Control Of The Surface Integrity Of Hard Cutting Cr12MoV Die Steel

Die steel Cr12MoV has a higher thermal stability, high hardenability, wearresistance and high flexural strength, after the performance of high speed steel, itis an important material for cold heading die, die and so on, its consumptionoccupies the first place in the die steel. Hard cutting technology has excellentmachining flexibility and environmental protection, the technology has beengradually replacing grinding as die steel processing technology. However, it isthe key to make the hard cutting process to completely replace the grinding thatimproving the surface integrity and performance, so the research on the surfaceintegrity is very necessary. In hard turning machining, tool wear is one of theimportant factor, so this paper consider the tool wear and cutting parameters tooptimize the parameters of hard turning Cr12MoV die steel surface integrity andfatigue life, and to make the optimization results are reliable, accurate forecastmodel is essential. The main contents of this paper include：Firstly, the orthogonal test of surface integrity was finished, and the featureindexes of surface integrity were determined by the date of the test. the maineffect on the surface integrity was analysed by range method., which reflectedhow did cutting conditions affect on surface integrity. And the surface integritywas studied comprehensively by the single factor test of main effect factors.Secondly，the relation of cutting conditions and fatigue life is researchedby gray relational theory and the univariate regression model of surface integrityand fatigue life，which resulted in the reasonable method of longer fatigue life.Finally, a predicting model of surface integrity and fatigue life is built inthe method of BP neural network and response surface methodology (RSM)which was optimized by genetic algorithm. It is the Matlab which was used tobuild a comprehensive system of hard turning，and this system can realize thefunction real-time input and output. At the same time，the parameters of surfaceintegrity and fatigue life are optimized with improved particle swarm algorithm，and all the works are based on the finished model. A test whichaimed to proved the optimized results is finished, therefore, the accuracy ofoptimized results is determined by comparing experimental results and optimizedones.