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Analysis of Earthquake Records from Structures: An Overview

  • Chapter
Strong Motion Instrumentation for Civil Engineering Structures

Part of the book series: NATO Science Series ((NSSE,volume 373))

Abstract

The paper presents an overview of the methods that are available to analyze seismic records from structures. A typical analysis involves data processing, system identification, and damage detection. Data processing aims to minimize the ambient and instrument noise in the data, as well as possible low-frequency drifts, outliers, and other unwanted signals. System identification deals with determining the dynamic characteristics of a structure from its recorded response. There are a large number of methods available in the literature for system identification, varying from simple Fourier analysis to stochastic adaptive filtering. Unless data require otherwise, simple methods should be preferred for identification, because they are more robust and results are easier to interpret. Modal identification is the most widely used form of system identification. An alternative is the discrete-time filters, which provide a convenient model for identification of linear as well as nonlinear structures. Special techniques can be developed to identify a particular component of response, such as torsion, soil-structure interaction, and inter-story drift. Damage detection is a subject that is closely related to nonlinear system identification. Since a damaged structure almost always behaves in a nonlinear fashion, the problem of damage detection becomes equivalent to identification of the nonlinear behavior in the structure. The standard method for damage detection has been to observe the changes in the frequencies of the structure, However, unless it is a major damage, frequencies are not very sensitive to damage, particularly to localized damage. More reliable methods for damage detection can be developed by using time-frequency analyses and wave propagation techniques.

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References

  1. ASCE (2000) The State of the Art Report in Structural Identification. Technical Committee on System Identification and Health Monitoring of Constructed Facilities, ASCE, Reston, VA (in preparation).

    Google Scholar 

  2. Beck J.L. (1978). Determining Models of Structures form Earthquake Records, EERL Report No. 78-01. California Institute of Technology, Pasadena

    Google Scholar 

  3. Beck J.L. and P.C. Jennings (1980). Structural identification using linear models and earthquake records. Earthq. Engng. aud Struct. Dyn., 8, 145–160.

    Article  Google Scholar 

  4. Bendat J.S. and Piersol, A.G. (1993). Engineering Application of Correlation and Spectral Analysis (2nd Ed.), John Wiley & Sons, Inc. New York, NY.

    Google Scholar 

  5. Benedettini, F., D. Capecchi and F. Vestroni (1995). Identification of hysteretic oscillators under earthquake loading by nonparametric models, J. Eng. Mech., ASCE. 121, 606–612.

    Article  Google Scholar 

  6. Branden B.V., Peeters, B. and Roeck, G.D. (1999). Introduction to MACEC (v 2.0): Modal Analysis on Civil Engineering Construction, Dept. of Civil Eng., Katholieke Iniversiteit Leuven, Belgium.

    Google Scholar 

  7. Caughey, T.K. and M.E.J. O’Kelly (1965). Classical normal modes in damped linear dynamic systems. J. Applied Mech.,ASME. 32, 583–588.

    Article  MathSciNet  Google Scholar 

  8. Chen H.M., G.Z. Qi, J.C.S. Yang, and F. Amini (1995). Neural networks for structural dynamic model identification. J. Eng. Mech.; ASCE. 121, 1377–1382.

    Article  Google Scholar 

  9. Cifuentes, A.O. (1984). System Identification of Hysteretic Structures, EERL Report No. 84-04, California Institute of Technology, Pasadena.

    Google Scholar 

  10. Clough R.W and Penzien, J. (1975). Dynamics of Struciures, McGraw-Hill, New York, NY.

    Google Scholar 

  11. Cohen, L. (1995). Time-Frequency Analysis. Prentice Hall PTR, Upper Saddle River, NJ.

    Google Scholar 

  12. Eykhoff, P (1974). System Identification: Parameter and State Estimation. Wiley, New York.

    Google Scholar 

  13. Gelb, A. (Ed.) (1992). Applied Optimal Esrimation. The M.I.T Press, Cambridge, MA.

    Google Scholar 

  14. Ghanem, R., Shinozuka, M. and Gavin, H. (1991). Experimental verification of a number of system identification algorithms, NCEER Tech. Rep. 91-0024. Nat. Ctr for Earthquake Engrg. Res., Buffalo, NY.

