Abstract
The error values of CMMs depends on the probing direction; hence its spatial variation is a key part of the probe inaccuracy. This paper presents genetically-generated fuzzy knowledge bases (FKBs) to model the spatial error characteristics of a CMM module-changing probe. Two automatically generated FKBs based on two optimization paradigms are used for the reconstruction of the direction- dependent probe error w. The angles beta and gamma are used as input variables of the FKBs; they describe the spatial direction of probe triggering. The learning algorithm used to generate the FKBs is a real/ binary like coded genetic algorithm developed by the authors. The influence of the optimization criteria on the precision of the genetically-generated FKBs is presented.
Original language | English |
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Title of host publication | Annual Meeting of the North American Fuzzy Information Processing Society, 2008. NAFIPS 2008. |
Publisher | IEEE |
Publication date | 2008 |
Pages | 1-4 |
ISBN (Print) | 978-1-4244-2351-4 |
DOIs | |
Publication status | Published - 2008 |
Event | Annual Meeting of the North American Fuzzy Information Processing Society, 2008. - New York City, NY Duration: 1 Jan 2008 → … |
Conference
Conference | Annual Meeting of the North American Fuzzy Information Processing Society, 2008. |
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City | New York City, NY |
Period | 01/01/2008 → … |