Fatigue Life Prediction of Gear Transmission Based on ANSYS

2014 ◽  
Vol 1055 ◽  
pp. 161-164
Author(s):  
Tao Wang ◽  
Wei Zhong Zhang ◽  
Chen Xie ◽  
Deng Xia Zhang ◽  
Yan Ru

With the study subject of the gear transmission in an unmanned system, several common methods of fatigue life prediction are analyzed. According to the actual running state, S-N nominal stress method is used to predict the fatigue life of the gears. Based on the S-N data of the gear material and the linear cumulative damage theory, ANSYS is used to estimate the bending fatigue life of the gears, so as to obtain the fatigue life loss coefficient of the gears. It provides a reliable data reference of the design, use and maintenance of the gear transmission in unmanned system.

1980 ◽  
Vol 47 (2) ◽  
pp. 324-328 ◽  
Author(s):  
Z. Hashin

It is shown that the simple Palmgren-Miner linear cumulative damage rule is a special case of a general cumulative damage theory previously established. Predictions of lifetimes for families of multistage loadings according to the Palmgren-Miner rule and the general cumulative damage theory are compared with the aim of arriving at qualitative guidelines for applicability of the Palmgren-Miner rule in cyclic loading programs.


Author(s):  
Avinash Singh

Abstract The stress-life (S-N) method along with the Palmgren-Miner cumulative damage theory is the simplest and the most commonly used fatigue life prediction technique. Its main advantage is that the material properties needed are easy to collect and life calculation is simple. However under many variable amplitude loading conditions, life predictions have been found to be unreliable. Various modifications have been proposed to the Palmgren-Miner theory, but they have not lead to more reliable life predictions. In this paper, a two-stage cumulative damage model will be developed and validated. This model divides fatigue life into two phases — a crack initiation phase and a crack propagation phase. It will be shown that the proposed method results in greatly improved life prediction capabilities. Also, the proposed method retains the simplicity of the S-N based approach in that the material data is still relatively simple to generate and the calculations are straightforward.


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