This paper reviews stochastic system identification methods that have been used to estimate the modal parameters of vibrating structures in operational conditions. It is found that many classical input-output methods have an output-only counterpart. For instance, the Complex Mode Indication Function (CMIF) can be applied both to Frequency Response Functions and output power and cross spectra. The Polyreference Time Domain (PTD) method applied to impulse responses is similar to the Instrumental Variable (IV) method applied to output covariances. The Eigensystem Realization Algorithm (ERA) is equivalent to stochastic subspace identification.

1.
Heylen, W., Lammens, S., and Sas, P., 1995, Modal Analysis Theory and Testing, Department of Mechanical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium.
2.
Maia, N. M. M., Silva, J. M. M., He, J., Lieven, N. A. J., Lin, R. M., Skingle, G. W., To, W.-M., and Urgueira, A. P. V., 1997, Theoretical and Experimental Modal Analysis, Research Studies Press, Taunton, Somerset, UK.
3.
Allemang, R. J., 1999, Vibrations: Experimental Modal Analysis, Course Notes, Seventh Edition, Structural Dynamics Research Laboratory, University of Cincinnati, OH. [http://www.sdrl.uc.edu/course_info.html].
4.
Ewins, D. J., 2000, Modal Testing: Theory, Practice and Application, Research Studies Press, Baldock, Hertfordshire, UK.
5.
Abdelghani
,
M.
,
Verhaegen
,
M.
,
Van Overschee
,
P.
, and
De Moor
,
B.
,
1998
, “
Comparison study of subspace identification methods applied to flexible structures
,”
Mech. Syst. Signal Process.
,
12
, No.
5
, pp.
679
692
.
6.
Petsounis, K. A., and Fassois, S. D., 2001, “Critical comparison and assessment of parametric time domain methods for the identification of vibrating structures.” Mech. Syst. Signal Process., accepted for publication.
7.
Peeters, B., 2000, “System Identification and Damage Detection in Civil Engineering,” PhD thesis, Department of Civil Engineering, Katholieke Universiteit Leuven, Belgium, [http://www.bwk.kuleuven.ac.be/bwm], Dec.
8.
Hermans
,
L.
, and
Van der Auweraer
,
H.
,
1999
, “
Modal testing and analysis of structures under operational conditions: industrial applications
,”
Mech. Syst. Signal Process.
,
13
, No.
2
, pp.
193
216
.
9.
Peeters
,
B.
, and
De Roeck
,
G.
,
2001
, “
One-year monitoring of the Z24-Bridge: environmental effects versus damage events
,”
Earthquake Eng. Struct. Dyn.
,
30
, No.
2
,
149
171
.
10.
Ljung, L., 1999, System Identification: Theory for the User, Second Edition, Prentice-Hall, Upper Saddle River, NJ.
11.
Peeters
,
B.
, and
De Roeck
,
G.
,
1999
, “
Reference-based stochastic subspace identification for output-only modal analysis
,”
Mech. Syst. Signal Process.
,
13
, No.
6
, pp.
855
878
.
12.
Akaike
,
H.
,
1974
, “
Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes
,”
Annals of the Institute of Statistical Mathematics
,
26
, pp.
363
387
.
13.
Basseville, M., and Nikiforov I. V., 1993, Detection of Abrupt Changes: Theory and Applications, Prentice-Hall, Englewood Cliffs, NJ. [http://www.irisa.fr/sigma2/kniga].
14.
Caines, P., 1998, Linear Stochastic Systems, Wiley, New York.
15.
Bendat, J. S. and Piersol, A. G., 1993, Engineering Applications of Correlation and Spectral Analysis, Second Edition, Wiley, New York.
16.
Stoica, P. and Moses, R. L., 1997, Introduction to Spectral Analysis, Prentice-Hall, Englewood Cliffs, NJ.
17.
Felber, A. J., 1993, “Development of a Hybrid Bridge Evaluation System,” PhD thesis, University of British Columbia, Vancouver, Canada.
