METHOD FOR SUPPRESSING CUTTING CHATTER IN NUMERICAL CONTROL MACHINE TOOLS

A new method for suppressing cutting chatter is studied by adjusting servo parameters of the numerical control （NC） machine tool and controlling the limited cutting width. A model of the cutting system of the NC machine tool is established. It includes the mechanical system, the servo system and the cutting chatter system. Interactions between every two systems are shown in the model. The cutting system stability is simulated and relation curves between the limited cutting width and servo system parameters are described in the experiment. Simulation and experimental results show that there is a mapping relation between the limited cutting width and servo parameters of the NC machine tool, and the method is applicable and credible to suppress chatter.

Bayesian networks modeling for thermal error of numerical control machine tools

The interaction between the heat source location, its intensity, thermal expansion coefficient, the machine system configuration and the running environment creates complex thermal behavior of a machine tool, and also makes thermal error prediction difficult. To address this issue, a novel prediction method for machine tool thermal error based on Bayesian networks (BNs) was presented. The method described causal relationships of factors inducing thermal deformation by graph theory and estimated the thermal error by Bayesian statistical techniques. Due to the effective combination of domain knowledge and sampled data, the BN method could adapt to the change of running state of machine, and obtain satisfactory prediction accuracy. Ex- periments on spindle thermal deformation were conducted to evaluate the modeling performance. Experimental results indicate that the BN method performs far better than the least squares (LS) analysis in terms of modeling estimation accuracy.

Bayesian zero-failure reliability modeling and assessment method for multiple numerical control(NC) machine tools

A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.

Real-Time Data and Visualization Monitoring of Computer Numerical Control Machine Tools Based on Hyper Text Markup Language 5

In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML)5 is proposed.The characteristics of the real-time monitoring technology of CNC machine tools under the traditional Client/Server(C/S)structure are compared and analyzed,and the technical drawbacks are proposed.Web real-time communication technology and browser drawing technology are deeply studied.A real-time monitoring and visible system for CNC machine tool data is developed based on Metro platform,combining WebSocket real-time communication technology and Canvas drawing technology.The system architecture is given,and the functions and implementation methods of the system are described in detail.The practical application results show that the WebSocket real-time communication technology can effectively reduce the bandwidth and network delay and save server resources.The numerical control machine data monitoring system can intuitively reflect the machine data,and the visible effect is good.It realizes timely monitoring of equipment alarms and prompts maintenance and management personnel.

Carbon Emission Modeling and Analysis in Manufacturing Process for Numerical Control Machine Tools

Reducing carbon emissions( CEs) is the urgent demand all over the world. In order to realize the low-carbon numerical control( NC) machining, the evaluation model of a part's manufacturing carbon emission with NC machine tools was built by considering the influences of the cutting tool geometrical parameters.The manufacturing CEs were produced by electric power,cutting tools,and cutting fluid consumed in manufacturing process. The parameters of cutting tools affected not only the CEs,but also the machining quality. Then the actual constraint models of the machine performance,machining quality were given in order to optimize the cutting parameters and achieve the low-CEs. Finally,a case was given to analyze the influences of the cutting tool angles on the manufacturing CEs. The results show that the CEs decrease as the rake angle and edge angle increase under the constraints of the machine specifications and machining quality.

Toward Intelligent Machine Tool

With the development of modern information technology-and particularly of the new generation of artificial intelligence(AI)technology-new opportunities are available for the development of the intelligent machine tool(IMT).Based on the three classical paradigms of intelligent manufacturing as defined by the Chinese Academy of Engineering,the concept,characteristics,and systemic structure of the IMT are presented in this paper.Three stages of machine tool evolution-from the manually operated machine tool(MOMT)to the IMT-are discussed,including the numerical control machine tool(NCMT),the smart machine tool(SMT),and the IMT.Furthermore,the four intelligent control principles of the IMT-namely,autonomous sensing and connection,autonomous learning and modeling,autonomous optimization and decision-making,and autonomous control and execution-are presented in detail.This paper then points out that the essential characteristic of the IMT is to acquire and accumulate knowledge through learning,and presents original key enabling technologies,including the instruction-domain-based analytical approach,theoretical and big-data-based hybrid modeling technology,and the double-code control method.Based on this research,an intelligent numerical control(INC)system and industrial prototypes of IMTs are developed.Three intelligent practices are conducted,demonstrating that the integration of the new generation of AI technology with advanced manufacturing technology is a feasible and convenient way to advance machine tools toward the IMT.

CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach

Building cyber-physical system(CPS) models of machine tools is a key technology for intelligent manufacturing. The massive electronic data from a computer numerical control(CNC) system during the work processes of a CNC machine tool is the main source of the big data on which a CPS model is established. In this work-process model, a method based on instruction domain is applied to analyze the electronic big data, and a quantitative description of the numerical control(NC) processes is built according to the G code of the processes. Utilizing the instruction domain, a work-process CPS model is established on the basis of the accurate, real-time mapping of the manufacturing tasks, resources, and status of the CNC machine tool. Using such models, case studies are conducted on intelligent-machining applications, such as the optimization of NC processing parameters and the health assurance of CNC machine tools.

