Fatigue of short-natural-fiber-reinforced high-density polyethylene: Stochastic modeling of single-gear-tooth bending

摘要

A Markov chain model was compared to experimental data in the testing of a natural-fiber-reinforced composite material proposed for low-torque gearing applications. The material is tested on a single gear tooth bench to assess multiple damage measurement methods. The model was coupled to three indices of single gear tooth damage: cracking monitored with a high resolution camera, residual load measured with the fatigue machine load cell, and acoustic emission detected by piezoelectric sensors. The model has predictive skill and contributed to better understanding of how damage to the material evolved during the fatigue tests.