18.
Felber, A. J. and Cantieni, R., 1996, Introduction of a New Ambient Vibration Testing System-Description of the System and Seven Bridge Tests, Internal Report 156’521, EMPA, Du¨bendorf, Switzerland.
19.
Cunha, A., Caetano, E., Calc¸ada, R., and Delgado, R., 1999, “Modal identification and correlation with finite element parameters of Vasco da Gama Bridge,” Proceedings of IMAC 17, pp. 705–711, Kissimmee, FL, Feb.
20.
Prevosto, M., 1982, “Algorithmes d’Identification des Caracte´ristiques Vibratoires de Structures Me´caniques Complexes,” PhD thesis, Universite´ de Rennes I, France, Mar.
21.
Shih
,
C. Y.
,
Tsuei
,
Y. G.
,
Allemang
,
R. J.
, and
Brown
,
D. L.
,
1988
, “
Complex mode indication function and its application to spatial domain parameter estimation
,”
Mech. Syst. Signal Process.
,
2
, No.
4
, pp.
367
377
.
22.
Brincker, R., Zhang, L., and Andersen, P., 2000, “Modal identification from ambient responses using frequency domain decomposition,” Proceedings of IMAC 18, the International Modal Analysis Conference, pp. 625–630, San Antonio, TX, Feb.
23.
Golub, G. H. and Van Loan, C. F., 1996, Matrix Computations, Third Edition, The Johns Hopkins University Press, Baltimore, MD.
24.
Schoukens J. and Pintelon R., 1991, Identification of Linear Systems: a Practical Guideline to Accurate Modelling, Pergamon Press, London, UK.
25.
Pintelon
,
R.
,
Guillaume
,
P.
,
Rolain
,
Y.
,
Schoukens
,
J.
, and
Van Hamme
,
H.
,
1994
, “
Parametric identification of transfer functions in the frequency domain-a survey
,”
IEEE Trans. Autom. Control
,
AC-39
, No.
11
, pp.
2245
2260
.
26.
Guillaume P., Verboven P., and Vanlanduit S., 1998, “Frequency-domain maximum likelihood identification of modal parameters with confidence intervals,” Proceedings of ISMA 23, Noise and Vibration Engineering, K. U. Leuven, Belgium.
27.
Vanlanduit, S, Guillaume P., and Schoukens, J., 1998, “High spatial resolution modal parameter estimation using a parametric MLE-like algorithm,” Proceedings of ISMA 23, Noise and Vibration Engineering, K. U. Leuven, Belgium.
28.
Hermans, L., Guillaume, P., and Van der Auweraer, H., 1998, “A frequency-domain maximum likelihood approach for the extraction of modal parameters from output-only data,” Proceedings of ISMA 23, Noise and Vibration Engineering, K. U. Leuven, Belgium.
29.
James
,
G. H.
,
Carne
,
T. G.
, and
Lauffer
,
J. P.
,
1995
, “
The natural excitation technique (NExT) for modal parameter extraction from operating structures
,”
Int. J. Anal. Exp. Modal Anal.
,
10
, No.
4
, pp.
260
277
.
30.
Leuridan, J., 1984, “Some Direct Parameter Model Identification Methods Applicable for Multiple Input Modal Analysis,” PhD thesis, University of Cincinnati, OH.
31.
Allemang, R. J., Brown, D. L., and Fladung, W. A., 1994, “Modal parameter estimation: a unified matrix polynomial approach,” Proceedings of IMAC 12, the International Modal Analysis Conference, pp. 501–514, Honolulu, HI.
32.
Benveniste
,
A.
, and
Fuchs
,
J.-J.
,
1985
, “
Single sample modal identification of a nonstationary stochastic process
,”
IEEE Trans. Autom. Control
,
AC-30
, No.
1
, pp.
66
74
.
33.
