微小几何特征微铣削试验研究

微小型零件几何特征的加工质量直接影响微小型零件的使用性能,本文对50μm厚的微小几何特征尺寸精度及表面质量开展试验研究。正交试验结果显示:微铣削黄铜材料时,铣削参数对铣削力的影响主次为每齿进给量f_z、轴向切深a_p、径向切深a_e;铣削参数对尺寸误差的影响主次为a_p> a_e> f_z;铣削参数对表面粗糙度的影响主次为a_p> f_z> a_e。试验获得优化参数组合为a_p=15μm、a_e=30μm、f_z=0. 7μm,表明微铣削过程中轴向切深对加工质量的影响大于其他参数。因此,实际生产中应选择合适的轴向切深,较大的进给量和径向切深,以保证微型几何特征的加工质量,获得较高的加工效率。     

荒铣加工轴向切深识别方法

铸造、锻造等毛坯工件荒铣加工时,加工余量均匀性较低,分布随机性较大,因此荒铣加工参数很难优化,导致刀具寿命较短、加工效率较低。通过对螺旋铣削力建模和铣削加工过程刀齿啮切状态研究,采用Matlab分析了切削力峰值和切削力平均值随轴向切深的变化规律,提出一种基于在线监测铣削力信号的轴向切深识别方法,最后,通过实际的加工实验验证了所提出的轴向切深识别方法,为荒铣加工参数优化提供了理论基础。     

基于铣削均匀性的切削参数优化

分析了高速铣削加工切屑形成过程中刀具—工件的接触行为,提出了考虑轴向切削深度和径向切削深度的铣削均匀性模型。在此基础上,以恒定的金属去除率为约束条件、铣削均匀性系数为优化目标,建立了切削参数的优化模型。通过对航空铝合金进行高速铣削试验,验证了铣削均匀性理论及优化模型的合理性。结果表明,对于航空铝合金的高速铣削加工,采用大径向切深—小轴向切深有利于提高铣削均匀性,减小切削力。     

不锈钢微结构铣削仿真与试验研究

针对不锈钢微结构微铣削过程中铣削力以及加工质量,进行了微铣削参数仿真及试验研究。通过单因素有限元仿真,揭示了微铣削关键工艺参数每齿进给量、轴向切深和径向切深对铣削力影响规律。结果显示,尺寸误差以及表面粗糙度随着径向切深的增加波动变化,总体数值变化不大,径向切深对不锈钢微结构微铣削过程中的加工质量影响不大。因此,实际生产中,可以采用大径向切深小进给,提高生产率并保证加工质量。     

SLM钛合金3D打印件铣削加工参数优化分析

针对SLM钛合金3D打印件表面质量无法满足装配精度要求,仍需进行二次加工的需求,设计正交试验方案,建立表面粗糙度的预测模型并进行铣削参数优化分析,为SLM钛合金3D打印件铣削加工的切削参数选择提供依据。首先,对实验数据进行多元线性回归,建立适用于SLM钛合金件的铣削加工表面粗糙度数学预测模型,给出了切削速度、每齿进给量、轴向切深及径向切深与表面粗糙度的量化关系;建立以加工效率和表面粗糙度为优化目标的多目标切削参数优化模型,使用Pareto最优解集理论进行多目标切削参数优化,优化结果表明在切削速度130 m/min,每齿进给量0.01 mm/齿,轴向切深0.40 mm时可以得到较好的加工表面粗糙度及较高的加工效率。     

微细铣削工艺参数优化实验研究

以被加工工件表面粗糙度为指标,对微细铣削工艺参数进行了实验研究,采用所研发的基于pmac运动控制器的开放式三轴桌面微细铣削机床,选取轴向切深,径向切深和进给量三个因素安排正交实验,对黄铜H59进行了微细铣削加工。运用白光干涉仪对微细铣削宽槽底部的表面粗糙度进行了测量,通过对测量数据的极差分析和方差分析,确定了各因素对表面粗糙度的影响规律及三个因素对表面粗糙度影响的主次顺序,实验表明径向切深对表面粗糙度值影响最大。     

