Computer-aided accuracy enhancement for multi-axis CNC machine tool

A computer-aided error compensation scheme has been developed to enhance the accuracy of multi-axis CNC machine tools by compensating for machine geometric and thermal errors in software way. Stationary geometric errors including the coupling effect of linkage errors between machine slides are calibrated off line. Dynamic thermal errors are predicted on line by an artificial neural network model. Because machine errors are variant with the cutting time and slide positions, a PC based compensation controller has been developed to upgrade commercial CNC controllers for real-time error compensation. The real-time compensation capability is achieved by digital I/0 communication between the compensation controller and CNC controller without the need of any hardware modification to the machine servo-drive loops. The compensation scheme implemented on a horizontal machining center has been proven to improve the machine accuracy by one order of magnitude using a laser interferometer and cutting test.     

基于BP神经网络的磨床力误差补偿方法

为建立磨削加工参数与磨削力导致的力变形误差之间的关系模型,提出基于神经网络的力误差建模和实时补偿方法.建立经遗传算法优化的BP神经网络以表征磨削参数与磨削力的关系;运用有限元方法对零件进行力学分析,建立磨削力与力变形量的关系模型;建立加工参数与切削力误差映射模型,预测误差补偿量,进行实时补偿.实验结果表明:该切削力误差...     

Geometric and force errors compensation in a 3-axis CNC milling machine

This paper proposes a new off line error compensation model by taking into accounting of geometric and cutting force induced errors in a 3-axis CNC milling machine. Geometric error of a 3-axis milling machine composes of 21 components, which can be measured by laser interferometer within the working volume. Geometric error estimation determined by back-propagation neural network is proposed and used separately in the geometric error compensation model. Likewise, cutting force induced error estimation by back-propagation neural network determined based on a flat end mill behavior observation is proposed and used separately in the cutting force induced error compensation model. Various experiments over a wide range of cutting conditions are carried out to investigate cutting force and machine error relation. Finally, the combination of geometric and cutting force induced errors is modeled by the combined back-propagation neural network. This unique model is used to compensate both geometric and cutting force induced errors simultaneously by a single model. Experimental tests have been carried out in order to validate the performance of geometric and cutting force induced errors compensation model.     

Position error compensation of robotic contour end-milling

Three-dimensional cutting force dynamics of end-milling is developed, and position error sources of robotic machining is studied. A strategy to compensate cutting force in force/motion control of robotic machining is established in order to achieve better positioning accuracy. Position error is analysed in the cutting process through reference points by using force sensor. The tip position error estimated with the aid of wrist-force sensor is compensated in feedforward control form. The quantitative results are obtained from the digital computer simulations of the dynamic model of the studied system.     

A grey prediction fuzzy controller for 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 non-linear 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. To solve this problem, a grey-theory algorithm was introduced into the TFC to predict the next output error of the system and the error change, rather than the current output error of the system and the current error change, as input variables of the TFC. This design of the grey prediction fuzzy controller (GPFC) cannot only simplify the TFC design, but also achieves the desired result in TFC implementation. 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 GPFC has better control performance in constant cutting force control than does the TFC, as verified in experimental results.     

Adaptive cutting force control for a machining center by using indirect cutting force measurements

This paper presents an adaptive cutting force controller for the milling process, which can be attached to most commercial CNC machining centers in a practical way. The cutting forces of x, y and z axes are measured indirectly from the use of currents drawn by a.c. feed-drive servo motors. A typical model for the feed-drive control system of a horizontal machining center is developed to analyze cutting force measurement from the drive motor. The pulsating milling forces can be measured indirectly within the bandwidth of the current feedback control loop of the feed-drive system. It is shown that indirectly measured cutting force signals can be used in the adaptive controller for cutting force regulation. The robust controller structure is adopted in the whole adaptive control scheme. The conditions under which the whole scheme is globally convergent and stable are presented. The suggested control scheme has been implemented into a commercial machining center, and a cutting experiment on face milling process is performed.     