Ho
,
B. L.
, and
Kalman
,
R. E.
,
1966
, “
Effective construction of linear state-variable models from input/output data
,”
Regelungstechnik
,
14
, pp.
545
548
.
34.
Zeiger
,
H. P.
, and
McEwen
,
A. J.
,
1974
, “
Approximate linear realization of given dimension via Ho’s algorithm
,”
IEEE Trans. Autom. Control
,
AC-19
, No.
2
, pp.
53
53
.
35.
Kung, S. Y., 1974, “A new identification and model reduction algorithm via singular value decomposition.” Procedings of the 12th Asilomar Conference on Circuits, Systems and Computers, pp. 705–714, Asilomar, CA, USA, Nov.
36.
Juang, J.-N., and Pappa, R. S., 1985, “An eigensystem realization algorithm for modal parameter identification and model reduction,” J. Guid. Control Dyn.
37.
Juang, J.-N., 1994, Applied System Identification, Prentice Hall, Englewood Cliffs, NJ.
38.
Desai
,
U. B.
,
Pal
,
D.
, and
Kirkpatrick
,
R. D.
,
1985
, “
A realization approach to stochastic model reduction
,”
Int. J. Control
42
, pp.
821
839
.
39.
Aoki M., 1987, State Space Modelling of Time Series, Springer-Verlag, Berlin, Germany.
40.
Arun
,
K. S.
, and
Kung
,
S. Y.
,
1990
, “
Balanced approximation of stochastic systems
,”
SIAM J. Matrix Anal. Appl.
,
11
, pp.
42
68
.
41.
Akaike
,
H.
,
1974
, “
Stochastic theory of minimal realization
,”
IEEE Trans. Autom. Control
,
19
, pp.
667
674
.
42.
Van Overschee, P., and De Moor, B. 1996, Subspace Identification for Linear Systems: Theory-Implementation-Applications, Kluwer Academic Publishers, Dordrecht, The Netherlands.
43.
Camba-Mendez
,
G.
, and
Kapetanios
,
G.
,
2001
, “
Testing the rank of the Hankel covariance matrix: a statistical approach
,”
IEEE Trans. Autom. Control
,
AC-46
, No.
2
, pp.
325
330
.
44.
Van Overschee
,
P.
, and
De Moor
,
B.
,
1993
, “
Subspace algorithm for the stochastic identification problem
,”
Automatica
,
29
, No.
3
, pp.
649
660
.
45.
Viberg
,
M.
,
1995
, “
Subspace-based methods for the identification of linear time-invariant systems
,”
Automatica
,
31
, No.
12
, pp.
1835
1851
.
46.
Kirkegaard P. H., and Andersen, P., 1997, “State space identification of civil engineering structures from output measurements,” Proceedings of IMAC 15, The International Modal Analysis Conference, pp. 889–895, Orlando, FL.
47.
Peeters, B., De Roeck, G., and Andersen, P., 1999, “Stochastic system identification: uncertainty of the estimated modal parameters,” Proceedings of IMAC 17, The International Modal Analysis Conference, pp. 231–237, Kissimmee, FL, Feb.
48.
Piombo, B., Ciorcelli, E., Garibaldi, L., and Fasana, A., 1993, “Structures identification using ARMAV models,” Proceedings of IMAC 11, the International Modal Analysis Conference, pp. 588–592, Orlando, FL.
49.
Andersen, P., 1997, “Identification of Civil Engineering Structures Using Vector ARMA Models,” PhD thesis, Department of Building Technology and Structural Engineering, Aalborg University, Denmark, May.
50.
Pandit, S. M., 1991, Modal and Spectrum Analysis: Data Dependent Systems in State Space, Wiley, New York.
51.
De, Roeck G., Claesen, W., and Van den Broeck, P., 1995, “DDS-methodology applied to parameter identification of civil engineering structures,” Vibration and Noise ’95, pp. 341–353, Venice, Italy, Apr.
You do not currently have access to this content.