Estimation of Damping for a Double-Layer Grid Using Input-Output and Output-Only Modal Identification Techniques

Document Type: Research Papers


1 Babol Noshirvani University of Technology.

2 Faculty of civil engineering, Babol Noshirvani university of technology

3 Department of Civil Engineering, Payame Noor University (PNU).


In large civil engineering structures, the output-only modal identification is the most applicable technique for estimating the modal parameters such as damping. However, due to no measurement and control of excitation force, the identified parameters obtained by output-only technique have more uncertainty than those derived from the input-output technique. Given the different nature and uncertainties of the two modal identification techniques, in the present study, the damping related to the first 12 modes of a double-layer grid developed from the ball joint system were identified via the two techniques and compared with each other. For this purpose, a double-layer grid was constructed by pipes and balls with free-free boundary conditions provided for both input-output and output-only experiments. Exciting the grid, its acceleration response was measured at appropriate degrees of freedom. Then, by using these data and performing modal analysis, involving four different methods of input-output and five different methods of output-only, the natural frequencies and damping ratios of the desired modes were extracted. The results indicated that despite the good agreement between the modal damping of the grid, as identified by different methods of input-output together and by different methods of output-only together, the results of input-output and output-only methods were different with each other. The damping values through the input-output modal identification methods were on average 65% higher than the corresponding values of the output-only modal identification methods.


