Advertisement

Journal of Civil Structural Health Monitoring

, Volume 9, Issue 1, pp 137–151 | Cite as

Sensitivity-based damage detection algorithm for structures using vibration data

  • C. G. KrishnanunniEmail author
  • R. Sethu Raj
  • Deepak Nandan
  • C. K. Midhun
  • A. S. Sajith
  • Mohammed Ameen
Original Paper
  • 223 Downloads

Abstract

Damage in a structure can lead to changes in the structural properties such as stiffness and natural frequencies. The ratio of frequency changes in two modes is a function of the damage location. In this paper, vibration data and static displacement measurements are used to detect and quantify structural damages. A sensitivity analysis is performed to study how natural frequencies and static displacements change in the presence of a structural damage. An objective function representing an error is defined using the sensitivity equation and minimized using Cuckoo Search algorithm. The effectiveness of the technique is demonstrated with the help of cantilever beams and fixed–fixed beam in which different damage scenarios are simulated using ANSYS and analyzed to obtain the modal parameters. In addition, a laboratory tested space frame model has been used to demonstrate the proposed technique. Numerical results indicate that damages can be accurately detected and quantified in a relatively shorter computational time using the Cuckoo Search algorithm.

Keywords

Damage Sensitivity equation Vibration Objective function Algorithm 

Notes

Acknowledgements

The authors would like to thank Enupala Indu for providing technical assistance for the work conducted at National institute of Technology, Calicut. The authors would also like to thank Minu Ann Peter for the technical assistance on the use of uni-axial shake table for data acquisition.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest in preparing this article.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

References

  1. 1.
    Zou Y, Tong GP, Steven (2000) Vibration-based model-dependent damage (delamination) identification and health monitoring for composite structures: a review. J Sound Vibr 230(2):357–378Google Scholar
  2. 2.
    Salawu OS (1997) Detection of structural damage through changes in frequency: a review. Eng Struct 19(9):718–723CrossRefGoogle Scholar
  3. 3.
    Pandey AK, Biswas M, Samman MM (1991) Damage detection from changes in curvature mode shapes. J Sound Vibr 145(2):321–332CrossRefGoogle Scholar
  4. 4.
    Zhao J, Ivan J, DeWolf J (1998) Structural damage detection using Artificial Neural Networks. J Infrastruct Syst 4(3):93–101CrossRefGoogle Scholar
  5. 5.
    Yam LH, Yan YJ, Jiang JS (2003) Vibration-based damage detection for composite structures using wavelet transform and neural network identification. J Compos Struct 60(4):403–412CrossRefGoogle Scholar
  6. 6.
    Hou Z, Noori M, Amand RST (2000) Wavelet based approach for structural damage detection. J Eng Mech 126(7):677–683Google Scholar
  7. 7.
    Curadelli RO, Riera JD, Ambrosini D, Amani MG (2008) Damage detection by means of structural damping identification. Eng Struct 30(12):3497–3504CrossRefGoogle Scholar
  8. 8.
    Hassiotis S, Jeong GD (1995) Identification of stiffness reduction using natural frequencies. J Eng Mech 121(10):1106–1113CrossRefGoogle Scholar
  9. 9.
    Hajela P, Soeiro FJ (1990) Structural damage detection based on static and modal analysis. AIAA J 28(4):1110–1115CrossRefGoogle Scholar
  10. 10.
    Hao Hong, Xia Yong (2002) Vibration-based damage detection of structures by genetic algorithm. J Comput Civ Eng 16(3):222–229MathSciNetCrossRefGoogle Scholar
  11. 11.
    Casciati S, Elia L (2017) Damage localization in a cable-stayed bridge via bio-inspired metaheuristic tools. Struct Control Health Monit 24(5):e1922CrossRefGoogle Scholar
  12. 12.
    Quaranta Giuseppe, Carboni Biagio, Lacarbonara Walter (2016) Damage detection by modal curvatures: numerical issues. J Vibr Control 22(7):1913–1927MathSciNetCrossRefGoogle Scholar
  13. 13.
    Courant R, Hilbert D (1953) Methods of mathematical phvsics. InterscienceGoogle Scholar
  14. 14.
    Yang X-S, Deb S (2009) Cuckoo search via Levy flights. In: Proceedings of world congress on nature and biologically inspired computing, IEEE Publications, pp 210–214.  https://doi.org/10.1109/NABIC.2009.5393690
  15. 15.
    Cawley P, Adams RD (1979) The location of defects in structures from measurements of natural frequencies. J Strain Anal 14(2):47–49CrossRefGoogle Scholar
  16. 16.
    Cho S, Yun CB, Sim SH (2015) Displacement estimation of bridge structures using data fusion of acceleration and strain measurement incorporating finite element model. Smart Struct Syst 15(3):645–663CrossRefGoogle Scholar
  17. 17.
    Gandomi AH, Yang XS, Alavi AH (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng Comput 29(1):17–35CrossRefGoogle Scholar
  18. 18.
    Yang JCS, Tsai T, Pavlin V, Chen J, Tsai WH (1985) Structural damage detection by the system identification technique. Shock Vibr Bull 55(1):57–66Google Scholar
  19. 19.
    Hansen PC (1999) The L-curve and it’s use in the numerical treatment of inverse problems. Department of Mathematical Modelling, IMM Technical University of Denmark, DenmarkGoogle Scholar
  20. 20.
    Krishnamoorthy CS (1995) Finite element analysis. Tata McGraw-Hill Education, New YorkGoogle Scholar
  21. 21.
    Shi ZY, Law SS, Zhang LM (2000) Structural damage detection form modal strain energy change. J Eng Mech ASCE 26:1216–1223CrossRefGoogle Scholar
  22. 22.
    Chen Z, Xie Z, Zhang J (2018) Measurement of Vehicle–Bridge-interaction force using dynamic tire pressure monitoring. Mech Syst Signal Process 104:370–383CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Structural Engineering Division, Department of Civil EngineeringNational Institute of TechnologyCalicutIndia

Personalised recommendations