Optimization Of Rough Turning Feed Speed Based On Spindle Power Model Of Machining Process

In traditional turning,the process parameters are selected by search manual or a trialcut method that could not guarantee a optimum cutting performance when machined in different environment.Optimization of process parameters has become an urgent need to reduce the cost of turning operations.Most of the current research methods are aimed at obtaining one or several groups of process parameters.However,this method cannot make full use of the process data which contained a large amount of process information,and the impact of different machine tool environments cannot be considered.In addition,it is also impossible to optimize the unsteady cutting shape of a certain section such as arc or cone during machining.In view of the above problems,this paper proposes a method of rough turning feed speed optimization which obtains the process parameter information in the machining process through the extraction algorithm,uses the machining process data to establish the spindle power prediction model and optimize the feed speed.In the research of process parameters extraction,there are programming methods such as fixed cycle and compound cycle that are difficult to extract directly.After decoding the G code,the machining program segment generated by the CNC system interpreter is composed of simple small line segments,whose extraction and calculation is simple and easy.According to different processing attributes,different processing types are distinguished to realize automatic extraction of process parameters for each processing position.According to the influence of the machine tool environment,take the machining process data obtained by cutting in the same experimental environment as the training test sample.Based on the parallel integrated neural network,the power prediction model of the turning spindle is established.Different machining environments are used to establish different models,and the accuracy of the model is verified by experiments.Aiming at the optimization problem of unsteady cutting conditions such as arc and cone,for improve the machining efficiency and spindle power stability,this paper proposes a feed speed optimization algorithm to solve the optimal feed rate at different machining positions.Based on the NSGA-II algorithm and improved the functions such as crossover and mutation,the search efficiency of the algorithm is effectively improved.The result of a verified experiment show that the optimization method can achieve the expected results wether the machining efficiency or the power fluctuation stability is prioritized.