Optimisation estimation of uncertainty integrated with production information based on Bayesian fusion method

被引:4
作者
Cheng, Yinbao [1 ]
Fu, Huadong [2 ]
Lyu, Jing [2 ]
Wang, Zhongyu [1 ]
Li, Hongli [3 ]
Chen, Xiaohuai [3 ]
机构
[1] Beihang Univ, Sch Instrumentat Sci & Optoelect Engn, Beijing, Peoples R China
[2] China Natl Accreditat Serv Conform Assessment, Beijing, Peoples R China
[3] Hefei Univ Technol, Sch Instrument Sci & Optoelect Engn, Hefei, Peoples R China
来源
JOURNAL OF ENGINEERING-JOE | 2019年 / 2019卷 / 23期
基金
中国国家自然科学基金;
关键词
inspection; Bayes methods; statistical analysis; sensor fusion; measurement uncertainty; production engineering computing; inference mechanisms; product inspection; optimisation estimation; Bayesian fusion method; statistical production information; product detection results; statistical inference principle; uncertainty evaluation; Bayesian information fusion model; generation geometrical product specifications; posteriori distribution function;
D O I
10.1049/joe.2018.9213
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The new generation Geometrical Product Specifications require consideration of the effects of measurement uncertainty in the product inspection. This study estimated the measurement results and the uncertainty by integrating the statistical production information into the product detection results to rationally and fairly narrow the uncertainty area of qualification determination. Based on the Bayesian information fusion and statistical inference principle, the model of uncertainty evaluation is established. The Bayesian information fusion model integrated measuring information with manufacturing information was built, with which the uncertainty of product inspection was reappraised based on posteriori distribution function. The validity of the proposed method and theory was demonstrated by the example analysis.
引用
收藏
页码:9178 / 9182
页数:5
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