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Online detection of the breathing crack using an adaptive tracking technique

Acta Mechanica volume 188, pages 139–154 (2007)Cite this article

Summary

Early detection of structural damage is an important goal of any structural health monitoring system. Among numerous data analysis techniques, those which are used for online damage detection have received considerable attention recently, although the problem of online detection in continuous structures, for example beams, is quite challenging. In this paper, it is shown how the type, the size and the location of breathing cracks are identified online with the use of the records which are gathered from a continuous beam. For determining the existence of a breathing crack in a beam, its vibrating behavior is simulated. The algorithm of the least square estimation with the use of adaptive tracking is employed for identification purposes. This algorithm is capable of detecting the abrupt changes in problem parameters and traces its variations. With the use of reducing domain algorithm, this identification method shows better results and can detect the breathing crack in beams more efficiently. Finally, it is shown that with the use of sufficient mode shapes the method is capable of identifying the breathing crack in beams and frames. The efficiency of the proposed algorithm is shown through some case studies.

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Authors and Affiliations

  1. Sharif University of Science and Technology, Tehran, Iran

    K. Sholeh & A. Vafai

  2. Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology, Tehran, Iran

    A. Kaveh

Authors
  1. K. Sholeh
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  2. A. Vafai
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  3. A. Kaveh
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Correspondence to A. Kaveh.

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Sholeh, K., Vafai, A. & Kaveh, A. Online detection of the breathing crack using an adaptive tracking technique. Acta Mechanica 188, 139–154 (2007). https://doi.org/10.1007/s00707-006-0383-y

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  • DOI: https://doi.org/10.1007/s00707-006-0383-y

Keywords

  • Fatigue Crack
  • Mode Shape
  • Single Crack
  • Adaptive Tracking
  • Structural Health Monitoring System