The three-stage artificial neural network method for damage assessment of building structures

Australian Journal of Structural Engineering

Volumn 14, Issue 1, 2013, Pages 13-26

  Bandara, R P ^a   Chan, T H T ^a   Thambiratnam, D P ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

Artificial neural networks (ANNs); Damage detection; Frequency response functions (FRFs); Principal component analysis (PCA)

Indexed keywords

ARTIFICIAL NEURAL NETWORK METHODS; BUILDING STRUCTURE; COMPUTATIONAL EFFORT; DAMAGE DETECTION TECHNIQUE; FREQUENCY-RESPONSE FUNCTIONS; NUMBER OF DEGREES OF FREEDOM; STRUCTURAL CONDITION MONITORING; STRUCTURAL DAMAGE DETECTION;

CONDITION MONITORING; FREQUENCY RESPONSE; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS;

DAMAGE DETECTION;

EID: 84880254305     PISSN: 13287982     EISSN: None     Source Type: Journal    
DOI: 10.7158/S12-036.2013.14.1     Document Type: Article

References (13)

1. Bandara, R. P., Chan, T. H. T. & Thambiratnam, D. P. 2013, "A statistical strategy to select optimal structural health monitoring data in operational modal analysis", Australian Journal of Structural Engineering, Vol. 14, No. 1, pp. 13-26, http://dx.doi.org/10.7158/S12-036.2013.14.1.
2. th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-5), 11-15 December, Cancún, México.
3. th Asia-Pacific Vibration Conference, Hong Kong Polytechnic University, Hong Kong.
4. Dackermann, U. 2009, "Dynamic based damage identification methods for civil engineering structures using artificial neural networks", PhD thesis, University of Technology Sydney, Sydney, Australia.
5. Dackermann, U., Li, J. & Samali, B. 2012, "Identification of boundary damage and mass changes on a two-storey framed structure using residual frequency response functions and artif cial neural networks", Journal of Sound and Vibration, in press.
6. Gonzalez, M. P. & Zapico, J. L. 2008, "Seismic damage identification in buildings using neural networks and modal data", Computers and Structures, Vol. 86, pp. 416-426.
7. Jiang, S.-F., Zhang, C.-M. & Zhang, S. 2011, "Two-stage structural damage detection using fuzzy neural networks and data fusion techniques", Expert Systems with Applications, Vol. 38, pp. 511-519.
8. Moragaspitiya, P. 2011, "Interactive axial shortening of columns and walls in high rise buildings", PhD thesis, Queensland University of Technology, Brisbane, Australia.
9. Ni, Y. Q., Zhou, X. T. & Ko, J. M. 2006, "Experimental investigation of seismic damage identif cation using PCA-compressed frequency response functions and neural networks", Journal of Sound and Vibration, Vol. 290, pp. 242-263.
10. Samali, B., Dackermann, U. & Li, J. 2012, "Location and Severity Identification of Notch-Type Damage in a Two-Storey Framed Structure utilising Frequency Response Functions and Artificial Neural Networks", Advances in Structural Engineering, Vol. 15, pp. 743-757.
11. Tang, J. 2005, "Frequency response based damage detection using principal component analysis", IEEE International Conference on Information Acquisition, Hong Kong and Macau, China, pp. 407-412.
12. Yuen, K.-V. & Lam, H.-F. 2006, "On the complexity of artificial neural networks for smart structures monitoring", Engineering Structures, Vol. 28, pp. 977-984.
13. Zang, C. & Imregun, M. 2001, "Structural damage detection using artificial neural networks and measured FRF data reduced via principal component projection", Journal of Sound and Vibration, Vol. 242, pp. 813-827.