Novel TQWT Algorithm for Structural Damage Identification
Arun Kumar K1, Mallikarjuna Reddy D2
1Arun Kumar K *, Research Scholar, Design and Automation, VIT University, Vellore.
2Mallika Arjuna Reddy D, Associate Professor, Design and Automation, VIT University, Vellore India.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5136-5146 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8332118419/2019©BEIESP | DOI: 10.35940/ijrte.D8332.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper tunable Q-factor wavelet transform is implemented into damage identification. Fixed – Fixed beam damage identification problem is demonstrated. Translation and Rotational mode shapes are used as an input signal, the TQWT algorithm depends Q-factor and asymptotic redundancy, when it matches with the oscillatory behavior of the input signal it is tuned. This method decomposes a signal into a high-Q-factor and low-Q-factor component, and it can be used to differentiate the damaged and undamaged mode shapes of the beam structure. TQWT coefficient is used as damage index to locate and quantify the damage. Proposed method evaluated experimentally and results shows TQWT algorithm has a potential to detect even a small damage (10% stiffness loss) present in the structure.
Keywords: Tunable Q-Factor Wavelet Transform (TQWT), Translational Mode Shapes, Rotational Mode Shapes, And Damage Detection.
Scope of the Article: Structural Engineering.