Research On Key Technology Of Micro Arc Oxidation Of Titanium Alloy

Titanium and its alloy were widely used in aviation,spaceflight,navigation,textile,biological medicine and industrial area due to their high specific strength,melting temperature and good biological compatibility.But the titanium and its alloy were poor of wear-resisting and corrosion resistance and their hardness is low.So the material surface was easily damaged to lead to the material failure.In order to obtain good performance,the material surface should be treated.Micro-arc oxidation is an effective surface treatment technology to improve the performance of titanium and its alloy.The technology aimed at getting a dense ceramic film of high hardness,high wear-resisting and corrosion resistance.It helps to prolong the service life of material and enlarge its application area.In this paper,the TC4 titanium alloy surface ceramic coatings were prepared by using micro-arc oxidation power.The influences of electric parameters on film performance were studied.A gradient current mode was proposed and the influences of different current modes on film performance were discussed.The Neural network was first time to be combined into MAO to achieve prediction of coating performance.The main research contents and conclusions of this paper as follows:1)The three-factor test for three-level orthogonal was created to optimize the electric parameters(current density,pulse frequency and duty cycle)on the performance indicators(thickness,roughness and hardness).The test selected current density of 10A/dm2,pulse frequency of 500Hz and duty cycle of 10%for optimal process plan.The influence of Electrical parameters on the surface morphology,the phase composition and the corrosion resistance were studied.2)The gradient current density parameters were set up based on the optimal electrical parameters.The TC4 titanium alloy MAO coatings were prepared by using constant current density mode and gradient current density mode respectively,and studied the effect of current density on the coating’s thickness,surface roughness,hardness,while the surface morphology,phase composition and corrosion resistance of the ceramic coatings were observed and analyzed.3)Based on the data of orthogonal experiment,A Network prediction model was established by applying BP neural network.The model could accurately predict the MAO coating’s thickness,surface roughness and microhardness.The average prediction errors of the coating’s three performance indictors were within 5%.The BP neural network prediction model has a certain practical significance for micro-arc oxidation technology application.