微细铣削毛刺宽度仿真与试验研究

作为一种重要的微小型精密零件加工工艺,微细铣削在铣削过程中产生的毛刺严重影响其加工质量及加工效率。为有效减小微细铣削过程中的毛刺尺寸,运用有限元分析软件DEFORM对微细铣削不锈钢材料的关键因素(轴向切深、每齿进给量、主轴转速及径向切深)进行有限元分析,得出了毛刺尺寸最小的优化铣削参数,并通过微细铣削试验验证了有限元分析结果的正确性及合理性,说明有限元仿真可以有效指导铣削试验,从而降低试验成本,提高试验效率。     

铸铁+铝合金双金属缸体铣削稳定性及刀具磨损实验研究

对铸铁+铝合金双金属材料缸体铣削稳定性和刀具磨损进行研究。采用单因素铣削实验的方法设计铣削实验,得到铣削速度、进给量、轴向切深等铣削参数及刀具主偏角对铣削稳定性的影响规律,对铣削过程中刀具磨损进行分析,优化切削参数,为双金属材料缸体接合面的高效铣削加工提供参考。     

拐角高速铣削切削力正交试验研究

对DMU60T高速加工中心加工P20模具钢时的15°、45°和75°拐角高速铣削切削力进行正交试验研究.绘制了单因素趋势图,运用单因素极差分析法分析了拐角切削力与切削参数(轴向切深ap、径向切深ae、进给速度f、主轴转速n)的关系,优化了拐角高速铣削参数.试验表明:轴向切深和进给速度是影响拐角切削力的主要因素,主轴转速和径向切深是次要因素.     

高速铣削镍基合金GH4169切削力的试验研究

镍基合金广泛应用于航空航天上,但加工起来比较困难。文中以镍基合金GH4169为试验对象,进行了高速铣削试验,研究铣削速度vc、轴向切深ap、径向切宽ae和进给量f四个切削参数对切削力F的影响,从而为生产实践提供指导。     

Counterbalance of cutting force for advanced milling operations

The goal of this work is to concurrently counterbalance the dynamic cutting force and regulate the spindle position deviation under various milling conditions by integrating active magnetic bearing (AMB) technique, fuzzy logic algorithm and an adaptive self-tuning feedback loop. Since the dynamics of milling system is highly determined by a few operation conditions, such as speed of spindle, cut depth and feedrate, therefore the dynamic model for cutting process is more appropriate to be constructed by experiments, instead of using theoretical approach. The experimental data, either for idle or cutting, are utilized to establish the database of milling dynamics so that the system parameters can be on-line estimated by employing the proposed fuzzy logic algorithm as the cutting mission is engaged. Based on the estimated milling system model and preset operation conditions, i.e., spindle speed, cut depth and feedrate, the current cutting force can be numerically estimated. Once the current cutting force can be real-time estimated, the corresponding compensation force can be exerted by the equipped AMB to counterbalance the cutting force, in addition to the spindle position regulation by feedback of spindle position. On the other hand, for the magnetic force is nonlinear with respect to the applied electric current and air gap, the characteristics of the employed AMB is investigated also by experiments and a nonlinear mathematic model, in terms of air gap between spindle and electromagnetic pole and coil current, is developed. At the end, the experimental simulations on realistic milling are presented to verify the efficacy of the fuzzy controller for spindle position regulation and the capability of the dynamic cutting force counterbalance.     

Active suppression of chatter in peripheral milling. Part II. Application of fuzzy control

In this paper, a feasibility study is conducted where fuzzy logic control is investigated to actively vary spindle speed modulation parameters for chatter suppression. A justification for using fuzzy control is given, as well as a brief synopsis of the fuzzy inferencing mechanism. Proportional and proportional-integral fuzzy control algorithms are developed. The set point in these controllers is established from experimental observations and measurements of the machined surfaces. Controller performance is tested by simulating changes in the axial depth of cut from a stable depth to 20% and 50% beyond the stable limit for constant speed cutting. It was found that both controllers were able to regulate the vibration in the milling process, however, the proportional-integral controller generally exhibited more desirable performance characteristics.     

