Quantification of cracks in beams on the Pasternak foundation using Haar wavelets and machine learning

DOI10.3176/PROC.2022.1.02zbMath1492.74078OpenAlexW4210715578MaRDI QIDQ5070912

Ljubov Jaanuska, Helle Hein

Publication date: 14 April 2022

Published in: Proceedings of the Estonian Academy of Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3176/proc.2022.1.02

zbMATH Keywords

inverse problemneural networkEuler-Bernoulli beamPasternak foundationHaar wavelet methodopen crackrandom forest approach

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Rods (beams, columns, shafts, arches, rings, etc.) (74K10) Brittle fracture (74R10) Numerical and other methods in solid mechanics (74S99) Inverse problems in dynamical solid mechanics (74H75)

Uses Software

• Wavelet Toolbox

Cites Work

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• Wavelets collocation methods for the numerical solution of elliptic BV problems
• Analytical methods in rotor dynamics
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• Sensitivity analysis of crack detection in beams by wavelet technique
• Some unexpected results in vibration of non-homogeneous beams on elastic foundation
• Numerical solution of differential equations using Haar wavelets
• Numerical solution of a class of delay differential and delay partial differential equations via Haar wavelet
• Haar wavelets. With applications
• Advanced Methods of Structural Analysis
• Comparison of machine learning methods for crack localization

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