一个基于数字化加工的铣削力预测系统

切削用量的实时获取是切削力预测的关键技术之一。基于数字化加工技术,通过在加工仿真过程中对三维实体图形进行分析,获得实时的切削参数,实现了切削力的实时预测。并开发了一个针对铣削加工的切削力预测的软件系统,通过实验验证了系统的正确性。     

基于刀具跳动的环形铣刀切削厚度模型的切削力计算

数控铣削过程中,切削变形引起的瞬时切削厚度是影响铣削加工切削力建模的重要参数之一,针对环形铣刀的切削特点,在考虑刀具跳动的情况下,对真实刀刃轨迹运动进行分析。将微细铣削的加工过程用宏观铣削来表示,从而建立了基于宏观铣削过程中刀具跳动下精密加工的瞬时切削厚度。通过仿真模拟和切削力试验来预测切削力,预测结果和试验结果具有一致性,表明该模型可以更好的预测加工过程中的切削力。     

基于铣削力精确建模的工件表面让刀误差预测分析

航空航天制造业结构件的高速铣削加工中,在切削力作用下由整体铣削刀具挠度变形所引起的工件表面让刀误差,严重制约零件的加工精度和效率。针对这一问题,通过建立铣削力精确预测模型,结合刀具刚度特点,对工件让刀误差进行预测分析。将切削速度和刀具前角对切削力的影响规律引入二维直角单位切削力预测模型,并通过试验进行相关系数标定。借助等效前角将直角切削力预测系数应用到斜角切削力的预测,通过矢量叠加构建整体刀具三维切削力模型。分析刀具挠度变形对铣削层厚度及铣削接触中心角范围影响规律。基于离散化的刀具模型和切削力模型,建立铣削载荷条件下刀具等效直径悬臂梁模型弯曲变形计算方法。构建以刀具变形对铣削过程影响作用规律为反馈的刚性工件表面让刀误差及切削力柔性预测模型,通过整体铣刀铣削试验验证所建立理论模型的预测精度。     

影响航空发动机精锻叶片切削力的工艺分析

针对航空发动机无余量精锻叶片榫头数控加工工艺参数对切削力的影响问题,进行了航空发动机精锻叶片的切削力实验与分析。首先,根据精锻叶片榫头的特点选择合适的铣削加工方法,并建立相应的数学模型,得出用于精锻叶片榫头加工的刀具切削力的数学表达式。其次,通过铣削工艺参数对切削力的建模与分析,计算出切削力对铣削工艺参数的灵敏度预测,并得出切削深度对切削力的影响最为明显。最后,通过三轴数控机床与自主搭建的测试系统进行切削力测试,了解评估指标与影响因素之间的相互作用规律,并通过该规律分析切削力验证了灵敏度预测结果。为精锻叶片榫头加工工艺参数的选择提供了依据。     

基于正交切削模拟的零件铣削加工变形预测研究

提出了基于正交切削模拟的零件铣削加工变形的预测方法,建立了三维铣削加工的有限元模型。基于正交切削加工模拟结果,利用铣削温度、铣削力的分析模型求解了三维铣削加工的瞬态温度和瞬态切削力,并将其作为动态载荷应用于三维切削加工的有限元模型,模拟了零件的三维铣削加工过程,预测了零件的变形。通过模拟结果与现场加工情况对比,证明该预测方法是行之有效的。     

型腔模具拐角高速加工的切削力研究

在型腔模具的高速铣削中,拐角处切削力的突变会影响加工的质量和加工效率。拐角高速铣削中,对影响切削力的主要因素有进给速度、轴向切深、径向切深和主轴转速。为了研究拐角加工中切削参数和切削力的关系,先进行了一系列的单因素实验,然后进行四因素四水平的正交试验,通过线性回归正交实验法,建立拐角铣削力预测模型。对该预测模型进行了回归方程和回归系数的显著性检验,证明了该预测模型的显著性及得出各因素的对切削力的影响顺序。该模型可用于高速拐角加工中预测切削力及合理选择铣削参数。     

