Process Monitoring And Intelligent Adjustment Based On Arc-Direct Rapid Prototyping Manufacturing

Arc-Direct Rapid Prototyping Manufacturing (ADRPM) is a new technique for direct manufacture of metal components. It stands out for its high efficiency of utilizing the materials and shaping the components, as well as its low cost of energy usage and equipment expense. Besides, due to simple material preparation and quick response to the market demands, ADRPM shows its value of various applications in the future. Since the component made by ADRPM is complete welding microstructure, the core technique of ADRPM is to choose proper technological parameters to ensure the shape, size and the formability of the components.The process of ADRPM is very complex, since there are a number of factors which influence the forming quality. To improve the technology level of ADRPM, the process monitoring of ADRPM, the analysis of technology characteristics, the prediction of forming quality and the intelligent adjustment of the main processing parameters have great significance.Based on the technology experiments of ADRPM and combined with pattern recognition, this paper made scientific research on the technology characteristics of existing parameters samples, and proposed the principles and algorithms of the quality predication and intelligent optimization of the technology parameters. The author chose Genetic Algorithms to design new technology parameters so as to guide the technology experiment, which expanded the amount of technology parameters.Then the author analyzed the expanded parameters samples based on Principal Component Analysis, extracted the technology characteristics, and then built a quality prediction model.In addition, the author analyzed each parameter's impact on the forming quality on account of feature extraction, and proposed the criterion of linear programming combined with pattern recognition evolutionary method to determine the direction of the parameters optimization and the range of parameters. This research analyzed the samples of parameters, and the results indicated: the samples analyzed by Principal Component Analysis have been decreased from 5 dimensions to 3 dimensions, and the mapping obtained from Principal Component Analysis could obviously distinguish the samples in high forming quality from the ones with relatively low quality , which fully reflected the technology characteristics; According to the Organizing Map's features of different desired value,the record of degrees' funtion can be established .The record of degree weighing width's stability is defined as the ratio of the radius of good area and the distance from the point in the Organizing Map to the centre of good area.Setting 0.714 as the standard value,if the forecasting point's record of degree is greaterthan 0.714 ,then we can judge the point as good point ,or no-good point.The record of degree weighing height's stability is defined as the ratio of the radius of sphere and the distance from the point in the Organizing Map to the centre of sphere.Setting 0.653 as the standard value,if the forecasting point's record of degree is greater than 0.653,then we can judge the point as good point ,or no-good point.the research used the quality prediction model to predict the forming quality of three groups of unknown technology parameters, and the experiment verified that the predictive values were consistent with the result of experiment, which further explained the rationality of the quality prediction model; The influence degree from various parametars to forming quality has been analysised .Weighing the width's standard deviation,parametars can be ranged for the forming quality's degree from much to little:wire feed speed,frequency,robot's speed of travel,Gun-board distance,pulse width ratio;Weighing the height's standard deviation,parametars can be ranged for the forming quality's degree from much to little:frequency,robot's speed of travel,wire feed speed,Gun-board distance,pulse width ratio; the research conducted the optimization control of the technology parameters, according to the direction of optimization which was determined by the criterion of linear programming and the range of parameters, three optimization sample points were designed. The experiment verified that the forming quality of the three groups of parameters increased gradually, which achieved the function of parameters optimization. In conclusion, the analysis of the characteristics of parameter samples could excavate the characteristics of parameter samples quickly, and the quality prediction model and technology optimization scheme were more reliable and practical, which could be used to guide to establish reasonable technological parameters in ADRPM .