    Google Scholar 

  15. Goodwin, G.C. and R.L. Payne (1977). Dynamic System Identification. Experiment Design and Data Analysts. Academic Press, New York.

    Google Scholar 

  16. Graupe, D. (1984). Time Series Analysis, Identification and Adaptive Filtering. Robert E. Krieger Publishing Co., Malabar, FL.

    MATH  Google Scholar 

  17. Hoshiya, M. and E. Saito (1984). Structural identification by extended Kalman filter. J. Eng. Mech., ASCE, 110, 1757–1770.

    Article  Google Scholar 

  18. Huang, N.E., Shen, Z., Long, S.R., Wu M.C., Shih, H.H., Zheng, Q., Yen, N: C., Tung, C.C., and Liu, H.H. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Pioc. R. Soc. Lond., 454, 903–995.

    Article  MathSciNet  MATH  Google Scholar 

  19. Hudson, D.E. (1979). Reading and Interpreting Strong Motion Accelerograms, Earthquake Engineering Reserach Institute, Oakland, CA

    Google Scholar 

  20. Jayakumar, P. and J.L. Beck (1988). System identification using nonlinear structural models. In: Pmc. Int. Workshop on Structural Safety Evaluation based on System Identification Approaches (H.G. Natke and J.T.P. Yao, Eds), Vieweg and Sons, Wiesbaden.

    Google Scholar 

  21. Jazwinski, A.H. (1970). Stochastic Processes and Filtering Theory. Academic Press, New York.

    MATH  Google Scholar 

  22. Jennings P. (1997). Use of strong motion data in earthquake resistant design, in Proc. SMIP97 Seminar on Utilization of Strong-Motion Data (Ed. by M.J. Huang), California Division of Mines and Geology. Sacramento, CA

    Google Scholar 

  23. Kailath, T. (1981). Lectures on Wiener and Kalman Filtering. Springer-Verlag, New York, NY

    MATH  Google Scholar 

  24. Kalman, R.E. and R.S. Bucy (1961). New results in linear filtering theory. J. Basic Eng. ASME. 83, 95–108.

    Article  MathSciNet  Google Scholar 

  25. Kitada, Y. (1998). Identification of nonlinear structural dynamic systems using wavelets, J. Eng. Mech., ASCE.124. 1059–1066.

    Article  Google Scholar 

  26. Köylüoğlu, U.H., Nielsen S.R.K., Abbott, J., and Çakmak, A. Ş. (1998). Local and modal damage indicators for RC frames subject to earthquakes, J. Eng. Mech., ASCE.124, 1371–1379.

    Article  Google Scholar 

  27. Kunnath, S., J.B. Mander, and L. Fang (1997). Parameter identification for degrading and pinched hysteretic structural concrete systems, Engineering Structures, 19, 224–232.

    Article  Google Scholar 

  28. Ljung, L. and T. Söderström (1983). Theory and Practice of Recursive Identification, MIT Press, Cambridge, MA.

    MATH  Google Scholar 

  29. Ljung, L. (1987). System Identification: Theory for the User. Prentice-Hall, New Jersey.

    MATH  Google Scholar 

  30. Masri, S.F, A.G. Chassiakos and T.K. Caughey (1993). Identification of nonlinear dynamic systems using neural networks. J. Applied Mech., ASME, 60, 123–133.

    Article  Google Scholar 

  31. Mathworks (1999a). Signal Processing Toolbox for MATLAB, Mathworks, Inc., Nattick, MA

    Google Scholar 

  32. Mathworks (1999b). System Identification Toolbox for MATLAB, Mathworks, Inc., Nattick, MA

    Google Scholar 

  33. Mau, S.T. and V Aruma (1994). Story drift, shear and OTM estimation from building seismic records. J. Struct. Eng., ASCE. 120, 3366–3385.

