An improved estimation method of gear fatigue strength based on sample expansion and standard deviation correction. (August 2022) - Mao, Tianyu; Liu, Huaiju; Wei, Peitang; Chen, Difa; Zhang, Peng; Liu, Guoqiang
Highlights: A fatigue strength estimation method under small samples is developed. The standard deviation correction considering the sample size is constructed. The improved fatigue strength estimation method has high accuracy in small samples. Abstract: The conventional data processing of gear fatigue staircase test is based on the Dixon-Mood method. Extreme estimates might appear under small-sample condition. To solve the aforementioned limitation, this paper proposes an improved estimated method based on standard deviation correction and sample expansion. Meanwhile, the bending fatigue test is carried out for validation. Results show that the relative error of fatigue strength between the Dixon-Mood method and the proposed method is only 0.51% with 22 samples. As the sample number reduces to 12, the maximum errors of the fatigue strength of the Dixon-Mood method and the proposed method are 12.70% and 5.32%, respectively. To control the maximum error within 10%, the sample number required by the Dixon-Mood method is 14, while the proposed method is 8. The proposed method provides a more effective gear fatigue estimation.