导航

ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2017, Vol. 38 ›› Issue (2): 220376-220382.doi: 10.7527/S1000-6893.2016.0210

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

Fatigue life prediction method for multi-site fatigue structure with lognormal fatigue life

TAN Xiufeng1, XIE Liyang1, MA Hongyi1, ZHANG Na2, LUO Yijian2   

  1. 1. College of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China;
    2. State Key Laboratory of Vehicle NVH and Safety Technology, R & D Center, China FAW Ltd. Co., Changchun 130011, China
  • Received:2016-04-27 Revised:2016-07-11 Online:2017-02-15 Published:2016-08-15
  • Supported by:

    National Natural Science Foundation of China (51335003); Project supported by the Collaborative Innovation Center of Major Machine Manufacturing in Liaoning Province

Abstract:

To predict the fatigue life of multi-site fatigue structure, a probabilistic fatigue life prediction method based on the probabilistic accumulated damage rule is proposed, considering that fatigue life obeys lognormal distribution. According to the precondition that the damage critical value is independent of stress level, the damage critical value is transformed from the traditionally deterministic value 1 into a random variable, and the accumulated damage is calculated by the median S-N curve. An accumulated damage-probabilistic damage critical value interference model is thus built. When logarithmic fatigue life standard deviation is constant, life prediction result of the proposed interference model is compared with that of the Miner accumulated damage model based on Monte Carlo simulation. The comparison result verifies accuracy and efficiency of the proposed model. When logarithmic fatigue life standard deviation is varied, the damage critical value is decided by damage equivalent stress, and a high-precision and safer life prediction result can be gained.

Key words: multiple-site fatigue, fatigue life, reliability, median damage, critical value of probabilistic damage, Monte Carlo simulation

CLC Number: