@inproceedings{db2d476bf3de472eb07b0aca3d14d44d,
title = "P-S-N curves with parameters estimated by particle swarm optimization and reliability prediction",
abstract = "The probabilistic characteristics of components can't be completely expressed by the S-N curve with parameters estimated by small number of specimens. Particle Swarm Optimization (PSO) is introduced to fit parameters with the incomplete test data, which can take advantage of the entire information of the specimens to obtain the globally optimal solution. With the fitness function offered based on the principle of the total minimum mean-square value of fitting errors, the parameters of the three-parameter P-S-N curve are estimated with PSO. In sequence, the obtained P-S-N curve is applied in the fatigue damage accumulation model for reliability prediction. The above models are verified with test data with relation to two different 45 steels. The simulation results match well with experiment data.",
keywords = "Fitness function, P-S-N curve, Parameter estimation, Particle swarm optimization, Reliability",
author = "Jinbao Zhang and Ming Liu and Yongqiang Zhao and Xingguo Lu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 10th International Conference on Natural Computation, ICNC 2014 ; Conference date: 19-08-2014 Through 21-08-2014",
year = "2014",
doi = "10.1109/ICNC.2014.6975908",
language = "英语",
series = "2014 10th International Conference on Natural Computation, ICNC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "627--631",
booktitle = "2014 10th International Conference on Natural Computation, ICNC 2014",
address = "美国",
}