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Control Chart Pattern Recognition System: A Fuzzy Neural Network Approach

Author: XuWen
Tutor: LiHongGuang
School: Beijing University of Chemical Technology
Course: Control Science and Engineering
Keywords: Control Chart Pattern Recognition Fuzzy Neural Network Criterion Fuzzy rules
CLC: TP273
Type: Master's thesis
Year: 2011
Downloads: 43
Quote: 0
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Abstract


The control chart is an effective monitoring of the statistical process control analysis and troubleshooting tools are widely used in the field of industrial production . Real-time monitoring to identify the control charts can be found as soon as possible and as early as anomalies generated to eliminate the potential dangers and hazards of the process to ensure that industrial production efficiency , stability and security . In recent years, the smart technology is more and more widely in the field of industrial process control applications . Control chart pattern recognition technology based on existing research more effective smart has become an inevitable trend. In this paper, a combination of neural networks and fuzzy logic to take full advantage of a priori knowledge , the establishment of hybrid intelligent control chart pattern recognition method based on fuzzy neural network , the main research contents are as follows : 1 . Proposed a control charts criterion symbolic fuzzy rules can effectively guide the intelligent recognition network modeling and initialization process , based on a combination of neural networks and fuzzy logic , the establishment of a control chart pattern recognition method based on fuzzy neural network . Generalized process model based on second-order time lag process effectively simulate the characteristics of industrial process , produce more in line with the actual situation of the control chart data . Fully generalized process model parameters were investigated based on the control chart pattern recognition , a generalized fuzzy neural network control chart pattern recognition system , and a case study for penicillin fermentation process , to verify the technical feasibility and effectiveness . 3 application -based VC MFC programming techniques to achieve generalized fuzzy neural network pattern recognition applications . Given the overall design of the system and software design solutions , modular frame structure , including the division of the system design and functional class as well as a friendly and easy-to-use graphical interface .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Automatic control,automatic control system
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