Research ArticleOpen AccessGoogle Scholar indexed
Damage Detection Method Using Support Vector Machine and First Three Natural Frequencies for Shear Structures
Department of System Design Engineering, Keio University, Yokohama, Japan
Department of System Design Engineering, Keio University, Yokohama, Japan
- 1 Department of System Design Engineering, Keio University, Yokohama, Japan
- 2 Department of System Design Engineering, Keio University, Yokohama, Japan
Open Journal of Civil Engineering·Volume 03 (2013)·Pages 104–112·Published 30 May 2013·DOI10.4236/ojce.2013.32012
Copy link · social · email
Abstract
A method is proposed for detecting damage to shear structure s by using Support Vector Machine (SVM) and only the first three natural frequencies of the translational modes. This method is able to determine the damage location in any story of a shear building with only two vibration sensors; to obtain modal frequencies , one sensor on the ground detects an input and the other on the roof detect s the output. Based on the shifts in the first three natural frequencies, damage location indicators are proposed, and used as new feature vectors for SVM. Simulations of five-story, nine-story and twenty-one-story shear structures and experiments on a five-story steel model were used to test the performance of the proposed method.
KeywordsSupport Vector MachineDamage DetectionNatural FrequencySystem IdentificationDamage Location Indicator
- A. Mita, “Structural Dynamic for Health Monitoring,” Sankeisha Co., Ltd, Nagoya, 2003.
- O. S. Salawu, “Detection of Structural Damage through Changes in Frequency: A Review,” Engineering Structures, Vol. 19, No. 9, 1997, pp. 718-723. doi:10.1016/S0141-0296(96)00149-6
- S. Doebling, et al., “Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: A Literature Review,” Los Alamos National Laboratory, Los Alamos, 1998.
- N. Stubbs, T. H. Broome and R. Osegueda, “Non-Destructive Construction Error Detection in Large Space Structures,” AIAA Journal, Vol. 28, No. 1, 1990, pp. 146-152. doi:10.2514/3.10365
- Z. Xing and A. Mita, “A Substructure Approach to Local Damage Detection of Shear Structure,” Structural Control and Health Monitoring, Vol. 19, No. 2, 2011, pp. 309-318. doi:10.1002/stc.439
- J. Sidhu and D. J. Ewins, “Correlation of Finite and Model Test Studies of a Practical Structure,” Proceedings of the 2nd International Modal Analysis Conference, Society for Experimental Mechanics, USA, 1984, pp. 756-762.
- H. P. Zhu and Y. L. Xu, “Damage Detection of Mono Coupled Periodic Structures Based on Sensitivity Analysis of Modal Parameter,” Journal of Sound and Vibration, Vol. 285, No. 1-2, 2005, pp. 365-390. doi:10.1016/j.jsv.2004.08.012
- A. Messina, E. J. Williams and T. Contursi, “Structural Damage Detection by a Sensitivity and Statistical-Based Method,” Journal of Sound and Vibration, Vol. 216, No. 5, 1998, pp. 791-808. doi:10.1006/jsvi.1998.1728
- B. Samanta, K. B. Al-Balushi and S. A. Al-Araimi, “Artificial Neural Networks and Support Vector Machines with Genetic Algorithm for Bearing Fault Detection,” Engineering Applications of Artificial Intelligence, Vol. 16, No. 7-8, 2003, pp. 657-665. doi:10.1016/j.engappai.2003.09.006
- D. Meyer, F. Leisch and K. Hornik, “The Support Vector Machine under Test,” Neurocomputing, Vol. 55, No. 1-2, 2003, pp. 169-186. doi:10.1016/S0925-2312(03)00431-4
- A. Mita and H. Hagiwara, “Quantitative Damage Diagnosis of Shear Structures Using Support Vector Machine,” KSCE Journal of Civil Engineering, Vol. 7, No. 6, 2003, pp. 683-689. doi:10.1007/BF02829138
- M. Shimada and A. Mita, “Damage Assessment of Bending Structures Using Support Vector Machine,” Smart Structures and Material 2005: Sensors and Smart Structures Technologies for Civil, Mechanical and Aerospace, San Diego, 2005, pp. 923-930.