Spindle vibration suppression for advanced milling process by using self-tuning feedback control

The goal of this work is to concurrently counterbalance the dynamic cutting force and regulate the spindle position deviation under various milling conditions by integrating active magnetic bearing (AMB) technique, fuzzy logic algorithm, and an adaptive self-tuning feedback loop. The experimental data, either for idle or cutting, are utilized to establish the database of milling dynamics so that the system parameters can be on-line estimated by employing the proposed fuzzy logic algorithm as the cutting mission is engaged. Based on the estimated milling system model and preset operation conditions, i.e., spindle speed, cut depth, and feed rate, the current cutting force can be numerically estimated. Once the current cutting force can be real time estimated, the corresponding compensation force can be exerted by the equipped AMB to counterbalance the cutting force, in addition to the spindle position regulation by feedback of spindle position. At the end, the experimental simulations on realistic milling are presented to verify the efficacy of the fuzzy controller for spindle position regulation and the capability of the dynamic cutting force counterbalance.     

基于现场总线的恒功率约束切削加工自适应控制

以进给速度为控制对象的自适应约束控制(ACC)技术有利于提高数控加工效率和实现刀具保护,在分析Profibus总线和模糊控制特点的基础上,针对铣削加工过程的非线性、时变性和不确定性,提出了基于现场总线的铣削加工过程自适应模糊控制的解决方案.采用恒功率约束,利用比例因子在线自调整的方法对切削参数变化的进给速度进行在线控制.仿真结果表明,方案克服了传统的模糊控制动态响应较慢的鲁棒性较差的缺点,具有响应速度快、实时性和稳定性好等优点.当切削深度突变时,能在线自适应调整进给速度,使切削功率接近参考值,防止刀具损坏和提高加工效率.     

Optimal Predicted Fuzzy PI Gain Scheduling Controller of Constant Turning Force Systems with Fixed Metal Removal Rate

The dynamic behaviour of the turning process is nonlinear and time-varying owing to variations in cutting depth. This paper proposes an optimal predicted fuzzy PI gain scheduling controller to control the constant turning force (CTF) process with a fixed metal removal rate (MRR) under various cutting conditions. The predicted fuzzy PI gain scheduling control scheme consists of two parts: the fuzzy PI gain scheduling controller; and the grey predictor. First, the optimal parameters of both the grey predictor and the optimal PI gains corresponding to each desired cutting depth in the range of operation, are designed off-line by using the proposed optimal combined method, i.e. Taguchi–RGA method, which integrates the Taguchi method and a real-coded genetic algorithm (RGA). Then, before the parameters of both the grey predictor and the PI gains are scheduled on-line, by fuzzy inference in terms of the changes of cutting depth, the optimal set of triangular-type membership functions of the fuzzy inference mechanism for scheduling the parameters of both the grey predictor and the PI gains are also designed off-line by using the Taguchi–RGA method. Computer simulations are performed to verify the applicability of this optimal predicted fuzzy PI gain scheduling control scheme for controlling the CTF process with a fixed MRR under various cutting conditions. It is shown that such an optimal predicted fuzzy PI gain scheduling control scheme can achieve satisfactory performance and better results than those reported recently in the literature.     

Effects of Cutting Parameters on Tool Insert Wear in End Milling of Titanium Alloy Ti6A14V

Titanium alloy is a kind of typical hard-to-cut material due to its low thermal conductivity and high strength at elevated temperatures, this contributes to the fast tool wear in the milling of titanium alloys. The influence of cutting conditions on tool wear has been focused on the turning process, and their influence on tool wear in milling process as well as the influence of tool wear on cutting force coefficients has not been investigated comprehensively. To fully understand the tool wear behavior in milling process with inserts, the influence of cutting parameters on tool wear in the milling of titanium alloys Ti6Al4 V by using indexable cutters is investigated. The tool wear rate and trends under different feed per tooth, cutting speed, axial depth of cut and radial depth of cut are analyzed. The results show that the feed rate per tooth and the radial depth of cut have a large influence on tool wear in milling Ti6Al4 V with coated insert. To reduce tool wear, cutting parameters for coated inserts under experimental cutting conditions are set as: feed rate per tooth less than 0.07 mm, radial depth of cut less than 1.0 mm, and cutting speed sets between 60 and 150 m/min. Investigation on the relationship between tool wear and cutting force coefficients shows that tangential edge constant increases with tool wear and cutter edge chipping can lead to a great variety of tangential cutting force coefficient. The proposed research provides the basic data for evaluating the machinability of milling Ti6Al4 V alloy with coated inserts, and the recommend cutting parameters can be immediately applied in practical production.     