    Article  Google Scholar 

  34. McVerry, G.H. (1980). Structural identification in the frequency domain from earthquake records. Earihq. Engng. and Struct. Dyn., 8, 161–180.

    Article  Google Scholar 

  35. Natke, H.G. (Ed.) (1982). Identification of Vibrating Structures. Springer-Verlag, New York.

    MATH  Google Scholar 

  36. Newland, D.E. (1989). Mechanical Vibrations Analysis and Computation, Longman Scientific & Technical, Essex, England.

    Google Scholar 

  37. Nielsen, S.R.K, Skjarbek, P.S., Köylüoğlu U.H., and Çakmak, A. Ş (1995). Preditiction of global damage and reliability based upon sequential identification and updating of RC stuructures subject to earthquakes, Soil Dynamics & Earthquake Engineering VII (Çakmak, A.Ş. and Brebbia, A., Eds.), Computational mEchanics Pubs., Southampton, England, 361–369.

    Google Scholar 

  38. Norton, M.P. (1989). Fundamentals of Noise and Vibration Analysis for Engineers, Cambridge University Press, Cambridge, England.

    Google Scholar 

  39. Oppenheim, A.V and Schafer, R.W. (1975). Digital Signal Processing. Prentice-Hall, Englewood Cliffs. NJ.

    MATH  Google Scholar 

  40. Overschee, P.V. and Moor B.D. (1996). Subspace Identification of Linear Systems: Theory — Implemention — Applicasion. Kluwer Academic Publishers.

    Google Scholar 

  41. Pilkey. WD. and R. Cohen (Eds) (1972). System Identification of Vibrating Structures. ASME. N.Y

    MATH  Google Scholar 

  42. Pines DJ. (1997) The use of wave propagation models for structural damage identification, in Structural Health Monitoring: Current Status and Perspectives (Ed. By F.-K Chang). Technomic Publishing Co. Inc., Lancaster, PA.

    Google Scholar 

  43. Press W.H., Tekolsky, S.A., Vetterling, W.T., and Flannery, B.P. (1992). Numerical Recipes in Fortran (2nd Ed.), Cambridge University Press, Cambridge, England.

    MATH  Google Scholar 

  44. Priestley M.B. (1981). Spectral Analysis and Time Series, Academic Press, New York.

    MATH  Google Scholar 

  45. Şafak, E. (1988) Analysis of recordings in stuructural engineering: Adaptive filtering, prediction, and control, Open-File Report 88.647, U. S. Geological Survey, Menlo Park, California.

    Google Scholar 

  46. Şafak, E. (1989). Adaptive modeling, identification, and control W dynamic structural systems: Part II-Applications, J. Eng. Mech., ASCE, 115, 2406–2426

    Article  Google Scholar 

  47. Şafak, E. (1991). Identification of linear stuructures using discrete-time filters, J. Struct. Eng., ASCE. 117, 3046–3085.

    Google Scholar 

  48. Şafak, E. (1993). Response of a 42-story steel-frame building to the Ms=7.1 Lorna Prieta earthquake, Engineering Structures, 15, 403–421.

    Article  Google Scholar 

  49. Şafak, E. (1995). Detection and identification of soil-sturucture interaction in buildings from vibration recordings, J. Struct. Eng., ASCE, 121

    Google Scholar 

  50. Şafak, E. (1997a). Models and methods to charactarize site amplification from a pair of records, Earthquake Spectra. EERI. 13, pp, 97–129.

    Article  Google Scholar 

  51. Şafak, E. (1997b) New directions in seismic monitoring of multi-story buildings, in Structural Health Monitoring: Current Status and Perspectives (Ed. by F.-K. Chang). Technomic Publising Co. Inc., Lancaster, PA., 418–429.

