Comparison of machine learning methods for crack localization

DOI10.12697/ACUTM.2019.23.13zbMath1431.74065OpenAlexW2969113534MaRDI QIDQ5205437

Helle Hein, Ljubov Jaanuska

Publication date: 11 December 2019

Published in: Acta et Commentationes Universitatis Tartuensis de Mathematica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.12697/acutm.2019.23.13

zbMATH Keywords

cracksEuler-Bernoulli beamHaar waveletrandom forestfree vibrationbackpropagation network

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Rods (beams, columns, shafts, arches, rings, etc.) (74K10) Vibrations in dynamical problems in solid mechanics (74H45) Numerical methods for wavelets (65T60)

Related Items (1)

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

Cites Work

• Analytical methods in rotor dynamics
• Exact solution of the multi-cracked Euler-Bernoulli column
• Vibration of cracked beams
• Using genetic algorithms and finite element methods to detect shaft crack for rotor-bearing system.
• Random forests

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