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Experimental Study On Design Of Automatic Control Of Supplying Material System For Extrusion Device And Extrusion Pretreatment Of Maize Germ For Solvent Extraction Of Oil

Posted on:2012-06-07Degree:MasterType:Thesis
Country:ChinaCandidate:J X WangFull Text:PDF
GTID:2178330332987224Subject:Agricultural mechanization project
Abstract/Summary:PDF Full Text Request
Extrusion technology in the field of deep processing of agricultural products used widely, while starch extrusion technology in the production of raw materials has changed the superiority and advanced more and more evident. Domestic and foreign experts shows that materials temperature feed rate screw speed humidity and materials such as adding enzyme is closely related to the effect of extrusion materials Homemade YJP200 type extruder's accuracy is not high feeding material water enzyme controlled the PID control the system sometimes unstable, the state does not fully measure. This topic based on the YJP200 single screw extruder for the study, design and development of an extrusion machine to adapt to the more accurate and intelligent traffic control system. On-line real-time control was used Dynamic BP algorithm, and then automatic control system of squeeze feed, water and enzyme was simulated, using Matlab software. Simulinking results show that neural network PID controller is superior to the traditional PID controller with high precision and strong adaptability and can achieve satisfactory control effect.For a high-oil crop based on the original oil extruder design and installs a pre-screwing device by myself, is used in extrusion pretreatment of wet corn germ. Researching process parameters in order to achieve lower production costs reduce residual oil rate and increase the soaking efficiency.Paper includes the following elements:(1)Based on the adding materiel, water and enzyme process and control requirements using PID control inverter control technique design plus powder adding water adding the enzymes control system.(2)Using the BP neural network determine the optimal PID parameters using Matlab software simulation. Simulinking results shows that the BP neural network PID controller for multivariable, strong coupling, nonlinear, large delay system has good control effect and improves the automation of the extrusion machine.(3) Designing and installing of a pre-screwed device, experiment certificates to achieve the initial anticipate effect of extrusion.(4) Through the three factors and five levels orthogonal rotation design, the residual oil is obtained mainly indicators of the extrusion system measures the optimum range of parameters: screw speed is 46.94~55.22 r/min, temperature is 77.86~82.06℃and material moisture content is 6.7~7.83%.Under these conditions, residual oil rate reached< 4%.In this paper, the materiel water enzyme optimization of the control system has achieved the desired function of the basic requirements showing the robustness and stability, has good practical value and reliability can be applied to large experiment and large-scale production. Pre-screwing device works well and gets optimum experiment parameters. For the next experiment study provides a theoretical basis and establishes a beneficial basis.
Keywords/Search Tags:Extrusion, BP neural network, PID flow control, Corn germ, Residual oil rate
PDF Full Text Request
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