基于过程集成优化的复杂曲面数控铣削性能分析

针对复杂自由曲面变曲率、大扭曲的特征及其铣削性能难预测的问题,提出加工过程的集成优化的切削性能分析方法,在曲面多轴铣削工作流程中综合评价和提高切削加工效率和质量。建立了自由曲面体零件多轴加工集成优化铣削模型,集成切削加工刀位轨迹计算、切削仿真与机床运动仿真、切削力预测、工艺参数优化工作流程及其输入输出文件,实时从输出文件中解析提取计算结果参数,有效分析预测切削参数与切削力对加工效率和质量的影响,实现复杂自由曲面铣削过程的集成与全局优化。将该方法应用于大型混流式水轮机叶片的数控铣削性能分析,并与生产数据进行对比,进一步验证了所提加工过程集成优化方法可有效分析和预测大型自由曲面的数控铣削性能。     

钛合金型面侧壁铣削力建模与仿真

钛合金型面件侧壁的铣削一般采用整体硬质合金立铣刀进行加工,因切削力的影响,加工过程较难控制且会产生零件变形,对铣削力进行建模和预测是控制加工变形的有效措施。通过圆柱螺旋立铣刀微元切削力矢量求和及合成,建立了整体立铣刀侧面铣削过程中的瞬态切削力预测模型;采用不同进给速度条件下的铣削力辨识试验,并对平均切削力试验数据进行数值线性拟合,获得了钛合金侧面铣削试验圆柱螺旋立铣刀的剪切力和犁耕力系数。计算了不同切削参数下的四刃整体硬质合金立铣刀的瞬时切削力,并结合钛合金侧面铣削试验验证了所建立的仿真模型的有效性。这为钛合金结构件侧面铣削加工工艺参数的制定和优化选择提供了理论指导依据。     

立铣加工动态切削力预测新方法及应用

通过切削力物理建模、仿真和应用研究来准确地预测切削力,是进行工艺优化的必要前提.动态切削力的预测对于研究切削机理和加工质量的控制都很重要.提出了一种新的螺旋立铣刀加工中动态切削力建模方法,通过微元法建立的切削力数学模型和斜角等厚度切削有限元模型两者结合,对高速铣削淬硬模具钢SKD11的动态切削力进行预测,并且对误差来源进行了分析.本建模方法通过建立单刃切削力数学模型,然后结合有限元分析得到单刃切削力曲线,经离散数据叠加后得到加工过程的动态铣削力曲线.此方法可避免传统建模中需要大量试验求取多个系数且预测精度差的特点.最后通过分析影响结果的主要因素及参数调节方法,保证了预测精度.     

圆柱平底螺旋立铣刀动态切削力仿真与应用

采用瞬时刚性力模型进行平底螺旋立铣刀动态切削力建模,推导出铣削切削力系数辨识公式。在卧式加工中心HMC63上进行7075铝合金全齿铣削切削力测试试验,辨识出切削力系数,并利用MATLAB进行切削力数值仿真。对试验结果和仿真结果进行对比,结果表明切削力建模是有效的,能够较准确地预测铣削力,进行切削力的预测和监测,用于工件加工变形控制。同时切削力系数可以进一步进行切削稳定性分析,提高航空结构件的加工精度和效率。     

New mathematical method for the determination of cutter runout parameters in flat-end milling

The cutting force prediction is essential to optimize the process parameters of machining such as feed rate optimization, etc. Due to the significant influences of the runout effect on cutting force variation in milling process, it is necessary to incorporate the cutter runout parameters into the prediction model of cutting forces. However, the determination of cutter runout parameters is still a challenge task until now. In this paper, cutting process geometry models, such as uncut chip thickness and pitch angle, are established based on the true trajectory of the cutting edge considering the cutter runout effect. A new algorithm is then presented to compute the cutter runout parameters for flat-end mill utilizing the sampled data of cutting forces and derived process geometry parameters. Further, three-axis and five-axis milling experiments were conducted on a machining centre, and resulting cutting forces were sampled by a three-component dynamometer. After computing the corresponding cutter runout parameters, cutter forces are simulated embracing the cutter runout parameters obtained from the proposed algorithm. The predicted cutting forces show good agreements with the sampled data both in magnitude and shape, which validates the feasibility and effectivity of the proposed new algorithm of determining cutter runout parameters and the new way to accurately predict cutting forces. The proposed method for computing the cutter runout parameters provides the significant references for the cutting force prediction in the cutting process.     

