并联机床的发展现状与展望

论述并联机床的发展现状及与传统机床的区别。在对国内外典型并联机床样机的工作原理分析的基础上，指出目前并联机床研究中所面临的主要问题，并对并联机床的研究发展方向进行了展望。

基于测量数据反演并联机床非线性位姿误差模型

利用最小二乘技术识别模型参数 ,将非线性问题作线性化处理 ,提出了一种基于测量数据反演非线性误差模型的建模方法。结合算例 ,指出了此类模型设计应注意的问题。五轴并联机床约束机构误差模型仿真结果表明 ,由此得到的误差模型精度高。利用所得模型对机床位姿进行补偿 ,即可提高机床沿该位姿方向的定位精度

基于四自由度并联机构的数控机床研究

介绍一种基于混合型四自由度并联平台机构开发的五坐标并联机床 .由于其独特的机构设计 ,与基于 Stewart平台的并联机床相比 ,X方向的进给运动与运动平台分离 ,改由工作台单独进给 ,因而其工作空间成倍增大 .采用龙门框架结构和滚珠丝杠支承方案使机床获得更高的刚度 .给出了该机床运动学逆解 ,控制系统采用基于 PC的数控系统进行五轴联动控制

一种并联机床运动平台位姿测量方法

提出一种采用附加测量机构直接测量并联机床运动平台位姿精度的方法。其基本思想是根据运动平台的运动特性在固定平台和运动平台之间增设附加测量机构，当运动平台运动时带动测量机构运动，通过安装在测量机构上的传感器测得广义坐标参量， 经运动学建模即可得到运动平台的位姿。当测量机构位姿正解求解速度满足实时控制要求时，利用该反馈信息对机床进行实时精度补偿和控制。基于上述思想建立的并联机床位姿测量系统可部分排除机床切削力变形和运动副间隙等误差， 从而提高机床的位姿测量精度。以一种五坐标并联机床为例，介绍采用附加测量机构直接测量运动平台位姿精度的建模方法。其中， 测量机构的综合十分重要。测量机构的组成决定了运动学模型的复杂程度， 即决定了运动学模型的计算效率。

并联机器人机床运动学正、逆解

基于一般ＳＴＥＷＡＲＴ机构研制的并联机器人机床是新一代智能化金属切削加工机床．然而，机床的运动学位置正、逆解呈强非线性，求解困难．出于机床精度的需要，本研究的模型样机在结构上采用了滚珠丝杠传动，因此又带来了关节运动耦合，导致机床运动学位置正、逆解求解更加复杂．利用运动学等效的原则，引入整机等效串联机构及分支等效串联机构，以等效广义坐标为中间变量建立机床运动学正、逆解求解迭代算法．仿真与控制实验表明，该算法具有收索速度快便于实际应用等特点。

可重构车间管理系统的关键设计技术研究

介绍了一个基于组件的可重构车间管理系统,分别从建模方法、体系结构和组件设计等角度描述了系统的设计思想,并阐述了系统涉及的组件分类、组件粒度划分及XML的应用等关键设计技术。开发的可重构车间管理系统已经用于沈阳第一机床厂两个不同类型生产车间的管理,应用效果良好。

成批生产计划调度的集成建模与优化

针对多品种批量生产类型,建立了调度约束的生产计划与调度集成优化模型。模型的目标函数是使总调整费用、库存费用及生产费用之和最小,约束函数包括库存平衡约束和生产能力约束,同时考虑了调度约束,即工序顺序约束和工件在单机上的加工能力约束,保证了计划可行性。该模型为两层混合整数规划模型,对其求解综合运用了遗传算法和启发式规则,提出了混合启发式求解算法。最后,针对某机床厂多品种批量生产类型车间进行了实例应用,对车间零件月份作业计划进行分解,得到各工段单元零件周作业计划,确定了零件各周生产批量与投产顺序。

Enabling ultra high precision on hard steels using surface defect machining

This paper is an extension to an idea coined during the 13th EUSPEN Conference (P6.23) named "surface defect machining" (SDM). The objective of this work was to demonstrate how a conventional CNC turret lathe can be used to obtain ultra high precision machined surface finish on hard steels without recourse to a sophisticated ultra precision machine tool. An AISI 4340 hard steel (69 HRC) workpiece was machined using a CBN cutting tool with and without SDM. Post-machining measurements by a Form Talysurf and a Scanning Electron Microscope (FEI Quanta 3D) revealed that SDM culminates to several key advantages (i) provides better quality of the machined surface integrity and offers (ii) lowering feed rate to 5μm/rev to obtain a machined surface roughness of 30 nm (optical quality).

