Design-Parameters Optimization of a Deep-Groove Ball Bearing for Different Boundary Dimensions, Employing Amended Differential Evolution Algorithm - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2019

Design-Parameters Optimization of a Deep-Groove Ball Bearing for Different Boundary Dimensions, Employing Amended Differential Evolution Algorithm

Parthiv B. Rana
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Jigar L. Patel
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D. I. Lalwani
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Résumé

Rolling-element bearing that is mostly used wherever rotary motion is provided to a shaft in rotating machineries. A deep-groove ball bearing is one type of rolling-element bearing which is used to support radial load, axial load or combination of both. After proper installation and condition, ball bearings usually fail because of fatigue under normal operating conditions. Therefore, the fatigue-life optimization is a prime objective in designing a ball bearing. In the present work, eleven different problems of a deep-groove ball bearing by changing boundary dimensions are optimize to obtain maximum fatigue life. Amended Differential Evolution Algorithm (ADEA), which is modified version of Differential Evolution (DE) algorithm along with constraint handling technique, is applied to these eleven problems and optimum results in the form of optimal design-parameters and fatigue life is reported. The design parameters are bearing pitch diameter, ball diameter, number of balls and curvature coefficient of the outer and inner raceway groove are considered. Further, optimal results are compared with the other researcher’s work and standard catalogue for the same problems. Better results for fatigue life are obtained using ADEA.
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Dates et versions

hal-02331329 , version 1 (24-10-2019)

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Parthiv B. Rana, Jigar L. Patel, D. I. Lalwani. Design-Parameters Optimization of a Deep-Groove Ball Bearing for Different Boundary Dimensions, Employing Amended Differential Evolution Algorithm. 15th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2019, Hersonissos, Greece. pp.213-222, ⟨10.1007/978-3-030-19823-7_17⟩. ⟨hal-02331329⟩
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