Research On Quality Characteristics Of Fiber Laser Cutting Of Stainless Steel Sheet And Multi-objective Optimization

The increasingly serious energy and environmental crisis in the international community promotes the continuous upgrading of the automobile industry,and the automobile manufacturing tends to be intelligent and precise,which poses a severe challenge to the automobile manufacturing process.As a new precision machining technology,fiber laser cutting technology can effectively solve the difficulties of traditional cutting methods in precision parts machining.Based on the research of domestic and international,this paper takes the quality characteristics of laser cutting stainless steel sheet as the main research object,studies the influence of laser drilling parameters on the cutting width and surface roughness,and establishes the quality prediction and process optimization model of laser cutting.Firstly,according to the energy balance equation and thermal stress theory of laser cutting,the sequential thermal mechanical coupling simulation finite element model of laser cutting stainless steel sheet is established by ABAQUS finite element software,and the temperature field of laser cutting is obtained.And then the stress field caused by temperature is obtained by combining ABAQUS element deletion subroutine,so that the material can be blown out to form kerf under the action of auxiliary gas and complete laser cutting process.The influence of cutting parameters on temperature field and stress field is also analyzed.Secondly,through the orthogonal experiment of laser cutting stainless steel sheet,the cutting quality under different laser power,cutting speed,gas pressure and defocusing amount was studied.The kerf width and the surface roughness of the cutting material were measured by laser confocal microscope.Based on the experimental data under different laser cutting parameters,the interaction relationship between laser cutting parameters and cutting quality is obtained.Finally,the preliminary analysis of the obtained experimental data was carried out.According to the results of analysis of variance,the significant factors affecting the kerf width and surface roughness were obtained.The order of the significant impact of the control parameters on the kerf width is: laser power(43.23%)> Defocus(33.08%)> Cutting speed(17.21%).The order of significant influence of control parameters on surface roughness is: cutting speed(40.22%)> laser power(34.82%).In order to further clarify the specific influence of laser parameters on cutting quality and supplement the previous laws,based on the above experimental data,this paper established a cutting quality prediction model through the generalized regression neural network(GRNN).Through GRNN prediction model,the accurate prediction of kerf width and surface roughness under given machining parameters is realized.Finally,this paper optimizes the quality characteristics based on the laser cutting parameters.Through the combination of GRNN-NSGAII,the multi-objective optimization of the slit width and surface roughness under different cutting parameters is performed,and the Pareto under the optimized conditions is determined.The optimal solution set provides reasonable parameter selection.According to the optimal solution set,different processing parameters can be selected.