    Google Scholar 

  52. Şafak, E. and M. Çelebi (1990a). “Method to estimate center of rigidity of a building using vibration recoordings”, J. Struct. Eng., ASCE. 116, 85–97

    Article  Google Scholar 

  53. Şafak, E. and M. Celebi (1990b). New techniques in record analyses: Torsional vibrations, Proc. 4th U. S. Nat. Conf on Earthq. Eng., EERI, 2, 411–420

    Google Scholar 

  54. Şafak, E and M. Celebi (1991). Seismic response of Transamerica Building: Part II — System identification, .J. Struct. Eng., ASCE, 117, 2405–2425.

    Article  Google Scholar 

  55. Şafak, E. and M. Çelebi (1992). Recorded seismic response of Pasific Park Plaza: Part II — System identification, J. Struct. Eng., ASCE. 118, 1566–1589.

    Article  Google Scholar 

  56. Schoukens, J. And Pintelon R. (1991). Identification of Linear Sytlems: A Practical Guideline for Acccurate Modeling. Pergamon Press, London England.

    MATH  Google Scholar 

  57. Sinha, N.K. and Kuszta, B. (1993). Modeling and Identification of Dynamic Systems. Von Nostrand Reinhold Co. Ioc., New York, NY

    Google Scholar 

  58. Söderström. T. and Stoica (1989). System Identification. Prentice-Hall, New York, NY.

    MATH  Google Scholar 

  59. Strang, G. and Nguyen, T. (1996). Wavelets and Filter Banks, Wellesley-Cambridge Press. Wellesley, MA

    MATH  Google Scholar 

  60. Sues, R.H., S.T. Mau, and Y.-K. Wen (1998). System identification of degrading hysteretic restoring forces, J. Eng. Mech., ASCE, 114, 833–846.

    Article  Google Scholar 

  61. Udwadia, F.E. and N. Jerath (1980). Time variations of structural properties during strong ground shaking. J. Eng. Mech. ASCE, 106, 111–121.

    Google Scholar 

  62. Werner, S.D., J.L. Beck and M. B. Levine (1987) Seismic response evaluation of Meloland Road Overpass using 1979 Imperial Valley earthquake records. Earthq. Engng and Struct. Dyn., 15, 749.274.

    Google Scholar 

  63. Wu, X, J. Ghaboussi, and J.H. Garrelt (1992). Use of neural networks in detection of structural damage, Computer & Structures, 42, 649–659.

    Article  MATH  Google Scholar 

  64. Y.P.C. (1984). Recursive Est imation and Time-Series Analysis. Spnnger-Verlag, New York, NY Zeldin, B.A. and P.D. Spanos (1998). Spectral identification of nonlin ear structural systems, J. Eng. Mech., ASCE, 124, 728-733.

    Google Scholar 

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Author information

Authors and Affiliations

  1. U.S Geological Survey, Golden, Colorado, USA

    Erdal Şafak

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  1. Erdal Şafak
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Editor information

Editors and Affiliations

  1. Department of Earthquake Engineering, Kandilli Observatory and Earthquake Research Institute, Çengelköy, Istanbul, Turkey

    M. Erdik

  2. Department of Earthquake Engineering, Boğaziçi University, Çengelköy, Istanbul, Turkey

    M. Erdik

  3. U.S. Geological Survey, Menlo Park, CA, USA

    M. Celebi

  4. Institute of Earthquake Engineering and Engineering Seismology, University of ’St. Cyril and Methodius’, Republic of Macedonia

    V. Mihailov

  5. Motorway Bridge Department, General Directorate of Turkish Highways, Zincirlikuyu, Istanbul, Turkey

    N. Apaydin

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Şafak, E. (2001). Analysis of Earthquake Records from Structures: An Overview. In: Erdik, M., Celebi, M., Mihailov, V., Apaydin, N. (eds) Strong Motion Instrumentation for Civil Engineering Structures. NATO Science Series, vol 373. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0696-5_7

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  • DOI: https://doi.org/10.1007/978-94-010-0696-5_7

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-0-7923-6917-2

  • Online ISBN: 978-94-010-0696-5

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