Reliability Analysis of Electrical System of Computer Numerical Control Machine Tool Based on Bayesian Networks

The core of computer numerical control(CNC) machine tool is the electrical system which controls and coordinates every part of CNC machine tool to complete processing tasks, so it is of great significance to strengthen the reliability of the electrical system. However, the electrical system is very complex due to many uncertain factors and dynamic stochastic characteristics when failure occurs. Therefore, the traditional fault tree analysis(FTA) method is not applicable. Bayesian network(BN) not only has a unique advantage to analyze nodes with multiply states in reliability analysis for complex systems, but also can solve the state explosion problem properly caused by Markov model when dealing with dynamic fault tree(DFT). In addition, the forward causal reasoning of BN can get the conditional probability distribution of the system under considering the uncertainty;the backward diagnosis reasoning of BN can recognize the weak links in system, so it is valuable for improving the system reliability.

Toolpath Interpolation and Smoothing for Computer Numerical Control Machining of Freeform Surfaces: A Review

Driven by the ever increasing demand in function integration,more and more next generation high value-added products,such as head-up displays,solar concentrators and intra-ocular-lens,etc.,are designed to possess freeform(i.e.,non-rotational symmetric)surfaces.The toolpath,composed of high density of short linear and circular segments,is generally used in computer numerical control(CNC)systems to machine those products.However,the discontinuity between toolpath segments leads to high-frequency fluctuation of feedrate and acceleration,which will decrease the machining efficiency and product surface finish.Driven by the ever-increasing need for high-speed high-precision machining of those products,many novel toolpath interpolation and smoothing approaches have been proposed in both academia and industry,aiming to alleviate the issues caused by the conventional toolpath representation and interpolation methods.This paper provides a comprehensive review of the state-of-the-art toolpath interpolation and smoothing approaches with systematic classifications.The advantages and disadvantages of these approaches are discussed.Possible future research directions are also offered.

大型CNC机床柔性随行夹具的开发与实现

为了解决大型结构件数控加工时,传统加工固持技术工装数量多、工艺准备时间长、加工连续性差等问题,设计了一种柔性随行夹具。该夹具采用旋摆气缸代替传统压板,根据机床刀具运行轨迹自动控制夹具避让主轴刀头,同时可通过调节压板长度以适应不同形状的工件,具备一定的柔性扩展能力,可应用在三坐标双主轴数控龙门铣床——V22500B或性能参数类似的数控机床上。

Algorithm for Smooth S-curve Feedrate Profiling Generation

The algorithms for feedrate profile generation,such as linear and S-curve profiles,have been widely used in machinery controllers,and these algorithms can greatly improve the smoothness of motion.However,most of the algorithms lead to the discontinuous acceleration/deceleration and jerk,or high jerk levels,which is very harmful to machine tool or robot in most occasions. This paper presents a smooth S-curve feedrate profiling generation algorithm that produces continuous feedrate,acceleration,and jerk profiles.Smooth jerk is obtained by imposing limits on the first and second time derivatives of acceleration,resulting in trapezoidal jerk profiles along the tool path.The discretization of smooth S-curve feedrate is realized with a novel approach that improves the efficiency without calculating the deceleration point in each sampled time.To ensure that the interpolation time is a multiple of the value of sampled time,the feedrate,acceleration,jerk,and jerk derivative are recalculated.Meantime,to improve the efficiency,the interpolation steps of all regions are computed before interpolation.According to the distance of trajectory,the smooth S-curve acceleration and decelerations are divided into three blocks：normal block,short block type-Ⅰ,and short block type-Ⅱ.Finally feedrate discretization of short block type-Ⅰand type-Ⅱis obtained with considering the efficiency.The proposed generation algorithm is tested in machining a part on a five axis milling machine,which is controlled with the CNC system for newly developed high-speed machine tools.The test result shows that the smooth S-curve approach has the smoother feedrate,acceleration,deceleration,and jerk profiles than S-curve.The proposed algorithm ensures the automated machinery motion smoothness,and improves the quality and efficiency of the automated machinery motion planning.

