Skip to main content
SpringerLink
Log in

Fast orthogonal search (FOS) versus fast Fourier transform (FFT) as spectral model estimations techniques applied for structural health monitoring (SHM)

  • Research Paper
  • Published:
Structural and Multidisciplinary Optimization Aims and scope Submit manuscript

Abstract

In the last decade, structural health monitoring (SHM) systems became essential to accurately monitor structural response due to real-time loading conditions, detect damage in the structure, and report the location and nature of this damage. Spectral analysis using Fourier transform has been widely used in SHM. In this research, a novel approach for the characterization of in structure damage in civil structure is introduced. The target is to develop vibration-based damage detection algorithms that can relate structural dynamics changes to damage occurrence in a structure. This article presents a new method utilizing high resolution spectral analysis based on Fast Orthogonal Search (FOS) techniques. FOS is a signal processing tool developed to provide high-resolution spectral estimation. In addition, it is a general-purpose non-linear modeling technique that finds functional expansions using an arbitrary set of non-orthogonal candidate functions. In order to examine the proposed method, the IASC-ASCE structural health monitoring benchmark structure is used in this study to illustrate the merits and limitation of the proposed approach. We also discuss the merits and the limitations of FOS as applied to SHM.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Ali EFA (2003) Application of the fast orthogonal search in automatic target detection. Ph.D. Thesis, Department of Electrical and Computer Engineering, Royal Military College of Canada, Kingston, Ontario

  • Chon KH (2001) Accurate identification of periodic oscillations buried in white or colored noise using fast orthogonal search. IEEE Trans Biomed Eng 48(6):622–629

    Article  Google Scholar 

  • Del Grosso A, Torre A, Rosa M, Lattuada BG (2004) Application of SHM techniques in the restoration of historical buildings: the Royal Villa of Monza. In: Boller C, Staszewski WJ (eds) Proceedings of the 2nd European workshop on structural health monitoring, Munich, Germany, pp 205–212

  • Doebling SW, Farrar CR, Prime MB (1998) A summary review of vibration-based damage identification methods. Shock Vib Digest 30(2):91–105

    Article  Google Scholar 

  • Frangopol DM, Neves LC, Petcherdchoo A (2004) Health and safety of civil infrastructures: a unified approach. In: Mufti A, Ansari F (eds) Proceedings of the 2nd international workshop on structural health monitoring of innovative civil structures, Winnipeg, Canada, pp 253–264

  • Friswell MI, Penny JET (1997) Is damage location using vibration measurements practical? In: Proceedings of the international workshop: DAMAS 97, structural damage assessment using advanced signal processing procedures, Sheffield, UK

  • Gentile C (2003) Dynamic performance of A P.C. Bridge: computation and tests. In: El-Dieb et al (eds) Proceedings of the international conference on performance of construction materials, ICPCM, Cairo, Egypt, vol 1, pp 449–458

  • Johnson EA, Lam HF, Katafygiotis LS, Beck JL (2004) The phase I IASC-ASCE structural health monitoring benchmark problem using simulated data. J Eng Mech ASCE 130(1):3–15

    Article  Google Scholar 

  • Kim J-T, Ryu Y-S, Choi H-M, Stubbs N (2003) Damage identification in beam-type structures: frequency-based method vs. mode-shape-based method. Eng Struct 25:57–67

    Article  Google Scholar 

  • Kinawi H, Reda Taha MM, El-Sheimy N (2002) Structural health monitoring using the semantic wireless web: a novel application for wireless networking. In: Proceedings of the 27th IEEE conference on local computer networks (LCN), FL, USA, Ed. pp 770–780

  • Korenberg MJ (1989) A robust orthogonal algorithm for system identification and time-series analysis. Biol Cybern 60:267–276

    Article  MathSciNet  MATH  Google Scholar 

  • Korenberg MJ, Paarmann LD (1989) Applications of fast orthogonal search: time-series analysis and resolution of signals in noise. Ann Biomed Eng 17:219–231

    Article  Google Scholar 

  • Manson G, Worden K, Allman D (2003) Experimental validation of a structural health monitoring technology: part II. Novelty detection on a gnat aircraft. J Sound Vib 259(2):345–363