Molecular dynamics simulation (MDS) to study nanoscale machining processes

Molecular Dynamics Simulations (MDS) are constantly being used to make important contributions to our fundamental understanding of material behaviour, at the atomic scale, for a variety of thermodynamic processes. This chapter shows that molecular dynamics simulation is a robust numerical analysis tool in addressing a range of complex nanofinishing (machining) problems that are otherwise difficult or impossible to understand using other methods. For example the mechanism of nanometric cutting of silicon carbide is influenced by a number of variables such as machine tool performance, machining conditions, material properties, and cutting tool performance (material microstructure and physical geometry of the contact) and all these variables cannot be monitored online through experimental examination. However, these could suitably be studied using an advanced simulation based approach such as MDS. This chapter details how MD simulation can be used as a research and commercial tool to understand key issues of ultra precision manufacturing research problems and a specific case was addressed by studying diamond machining of silicon carbide. While this is appreciable, there are a lot of challenges and opportunities in this fertile area. For example, the world of MD simulations is dependent on present day computers and the accuracy and reliability of potential energy functions [109]. This presents a limitation: Real-world scale simulation models are yet to be developed. The simulated length and timescales are far shorter than the experimental ones which couples further with the fact that contact loading simulations are typically done in the speed range of a few hundreds of m/sec against the experimental speed of typically about 1 m/sec [17]. Consequently, MD simulations suffer from the spurious effects of high cutting speeds and the accuracy of the simulation results has yet to be fully explored. The development of user-friendly software could help facilitate molecular dynamics as an integral part of computer-aided design and manufacturing to tackle a range of machining problems from all perspectives, including materials science (phase of the material formed due to the sub-surface deformation layer), electronics and optics (properties of the finished machined surface due to the metallurgical transformation in comparison to the bulk material), and mechanical engineering (extent of residual stresses in the machined component) [110]. Overall, this chapter provided key information concerning diamond machining of SiC which is classed as hard, brittle material. From the analysis presented in the earlier sections, MD simulation has helped in understanding the effects of crystal anisotropy in nanometric cutting of 3C-SiC by revealing the atomic-level deformation mechanisms for different crystal orientations and cutting directions. In addition to this, the MD simulation revealed that the material removal mechanism on the (111) surface of 3C-SiC (akin to diamond) is dominated by cleavage. These understandings led to the development of a new approach named the “surface defect machining” method which has the potential to be more effective to implement than ductile mode micro laser assisted machining or conventional nanometric cutting.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine's capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine's potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

Monitoring in precision metal drilling process using multi-sensors and neural network

This paper presents a new method to estimate hole diameters and surface roughness in precision drilling processes, using coupons taken from a sandwich plate composed of a titanium alloy plate (Ti6Al4V) glued onto an aluminum alloy plate (AA 2024T3). The proposed method uses signals acquired during the cutting process by a multisensor system installed on the machine tool. These signals are mathematically treated and then used as input for an artificial neural network. After training, the neural network system is qualified to estimate the surface roughness and hole diameter based on the signals and cutting process parameters. To evaluate the system, the estimated data were compared with experimental measurements and the errors were calculated. The results proved the efficiency of the proposed method, which yielded very low or even negligible errors of the tolerances used in most industrial drilling processes. This pioneering method opens up a new field of research, showing a promising potential for development and application as an alternative monitoring method for drilling processes. © 2012 Springer-Verlag London Limited.

Estimação do diâmetro e rugosidade em um processo de furação utilizando multi sensores e redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo da predição da circularidade e rugosidade de peças retificadas utilizando as redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise da influência da rigidez do sistema nos erros dimensionais e geométricos no processo de torneamento

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)