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A New Structural Damage Detection Method for Cantilever Beam Using Generalized Flexibility Quotient Difference Method

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Abstract

Background

The natural frequencies and mode shapes are extensively utilized in the detection of damage. Natural frequencies may be measured fairly accurately and which are sensitive to local damage. However, mode shapes are difficult to acquire and are contaminated with measurement errors. The use of polluted mode shapes can show adverse effects in showing the damage position correctly.

Method

To address this problem, a newly formulated structural damage detection method for cantilever beams using the generalized flexibility quotient difference method is proposed. The proposed technique requires only two steps and can be effectively implemented for detecting the damage in single and multiple elements of a beam with two induced crack depths using the first modes of vibration. The damage index is computed utilizing stiffness matrix of the healthy element instead of the element which is damaged. To verify the robustness of the suggested damage detection approach, six damage scenarios were used.

Results

The results reveal that the proposed method efficiently detects the degree of damage on the basis of the crack depth in single and multiple locations. Experimental investigations were conducted by inducing damage in the form of milling for similar elements considered in the damage detection method. To validate the experimental results, FE simulations were also performed.

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Authors and Affiliations

  1. Department of Civil Engineering, Siddaganga Institute of Technology, B.H. Road, Tumakuru, 572 103, Karnataka, India

    Siddesha Hanumanthappa

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  1. Siddesha Hanumanthappa
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Correspondence to Siddesha Hanumanthappa.

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Hanumanthappa, S. A New Structural Damage Detection Method for Cantilever Beam Using Generalized Flexibility Quotient Difference Method. J. Vib. Eng. Technol. 11, 1525–1533 (2023). https://doi.org/10.1007/s42417-022-00655-0

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  • DOI: https://doi.org/10.1007/s42417-022-00655-0

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