【作者】 刘强；

【导师】 刘献礼；

【作者基本信息】 哈尔滨理工大学 ， 机械制造及其自动化， 2018， 博士

【摘要】 深孔镗削加工中,镗杆的振动是制约加工质量与效率的关键因素。由于振动的存在,易产生内孔表面缺陷(振纹、微裂纹),降低工件表面精度,缩短刀具使用寿命(易崩刃),衰减机床精度,振动严重时甚至威胁操作人员与机床设备的安全。随着科技的不断发展,深孔类零件在涉及关系国防与民生的重大领域(军工、航空航天、能源装备等)得到了广泛的应用。目前受我国制造技术水平的限制,军用关键零部件的深孔加工所使用的刀具大多为进口刀具,此种状态对我国国防安全产生极大威胁,实现深孔加工技术突破具有重大需求,而刀具振动的有效控制是实现深孔加工技术突破的关键。因此,开展深孔减振刀具原理与控制研究,对实现深孔减振加工技术突破,提升深孔加工质量与效率具有重大意义。对镗削加工中振动成因进行分析,揭示由于负阻尼,负刚度的存在对镗削过程的影响。建立了考虑刀具振动的镗削力模型,获得刀尖点的振动姿态与轨迹,并对镗削表面形貌进行建模,分析了加工参数与刀具角度对镗削过程的影响,提出通过动力吸振器对镗杆的振动进行控制的方法,建立了动力吸振器的动力学模型,分析了外部载荷与系统自身参数对减振性能的影响,为智能减振镗杆的设计与振动控制策略的提出提供理论基础。基于动力吸振理论,提出通过智能控制变刚度吸振器刚度,实现对智能减振镗杆减振性能进行调节的方法,并完成了智能减振镗杆的设计。基于所建立了的变刚度吸振器动力学模型,揭示变刚度吸振器的工作原理。在以上研究基础上,完成了智能减振镗杆动力学模型的建立和减振性能分析,发现幅倍率曲面存在减振区域与非减振区域,最终获得最优曲线与最优控制点,为智能减振镗杆控制系统提供理论最优解。通过对振动信号的分析,掌握在镗削加工全周期中镗杆振动的变化规律。提出振动状态评价指标,为振动状态的判断与减振控制提供阈值,实现振动状态的感知评价与减振性能反馈。提出智能减振镗杆控制策略,通过小区间遍历的方式实现智能减振镗杆实际最优解的求解,并对控制系统进行性能分析。基于BP神经网络实现振动状态辨识,并通过遗传算法优化的BP神经网络实现智能减振镗杆的智能学习,使智能减振镗杆能够快速查找与预测实际最优解,提高智能减振镗杆减振性能调节效率。在此基础上搭建智能减振镗杆控制平台,为智能减振镗杆提供控制系统。对所提出的智能减振镗杆的零部件动力学基础参数进行测试,确保理论模型中参数的准确性。同时,对智能减振镗杆进行静/动态性能测试及稳态激励实验,获得智能减振镗杆的静/动力学特性。在此基础上,进行镗削实验,分析切削参数对智能减振镗杆振动特性的影响,为实际加工中切削参数的选取提供指导。最后通过减振性能验证实验,验证智能减振镗杆的减振性能,此部分研究对智能减振镗杆的使用具有一定指导意义。以智能减振镗杆为研究对象,针对智能减振镗杆在深孔加工中的振动控制展开深入研究。提出一种集状态感知、智能控制、智能学习功能于一体的新型智能减振镗杆。对涉及镗削过程、状态感知、减振机理、减振性能调节、智能控制策略和智能学习等关键技术展开研究,研究结果对智能减振镗杆的设计和使用具有一定的指导意义和参考价值。更多还原