OPEN ARCHITECTURE CNC SYSTEM HITCNC AND KEY TECHNOLOGY

Aiming at the characteristics of modularity and reconfigurable in open architecture computer numerical control （CNC） system, the open architecture CNC system, Harbin Institute of Tech- nology computer numerical control （HITCNC）, is researched and manufactured based on the interface standards. The system＇s external interfaces are coincident with the corresponding international standards, and the internal interfaces follow the open modular architecture controller （OMAC） agreement. In the research and manufacturing process, object-oriented technology is used to ensure the openness of the HITCNC, and static programming is applied in the CNC system according to the idea of modularization disassembly. The HITCNC also actualizes real-time and unreal-time modules adopting real-time dynamical linked library （RTDLL） and component object model （COM）. Finite state ma- chine （FSM） is adopted to do dynamically modeling of HITCNC. The complete separation between the software and the hardware is achieved in the HITCNC by applying the SoftSERCANS technique. The application of the above key techniques decreases the programming workload greatly, and uses software programs replacing hardware functions, which offers plenty technique ensures for the openness of HITCNC. Finally, based on the HITCNC, a three-dimensional milling system is established. On the system, series experiments are done to validate the expandability and interchangeability of HITCNC. The results of the experiments show that the established open architecture CNC system HITCNC is correct and feasible, and has good openness.

The Innovation of CNC Machine Interface Based on DNC System

This paper describes the innovation schemes of the interface of a CNC machine which cannot communicate with a computer by a Direct Numerical Control(DNC)interface and the functions of a DNC interface system.One architecture of hardware and software of a practi- cal single-chip computer based on DNC interface system developed by the authors is given. Without any change of the original hardware and software,this DNC interface system has been used to innovate the CNC machine's interface to implement the direct communication between a computer and a CNC machine and to achieve no tape transmission of a part program and ma- chine parameters.It has been demonstrated that this DNC interface system has certain practical values in improving the reliability,efficiency and production management of CNC/NC machine.

A framework from point clouds to workpieces

Combining computer-aided design and computer numerical control(CNC)with global technical connections have become interesting topics in the manufacturing industry.A framework was implemented that includes point clouds to workpieces and consists of a mesh generation from geometric data,optimal surface segmentation for CNC,and tool path planning with a certified scallop height.The latest methods were introduced into the mesh generation with implicit geometric regularization and total generalized variation.Once the mesh model was obtained,a fast and robust optimal surface segmentation method is provided by establishing a weighted graph and searching for the minimum spanning tree of the graph for extraordinary points.This method is easy to implement,and the number of segmented patches can be controlled while preserving the sharp features of the workpiece.Finally,a contour parallel tool-path with a confined scallop height is generated on each patch based on B-spline fitting.Experimental results show that the proposed framework is effective and robust.

Importance Analysis on Subsystem of CNC Lathe Based on TOPSIS

An importance analysis model for computer numerical control（CNC）lathe subsystems was proposed.The model was based on technique for order preference by similarity to an ideal solution（TOPSIS）and considered the structure correlation between subsystems and the complete machine,the fault correlation of each subsystem and so on.The model can obtain a comprehensive sequencing of subsystems based on their importance to the complete machine.It lays a theoretical foundation for reliability allocation.

The Mechanical Strength Property of Brick Material and its Impact on the Processing Quality

A large number of experiments have been done for analyzing the two important indicators -compressive strength and flexural strength, which affect computer numerical control （CNC） engraving material physical properties. Using Matlab for simulation experiment, the processing quality of different intensity brick materials is analyzed by the theory of fracture toughness. The result show that porosity is an important factor for engraving, and the research also provide a reference for further study which can improve the quality of brick carving.

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.

