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Optimization Of Rotating Arc Sensor Welding Parameters For Corner Joint And Numerical Simulation Of Thermal Stress

Posted on:2018-07-23Degree:MasterType:Thesis
Country:ChinaCandidate:W XuFull Text:PDF
GTID:2321330518466139Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
The rotating arc sensor welding is an important process in the field of welding.Different welding parameters corresponding to the welding temperature field and stress strain field are different,which is a great obstacle to research of subsequent deformation control.It is necessary to use welding intelligent optimization algorithm optimize the welding process parameters combined with numerical simulation method to obtain high quality weld joint,and the superior process parameters can be used for welding thermodynamics research,which will save test cost and shorten the cycle of research and development.In order to optimize the welding parameters,to reduce the number of tests and improve the welding efficiency,it can use the orthogonal test method based on minitab firstly,and consider the interaction and influence of the welding parameters,and the orthogonal test model is established and the corresponding welding test is used to measure the size of weld joint after welding.In addition,the subjective analysis and residual analysis method are used to analyze the matching relationship between each welding process parameter and goodness of fit.A prediction model of weld joint size of rotating arc sensor welding is established for rapid access to better welding process parameters based on BP(Back Propagation,BP)neural network.Moreover,the mapping relationship between the welding parameters and the weld size is obtained through the training of the predicted sample data,and the predicted samples can verify the genetic neural network after debugging.In addition,the optimization model of rotary arc welding parameter of genetic neural network is established,and the welding parameters are optimized based on the nonlinear mapping prediction ability of BP neural network and global optimization ability of genetic algorithm.In order to simulate the external load of the workpiece during the welding process accurately,the method of numerical simulation and experiment based on ANSYS is used to simulate the external restraint of the welding fixture by the application of the displacement constraint and the concentrated force constraint,and obtain the support and clamping force of workpiece through the contact analysis.Finally,three kinds of multi-body coupling models are used to simulate the clamping effect of the fixture and the workpiece respectively,and analyzes the von Mises stress and the X or Y stress and deformation forming mechanism distributions of the upper and lower sides of the workpiece.As the results of the simulation analysis of the external binding model to be verified,it is necessary to build a test platform of rotary arc fillet workpiece deformation measurement.The corresponding measuring point of the lower side plate of the workpiece is accurately measured by the special angle gauge of the fillet weld to obtain the workpiece angle deformation and bending deformation,so as to complete and improve thermal stress numerical simulation platform of the rotating arc sensor welding.
Keywords/Search Tags:rotating arc, welding parameters, back propagation neural network, genetic algorithm, numerical simulation
PDF Full Text Request
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