Integrated real time compensation system for errors introduced by measurement probe and machine geometry in commercial CMMs

In this paper, an integrated real time compensation system has been proposed for the errors introduced by the probe and machine geometry in commercial CMMS. For efficient probe error mapping, a compact notation (ε, θ) for probing direction and corresponding concentric diagram is proposed. A set of integrated volumetric error equations are also proposed for the volumetric error map integrating the probe error and the machine geometric error. For the real time error compensation scheme, an interface box and an appropriate software driver have been designed and implemented between the CMM and machine controller. The data flow is intercepted and corrected according to the integrated volumetric error map without the controller being noticed. Thus the real time error compensation system has been successfully implemented for the machine with minimum interference to the existing coordinate measurement system. The developed system has been applied to a commercial CMM on the shop floor, and the measurement accuracy has been improved remarkably.     

Tracking control and active disturbance rejection with application to noncircular machining

Control systems are usually required to track reference signals while operating under the influence of disturbances. A fast tool servo system for noncircular machining application works under such conditions, resulting in large control efforts. This paper presents a linear active disturbance rejection controller design for a voice coil motor-driven fast tool servo system for noncircular machining application. The controller is designed through an extended state observer to estimate and compensate the variant dynamics of the system, nonlinearly variable cutting load, and other uncertainties. Then, a simple proportional derivative controller produces the control law. To improve the tracking performance of the fast tool servo, the tracking error from the trial-cutting workpiece is added to the reference input and used as feed-forward error compensation. In such a combined control arrangement, the active disturbance rejection controller provides active disturbance rejection ability for the controller, and the feed-forward error compensation controller improves the tracking precision. Both the tracking control and disturbance rejection performances are thus enhanced. In real-time control and implementation, the effects of finite word length, position feedback resolution, and short sampling period are analyzed and addressed. Machining experiments are conducted, and the results illustrate the control system synthesis procedures and a substantial improvement over the tracking error generated by the linear active disturbance rejection controller alone.     

Deformation prediction and error compensation in multilayer milling processes for thin-walled parts

Deformation prediction and error compensation are effective approaches to improve machining accuracy in milling thin-walled parts. In this paper, it is considered that the machining deformation of the previous layer will influence the nominal cutting depth of the current layer. Therefore, a dynamical model is established to predict the deformation in multilayer machining a thin-walled part. The coupling relation between cutting force and machining deformation is taken into account using iterative computation. The dynamical model is validated by comparing the simulation result with the experimental one. A new approach of active error compensation is proposed, in which the machining error is compensated at each layer. By comparing the simulation results of compensation at the last layer with the results of compensation at per-layer, a conclusion is drawn that compensation at per-layer makes smaller machining errors and the errors are more uniform.     

数控机床直线电机进给伺服驱动的摩擦力和扰动抑制措施

针对永磁直线同步伺服电机(PMLSM)直接驱动数控机床伺服系统,提出了一种基于摩擦力和扰动补偿的零相位误差跟踪控制策略.以解决摩擦力和扰动对系统性能的影响.零相位误差跟踪控制器保证了快速性,使系统实现准确跟踪;而补偿制器克服了摩擦和扰动等不确定性影响,保证了系统具有较强的鲁棒性和定位精度.仿真结果表明,该种控制方案较好地改善数控机床进给的定位精度和跟踪性能.     

Development of a virtual machining system, part 3: cutting process simulation in transient cuts

In Parts 1 and 2 of this three-part paper, a mechanistic cutting force model was developed and machined surface errors for steady cuts under fixed cutting conditions were predicted. The virtual machining system aims to simulate and analyze the machining and the machined states in a general flat end-milling process. This frequently involves transient as well as steady cuts. Therefore, a method for simulating the cutting process of transient cuts needs to be developed to realize the virtual machining system concept. For this purpose, this paper presents a moving edge-node (ME) Z-map model for the cutting configuration calculation. The simulation results of four representative transient cuts in two-dimensional pocket milling and an application of off-line feed-rate scheduling are also given.

