Operation Optimization For Gas Fractionation Plant Based On Intelligent Approach

Establish the model and look for the solution to solve the method is key factor of chemical engineering process system optimization including of design, decision-making, assign and control. Because of the chemical system's complication and largeness, there are many influence factors of chemical engineering process. It is hardly to establish completely and strict mechanism model. An integration of neural network and genetic algorithm method is proposed for optimizing the operating conditions in order to lower energy consumption of gas fractionation plant.This paper synthesizes the current chemical engineering process optimization and characterizes chemical engineering process many layer optimizations frame to proceeds first, and treatise detailed operation optimization at the same time.The research work of this thesis consist of the following major part:1.According to target problem, the current operation status of the separation section of a plant was analysed. The major controllable independent variables, dependent variables and the object function of optimization problem was formed.2.The craft process model of the device was constructed with ASPEN PLUS system, make sure boundary operation term and proceed hand orthogonal design.3.Regarding the core work in operation optimization, the mapping of the inputs and outputs of theoretical model to a artificial neural network model with nonlinear constrain were constructed.4.The current status of rule extraction of neural network was summaried. The neural network model of device was studied in rule extraction.5. The genetic algorithm was applied to solute nonlinear constraint optimization problems. The optimum solution was explained in determine the nature from the craft's angle.