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
Link To Document :
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