In transient cuts, the cutting configurations that are used to predict the cutting force vary during the machining operation. The cutting force model (Part 1) and surface error prediction method (Part 2) were developed for steady cuts; these are extended to transient situations using the ME Z-map model to calculate the varying cutting configurations efficiently. The cutting force and surface errors are then predicted. To validate the feasibility of the proposed scheme, the measured and predicted cutting forces for transient test cuts were compared. The predicted surface error maps for transient cuts were constructed using a computer simulation. Also, off-line feed-rate scheduling is shown to be more accurately performed by applying the instantaneous cutting coefficients that were defined in Part I.     

Real time monitoring and diagnosis system development in turning through measuring a roundness error based on three-point method

A real time monitoring and diagnosis system to measure spindle center displacement (roundness error) during turning operation is introduced in this paper. The system was developed based on the three-point method. The error generated during cutting process was monitored and diagnosed by using a system equipped with a designed DSP (Digital Signal Processor) board and FFT (Fast Fourier Transform) algorithm. The system could estimate cutting force and predict other cutting characteristics such as chattering and tool wear. Using the spindle center fluctuation, i.e. a roundness error movement from the center, the relationship between the cutting force and the roundness error could also be investigated. The roundness error that eliminated geometric shape error and eccentric error from the measured signals in the frequency domain proved to be a dominating factor in determining cutting characteristics.     

融合光纤感知的气动执行器夹持力控制策略研究

为了降低气动执行器夹持力/气压迟滞的影响,提高夹持力跟踪控制精度,提出一种基于Prandtl-Ishlinskii （P-I） 逆模型的前馈补偿结合模糊PID的控制策略。分析气动执行器的夹持力/气压迟滞特性,通过初载曲线法辨识迟滞模型参数,建立P-I逆模型;设计融合FBG力感知的模糊PID控制算法,基于自制的FBG传感器实现夹持力反馈,通过标定实验验证传感器的静态特性。在Simulink中构建前馈补偿和融合FBG力感知的模糊PID相结合的复合控制器,完成与传统PID以及模糊PID控制器的夹持力控制仿真对比。仿真结果显示：前馈补偿可以降低稳态误差,提高控制精度。最后,在气动执行器夹持力控实验平台上开展动态跟踪实验,验证了所设计复合控制器的有效性。     

Indirect cutting force measurement in multi-axis simultaneous NC milling processes

There have been many research works for the indirect cutting force measurement in machining process, which deal with the case of one-axis cutting process. In multi-axis cutting process, the main difficulties to estimate the cutting forces occur when the feed direction is reversed. This paper presents the indirect cutting force measurement method in contour NC milling processes by using current signals of servo motors. A Kalman filter disturbance observer and an artificial neural network (ANN) system are suggested. A Kalman filter disturbance observer is implemented by using the dynamic model of the feed drive servo system, and each of the external load torques to the x and y-axis servo motors of a horizontal machining center is estimated. An ANN system is also implemented with a training set of experimental cutting data to measure cutting force indirectly. The input variables of the ANN system are the motor currents and the feedrates of x and y-axis servo motors, and output variable is the cutting force of each axis. A series of experimental works on the circular interpolated contour milling process with the path of a complete circle has been performed. It is concluded that by comparing the Kalman filter disturbance observer and the ANN system with a dynamometer measuring cutting force directly, the ANN system has a better performance.     

神经网络PID控制的液压驱动主动升沉补偿预测控制研究

为了提高船舶在海面上作业时补偿精度,采用BP神经网络PID控制方法,并对船舶升沉运动输出误差进行仿真。建立船舶主动升沉补偿系统简图,分析船舶升沉运动工作原理,给出液压缸驱动传递函数。引用BP神经网络算法,采用梯度下降法对BP神经网络加权值进行修正,通过学习速率来补偿控制系统输出误差,从而实现PID控制器参数在线调节。在受到不同负载影响状况下,采用MATLAB软件对船舶升沉运动补偿精度进行仿真,并且与PID控制补偿精度进行对比。结果表明:采用PID控制器,船舶升沉运动输出误差较大,控制系统反应速度较慢;而采用BP神经网络PID控制器,船舶升沉运动输出误差较小,控制系统反应速度较快,同时,随着负载质量的增加,输出误差就会增大。采用BP神经网络PID控制系统,响应速度快,补偿精度高,提高了船舶在海面上作业定位精度。     

