Vibration based skin damage statistical detection and restoration assessment in a stiffened aircraft panel, Mechanical Systems and Signal Processing, 22 (2008), 315–337.

DOI: 10.1016/j.ymssp.2007.07.012

Google Scholar

[17] L. Ljung, System identification: Theory for the User, 2nd edition, Prentice-Hall, (1999).

Google Scholar

[18] S.M. Kay, S.L. Marple Jr, Spectrum analysis – a modern perspective, Proceedings of the IEEE, 69 (1981) 1380–1419.

DOI: 10.1109/proc.1981.12184

Google Scholar

[19] K. Nair, A. Kiremidjian, K. Law, Time series based damage detection and localization algorithm with application to the asce benchmark structure, J. Sound Vib. 291 (2006) 349–368.

DOI: 10.1016/j.jsv.2005.06.016

Google Scholar

[20] H. Sohn, C.F. Farrar, Damage diagnosis using time series analysis of vibration signals, Smart Materials and Structures 10 (2001) 1–6.

DOI: 10.1088/0964-1726/10/3/304

Google Scholar

[21] Y. Liu, S.B. Kim, A. Chattopadhyay, D. Doyle, Application of system identification techniques to health monitoring of on-orbit satellite boom structures J. Spacecraft Rockets 48-4 (2011) 589–98.

DOI: 10.2514/1.51818

Google Scholar

[22] M. Basseville, M. Abdelghani, A. Benveniste, Subspace-based fault detection algorithms for vibration monitoring, Automatica 36 (2000) 101–9.

DOI: 10.1016/s0005-1098(99)00093-x

Google Scholar

[23] E. Zugasti, A. Gómez González, J. Anduaga, M.A. Arregui, F. Martínez, NullSpace and AutoRegressive damage detection: a comparative study, Smart Materials and Structures, 21(8): 085010 (2012).

DOI: 10.1088/0964-1726/21/8/085010

Google Scholar

[24] R. Yao, S.N. Pakzad, Structural Damage Detection Unsing Multivariate Time Series Analysis, Topics on the Dynamics of Civil Structures, Volume I, Conference Proceedings of the Society for Experimental Mechanics Series 26, (2012), 299–308.

DOI: 10.1007/978-1-4614-2413-0_30

Google Scholar