Robust Sensor and Exciter Design for Linear Structures

  • Fabien MauganEmail author
  • Scott Cogan
  • Emmanuel Foltête
  • Aurélien Hot
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)


A wide variety of model-based modal test design methodologies have been developed over the past two decades using a non-validated baseline model of the structure of interest. Due to the presence of lack of knowledge, this process can lead to less than optimal distributions of sensors and exciters due to the discrepancy between the model and the prototype behaviors. More recent strategies take into account statistical variability in model parameters but the results depend strongly on the hypothesized distributions. This paper provides a decision making tool using a robust satisficing approach that provides a better understanding of the trade-off between the performance of the test design and its robustness to model form errors and associated imprecisions. The latter will be represented as an info-gap model and the proposed methodology seeks a sensor and exciter distribution that will satisfy a given design performance while tolerating a specified degree of modeling error. The evolution of this performance for increasing horizons of uncertainty is an important information for the test planner in choosing the total number of sensors. The methodology will be illustrated on an academic but practically useful example under severe uncertainty.


Sensor placement Robustness Info-gap Uncertainty Lack of knowledge 



The authors want to thanks the CNES of Toulouse and Région Franche-Comté for their financial support.


  1. 1.
    Abdelghani, M., Friswell, M.I.: Sensor validation for structural systems with multiplicative sensor faults. Mech. Syst. Signal Process. 21, 270–279 (2007)CrossRefGoogle Scholar
  2. 2.
    Balmes, E.: Uncertainty propagation in experimental modal analysis. In: International Modal Analysis Conference (2004)Google Scholar
  3. 3.
    Balmes, E.: Orthogonal maximum sequence sensor placements algorithms for modal tests, expansion and visibility. In: International Modal Analysis Conference, Orlando (2005)Google Scholar
  4. 4.
    Ben-Haim, Y.: Info-Gap, Decision theory, Decisions Under Severe Uncertainty, 2nd edn. Academic, New York (2006)Google Scholar
  5. 5.
    Golub, G., Kahan, W.: Calculating the singular values and pseudo-inverse of a matrix. J. Soc. Ind. Appl. Math. Ser. B Numer. Anal. 2 (2), 205–224 (1965)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Hemez, F., Farhat, C.: An energy based optimum sensor placement criterion and its application to structural damage detection. In: International Modal Analysis Conference, pp. 1568–1575 (1994)Google Scholar
  7. 7.
    Kammer, D.C.: Sensor placement for non-orbitmodal identification and correlation of large space strucutres. J. Guid. Control Dyn. 14 (2), 251–259 (1991)CrossRefGoogle Scholar
  8. 8.
    Kammer, D.C.: Effect of model error on sensor placement for on-orbit modal identification of large space structures. J. Guid. Control Dyn. 15 (2), 334–341 (1992)CrossRefzbMATHGoogle Scholar
  9. 9.
    Kammer, D.C., Falnigan, C.C., Dreyer, W.: A super-element approach to test-analysis model development. In: Proceedings of the Fourth International Modal Analysis Conference, pp. 663–673 (1986)Google Scholar
  10. 10.
    Lallement, G., Ramanitrajan, A., Cogan, S.: Optimal sensor deployment: application to model updating. J. Vib. Control 4, 29–46 (1998)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Papapdimitriou, C., Beck, J.L., Au, S.K.: Entropy-based optimal sensor location for structural model updating. J. Vib. Control 6, 781–800 (2000)CrossRefGoogle Scholar
  12. 12.
    Qstro-Triguero, R., Murugan, S., Gallego, R., Friswell, M.I.: Robustnessofoptimalsensorplacementunder parametric uncertainty. Mech. Syst. Signal Process. 41, 268–287 (2013)CrossRefGoogle Scholar
  13. 13.
    Schedlinski, C., Link, M.: An approach to optimal pick-up and exciter placement. In: Proceedings-SPIE the International Society for Optical Engineering, SPIE International Society for Optical, pp. 376–382 (1996)Google Scholar
  14. 14.
    Schueller, G.I.: On the treatment of uncertainties in structural mechanics and analysis. Comput. Struct. 2007, 235–243 (2007)CrossRefGoogle Scholar
  15. 15.
    Vinot, P., Cogan, S., Cipolla, V.: A robust model-based test planning procedure. J. Guid. Control Dyn. 288, 571–585 (2005)Google Scholar
  16. 16.
    Williams, R., Crowley, J., Vold, H.: The multivariate mode indicator function in modal analysis. In: International Modal Analysis Conference, pp. 66–70 (1985)Google Scholar
  17. 17.
    Zang, C., Friswell, M.I., Mottershead, J.E.: A review of robust design and its application in dynamics. Comput. Struct. 83, 315–326 (2005)CrossRefGoogle Scholar

Copyright information

© The Society for Experimental Mechanics, Inc. 2016

Authors and Affiliations

  • Fabien Maugan
    • 1
    Email author
  • Scott Cogan
    • 1
  • Emmanuel Foltête
    • 1
  • Aurélien Hot
    • 2
  1. 1.Applied Mechanics DepartmentFEMTO-ST InstituteBesançonFrance
  2. 2.Spatial Center of ToulouseToulouse Cedex 9France

Personalised recommendations