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Analysis And Design Process Control System Of360m~2Sintering Maching In Rizhaosteel Company

Posted on:2014-10-18Degree:MasterType:Thesis
Country:ChinaCandidate:L X HeFull Text:PDF
GTID:2268330422966016Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
Now, the process detection and basic control equipment are equipped in large and middlescale sintering plants in China. It is the next assignment that investigating the method of totalcontrol of sintering process and developing the sintering process control system.This paper is based on the analysis of the sintering process on the basis of sintering systemin RiZhao steel Company, look through a large number of reference,with a deeper ofunderstanding about instrument selection and PLC and PC hardware and software structure,communication network are analyzed and design. Combined with the ingredients of thetechnological requirements and control instructions, the analysis of ingredients principle. At last,the design of hardware selection debugging and software programming.In fact, sintering process for the control of BTP, due to the influence of mixed materialpermeability or equipment defects, it is difficult to get the ideal BTP location directly. So BTPloop control can not be achieved. This paper introducing fuzzy wavelet neural network, putsforward the multi scale wavelet approximation method, using a combination of feedback andfeed forward control strategies. Referring home and abroad fuzzy control models, in this paper,based on the bellows exhaust gas temperature curve, and a method based on wavelet processneural network BTP prediction of sintering machine, established a simple model, under themodel can simulate the steady state of the sintering machine operation, through the simulation ofMatlab and compared with Elman neural network prediction. The simulation results show that,theoretically proved the prediction of BTP control algorithm is better than Elman neural networkcontrol.
Keywords/Search Tags:sintering burden, burning through point, wavelet analysis, neural network, modelprediction, time series
PDF Full Text Request
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