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Research on Controlling Cutting Quality of Abrasive Water Jet

Author: YangGuiLin
Tutor: LeiYuYong
School: West China University
Course: Mechanical Manufacturing and Automation
Keywords: Abrasive Water Jet Cutting Surface quality Artificial Neural Networks MATLAB
CLC: TG73
Type: Master's thesis
Year: 2006
Downloads: 155
Quote: 5
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Abstract


In this paper, the analysis of the water jet technology development status at home and abroad , abrasive water jet cutting section quality control issues . Papers on the principle of the abrasive water jet technology , the microscopic mechanism of abrasive water jet cutting theoretical analysis . In the study concluded abrasive water jet cutting process characteristics based on the application of artificial neural network theory to establish artificial neural network model for control abrasive water jet cutting section quality . Experimental study to obtain a large number of sample data , and training based on artificial neural network model MATALAB programming . The last artificial neural network model established in the laboratory . The purpose of this thesis is to establish the abrasive water jet cutting non-linear relationship between the various process parameters , which provide a theoretical basis for the precision machining of abrasive water jet . The major contents of study include : 1 , Summary of water jet technology development status at home and abroad . 2 , the microscopic mechanism of abrasive water jet cutting . 3 , based on artificial neural network theory , abrasive water jet cutting BP neural network model . The input and output parameters of the model as the jet pressure, abrasive flow, thickness of the material , target distance , and cutting the roughness of the surface and the nozzle traverse speed (feed rate ) . 4 , experimental study of abrasive water jet cutting . Experimental planning based on data for cutting the sample material , stainless steel , for experimental samples . 5 , abrasive water jet cutting artificial neural network model calculations . Application Levenberg-Marquard (LM) algorithm , artificial neural network based on MATLAB toolbox utility functions and test

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CLC: > Industrial Technology > Metallurgy and Metal Craft > Cutting tools, abrasives,abrasive tools,fixtures,molds and hand tools > Abrasive
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