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Based on Artificial Neural Networks oil-water separation hydrocyclone mathematical model

Author: YiJingWei
Tutor: ShuChaoZuo
School: Huazhong University of Science and Technology
Course: Chemical Process Equipment
Keywords: Oil and water separator Hydrocyclone Mathematical model BP neural network GA PRP conjugate gradient method
CLC: TE977
Type: Master's thesis
Year: 2005
Downloads: 202
Quote: 1
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Abstract


Oil-water separation hydrocyclone oil industry in an important new centrifugal separation equipment. Hydrocyclone separation process is very complex , factors and indicators for the relationship between the parameters is a typical multi-dimensional nonlinear system , it is difficult to use simple linear mathematical tools to describe . Artificial neural network is a nonlinear dynamic system , in dealing with multivariable nonlinear systems and unknown model system has great advantages . In this paper, artificial neural network to establish oil-water separation hydrocyclone mathematical model, based on the physical parameters of the cyclone , structural and operating parameters to predict cyclone separation performance . According to the actual operation of the cyclone conditions, in considering the speed of network training , the training error and the prediction error to given based on optimized 18-30-2 three-layer BP neural network model . BP neural network for defects , the use of PRP conjugate gradient method and genetic algorithm to optimize BP neural network algorithm, the neural network training speed and the prediction accuracy was significantly improved. Using artificial neural network model hydrocyclone separation performance was predicted, the results show that the improved BP neural network model to simulate the hydrocyclone separation process is feasible. According to oil-water separation hydrocyclone neural network model to study the various factors on the cyclone separation efficiency and classification efficiency curve effect , and the actual test results agree well , indicating that the network model is very practical. Results of this study , both theory and practice are all oil-water separation hydrocyclone to promote the application of positive significance. The text of the software design using Visual Basic 6.0 programming language and Microsoft Access database design software.

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CLC: > Industrial Technology > Oil and gas industry > Oil machinery and equipment and automation > Oil and gas storage and transportation machinery and equipment > Oil and gas gathering and transportation machinery and equipment
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