An Algebraic Wavenumber Identification (AWI) technique under stochastic conditions. (1st April 2023)

• Record Type: Journal Article
• Authors: Li, Xuefeng; Ichchou, Mohamed; Zine, Abdelmalek; Droz, Christophe; Bouhaddi, Noureddine
• Is Part Of: Mechanical systems and signal processing. Volume 188(2023)
• Publication Date: 2023-04-01
• Subjects: Wavenumber identification -- Periodic structures -- Inverse method -- Small perturbation -- Signal noise -- Nonuniform sampling; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.109983
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: This paper presents an inverse Algebraic Wavenumber Identification (AWI) technique for multi-modal 1D-periodic structures, which can extract complex wavenumbers from steady-state vibration measurements under stochastic conditions. These wave dispersion characteristics provide valuable vibroacoustic indicators for model updating, damage monitoring in operational conditions, or metamaterial design. Wavenumber extraction techniques are highly sensitive to noisy measurements, nonuniform sampling points, or geometrical uncertainties. The proposed formulation relies on algebraic parameters identification to enable the extraction of complex wavenumbers in four scenarios: (a) low Signal Noise Ratio; (b) small perturbation caused by uncertainties on sampling points' coordinates; (c) unknown structural periodicity; (d) nonuniform sampling. This AWI is compared with Inhomogeneous Wave Correlation (IWC) method and INverse COnvolution MEthod (INCOME) to assess the robustness and accuracy of the method. Highlights: An algebraic wavenumber identification method is proposed for 1D periodic structures. The method is robust to noise, small perturbations, nonuniform sampling and structural uncertainties. The method has a low computational cost and is exact under deterministic conditions. Comparisons are provided with Inhomogeneous Wave Correlation and Inverse Convolution Methods.