Abstract
To analyse the influence of material parameters and the working condition on the friction and wear performance of brakes with less test data, the Sobol method is employed to obtain factor sensitivity, which could reflect the importance of different factors to brake performance, and a surrogate prediction model, which is necessary in the Sobol method, is established by support vector machine (SVM). The predicted values for training and investigation are accurate in comparison with the measured test data, which could prove the acceptability of the SVM model in the Sobol method. The result shows that the working condition might be the primary cause of brake friction and differences in wear, and the fibre matrix of carbon has a different influence on the linear wear and mass wear according to the sensitivity of density before or after pitch or resin impregnation. This paper describes an application in the field of reduced test data methodologies for prediction and factor analysis of the friction and wear performance of brakes using the Sobol method with the SVM modelling strategy, which could be convenient for designing and testing carbon brakes in engineering practice.
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This work is supported by the National Natural Science Foundation of China (51606219).
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Technical Editor: André Cavalieri.
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Zhou, B., Wang, L., Liu, Y. et al. Analysis of factor sensitivity in brake friction and wear performance based on the Sobol method. J Braz. Soc. Mech. Sci. Eng. 40, 345 (2018). https://doi.org/10.1007/s40430-018-1269-3
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DOI: https://doi.org/10.1007/s40430-018-1269-3