DocumentCode
175807
Title
P-S-N curves with parameters estimated by particle swarm optimization and reliability prediction
Author
Jinbao Zhang ; Ming Liu ; Yongqiang Zhao ; Xingguo Lu
Author_Institution
Sch. of Mechatron. Eng., Harbin Inst. of Technol., Harbin, China
fYear
2014
fDate
19-21 Aug. 2014
Firstpage
627
Lastpage
631
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
fatigue; parameter estimation; particle swarm optimisation; probability; reliability theory; P-S-N curves; PSO; fatigue damage accumulation model; fitness function; fitting errors; parameter estimation; particle swarm optimization; probabilistic characteristics; reliability prediction; test data; total minimum mean-square value; Fatigue; Fitting; Loading; Mathematical model; Particle swarm optimization; Predictive models; Reliability; P-S-N curve; Particle Swarm Optimization; fitness function; parameter estimation; reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2014 10th International Conference on
Conference_Location
Xiamen
Print_ISBN
978-1-4799-5150-5
Type
conf
DOI
10.1109/ICNC.2014.6975908
Filename
6975908
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