Development of an automatic arc welding system using SMAW process

In end milling of pockets, variable radial depth of cut is generally encountered as the end mill enters and exits the corner, which has a significant influence on the cutting forces and further affects the contour accuracy of the milled pockets. This paper proposes an approach for predicting the cutting forces in end milling of pockets. A mathematical model is presented to describe the geometric relationship between an end mill and the corner profile. The milling process of corners is discretized into a series of steady-state cutting processes, each with different radial depth of cut determined by the instantaneous position of the end mill relative to the workpiece. For the cutting force prediction, an analytical model of cutting forces for the steady-state machining conditions is introduced for each segmented process with given radial depth of cut. The predicted cutting forces can be calculated in terms of tool/workpiece geometry, cutting parameters and workpiece material properties, as well as the relative position of the tool to workpiece. Experiments of pocket milling are conducted for the verification of the proposed method.     

Prediction of cutting forces in helical milling process

The prediction of cutting forces is important for the planning and optimization of machining process in order to reduce machining damage. Helical milling is a kind of hole-machining technique with a milling tool feeding on a helical path into the workpiece, and thus, both the periphery cutting edges and the bottom cutting edges all participated in the machining process. In order to investigate the characteristics of discontinuous milling resulting in the time varying undeformed chip thickness and cutting forces direction, this paper establishes a novel analytic cutting force model of the helical milling based on the helical milling principle. Dynamic cutting forces are measured and analyzed under different cutting parameters for the titanium alloy (Ti–6Al–4V). Cutting force coefficients are identified and discussed based on the experimental test. Analytical model prediction is compared with experiment testing. It is noted that the analytical results are in good agreement with the experimental data; thus, the established cutting force model can be utilized as an effective tool to predict the change of cutting forces in helical milling process under different cutting conditions.     

Milling Force Model for Aviation Aluminum Alloy:Academic Insight and Perspective Analysis

Aluminum alloy is the main structural material of aircraft,launch vehicle,spaceship,and space station and is pro-cessed by milling.However,tool wear and vibration are the bottlenecks in the milling process of aviation aluminum alloy.The machining accuracy and surface quality of aluminum alloy milling depend on the cutting parameters,material mechanical properties,machine tools,and other parameters.In particular,milling force is the crucial factor to determine material removal and workpiece surface integrity.However,establishing the prediction model of milling force is important and difficult because milling force is the result of multiparameter coupling of process system.The research progress of cutting force model is reviewed from three modeling methods:empirical model,finite element simulation,and instantaneous milling force model.The problems of cutting force modeling are also determined.In view of these problems,the future work direction is proposed in the following four aspects:(1)high-speed milling is adopted for the thin-walled structure of large aviation with large cutting depth,which easily produces high residual stress.The residual stress should be analyzed under this particular condition.(2)Multiple factors(e.g.,eccentric swing milling parameters,lubrication conditions,tools,tool and workpiece deformation,and size effect)should be consid-ered comprehensively when modeling instantaneous milling forces,especially for micro milling and complex surface machining.(3)The database of milling force model,including the corresponding workpiece materials,working condi-tion,cutting tools(geometric figures and coatings),and other parameters,should be established.(4)The effect of chatter on the prediction accuracy of milling force cannot be ignored in thin-walled workpiece milling.(5)The cutting force of aviation aluminum alloy milling under the condition of minimum quantity lubrication(mql)and nanofluid mql should be predicted.     

Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations

Optimization of cutting parameters is valuable in terms of providing high precision and efficient machining. Optimization of machining parameters for milling is an important step to minimize the machining time and cutting force, increase productivity and tool life and obtain better surface finish. In this work a mathematical model has been developed based on both the material behavior and the machine dynamics to determine cutting force for milling operations. The system used for optimization is based on powerful artificial intelligence called genetic algorithms (GA). The machining time is considered as the objective function and constraints are tool life, limits of feed rate, depth of cut, cutting speed, surface roughness, cutting force and amplitude of vibrations while maintaining a constant material removal rate. The result of the work shows how a complex optimization problem is handled by a genetic algorithm and converges very quickly. Experimental end milling tests have been performed on mild steel to measure surface roughness, cutting force using milling tool dynamometer and vibration using a FFT (fast Fourier transform) analyzer for the optimized cutting parameters in a Universal milling machine using an HSS cutter. From the estimated surface roughness value of 0.71 μm, the optimal cutting parameters that have given a maximum material removal rate of 6.0×10³ mm³/min with less amplitude of vibration at the work piece support 1.66 μm maximum displacement. The good agreement between the GA cutting forces and measured cutting forces clearly demonstrates the accuracy and effectiveness of the model presented and program developed. The obtained results indicate that the optimized parameters are capable of machining the work piece more efficiently with better surface finish.     

