Finite Element Analysis and Support Vector Regression-Based Optimal Design to Minimize Deformation of Indoor Bicycle Handle Frame Equipped with Monitor

Abstract

Exercise has been gaining importance, as well as people’s interest. Nowadays, exercise bikes and similar home training devices usually feature a monitor to provide visual information and increase people’s convenience. With the increasing size of the mounted monitor frame, it is imperative to consider the monitor weight while designing the handle for an indoor exercise bike equipped with a monitor. In this study, optimal design based on finite element (FE) analysis was applied to increase the safety and robustness of the handle of an indoor bicycle equipped with a monitor. Considering the load that may be imposed on the handle, and its location, four FE analysis cases were performed. Loading conditions that contributed the largest von Mises stress (out of the four cases) were applied. Five design variables were chosen to minimize the effective stress. Moreover, the factor arrangement method using five factors and two levels required the run of 25 = 32 design cases. The resulting Pareto chart and sensitivity analysis confirmed the relationship between the effective stress and the chosen design variables. To obtain a predictive model using support vector regression (SVR), we subsequently increased the data range to five factors and three levels. The SVR prediction model was trained using a polynomial kernel to find the kernel parameters that provided the highest accuracy. Based on the coefficient of determination, the accuracy of the SVR prediction model was found to be superior to the conventional regression-based optimal design method. Additionally, the value of the design variable with the minimum effective stress was obtained using the SVR prediction model. Furthermore, upon redesigning the handle of the bicycle with the optimized design variable values, we found that the maximum effective stress was reduced by 80% compared with the initial model. Finally, the effective stress predicted by the SVR model was similar to that from the FE analysis, which confirmed the reliability of the predictive model.