Effects of cutting parameters on tool insert wear in end milling of titanium alloy Ti6Al4V

Titanium alloy is a kind of typical hard-to-cut material due to its low thermal conductivity and high strength at elevated temperatures, this contributes to the fast tool wear in the milling of titanium alloys. The influence of cutting conditions on tool wear has been focused on the turning process, and their influence on tool wear in milling process as well as the influence of tool wear on cutting force coefficients has not been investigated comprehensively. To fully understand the tool wear behavior in milling process with inserts, the influence of cutting parameters on tool wear in the milling of titanium alloys Ti6Al4V by using indexable cutters is investigated. The tool wear rate and trends under different feed per tooth, cutting speed, axial depth of cut and radial depth of cut are analyzed. The results show that the feed rate per tooth and the radial depth of cut have a large influence on tool wear in milling Ti6Al4V with coated insert. To reduce tool wear, cutting parameters for coated inserts under experimental cutting conditions are set as: feed rate per tooth less than 0.07 mm, radial depth of cut less than 1.0 mm, and cutting speed sets between 60 and 150 m/min. Investigation on the relationship between tool wear and cutting force coefficients shows that tangential edge constant increases with tool wear and cutter edge chipping can lead to a great variety of tangential cutting force coefficient. The proposed research provides the basic data for evaluating the machinability of milling Ti6Al4V alloy with coated inserts, and the recommend cutting parameters can be immediately applied in practical production.     

Self-organizing fuzzy control of constant cutting force in turning

Constant force control is gradually becoming an important technique in the modern manufacturing process. Especially, constant cutting force control is a useful approach in increasing the metal removal rate and the tool life for turning systems. However, turning systems generally have nonlinear with uncertainty dynamic characteristics. Designing a model-based controller for constant cutting force control is difficult because an accurate mathematical model in the turning system is hard to establish. Hence, this study employed a model-free fuzzy controller to control the turning system in order to achieve constant cutting force control. Nevertheless, the design of the traditional fuzzy controller (TFC) presents difficulties in finding control rules and selecting an appropriate membership function. Moreover, the database and fuzzy rules of a TFC are fixed after the design step and then cannot appropriately regulate ones real time according to the system output response and the desired control performance. To solve the above problem, this work develops a self-organizing fuzzy controller (SOFC) for constant cutting force control to evaluate control performance of the turning system. The SOFC continually updates the learning strategy in the form of fuzzy rules, during the turning process. The fuzzy rule table of this SOFC can be begun with zero initial fuzzy rules which not only overcome the difficulty in the TFC design, but also establish a suitable fuzzy rules table, and support practically convenient fuzzy controller applications in turning systems control. To confirm the applicability of the proposed intelligent controllers, this work retrofitted an old lathe for a turning system to evaluate the feasibility of constant cutting force control. The SOFC has a better control performance in constant cutting force control than does the TFC, as verified in experimental results.     

Self-organizing fuzzy control of constant cutting force in turning

Constant force control is gradually becoming an important technique in the modern manufacturing process. Especially, constant cutting force control is a useful approach in increasing the metal removal rate and the tool life for turning systems. However, turning systems generally have nonlinear with uncertainty dynamic characteristics. Designing a model-based controller for constant cutting force control is difficult because an accurate mathematical model in the turning system is hard to establish. Hence, this study employed a model-free fuzzy controller to control the turning system in order to achieve constant cutting force control. Nevertheless, the design of the traditional fuzzy controller (TFC) presents difficulties in finding control rules and selecting an appropriate membership function. Moreover, the database and fuzzy rules of a TFC are fixed after the design step and then cannot appropriately regulate ones real time according to the system output response and the desired control performance. To solve the above problem, this work develops a self-organizing fuzzy controller (SOFC) for constant cutting force control to evaluate control performance of the turning system. The SOFC continually updates the learning strategy in the form of fuzzy rules, during the turning process. The fuzzy rule table of this SOFC can be begun with zero initial fuzzy rules which not only overcome the difficulty in the TFC design, but also establish a suitable fuzzy rules table, and support practically convenient fuzzy controller applications in turning systems control. To confirm the applicability of the proposed intelligent controllers, this work retrofitted an old lathe for a turning system to evaluate the feasibility of constant cutting force control. The SOFC has a better control performance in constant cutting force control than does the TFC, as verified in experimental results.