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Fuzzy Modeling On Heavy Plate High Denseness Pipe Flow For The Water Supply System And Controlled Cooling Mechanics Performance Prediction

Posted on:2007-04-13Degree:MasterType:Thesis
Country:ChinaCandidate:X H ChenFull Text:PDF
GTID:2121360212973966Subject:Mechanical design and theory
Abstract/Summary:PDF Full Text Request
The modeling and optimizing control for the water supply system, a key sub system of high denseness pipe flow controlled cooling system in Steel Plate Plant, are investigated in this thesis. The water supply system is a nonlinear, tight coupled multivariable system which is difficult to accurately describe with traditional mathematical model. Due to the fact that fuzzy control, compared to conventional controls, is more suitable for those controlled plants that are difficult to model analytically and exhibit coupling features as well as nonlinear characteristics, the fuzzy logic methodology is employed to solve the modeling and optimizing control problems of water supply system. To this end, the author took part in the on-site test of the high denseness pipe flow controlled cooling and obtained the measured input-output data for the water supply system.Based on the collected mass measured data in situation for medium and heavy plate cooling in Anshan Iron and Steel Company board, the regression analysis to the effect of process parameters-initial cooling temperature, end cooling temperature, speed of roll way, number of gather the piping roll on the tensile properties of steel 16 MnR medium and heavy plate was carried out, and the relative mathematical model has been established.Based on measured value of main parameters of cooling and mechanical property of 16MnR medium and heavy plate such as initial cooling temperature in Anshan Iron and Steel Company board, end cooling temperature, speed of roll way, number of gather the piping, the mathematical model for predication of yield and tensile strength of medium and heavy plate has been established by relative mathematical model obtained by statistic regression analysis combined with fuzzy clustering and fuzzy identification mathematical model.The results show that the relative error between predicting value and measured value of yield strength of 16 MnR medium and heavy plate is 1.87%~3.58%, and the relative error of tensile strength is 1.38%~7.47%. The actual value and the forecast value basic tally, proved uses the method is correct, may apply after the further massive confirmations in the actual production.
Keywords/Search Tags:Controlled Cooling, Fuzzy Modeling, Tensile Property, Regression Analysis, Predication of Mechanical Property, Fuzzy Analysis
PDF Full Text Request
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