    Article  Google Scholar 

  • McGaughey DR, Korenberg MJ, Adeney KM, Collins SD, Aitken GJ (2003) Using the fast orthogonal search with first term reselection to find subharmonic terms in spectral analysis. Ann Biomed Eng 31:741–751

    Article  Google Scholar 

  • Mitra SK (2001) Digital signal processing: a computer-based approach, 2nd edn. McGraw Hill, NY

    Google Scholar 

  • Park S, Stubbs N, Bolton RW (1998) Damage detection on a steel frame using simulated modal data. In: Proceedings of the 16th international modal analysis conference, Santa Barbara, CA, USA, SPIE-International Society for Optical Engineering, pp 612–622

  • Pothisiri T, Hjelmstad KD (2003) Structural damage detection and assessment from modal response. ASCE J Eng Mech 129(2):135–145

    Article  Google Scholar 

  • Ren W-X, De Roeck G (2002) Structural damage identification using modal data. I: simulation verification. ASCE J Struct Eng 128(1):87–95

    Article  Google Scholar 

  • Rytter A (1993) Vibration based inspection of civil engineering structures. PhD. Dissertation, Aalborg University, Aalborg, Denmark

  • Schmidt H, Telgkamp J, Schmidt-Bramdecker B (2004) Application of structural health monitoring to improve efficiency of aircraft structure. In: Boller C, Staszewski WJ (eds) Proceedings of the 2nd European workshop on structural health monitoring, Munich, Germany, pp 11–18

  • Sohn H, Farrar C (2001) Damage diagnosis using time-series analysis of vibrating signals. Journal of Smart Materials and Structures, IOP 10(3):446–451

    Article  Google Scholar 

  • Staszewski WJ (1998) Structural and mechanical damage detection using wavelets. Shock Vib Digest 30(6):557–472

    Article  Google Scholar 

  • Yang D-M, Stronach AF, MacConnell P (2003) The application of advanced signal processing techniques to induction motor bearing condition diagnosis. Meccanica 38(2):297–308

    Article  MATH  Google Scholar 

  • Yong X (2002) Condition assessment of structures using dynamic data. Ph.D. Dissertation, School of Civil and Environmental Engineering, Nanyang Technological University, Singapore

  • Yuen K-V, Au SK, Beck JL (2004) Two-stage structural health monitoring approach for phase 1 benchmark studies. J Eng Mech ASCE 130(1):16–33

    Article  Google Scholar 

Download references

Acknowledgments

This research is supported by the first author research grant from Smart Engineering Group, University Kebangsaan Malaysia the research grant UKM-DLP-2011-002 and UKM-KK-02-FRGS0125-2009 and eScienceFund 01-01-02-SF0581, ministry of Technology, Science and Innovation (MOSTI). The authors acknowledge the financial support of NSERC and the experimental data provided by Dr. Mahmoud Reda-Taha, Department of Civil Engineering, University of New Mexico. We also wish to thank Molly McCuskey (Department of Civil Engineering, University of New Mexico) for providing the experimental data used in this study.

Author information

Authors and Affiliations

  1. Civil & Structural Engineering Department, University Kebangsaan Malaysia, Bangi, Malaysia

    Ahmed El-Shafie

  2. Department of Electrical and Computer Engineering, Royal Military College of Canada, Kingston, Canada

    Aboelmagd Noureldin & Don McGaughey

  3. Electric, Electronics Systems Engineering Department, University Kebangsaan Malaysia, Bangi, Malaysia

    Aini Hussain

Authors
  1. Ahmed El-Shafie
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aboelmagd Noureldin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Don McGaughey
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aini Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ahmed El-Shafie.

Rights and permissions

Reprints and permissions

About this article

Cite this article

El-Shafie, A., Noureldin, A., McGaughey, D. et al. Fast orthogonal search (FOS) versus fast Fourier transform (FFT) as spectral model estimations techniques applied for structural health monitoring (SHM). Struct Multidisc Optim 45, 503–513 (2012). https://doi.org/10.1007/s00158-011-0695-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00158-011-0695-y

Keywords

Search

Navigation