An advanced FEA based force induced error compensation strategy in milling

The study introduces a multi-level machining error compensation approach focused on force-induced errors in machining of thin-wall structures. The prediction algorithm takes into account the deflection of the part in different points of the tool path. The machining conditions are modified at each step when the cutting force and deflection achieve a local equilibrium. The machining errors are predicted using a theoretical flexible force-deflection model. The error compensation is based on optimising the tool path taking into account the predicted milling error. The error compensation scheme is simulated using NC simulation package and is experimentally verified.     

基于ARM_Linux的数控机床热误差补偿控制器的设计

以减小机床热误差,提高加工精度为主要目标,设计以S3C2440A处理器与嵌入式Linux操作系统为控制平台,运用BP神经网络建立误差模型的热误差补偿控制器。首先,控制器通过布置在机床关键温度点上的温度传感器采集加工中心的温度信号,该信号经温度采集模块处理后送到CPU处理器计算出温度值。同时,用激光干涉仪检测出机床对应时刻的误差值。BP神经网络模型根据温度值与误差值计算出综合误差补偿值。然后,将计算出的补偿值通过接口传送给CNC控制中心,CNC控制中心做出误差控制指令,修正机床热变形造成的被加工工件的尺寸误差。仿真实验结果表明了补偿效果的可行性。     

移动机器人神经网络补偿计算力矩控制

针对存在动力学不确定建模项、建模误差及外界干扰的移动机器人,设计RBF神经网络补偿计算力矩控制算法。基于反步法设计运动学辅助速度控制率。根据动力学理想名义模型,基于计算力矩法设计一般的力矩控制器。在此基础上,建立具有不确定建模项、建模误差及外界干扰的移动机器人动力学模型,基于计算力矩法设计带有RBF神经网络补偿的力矩控制器,神经网络的权值由自适应律给出。最后,利用Lyapunov理论证明了系统的稳定性。仿真结果表明：神经网络对系统不确定项具有良好的逼近性能,相比于一般的计算力矩控制,所提出的神经网络补偿计算力矩控制算法具有更好的跟踪性能,控制系统具有更好的鲁棒性。     

Intelligent adaptive control and monitoring of band sawing using a neural-fuzzy system

In bandsaw machines, it is desired to feed the bandsaw blade into the workpiece with an appropriate feeding force in order to perform an efficient cutting operation. This can be accomplished by controlling the feed rate and thrust force by accurately detecting the cutting resistance against the bandsaw blade during cutting operation. In this study, a neural-fuzzy-based force model for controlling band sawing process was established. Cutting parameters were continuously updated by a secondary neural network, to compensate the effect of environmental disturbances. Required feed rate and cutting speed were adjusted by developed fuzzy logic controller. Results of cutting experiments using several steel specimens show that the developed neural-fuzzy system performs well in real time in controlling cutting speed and feed rate during band sawing. A material identification system was developed by using the measured cutting forces. Materials were identified at the beginning of the cutting operation and cutting force model was updated by using the detected material type. Consequently, cutting speed and feed rate were adjusted by using the updated model. The new methodology is found to be easily integrable to existing production systems.     

Implementation of pole placement adaptive controller for force control of non-minimum phase end milling operations

The design and implementation of a pole placement adaptive controller are discussed for force control of the end milling process. The end milling process considered is a non-minimum phase system whose computational delay exceeds one half of the control interval. The internal model principle is included in the controller design to ensure a zero steady-state tracking error. Experimental results show that the pole placement adaptive controller is effective for force control of the non-minimum phase end milling operation and the closed-loop control system is stable over a wide range of cutting conditions.