Avitabile, P. (2006). “Modal space: Someone told me that operating modal analysis produces better results and that damping is much more realistic”, Experimental Techniques, 30 (6), 25-26.
Azam, S.E., Mariani, S. and Attari, N.K.A. (2017). “Online damage detection via a synergy of proper orthogonal decomposition and recursive Bayesian filters”, Nonlinear Dynamics, 89(2), 1489-1511.
Beskhyroun, S., Wotherspoon, L.M. and Ma, Q.T. (2013). “System identification of a 13-Story reinforced concrete building through ambient and forced vibration”, 4th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN), Kos Island, Greece.
Brincker, R., Ventura, C.E. and Andersen, P. (2001). “Damping estimation by frequency domain decomposition”, Proceedings of the 19th International Modal Analysis Conference (IMAC), February 5-8, The Hyatt Orlando, Kissimmee, Florida, pp. 698-703.
Brincker, R., Ventura, C. and Andersen, P. (2003). “Why output-only modal testing is a desirable tool for a wide range of practical applications”, Proceedings of  IMAC-21: A Conference on Structural Dynamics, February 3-6, The Hyatt Orlando, Kissimmee, Florida, pp. 265-272.
Brincker, R. and Andersen, P. (2006). “Understanding stochastic subspace identification”,  Proceedings of the 24th (IMAC), The Hyatt Orlando, Kissimmee, Florida, pp. 279-311.
Brincker, R. and Kirkegaard, P.H. (2010). “Special issue on operational modal analysis”, Mechanical Systems and Signal Processing, 5(24), 1209-1212.
Brincker, R. and Ventura, C. (2015). Introduction to operational modal analysis, John Wiley and Sons.
Chopra, A.K. (2001). Dynamics of structures: Theory and applications to earthquake engineering, Prentice Hall.
Davoodi, M.R., Navayi Neya, B., Mostafavian, S.A., Nabavian, S.R. and Jahangiry, Gh.R. (2017). “Determining minimum number of required accelerometer for output-only structural identification of frames”, 7th International Operatuinal Modal Analysis Conference “IOMAC2017”, May 10-12, Ingolstadt, Germany.
Davoodi, M.R., Mahdavi, M. and Mostafavian, S.A. (2012). “Experimental and analytical determination of dynamic properties of a steel frame with bolted flange joints”, Proceedings of International Conference on Engineering and Information Technology “ICEIT2012”, September, Toronto, Canada, pp. 17-18.
Davoodi, M.R., Amiri, J.V., Gholampour, S. and Mostafavian, S.A. (2012). “Determination of nonlinear behavior of a ball joint system by model updating”, Journal of Constructional Steel Research, 71, 52-62.
De Almeida Cardoso, R., Cury, A., Barbosa, F. and Gentile, C. (2019). “Unsupervised real-time SHM technique based on novelty indexes”, Structural Control and Health Monitoring, 26(7), e2364.
  Dertimanis, V.K., Chatzi, E.N., Azam, S.E. and Papadimitriou, C. (2019). “Input-state-parameter estimation of structural systems from limited output information”, Mechanical Systems and Signal Processing, 126, 711-746.
Ewins, D.J. (2000). Modal testing : Theory, practice, and application,  John Wiley & Sons.
Felber, A.J. (1994). “Development of a hybrid bridge evaluation system”, Ph.D. Thesis, University of British Columbia.
Gade, S., Møller, N., Herlufsen, H. and Konstantin-Hansen, H. (2005). “Frequency domain techniques for operational modal analysis”, The 1st IOMAC Conference, April 26, Copenhagen, Denmark.
Giraldo, D.F., Song, W., Dyke, S.J. and Caicedo, J.M. (2009). “Modal identification through ambient vibration: Comparative study”, Journal of Engineering Mechanics, 135 (8), 759-770.
Gomes, J., Pereira, S., Magalhães, F., Lemos, J.V. and Cunha, A. (2018). “Input-output vs output-only modal identification of Baixo Sabor Concrete Arch Dam”, The 9th European Workshop on Structural Health Monitoring, July 10-13, Manchester, United Kingdom.
He, J. and Fu, Z.F. (2001). Modal analysis, Butterworth-Heinemann.
Jacobsen, N.J., Andersen, P. and Brincker, R. (2008). “Applications of frequency domain curve-fitting in the EFDD technique”, Proceedings IMAC XXVI Conference, February 4, Orlando, Florida, United States.
Lauwagie, T., Van Assche, R., Van der Straeten, J. and Heylen, W. (2006). “A comparison of experimental, operational, and combined experimental-operational parameter estimation techniques”, Proceedings of the International Noise and Vibration Conference, ISMA,  September 1, Heverlee, Belgium, pp. 2997-3006.
Magalhães, F., Cunha, A., Caetano, E. and Brincker, R. (2010). “Damping estimation using free decays and ambient vibration tests”, Mechanical Systems and Signal Processing, 24 (5), 1274-1290.
Mbarek, A., Del Rincon, A., Hammami, A., Iglesias, M., Chaari, F., Viadero, F. and Haddar, M. (2018). “Comparison of experimental and operational modal analysis on a back to back planetary gear”, Mechanism and Machine Theory, 124, 226-247.
Mostafavian, S.A., Davoodi, M.R. and Vaseghi Amiri, J. (2012). “Ball joint behavior in a double layer grid by dynamic model updating”, Journal of Constructional Steel Research, 76,  28-38.
Orlowitz, E. and Brandt, A. (2017). “Comparison of experimental and operational modal analysis on a laboratory ttest plate”, Measurement, 102(May), 121-130.
Perez-Ramirez, C.A., Amezquita-Sanchez, J.P., Valtierra-Rodriguez, M., Adeli, H., Dominguez-Gonzalez, A. and Romero-Troncoso, R.J. (2019). “Recurrent neural network model with Bayesian training and mutual information for response prediction of large buildings”, Engineering Structures, 178, 603-615.
Qarib, H. and Adeli, H. (2016). “A comparative study of signal processing methods for structural health monitoring”, Journal of Vibroengineering, 18(4), 2186-2204.
Qarib, H. and Adeli, H. (2015). “A new adaptive algorithm for automated feature extraction in exponentially damped signals for health monitoring of smart structures”,  Smart Materials and Structures, 24(12), 125040.
Rainieri, C. and Fabbrocino, G. (2014) “Influence of model order and number of block rows on accuracy and precision of modal parameter estimates in stochastic subspace identification”, International Journal of Lifecycle Performance Engineering 10, 1(4), 317-334.
Reynders, E. and  De Roeck, G. (2008). “Reference-based combined deterministic–stochastic subspace identification for experimental and operational modal analysis”, Mechanical Systems and Signal Processing, 22(3), 617-637.
Rezaifar, O. and Doost Mohammadi, M.R. (2016). “Damage detection of axially loaded beam: A frequency-based method”, Civil Engineering Infrastructures Journal, 49(1), 165-172.
Sestieri, A. and D’ambrogio, W. (2003). “Frequency response function versus output-only modal testing identification”, Proceedings of 21st IMAC, 3-6 February, Kissimmee, Florida, pp. 41-46.
Sony, S., Laventure, S. and Sadhu, A. (2019). “A literature review of next‐generation smart sensing technology in structural health monitoring”, Structural Control and Health Monitoring, 26(3), e2321.
Srikantha Phani, A. and Woodhouse, J. (2007). “Viscous damping identification in linear vibration”, Journal of Sound and Vibration, 303 (3-5), 475-500.
Structural Vibration Solutions (SVS). (2015). ARTeMIS Modal 4, Denmark.
Thibault, L., Marinone, T. Avitabile, P. and van Karsenvan, C. (2012). “Comparison of modal parameters estimated from opproaches”, In: Topics in Modal Analysis I, Volume 5, 77-88, Springer.
Van Overschee, P. and De Moor, B.L. (2012). Subspace identification for linear systems: Theory-implementation-applications, Springer Science and Business Media.
Yasi, B. and Mohammadizadeh, M.R. (2018). “Identification of structural defects using computer algorithms”, Civil Engineering Infrastructures Journal, 51(1), 55-86.
Zhang, G., Tang, B. and Tang, G. (2012). “An improved stochastic subspace identification for operational modal analysis”, Measurement, 45(5), 1246-1256.