Fuzzy Tuned PID Controller for Envisioned Agricultural Manipulator

The implementation of image-based phenotyping systems has become an important aspect of crop and plant science research which has shown tremendous growth over the years. Accurate determination of features using images requires stable imaging and very precise processing. By installing a camera on a mechanical arm driven by motor, the maintenance of accuracy and stability becomes non-trivial. As per the state-of-the-art, the issue of external camera shake incurred due to vibration is a great concern in capturing accurate images, which may be induced by the driving motor of the manipulator. So, there is a requirement for a stable active controller for sufficient vibration attenuation of the manipulator. However, there are very few reports in agricultural practices which use control algorithms. Although, many control strategies have been utilized to control the vibration in manipulators associated to various applications, no control strategy with validated stability has been provided to control the vibration in such envisioned agricultural manipulator with simple low-cost hardware devices with the compensation of non-linearities. So, in this work, the combination of proportional-integral-differential(PID) control with type-2 fuzzy logic(T2-F-PID) is implemented for vibration control. The validation of the controller stability using Lyapunov analysis is established. A torsional actuator(TA) is applied for mitigating torsional vibration, which is a new contribution in the area of agricultural manipulators. Also, to prove the effectiveness of the controller, the vibration attenuation results with T2-F-PID is compared with conventional PD/PID controllers, and a type-1 fuzzy PID(T1-F-PID) controller.

Improved time-optimal B-spline feedrate scheduling for NURBS tool paths in CNC machining

Feedrate scheduling in computer numerical control(CNC)machining is of great importance to fully develop the capabilities of machine tools while maintaining the motion stability of each actuator.Smooth and time-optimal feedrate scheduling plays a critical role in improving the machining efficiency and precision of complex surfaces considering the irregular curvature characteristics of tool paths and the limited drive capacities of machine tools.This study develops a general feedrate scheduling method for non-uniform rational B-splines(NURBS)tool paths in CNC machining aiming at minimizing the total machining time without sacrificing the smoothness of feed motion.The feedrate profile is represented by a B-spline curve to flexibly adapt to the frequent acceleration and deceleration requirements of machining along complex tool paths.The time-optimal B-spline feedrate is produced by continuously increasing the control points sequentially from zero positions in the bidirectional scanning and sampling processes.The required number of knots for the time-optimal B-spline feedrate can be determined using a progressive knot insertion method.To improve the computational efficiency,the B-spline feedrate profile is divided into a series of independent segments and the computation in each segment can be performed concurrently.The proposed feedrate scheduling method is capable of dealing with not only the geometry constraints but also high-order drive constraints for any complex tool path with little computational overhead.Simulations and machining experiments are conducted to verify the effectiveness and superiorities of the proposed method.

Thermal error modeling based on BiLSTM deep learning for CNC machine tool

The machining accuracy of computer numerical control machine tools has always been a focus of the manufacturing industry.Among all errors,thermal error affects the machining accuracy considerably.Because of the significant impact of Industry 4.0 on machine tools,existing thermal error modeling methods have encountered unprecedented challenges in terms of model complexity and capability of dealing with a large number of time series data.A thermal error modeling method is proposed based on bidirectional long short-term memory(BiLSTM)deep learning,which has good learning ability and a strong capability to handle a large group of dynamic data.A four-layer model framework that includes BiLSTM,a feedforward neural network,and the max pooling is constructed.An elaborately designed algorithm is proposed for better and faster model training.The window length of the input sequence is selected based on the phase space reconstruction of the time series.The model prediction accuracy and model robustness were verified experimentally by three validation tests in which thermal errors predicted by the proposed model were compensated for real workpiece cutting.The average depth variation of the workpiece was reduced from approximately 50μm to less than 2μm after compensation.The reduction in maximum depth variation was more than 85%.The proposed model was proved to be feasible and effective for improving machining accuracy significantly.

Prediction of product roughness,profile,and roundness using machine learning techniques for a hard turning process

High product quality is one of key demands of customers in the field of manufacturing such as computer numerical control(CNC)machining.Quality monitoring and prediction is of great importance to assure high-quality or zero defect production.In this work,we consider roughness parameter Ra,profile deviation Pt and roundness deviation RONt of the machined products by a lathe.Intrinsically,these three parameters are much related to the machine spindle parameters of preload,temperature,and rotations per minute(RPMs),while in this paper,spindle vibration and cutting force are taken as inputs and used to predict the three quality parameters.Power spectral density(PSD)based feature extraction,the method to generate compact and well-correlated features,is proposed in details in this paper.Using the efficient features,neural network based machine learning technique turns out to be able to result in high prediction accuracy with R2 score of 0.92 for roughness,0.86 for profile,and 0.95 for roundness.