中南大学学报(英文版)
中南大學學報(英文版)
중남대학학보(영문판)
JOURNAL OF CENTRAL SOUTH UNIVERSITY OF TECHNOLOGY(ENGLISH EDITION)
2015年
2期
560-566
,共7页
张秀玲%赵亮%臧佳音%樊红敏
張秀玲%趙亮%臧佳音%樊紅敏
장수령%조량%장가음%번홍민
pattern recognition%T-S cloud inference network%cloud model%mixed programming%virtual reality%visual recognition
Flatness pattern recognition is the key of the flatness control. The accuracy of the present flatness pattern recognition is limited and the shape defects cannot be reflected intuitively. In order to improve it, a novel method via T-S cloud inference network optimized by genetic algorithm (GA) is proposed. T-S cloud inference network is constructed with T-S fuzzy neural network and the cloud model. So, the rapid of fuzzy logic and the uncertainty of cloud model for processing data are both taken into account. What’s more, GA possesses good parallel design structure and global optimization characteristics. Compared with the simulation recognition results of traditional BP Algorithm, GA is more accurate and effective. Moreover, virtual reality technology is introduced into the field of shape control by LabVIEW, MATLAB mixed programming. And virtual flatness pattern recognition interface is designed. Therefore, the data of engineering analysis and the actual model are combined with each other, and the shape defects could be seen more lively and intuitively.