FUZZY ECCENTRICITY AND GROSS ERROR IDENTIFICATION  

作　　者：YE Bing FEI Yetai LIAO Benqiang 

机构地区：[1]School of Science,Hefei University of Technology, Hefei 230009, China [2]School of Instrumentation,Hefei University of Technology, Hefei 230009, China

出　　处：《Chinese Journal of Mechanical Engineering》2006年第1期143-145,共3页中国机械工程学报（英文版）

基　　金：This project is supported by National Natural Science Foundation of China (No.59575081,No.59735120).

摘　　要：The dominant and recessive effect made by exceptional interferer is analyzed in measurement system based on responsive character, and the gross error model of fuzzy clustering based on fuzzy relation and fuzzy equipollance relation is built. The concept and calculate formula of fuzzy eccentricity are defined to deduce the evaluation rule and function ofgruss error, on the base of them, a fuzzy clustering method of separating and discriminating the gross error is found, utilized in the dynamic circular division measurement system, the method can identify and eliminate gross error in measured data, and reduce measured data dispersity. Experimental results indicate that the use of the method and model enables repetitive precision of the system to improve 80% higher than the foregoing system, to reach 3.5 s, and angle measurement error is less than 7 s.The dominant and recessive effect made by exceptional interferer is analyzed in measurement system based on responsive character, and the gross error model of fuzzy clustering based on fuzzy relation and fuzzy equipollance relation is built. The concept and calculate formula of fuzzy eccentricity are defined to deduce the evaluation rule and function ofgruss error, on the base of them, a fuzzy clustering method of separating and discriminating the gross error is found, utilized in the dynamic circular division measurement system, the method can identify and eliminate gross error in measured data, and reduce measured data dispersity. Experimental results indicate that the use of the method and model enables repetitive precision of the system to improve 80% higher than the foregoing system, to reach 3.5 s, and angle measurement error is less than 7 s.

关 键 词：Fuzzy clustering Gross error model Fuzzy eccentricity Repetitive precision improvement 

分 类 号：TB114.3[理学—概率论与数理统计] O159[理学—数学]