Tool Wear Characteristics In Laser Ultrasonically Combined Precision Cutting Of Tungsten Carbide

Tungsten carbide has many superior physical and mechanical properties such as high strength,high hardness,excellent wear resistance and so on,which has been applied in many fields such as aerospace,national defense and apparatus.However,tungsten carbide is very difficult to machine owing to its high brittleness and low facture toughness that cause high cutting force,severe tool wear and high processing cost.As a result,the development of the technology of high-efficient and precise machining difficult-to-cut material is limited.In order to realize high efficient and precise machining of tungsten carbide,a novel hybrid machining technique called laser ultrasonically combined cutting is introduced.Through theoretical analysis,numerical simulation and experimental verification,the present study aims at studying the wear characteristics and wear mechanisms of super hard tools and realizing the recognition and prediction of tool wear condition in laser ultrasonically combined cutting tungsten carbide.The laser ultrasonically combined cutting principle was analyzed.The laser ultrasonically combined cutting force model was established,the optimum parameters for the minimum cutting force during laser ultrasonically combined cutting tungsten carbide were obtained through orthogonal experiment,and the cutting force characteristics were studied through a series of contrast experiments in conventional cutting,ultrasonically elliptical vibration cutting,laser assisted cutting and laser ultrasonically combined cutting tungsten carbide materials with Cubic Boron Nitride(CBN)and Polycrystalline Diamond(PCD)tools.Based on heat transfer theory,the mathematical analytic model and the finite element model of the temperature field were established under the condition of laser ultrasonically combined cutting tungsten carbide,the temperature distributions of the workpiece surface and along the direction of cutting depth were simulated and analyzed in the process of laser ultrasonically combined cutting tungsten carbide,and the influence rules of different cutting parameters on cutting temperature were experimentally researched that verified the correctness of the analytic model and the finite element model.The tool flank wear model was established during laser ultrasonically combined cutting tungsten carbide.The tool life and tool wear patterns of CBN tools and PCD tools during conventional cutting,ultrasonically elliptical vibration cutting,laser assisted cutting and laser ultrasonically combined cutting tungsten carbide were studied.The effects of cutting methods,tool materials,workpiece materials and cutting parameters on tool wear characteristics were investigated,and the influence rules of tool wear on cutting force,cutting temperature and workpiece surface quality were obtained.Besides,the tool wear morphology and wear patterns during conventional cutting,ultrasonically elliptical vibration cutting,laser assisted cutting and laser ultrasonically combined cutting tungsten carbide were observed and analyzed by using digital microscope with super depth,Scanning Electron Microscope(SEM)and energy spectrum analysis on the tool flank face,rake face and tip location,and the wear mechanisms of CBN and PCD tools in the process of laser ultrasonically combined cutting tungsten carbide were revealed.The tool wear condition monitoring system in the process of laser ultrasonically combined cutting tungsten carbide was constructed,the acoustic emission signals generated by tool wear were decomposed and reconstructed by using wavelet packet transform,and the energy eigenvalues under different tool wear conditions were obtained.By constructing the neural network,the extracted energy eigenvectors were trained and tested,and the tool wear condition recognition during laser ultrasonically combined cutting tungsten carbide was realized.Based on the gray markov theory,the tool wear prediction model that could predict tool wear condition in the process of laser ultrasonically combined cutting tungsten carbide was built,and its prediction were comparatively analyzed with that based on time series model.The research results show that the tool flank wear prediction are basically in accordance with the experimental results,which can determine the tool wear condition at next moment.Besides,compared to grey model and time series model based on neural network,the normalized prediction relative errors based on grey morkov model are reduced 74% and 28.1%,respectively,which verify the reasonableness and accuracy of grey markov model.