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Machine learning based nominal root stress calculation model for gears with a progressive curved path of contact
ID Urbas, Uroš (Author), ID Zorko, Damijan (Author), ID Vukašinović, Nikola (Author)

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Abstract
The study aims to investigate the possibility of employing machine learning models in the design of non-involute gears. Such a model would be useful for design calculations of non-standard gears, where there are no available guidelines. The aim is to create a decision-support model accompanying the Finite Element Method (FEM) simulations, from which the data for training was collected. Multiple models for numerical prediction were tested, i.e. linear regression, Support Vector Machine, K-nearest neighbour, neural network, AdaBoost, and random forest. The models were firstly validated with N-fold cross-validation. Further validation was done with new FEM simulations. The results from the simulations and the models were in good agreement. The best-performing ones were random forest and AdaBoost. Based on the validation results, a machine learning constructed model for calculating nominal root stress in gears with a progressive curved path of contact is proposed. The model can be used as an alternative to FEM simulations for determining the nominal root stress in real-time, and is able to calculate the stress for gears with different number of teeth, widths, modules, paths of contact, materials, and loads. Therefore, many combinations of gear geometries can be analysed and the most suitable can be chosen.

Language:English
Keywords:machine learning, nominal root stress, gears, Finite Element Method, FEM, random forest, AdaBoost
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Publication status:Published
Publication version:Version of Record
Year:2021
Number of pages:14 str.
Numbering:Vol. 165, art. 104430
PID:20.500.12556/RUL-138691 This link opens in a new window
UDC:004.85:621.833:519.61
ISSN on article:0094-114X
DOI:10.1016/j.mechmachtheory.2021.104430 This link opens in a new window
COBISS.SI-ID:69206531 This link opens in a new window
Publication date in RUL:09.08.2022
Views:819
Downloads:133
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Record is a part of a journal

Title:Mechanism and machine theory
Shortened title:Mech. mach. theory
Publisher:Elsevier
ISSN:0094-114X
COBISS.SI-ID:5762311 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:strojno učenje, korenska napetost, zobniki, metoda končnih elementov

Projects

Funder:Other - Other funder or multiple funders
Funding programme:Republic of Slovenia
Project number:C3330–18–952014
Acronym:MAPgears

Funder:EC - European Commission
Funding programme:European Regional Development Fund
Acronym:MAPgears

Funder:ARRS - Slovenian Research Agency
Funding programme:Young researchers

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