Erratum to Localized damage detection of structures subject to multiple ambient excitations using two distance measures for autoregressive models (Structural Health Monitoring: An International Journal, 2009, 8, 3, 10.1177/1475921708102145);Localized damage detection of structures subject to multiple ambient excitations using two distance measures for autoregressive models

Structural Health Monitoring

Volumn 8, Issue 3, 2009, Pages 207-222

  Zheng, Haitao ^a   Mita, Akira ^a  

^a KEIO UNIVERSITY   (Japan)

Author keywords

Autoregressive model; Cepstral distance; Damage detection; Distance measure; Itakura distance; Pre whitening filter

Indexed keywords

EID: 65349104144     PISSN: 14759217     EISSN: 17413168     Source Type: Journal    
DOI: 10.1177/1475921709107052     Document Type: Erratum

References (22)

1. Mita, A. (2003). Structural Dynamics and Health Monitoring, Japan, Sankeisha.
2. Pardoen, G.C. (1983). Ambient vibration test of the Imperial County Services Building. Bulletin of the Seismological Society of America, 73, 1895-1902.
3. Kadakal, U. and Yuzugullu, O. (1996). A comparative study on the identification methods for the autoregressive modeling from the ambient vibration records. Soil Dynamics and Earthquake Engineering, 15(1), 45-49.
4. He, X. and De Roeck, G. (1997). System identification of mechanical structures by a high-order multivariate autoregressive model. Computers & Structures, 64, 341-351.
5. Huang, C.S. (2001). Structural identification from ambient vibration measurement using the multivariate AR model. Journal of Sound and Vibration, 241, 337-359.
6. Chang, P.C., Flatau, A. and Liu, S.C. (2003). Review paper: Health monitoring of civil infrastructure. Structural Health Monitoring, 2(3), 257-267.
7. Carden, E.P. and Fanning, P. (2004). Vibration based condition monitoring: A review. Structural Health Monitoring, 3(4), 355-377.
8. Worden, K., Manson, G. and Fieller, N.R.J. (2000). Damage detection using outlier analysis. Journal of Sound and Vibration, 229(3), 647-667.
9. Sohn, H. and Farrar, C.R. (2001). Damage diagnosis using time series analysis of vibration signals. Smart Materials and Structures, 10, 446-451.
10. Lynch, J.P., Sundararajan, A., Law, K.H., Kiremidjian, A.S. and Carryer, E. (2004). Embedding damage detection algorithms in a wireless sensing unit for attainment of operational power efficiency. Smart Materials and Structures, 13, 800-810.
11. Mattson, S.G. and Pandit S.M. (2006). Statistical moments of autoregressive model residuals for damage localization. Mechanical Systems and Signal Processing, 20(3), 627-745.
12. De Lautour, O.R. and Omenzetter, P. (2006). Detection of seismic damage in buildings using time series analysis and pattern recognition. In: Proceedings of the 4th World Conference on Structural Control and Monitoring, San Diego, USA, 11-13 July, pp.1-8, on CD-ROM.
13. Itakura, F. (1975). Minimum prediction residual principle applied to speech recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 23(1), 67-72.
14. Gray, A.H. and Markel, J.D. (1976). Distance measures for speech processing. IEEE Transactions on Acoustics, Speech, and Signal Processing, 24(5), 380-391.
15. Rabiner, L. and Juang, B.H. (1993). Fundamentals of Speech Recognition, Prentice Hall.
16. Kong, X. and Brambrink, A. (1999). Quantification of injury-related EEG signal changes using distance measures. IEEE Transactions on Biomedical Engineering, 46(7), 899-901.
17. Pham, T.D. (2006). LPC cepstral distortion measure for protein sequence comparison. IEEE Transactions on Nano Bioscience, 5(2), 83-88.
18. Martin, R.J. (2000). A metric for ARMA processes. IEEE Transactions on Signal Processing, 48(4), 1164-1170.
19. Oppenheim, A.V. and Schafer, R.W. (1975). Digital Signal Processing, pp. 480 - 531, London: Prentice Hall International.
20. Yoshimoto, R. and Mita, A. (2002). Parallel identification of structural damages using vibration modes and sensor characteristics. JSCE Journal of Structural Engineering, 48, 487-492.
21. Building Research Institute of Japan (2004). Guidelines for structural health monitoring of buildings and its application. Report of the Building Research Institute, 142, 78-83.
22. Cichocki, A. and Amari, S. (2002). Adaptive Blind Signal and Image Processing, pp. 130-175, West Sussex: John Wiley & Sons.