Abstract
Information fusion technique has been widely applied to a variety of subjects such as fault diagnosis and image identification. Bayes estimation is a special type of information fusion technique applied to parameter estimation for probability distribution of random variable. The present paper presents a new type of information fusion technique for material strength distribution estimation in the situation of small size sample. To precisely describe material strength, three-parameter Weibull distribution is used. To find out a reasonable location parameter in the situation that only a few experimental observations are available, the knowledge and information from different aspects are utilized. First, an empirical shape parameter is chosen with reference to the strength distribution of similar material. Then, a location parameter is assigned to make the estimated material strength variation at a realistic level, by judging the rationality of the location parameter through the strength probability distribution thus estimated. At last, big data technique is applied to further verify the rationality of the estimated material strength distribution by testing the relation between location parameter and the minimum observation in a sample of particular size for a special three-parameter Weibull distribution.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Shen, Y., Xie, M.: Nonparametric estimation of decreasing mean residual life with type II censored data. IEEE Trans. Reliab. 59(1), 111–116 (2010)
McLain, A.C., Ghosh, S.K.: Nonparametric estimation of the conditional mean residual life function with censored data. Lifetime Data Anal. 17, 514–532 (2011)
Soliman, A.A.: Estimation of the parameters of life for Gompertz distribution using progressive first-failure censored data. Comput. Stat. Data Anal. 56, 2471–2485 (2012)
Zhao, M., Jiang, H., Liu, X.: A note on estimation of the mean residual life function with left-truncated and right-censored data. Stat. Probab. Lett. 83, 2332–2336 (2013)
Elmahdy, E.E.: A new approach for Weibull modeling for reliability life data analysis. Appl. Math. Comput. 250, 708–720 (2015)
Abernethy, R.B.: The New Weibull Handbook: Reliability & Statistical Analysis for Predicting Life, Safety, Survivability, Risk, Cost, and Warranty Claims, 5th edn. Gulf Publishing Company, Florida (2010)
Jia, X., Wang, D., Jiang, P., et al.: Inference on the reliability of Weibull distribution with multiply type-I censored data. Reliab. Eng. Syst. Saf. 150, 171–181 (2016)
Mazhar, M.I.: Remaining life estimation of used components in consumer products. J. Oper. Manag. 25, 1184–1193 (2007)
Ducros, F., Pamphile, P.: Bayesian estimation of Weibull mixture in heavily censored data setting. Reliab. Eng. Syst. Saf. 180, 453–462 (2018)
Ahmed, M.: Bayesian. Estimator for Weibull distribution with censored data using extension of Jeffrey prior information. Procedia Soc. Behav. Sci. 8, 663–669 (2010)
Sobhi, A.A.: Soliman. Estimation for the exponentiated Weibull model with adaptive type-II progressive censored schemes. Appl. Math. Model. 40, 1180–1192 (2016)
Nagatsuka, H.: A study of estimation for three-parameter Weitull distribution based on doubly type-II censored data using a least square method. In: 2nd International Conference on Secure System Integration and Reliability Improvement, Yokohama, Japan, pp. 58–165. IEEE Conference Publications (2008)
Zhao, Y.X., Liu, H.B.: Weibull modeling of the probabilistic S-N curves for rolling contact, fatigue. Int. J. Fatigue 66, 47–54 (2014)
Yang, J.W., Wang, J.H., Huang, Q.: Reliability assessment for the solenoid valve of a high-speed train braking system under small sample size. Chin. J. Mech. Eng. 31, 47 (2018)
Abbasi, B.: Estimating parameters of the three-parameter Weibull distribution using a neural network. Eur. J. Ind. Eng. 2(4), 428–445 (2008)
Acknowledgement
This research is subsidized by NSFC (Grant No. U1708255).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Xie, L., Qin, B., Wu, N. (2020). A Multi-attribute Information Based Method of Material Strength Distribution Fitting. In: Gdoutos, E., Konsta-Gdoutos, M. (eds) Proceedings of the Third International Conference on Theoretical, Applied and Experimental Mechanics. ICTAEM 2020. Structural Integrity, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-030-47883-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-47883-4_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-47882-7
Online ISBN: 978-3-030-47883-4
eBook Packages: EngineeringEngineering (R0)