Skip to main content
Log in

Improved eigensystem realization algorithm and its application on ocean platforms

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

Based on the matrix mapping theory, an improved eigensystem realization algorithm (ERA), called C/ERA, is proposed in this paper. It rebuilds a Hankel matrix by replacing all elements of each anti-subdiagonal with the arithmetic average of the elements along the anti-subdiagonal, and introduces the concept of using the Frobenius norm (L2-norm) to control the iterations number after implementing the SVD algorithm by the ERA method. With the data associated with a 5-DOF mass-spring-dashpot system and jacket-type platform under impact loading, it is demonstrated that C/ERA has a better capacity of de-noising, and a higher accuracy for low-order modes, and can identify more high-order modes than the ERA method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Juang, J.N., Pappa, R.S.: Eigensystem realization algorithm (ERA) for modal parameter identification and model reduction. J. Guid. Control Dyn. 8(5), 620–627 (1985)

    Google Scholar 

  2. Hu, S.-L.J., Li, P., Vincent, H., Li, H.: Modal parameter estimation for jacket-type platforms using free-vibration data. J. Waterway Port Coast Ocean Eng 37(5), 45–53 (2011)

    Google Scholar 

  3. Xin, J.F., Sheng, J.L., Zhang, Y.B.: Data-driven stochastic subspace method selection and noise matrix dimension problem research. Vib. Shock 32(16), 152–157 (2013)

    Google Scholar 

  4. Cunha, A., Caetano, E.: Experimental modal analysis of civil engineering structures. Sound Vib. 40(6), 12–20 (2006)

    Google Scholar 

  5. Juang, J.N., Pappa, R.S.: Effects of noise on modal parameters identified by eigensystem realization algorithm. J. Guid. Control Dyn. 9(3), 294–303 (2015)

    Google Scholar 

  6. Cadzow, J.A.: Signal enhancement of composite property mapping algorithm. IEEE Trans. Acoust. Speech Signal Process. 36(1), 49–62 (1988)

    Google Scholar 

  7. Chu, M.T., Funderlic, R.E., Plemmons, R.J.: Structured low rank approximation. Linear Algebr. Appl. 366(2), 157–172 (2003)

    Google Scholar 

  8. Xin, J.F.: Study on modal parameter identification of offshore platform based on stochastic subspace method. Ocean University of China (2013)

  9. ANSYS. Inc, ed.: ANSYS academic research. Release 9.0. Help System. Coupled Field Analysis Guide10 (2004)

Download references

Acknowledgements

The study has been supported by Natural Science Foundation of China (Grant No. 51609120), Science and Technology Plan for Shandong University(Grant No. J16LB7) and Qingdao Urban and Rural Construction Committee (Grant No. JK2015-15).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Junfeng Xin.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xin, J., Lei, W., Shixin, L. et al. Improved eigensystem realization algorithm and its application on ocean platforms. Cluster Comput 22 (Suppl 2), 3643–3650 (2019). https://doi.org/10.1007/s10586-018-2213-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-018-2213-0

Keywords

Navigation