Studies of layout of world machine tools industry based on patent analysis

As the foundation of an industrialized country nowadays,machine tools industry is regarded as the engine of industrial development of a country.The developed countries,such as USA,Germany and Japan,have widely deployed the technology of using the patent in order to keep their strength in various fields.This research examins the CNC machine tools industry in the world by using the patent analysis method.It first gives an overview about the world patent application in CNC machine tools industry from 1963 to 2010 and divides the development of the industry into five stages.It also lists the patent application of the world top 20 countries,where the top 5 countries are compared.The patents of the world top 10 companies of machine tools manufacturers are mapped according to the international patent classification(IPC),and the future trends of world machine tools industry are discussed.Finally conclusions and suggestions are presented.

Patterns of CNC Machine Tool Reference Return and Its Trouble Shooting Methods

This paper presents four patterns of reference-return positions for CNC machine tools and analyses some causes of return reference troubles by showing typical examples of trouble shooting.Finally,it introduces several methods of trouble shooting.

STUDY ON THE FEEDFORWARD COMPENSATION OF THE MOTIONERRORS OF NC MACHINE TOOLS

A feedforward compensation naethod of the motion errors of NC machine tools imple- mented with software is proposed , with which the motion errors can be compensated whithout changing the original computer control systems of the NC machine tools. The experimental results show that the circular interpolation profile machining errors decrease by a factor of 2/3 after com- pensated.

数控机床液压系统分析与装配工艺实践

研究机床液压系统的工作原理、完善液压元件的安装工艺是机床生产和使用单位从装配细节着手提高机床稳定性等综合性能的有效途径。文章以某知名国产品牌数控车床的液压系统为研究对象,分析了该产品液压系统的组成及控制回路的工作原理,并对液压元件通用装配工艺做出了详细的规范性技术要求。通过在机床生产与维修中的实践证明,此技术规范可提高机床装配质量和综合性能的稳定性,可为机床技术从业人员掌握机床液压系统的基本知识提供一定的参考,对正确安装、调试、使用、维护和维修机床有着重要的指导意义。

某超长条结构件柔性工装平台结构设计与实现

针对某超长条结构件加工过程中由于使用传统工装夹具造成的工艺准备时间长、工装数量多、材料浪费严重等问题,开展一种柔性工装平台的研究。该工装平台采用多个可旋转夹臂替代传统夹具进行夹持,在工件外形变化时,可通过更换夹臂长度、按压角度等保持良好夹持效果,满足柔性工装的需求。对该工装平台结构进行设计,对关键参数进行建模和校核,通过样机对工装效果进行验证。结果表明,该工装平台在加工相同工件的情况下,可节省约3%的零件材料,缩短310 min工艺准备时间,同时由于该工装平台采用了新型柔性固持方案,还提高了加工连续性,避免由于工艺变化造成大量的夹具浪费,为超长条结构件的加工提供了一种新的工装固持方案。

复杂曲面零件的五轴数控加工技术研究

随着科技水平的不断提升,精密复杂曲面零件的应用越来越广泛。曲面驱动是复杂曲面零件加工的重要方法,驱动刀轨的规划直接关系到曲面物理特性的调控,应用五轴数控加工技术能够提升复杂曲面零件的加工质量。文章主要研究复杂曲面零件的五轴数控加工技术,以佛像这个复杂曲面零件为例,分析了曲面驱动刀轨规划、工装方案设计、加工策略以及试制加工过程。在实际加工过程中,技术人员应充分理解驱动刀轨规划思路与原理,在粗加工、精加工中完善刀轨设计,并进行试制加工。

薄壁零件数控加工质量的提升策略

薄壁零件在机械制造中的应用越来越广泛,但其加工难度较大。提升薄壁零件的数控加工精度,可以改善零件质量,提高生产率,降低费用,进而推动先进设备制造业的发展。文章分析影响薄壁零件数控加工质量的因素,包括加工工艺、外部荷载、温度系数及刀具等,并提出提高加工质量的措施,如合理选用刀具、选择合理的切削用量和技术方案、保证尺寸的精度以及适当延长切削时间等。

基于数控工艺信息挖掘的型腔特征粗加工刀具序列优化决策方法

为有效提升数控加工过程中粗加工刀具的使用效率,提出一种基于数控工艺信息挖掘的型腔特征粗加工刀具序列优化决策方法。首先计算型腔特征的中轴变换表征数控加工的刀具轨迹,探究中轴变换与数控加工的映射机理;然后基于加工规则和中轴变换参数,挖掘隐含在型腔特征中的深层次数控工艺信息;最后综合考虑材料去除量和加工连续性,建立刀具序列决策的多目标优化模型,采用混合蚁群/模拟退火算法进行优化求解。实验结果表明,该方法能够高效、自动生成型腔特征最优粗加工刀具序列,提升企业数控工艺设计智能化水平。

