A novel prediction approach of polymer gear contact fatigue based on a WGAN‐XGBoost model.

Polymer gears have long been used on power transmissions with the fundamental durability data, including fatigue S‐N curves, yielding important data informing reliable and compact designs. This paper proposed a prediction method for polyformaldehyde (POM) gear fatigue life based on the innovative WGAN‐XGBoost algorithm. The findings generated herein revealed that the proposed method performs well in terms of prediction accuracy. The predicted fatigue lives, analyzed under different loading conditions, were within 1.5 times dispersion band compared with experimental results. Furthermore, based upon the enhanced fatigue dataset, a thermo‐mechanical coupled prediction formula for POM gear contact fatigue life was proposed. These findings offered a new approach for high‐power density design of polymer gears. Highlights: A prediction method for POM gear fatigue life based on the WGAN‐XGBoost is proposed.A thermo‐mechanical coupled fatigue life prediction formula for POM gears is proposed.The method could shorten the sample size by 25% with the error band within 1.5. [ABSTRACT FROM AUTHOR]