Prediction of the Friction Coefficient Based on the Hysteresis Value of Rubber

XVII International Conference on Systems, Automatic Control and Measurements, SAUM 2024 (pp. 142-144)

АУТОР(И) / AUTHOR(S): Milan Nikolić, Milan Banić , Milan Pavlović , Vukašin Pavlović , Aleksandar Miltenović 

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DOI:  10.46793/SAUM24.142N

САЖЕТАК / ABSTRACT:

This paper describes the prediction of the friction coefficient based on the measured hysteresis value of rubber used for shoe soles, including other parameters that affect the friction coefficient, such as hardness, tile roughness, sliding speed, and surface condition. Data collection necessary for the design and development of the neural network was conducted by testing the friction coefficient on a test device specially designed for that purpose. Data on rubber hysteresis was also collected through measurements using a tensile testing machine. Since the hysteresis of rubber is crucial for its characteristics, it is introduced in this paper as an important parameter that influences the friction coefficient and for friction prediction using ANN.

КЉУЧНЕ РЕЧИ / KEYWORDS:

friction coefficient prediction, hysteresis, neural network

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