Research On Machine Tool Energy Consumption Prediction And Process Parameters Optimization Of High-speed Dry Hobbing

As a gear processing method with large quantity and wide range,gear hobbing is widely favored by manufacturing enterprises.Traditional gear hobbing mostly depends on the use of cutting fluid,and the cutting speed is low,which is difficult to meet the current environmental protection concept of green development and the benefit needs of production enterprises.In view of this,the green and efficient gear processing technology-high-speed dry hobbing technology came into being.The high-speed dry hobbing process abandons the use of cutting fluid,and the cutting speed is high.It is a dynamic machining process coupled with multiple machining variables.When machining gears,it is very vulnerable to the influence of process conditions,resulting in the problems of high transient energy of machine tool,complex change of energy consumption,poor machining quality of gears and so on.Due to the multi-source,dynamic and complexity of machine tool energy consumption,how to effectively predict the machine tool energy consumption in the machining process and carry out energy-saving process parameter optimization is the focus and difficulty of this paper.In view of this,relying on the national key R & D plan "development of key technologies and complete sets of equipment for green precision machining of new energy automobile gears"(Project No.: 2020YFE0201000),this paper takes the key equipment of high-speed dry hobbing machine tool as the research object,and carries out the research on the energy consumption prediction and process parameter optimization method of high-speed dry hobbing machine tool.Firstly,the energy consumption distribution characteristics of high-speed dry hobbing machine tool are studied.The composition of high-speed dry hobbing process parameters is analyzed,the energy consumption characteristics experiment of high-speed dry hobbing machine tool is carried out,the power model of high-speed dry hobbing machine tool is studied from the spatial dimension,and the variation laws of machining energy consumption and no-load energy consumption of machine tool under variable process parameters are revealed from the time dimension.The above theoretical analysis lays a theoretical foundation for the follow-up research on machine tool energy consumption prediction and process parameter optimization.Then,a prediction method of energy consumption of high-speed dry hobbing machine tool is proposed.Aiming at the problem of energy consumption prediction,this paper analyzes the influence relationship between the two main cutting parameters of spindle speed and feed rate on the machine tool energy consumption,establishes the hobbing energy consumption prediction model,puts forward an energy consumption prediction method of high-speed dry hobbing machine tool based on linear decreasing PSO improved radial basis function neural network,expounds the construction process of the energy consumption prediction method,and finally verifies the method through the energy consumption data of high-speed dry hobbing machine tool,The predicted value of energy consumption is obtained.Secondly,an optimization method of high-speed dry hobbing process parameters for high efficiency and energy saving is proposed.The optimization problem of high-speed dry hobbing is described,a hobbing optimization model for low energy consumption and high efficiency is established,a high-speed dry hobbing process parameter optimization method based on multi-objective salp swarm algorithm is proposed,and the optimal process parameter solution is obtained.The effectiveness of the proposed method is verified by experiments and comparative analysis.Thirdly,an integrated optimization method of hob parameters and cutting parameters for energy consumption cost quality optimization is proposed.As the optimization of hobbing process parameters mostly focuses on the optimization of cutting parameters,taking the hob parameters and cutting parameters as the variables to be optimized at the same time,a multi-objective optimization model is constructed,and a multi-objective optimization decision-making method for high-speed dry hobbing based on MOMVO-TOPSIS is proposed.The parameters of the integrated optimization problem are solved based on the MOMVO optimization module,and the Pareto solution of the optimized process parameters is obtained,After the Pareto parameter set is obtained,the process parameter solution of TOPSIS is determined,and the process parameter solution of TOPSIS is obtained.Finally,the decision support system for the optimization of process parameters of high-speed dry hobbing for high efficiency and energy saving is designed in detail,including the system functional requirements,overall scheme,functional planning anddatabase.The decision support system for the optimization of process parameters of high-speed dry hobbing for high efficiency and energy saving is developed,and the preliminary application of the system is realized.