数控机床几何误差单轴五次测量与辨识方法

针对数控机床几何误差项的准确测量与辨识问题,提出了一种基于激光干涉仪的机床空间几何误差单轴五次测量与辨识方法。首先,针对X、Y、Z轴分别设置了一条测量线,测量了3条划定线上除滚转误差外的其他15项几何误差,共计15次测量;然后,分析了转角误差对直线度误差以及直线度误差对定位误差的耦合影响,并建立了误差辨识方程组;最后,根据误差辨识方程组,得到了机床21项几何误差;并进行了单轴五次测量法的测量和辨识实验,并将所得结果与空间九线法测量辨识结果进行了对比分析。研究结果表明:单轴五次测量法与空间九线法测量辨识结果的空间误差向量最大偏差为1.93μm,平均偏差为0.58μm,该结果验证了单轴五次测量法是准确和有效的。该方法考虑了实际测量过程中的误差耦合情况,因此相比于空间九线法,该方法减少了测量线数与测量次数,简化了误差项的求解过程;同时,采用单轴运动方式可以有效避免其他轴对当前运动轴误差的影响。

数控机床伺服驱动系统的多电机同步控制策略

以数控机床伺服驱动系统的多电机同步控制为研究对象,提出了一种基于多交流伺服电机的同步控制策略。此策略将虚拟主轴和偏差耦合的同步控制方式相结合,并加入反向传播神经网络比例积分微分控制以及自适应鲁棒控制。通过搭建Matlab/Simulink仿真平台模拟了系统的运行状态。结果表明,所提同步控制策略具有良好的同步性能和伺服效果,在提高多电机联动系统的控制精度和响应速度、减少摩擦和齿隙的影响以及增强系统鲁棒性方面表现出优越性。

基于三维扫描技术的高精度数控加工工艺研究

为研究基于三维扫描技术的高精度数控加工工艺,对工件进行三维扫描,获取精确几何模型,结合数控加工技术,实现了工件的高精度加工。阐述了三维扫描技术与数控加工工艺原理、应用现状及关键技术,分析了三维扫描数据处理、刀具路径规划、刀具磨损补偿等环节的策略和方法,通过加工仿真和实验验证,优化了加工工艺参数,在发动机缸盖加工案例中证明了该工艺的可行性和有效性。结果表明,基于三维扫描的数控加工工艺能显著提高复杂零件的加工精度、表面质量和生产效率,具有广阔的应用前景。

关于不规则零件的数控机床加工工艺分析

与传统的机械加工手段相比,数控机床具备更高的加工精度、更快的生产速度和更广的适用范围。特别是在加工复杂、高精度、小批量或者形态不规则的零件时,数控机床显现出其无与伦比的优势。不规则零件的数控机床加工工艺不仅关乎数控编程技巧,还涉及刀具选择、切削参数设定、工艺路线规划等多方面的内容。对于每一种不规则零件,都需要进行深入的分析,制定最合适的数控加工策略,确保其在生产线上的高效、稳定。

基于ResNet多特征图融合的钻削表面粗糙度分类方法

传统五面复合数控(CNC)钻削表面粗糙度测量工作复杂,采用人工测量存在较大人为误差。传统多元回归、多项式拟合方法仅采用转速和进给速度参数,数据利用率低且噪声敏感性强;用传统机器学习方法无法有效提取信号的深层复杂特征。针对上述问题,提出了一种基于ResNet模型、频谱图特征与时频图特征融合的钻削表面粗糙度分类预测方法。首先,根据CNC钻削加工理论和企业实际CNC钻削经验确定了CNC钻削加工实验的工艺参数变量;然后,基于SYNTEC CNC系统开发了多源数据采集系统,实时采集了钻削加工过程数据;接着,分析了三轴振动信号的频谱特征和时频特征,验证了振动信号跟表面粗糙度类别的关联性;随后,采用卡尔曼滤波对三轴振动信号进行了降噪处理,采用快速傅里叶变换(FFT)和连续小波变换(CWT)进行了振动信号频谱热图与时频图转换,采用矩阵拼接对三轴振动信号的单轴时频图进行了拼接融合,得到了三轴振动时频图;最后,对频谱热图和时频图进行了卷积运算融合频谱特征与时频特征,并进行了ResNet和其他网络模型如Densenet、Shufflenet和Mobilenet_v3_small等的对比实验。研究结果表明:相对上述其他网络模型,基于ResNet网络模型的表面粗糙度分类正确率提高了约9%,同时也验证了三轴时频特征融合以及频谱特征和时频特征融合方法的正确性。由于模型训练成本低、训练收敛速度快,该方法在轻量级、低成本的CNC机床钻削表面粗糙度预测分类中具有良好的工业应用前景。