Skip to main content

On the Probability of Localizing Damages Based on Mode Shape Changes

  • Conference paper
  • First Online:
European Workshop on Structural Health Monitoring (EWSHM 2022)

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 253))

Included in the following conference series:

  • 1941 Accesses

Abstract

Obtaining reliable diagnosis results based on modal parameter changes is a challenge due to their low sensitivity to local damages and uncertainties related to their estimation, especially under ambient excitation. In non-destructive testing, the reliability is quantified through probability of detection (POD) curves, which are often limited to damage detection and cannot be applied to structural health monitoring applications where no data from the damaged state is available. To fill this gap, a method is developed in this paper that allows one to create probability of localization curves (POL curves) based on measurements from undamaged structures. The approach is based on statistical damage localization tests and requires a finite element model. For proof of concept, the method is applied to a simple numerical structure, demonstrating that it is a powerful tool to analyze the performance of SHM systems before damage occurs. The findings demonstrate that the POL increases with an increasing number of observed modes of vibration, an increasing measurement duration, an appropriate sensor layout, and low measurement noise levels.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Farrar, C., Worden, K.: Structural Health Monitoring: A Machine Learning Perspective. Wiley, Oxford (2012)

    Book  Google Scholar 

  2. Deraemaeker, A., Reynders, E., De Roeck, G., Kullaa, J.: Vibration-based structural health monitoring using output-only measurements under changing environment. Mech. Syst. Signal Process. 22(1), 34–56 (2008)

    Article  Google Scholar 

  3. Salawu, O.S.: Detection of structural damage through changes in frequency: a review. Eng. Struct. 19(9), 718–723 (1997)

    Article  Google Scholar 

  4. Anastasopoulos, D., De Roeck, G., Reynders, E.P.: One-year operational modal analysis of a steel bridge from high-resolution macrostrain monitoring: influence of temperature vs. retrofitting. Mech. Syst. Signal Process. 161, 107951 (2021)

    Article  Google Scholar 

  5. Merainani, B., Xiong, B., Baltazart, V., Dumoulin, J., Dohler, M., Zhang, Q.: Experimental investigation of structural modal identification using pixels intensity and motion signals from video-based imaging devices: performance, comparison and analysis. In: Multimodal Sensing and Artificial Intelligence: Technologies and Applications II, vol. 11785, p. 1178508. International Society for Optics and Photonics, June 2021

    Google Scholar 

  6. Berens, A.P.: NDE Reliability Data Analysis-Metals Handbook. ASM International, United States (1989)

    Google Scholar 

  7. Mendler, A., Döhler, M., Ventura, C.E.: A reliability-based approach to determine the minimum detectable damage for statistical damage detection. Mech. Syst. Signal Process. 154, 107561 (2021)

    Article  Google Scholar 

  8. Yan, A.M., Golinval, J.C.: Null subspace-based damage detection of structures using vibration measurements. Mech. Syst. Signal Process. 20(3), 611–626 (2006)

    Article  Google Scholar 

  9. Greś, S., Döhler, M., Andersen, P., Mevel, L.: Subspace-based Mahalanobis damage detection robust to changes in excitation covariance. Struct. Control. Health Monit. 28(8), e2760 (2021)

    Article  Google Scholar 

  10. Basseville, M., Abdelghani, M., Benveniste, A.: Subspace-based fault detection algorithms for vibration monitoring. Automatica 36(1), 101–109 (2000)

    Article  MathSciNet  Google Scholar 

  11. Döhler, M., Mevel, L., Hille, F.: Subspace-based damage detection under changes in the ambient excitation statistics. Mech. Syst. Signal Process. 45(1), 207–224 (2014)

    Article  Google Scholar 

  12. Benveniste, A., Basseville, M., Moustakides, G.: The asymptotic local approach to change detection and model validation. IEEE Trans. Autom. Control 32(7), 583–592 (1987)

    Article  MathSciNet  Google Scholar 

  13. Basseville, M., Mevel, L., Goursat, M.: Statistical model-based damage detection and localization: subspace-based residuals and damage-to-noise sensitivity ratios. J. Sound Vib. 275(3–5), 769–794 (2004)

    Article  Google Scholar 

  14. Fox, R.L., Kapoor, M.P.: Rates of change of eigenvalues and eigenvectors. AIAA J. 6(12), 2426–2429 (1968)

    Article  Google Scholar 

  15. Nelson, R.B.: Simplified calculation of eigenvector derivatives. AIAA J. 14(9), 1201–1205 (1976)

    Article  MathSciNet  Google Scholar 

  16. Reynders, E., Pintelon, R., De Roeck, G.: Uncertainty bounds on modal parameters obtained from stochastic subspace identification. Mech. Syst. Signal Process. 22(4), 948–969 (2008)

    Article  Google Scholar 

  17. Döhler, M., Mevel, L.: Efficient multi-order uncertainty computation for stochastic subspace identification. Mech. Syst. Signal Process. 38(2), 346–366 (2013)

    Article  Google Scholar 

  18. Mendler, A., Döhler, M., Ventura, C.E.: Sensor placement with optimal damage detectability for statistical damage detection. Mech. Syst. Signal Process. 170, 108767 (2022)

    Article  Google Scholar 

Download references

Acknowledgements

This research study is funded by dtec.bw - Digitalization and Technology Research Center of the Bundeswehr.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexander Mendler .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mendler, A., Greś, S., Döhler, M., Keßler, S. (2023). On the Probability of Localizing Damages Based on Mode Shape Changes. In: Rizzo, P., Milazzo, A. (eds) European Workshop on Structural Health Monitoring. EWSHM 2022. Lecture Notes in Civil Engineering, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-031-07254-3_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-07254-3_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-07253-6

  • Online ISBN: 978-3-031-07254-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics