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Intelligent algorithms based carbon fiber spinning process monitoring and optimization

Author: ZhouQiang
Tutor: DingYongSheng
School: Donghua University
Course: Control Theory and Control Engineering
Keywords: Gray correlation Online Monitoring Genetic Optimization Support vector regression Expert System
CLC: TQ342.742
Type: Master's thesis
Year: 2012
Downloads: 34
Quote: 0
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Abstract


Carbon fiber spinning is a complex with multiple production processes and production conditions of the large-scale production systems , its production process monitoring and control, and the need to combine the production equipment and production technology understanding and modeling, as well as on the production line control system design and optimization to proceed. This paper is carbon fiber spinning process monitoring , optimization and control integration projects sub-topics , the main research carbon fiber spinning process on-line monitoring and optimization problems. The main research work is as follows : First, the study of carbon fiber precursor spinning process , determine the impact of each channel technology carbon fiber performance parameters and to determine the performance of the original wire structure and quality indicators . Then through the gray correlation analysis method affect the quality of the carbon fiber precursor spinning process parameters. Secondly, the establishment of network monitoring equipment based NetCon carbon fiber spinning process online monitoring system, first determine the parameters to be monitored , then the system hardware and software platform to build and design and build the database system stores monitoring data. In this platform , based on the proposed genetic algorithm -based support vector regression machine carbon fiber performance prediction model , which can be real-time parameters of carbon fiber precursor online predict the performance of carbon fiber precursor , as an early warning role. Then, create a carbon fiber spinning process optimization expert system . Expert system uses collaborative framework divided into the main system and a number of subsystems , including the realization of expert system knowledge representation and inference engine design, knowledge of the global knowledge base and sub- domain knowledge , reasoning machine using radial basis function neural network (RBF) reverse inference , find the optimized performance parameters to achieve online optimization purposes. Finally based on C / S structure of the carbon fiber precursor spinning process monitoring and optimization system software software solution , and gives the overall system design framework diagram, function of each module and system database forms design, carbon fiber spun silk monitoring and intelligent optimization software provides a good platform .

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CLC: > Industrial Technology > Chemical Industry > The chemical fiber industry > Synthetic fiber > Special fiber > Carbon fiber to maintain the fiber > Carbon fiber
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