【Abstract】 In deep hole boring,vibration of boring bar is the key factor restricting machining quality and efficiency.Due to the existence of vibration,it is easy to produce internal hole surface defects(vibrogram,micro-crack),reduce the surface precision of workpiece,shorten the service life of tool(easy to break the edge),attenuate the precision of machine tool.When vibration is serious,it even threatens the safety of operators and machine tools.With the continuous development of science and technology,deep-hole parts have been widely used in the important fields(military industry,aerospace,energy equipment,etc.)related to national defense and people’s livelihood.At present,limited by the level of manufacturing technology in our country,most of the cutting tools used in deep hole machining of key military components are imported tools,which poses a great threat to the national defense security of our country.There is a great demand for technological breakthrough in deep hole processing,and the effective control of tool vibration is the key to realize the breakthrough of deep hole machining technology.Therefore,it is of great significance to carry out the research on the principle and control method of deep hole vibration reduction cutting tool for realizing the breakthrough of deep hole vibration reduction machining technology and improving the quality and efficiency of deep hole machining.The causes of vibration in boring process are analyzed,and the influences of negative stiffness and negative damping on the boring process are revealed.Cutting force model considering tool vibration is established,and the vibration attitude and trajectory of cutter tip are obtained.The surface morphology is modeled and the influence of machining parameters and cutting tool angle on the boring process is revealed.A method to control vibration of boring bar by using dynamic vibration absorber is put forward.The dynamic model of dynamic vibration absorber is established,and the influence of external load and system parameters on vibration reduction performance is analyzed.This paper provides a theoretical basis for the design of intelligent vibration reduction boring bar and the proposal of vibration control strategy.An intelligent control method is proposed based on the theory of dynamic vibration absorption,which adjusts the vibration reduction performance of intelligent vibration reduction boring bar by intelligent control the stiffness of variable stiffness vibration absorber,and the design of intelligent vibration reduction boring bar is completed.The operational principle of variable stiffness vibration absorber is revealed based on the established dynamic model of variable stiffness vibration absorber.On the basis of the above research,the dynamic model of intelligent vibration reduction boring bar is established and the vibration reduction performance is analyzed.It is found that there are damping and non-damping areas on the amplitude ratio surface,and the optimal curve and the optimal control point are obtained.It provides a theoretical optimal solution for the intelligent vibration reduction boring bar control system.Through the analysis of vibration signal,the vibration variation law of boring bar during the whole period of boring is obtained.The evaluation index of vibration state is put forward,which provides the threshold for judging and controlling vibration state.The perceptual evaluation of vibration state and feedback of vibration reduction performance are realized.The control strategy of intelligent vibration reduction boring bar is put forward,and the practical optimal solution of intelligent vibration rreduction boring bar is solved by interval traversal.The performance of the control system is analyzed.The vibration state identification is realized based on BP neural network.Based on BP neural network optimized by genetic algorithm,intelligent learning is realized which make intelligent vibration reduction boring bar quickly find and predict the actual optimal solution,and improve the adjustment efficiency of the vibration reduction performance.On this basis,control platform has been built to provide a control system for the intelligent vibration reduction boring bar.The dynamic parameters of the intelligent vibration reduction boring bar are tested to ensure the accuracy of the parameters in the theoretical model.At the same time,the static/dynamic performance tests and steady excitation experiments are carried out to obtain the basic static/dynamic characteristics of intelligent vibration reduction boring bar.Then the boring experiments are carried out,and the influence of cutting parameters on the vibration performance is analyzed,which provides guidance for the selection of cutting parameters in practical machining.Finally,the vibration reduction performance of the intelligent vibration reduction boring bar is verified by the verification experiments.The research of this part has certain guiding significance for the use of intelligent vibration reduction boring bar.In this paper,taking the intelligent vibration reduction boring bar as the research object,and the vibration control of intelligent vibration reduction boring bar in deep hole machining is studied in depth.A new type of intelligent vibration reduction boring bar which integrates state perception,intelligent control and intelligent learning functions is proposed.The key technologies such as boring process,state perception,vibration reduction mechanism,vibration reduction performance adjustment,intelligent control strategy and intelligent learning are studied.The research results have certain guiding significance and reference value for the design and use of intelligent vibration reduction boring bar.更多还原