Study On Tool Wear And Evolution Mechanism Of High-speed Cutting Titanium Alloy TC4

With the successive introduction to new concepts such as "Industry 4.0" in Germany and "Industrial Internet" in the United States,China promulgated the new idea of "China Manufacturing 2025" to closely follow the pace of the development of manufacturing industry.The essence of all three is being "Internet + Manufacturing",This is intelligent manufacturing.High-speed and high-efficiency cutting,as the high-tech of "made in China 2025",compared with the traditional machining,with higher processing efficiency,mor excellent surface quality and other significant advantages.It has been widely used in aerospace,defense,military and other fields.However,with the continuous development of China’s aerospace field,the comprehensive performance requirements of the selected materials are more stringent.Know as the "space metal" titanium alloy TC4 material,with good corrosion resistance,heat resistance,high strength and other outstanding characteristic,has excellent application prospects for the field of aerospace,but also because the material has small coefficient of thermal conductivity,high chemical and low elastic modulus of features,making it a typical hard-to-process materials.Therefore,based on the artificial neural network technology,linear regression analysis and solving techniques,energy dispersive spectrum analysis and other modern science technology,the tools wear of the high speed cutting of titanium alloy TC4 conduct is researched deeply and the feasibility reference is provided for the modern processing enterprises.First of all,using artificial neural network technology to build a four-input and two-output and three-layer network structure,the use of four-factor and four-level orthogonal design tests method of titanium alloy TC4 bar material in the high-speed dry cutting experiments,in order to achieve the contrast between the experimental value and the predicted value of cutting force and tool wear amount in different cutting parameters,the testing the feasibility of the BP neural network at the same time.After 16 sets of orthogonal experiments and neural network training prediction and demonstration,The maximum error of the cutting force were 9.98% and the maximum wear error was5.83%.There are more experts and scholars study on cutting titanium alloy TC4 tool wear,but the high-speed cutting titanium alloy TC4 very few.According to the high-speed range of cutting titanium alloy provided by foreign scholars,110m/min is selected as thetest arrangement for cutting speed.The cutting speed is already in the category of TC4high-speed cutting.At the same time,by controlling the single factor variable of cutting length,after a large number of cutting experiments and obtaining effective experimental data,the wear curve of TC4 tool of high-speed cutting titanium alloy was acquired:Under the condition of high speed cutting,the initial wear stage is passed in a moment.After the cutting length reaches 600 mm,the tool wear enters into the sharp wear stage.Based on the study on tool wear curve,combined with the former scholars research results of high speed cutting of titanium alloy,in this paper,scanning electron microscopy(SEM)and EDS spectrometer(SEM)are used to observe the SEM morphology of the tool wear area and the detection of chemical composition elements,integrated the affinity of the titanium alloy material is large,The conclusions are as follows: At the cutting speed of 110 m/min,the wear mechanism of high speed cutting titanium alloy TC4 is still dominated by bond wear,with oxidative wear and no diffusion wear.