Open AccessOptimisation estimation of uncertainty integrated with production information based on Bayesian fusion method
Author(s) -
Cheng Yinbao,
Fu Huadong,
Lyu Jing,
Wang Zhongyu,
Li Hongli,
Chen Xiaohuai
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9213
Subject(s) - information fusion , bayesian probability , computer science , uncertainty analysis , production (economics) , product (mathematics) , statistical inference , bayesian inference , data mining , sensitivity analysis , sensor fusion , prior information , measurement uncertainty , function (biology) , reliability engineering , artificial intelligence , statistics , mathematics , engineering , simulation , geometry , evolutionary biology , biology , economics , macroeconomics
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.