An In-Process Neural Network-Based Surface Roughness Prediction (INN-SRP) System Using a Dynamometer in End Milling Operations

Surface roughness is influenced by the machining parameters and other uncontrollable factors resulting from the cutting tool in end milling operations. To perform the in-process surface roughness prediction (ISRP) system accurately, the uncontrollable factors must be monitored. In this paper, an empirical approach using a statistical analysis was employed to discover the proper cutting force to represent the uncontrollable factors in end milling operations. Furthermore, an in-process neural network-based surface roughness prediction (INN-SRP) system was developed. A neural network associated with sensing technology was applied as a decision-making system to predict the surface roughness for a wide range of machining parameters. The good accuracy of the results for a wide range of machining parameters indicates that the system is suitable for application in industry. ID="A1"Correspondance and offprint requests to: Dr J. C. Chen, Department of Industrial Education and Technology, Iowa State University, 221 I. ED II, Ames, IA 50011–3130, USA. E-mail: cschen@iastate.edu     

Analysis of cutting force coefficients in high-speed ball end milling at varying rotational speeds

In high-speed ball end milling, cutting forces influence machinability, dimensional accuracy, tool failure, tool deflection, machine tool chatter, vibration, etc. Thus, an accurate prediction of cutting forces before actual machining is essential for a good insight into the process to produce good quality machined parts. In this article, an attempt has been made to determine specific cutting force coefficients in ball end milling based on a linear mechanistic model at a higher range of rotational speeds. The force coefficients have been determined based on average cutting force. Cutting force in one revolution of the cutter was recorded to avoid the cutter run-out condition (radial). Milling experiments have been conducted on aluminum alloy of grade Al2014-T6 at different spindle speeds and feeds. Thus, the dependence of specific cutting force coefficients on cutting speeds has been studied and analyzed. It is found that specific cutting force coefficients change with change in rotational speed while keeping other cutting parameters unchanged. Hence, simulated cutting forces at higher range of rotational speed might have considerable errors if specific cutting force coefficients evaluated at lower rotational speed are used. The specific cutting force coefficients obtained analytically have been validated through experiments.     

铣削力预测研究进展

从切削几何条件不变的平直面加工和切削几何条件可变的曲面加工两个方面综述了当前铣削力预测方面的研究成果。指出研究复杂曲面加工的铣削力预测,尤其是非球头铣刀复杂曲面五轴加工的铣削力预测是本领域的重要发展方向。     

Mill-cut: a neural network system for the prediction of thermo-mechanical loads induced in end-milling operations

This paper presents the design and implementation issues of a generalized system called mill-cut, developed for the prediction of cutting forces and temperature in end-milling operations. Based on an ANN approach, mill-cut predicts all the three components of cutting forces and average shear plane temperature for a given set of machining parameters broadly categorized into three groups viz. (i) cutting tool geometrical parameters (ii) cutting parameters and (iii) workpiece material properties. In the present work, for representing overall machining condition, 15 machining parameters having major impact on the cutting forces and cutting temperature were chosen. The feed-forward back-propagated ANN architecture has been incorporated, which was initially trained with analytical data before incorporating it as part of an integrated system. Results obtained from the proposed model show good agreement with the experimental/numerical (FEM based) results available in the literature.     

一种新的螺旋刃球头铣刀铣削力模型

为提高铣削加工的安全性和生产效率，有必要在加工实际进行之前准确地预测切削过程的物理信息，如铣削力、刀具振动等。给出了球头铣刀丸线几何模型，采用理论削力分析与实验--系数识别相结合的方法建立了新的螺旋刃球头铣刀的铣削力模型。对不同切削条件下的铣削力进行了仿真，与实验测量数据吻合良好，证明离线仿真可以对铣削力做出较准确的预测。