Polymer gear failure prediction: A regression-Based approach using FEA and photoelasticity technique

Abstract

The research aims to develop a model to predict the maximum contact stress depth, which will be correlated with polymer gear failures such as wear and rapid thermal deformation. A thorough 3D Finite Element Analysis (FEA) was performed for different gear parameters (varying module, number of teeth, and face width) in different combinations (Polymer – Polymer, Steel – Polymer, and Polymer – Steel). The simulation results showed that the contact stress depth increases with respect to the module and number of teeth; meanwhile, very negligible variations were found along the face width. Also, the findings indicate that the contact stress depth varied in the following descending combinations of gear pair: Polymer – Polymer, Steel – Polymer, and Polymer – Steel. The 3D FEA contact stress patterns were validated experimentally by utilizing the in-house developed photoelasticity test rig. The data obtained from the simulation results were used to develop regression models (Linear regression and Random Forest regressor) for estimating the maximum contact stress depth. A feature importance study was done using the mean reduction of the Gini index or impurities in random forest. It was found that torque applied and contact width of the gear pair were significantly influenced by the contact stress depth. Finally, an equation was developed correlating torque and contact width to predict the depth occurrence of maximum contact stress through which the failure mode of the polymer gear could be predicted.