基于间歇性车削加工过程中刀具状态实时检测的研究

针对间歇性切削过程中刀具受间歇性冲击导致的损坏,基于一种新的信号处理方法提出一种用于在线预测刀具切削过程中刀具状态监测方法。该方法基于希尔伯特黄变换(HHT)和Taer-Kaiser能量算符(TKEO),不依赖于切削参数和工件材料对预失效阶段的非稳定裂纹拓展特性进行识别。对刀具状态与切削参数和工件材料参数之间的相关性加以分析并用于保护加工表面。通过实验对监测系统的有效性进行验证,能够保证在刀具损坏之前停止机床操作,验证了该系统的准确性。     

A critical analysis of effectiveness of acoustic emission signals to detect tool and workpiece malfunctions in milling operations

The industrial demands for automated machining systems to increase process productivity and quality in milling of aerospace critical safety components requires advanced investigations of the monitoring techniques. This is focussed on the detection and prediction of the occurrence of process malfunctions at both of tool (e.g. wear/chipping of cutting edges) and workpiece surface integrity (e.g. material drags, laps, pluckings) levels. Acoustic emission (AE) has been employed predominantly for tool condition monitoring of continuous machining operations (e.g. turning, drilling), but relatively little attention has been paid to monitor interrupted processes such as milling and especially to detect the occurrence of possible surface anomalies.This paper reports for the first time on the possibility of using AE sensory measures for monitoring both tool and workpiece surface integrity to enable milling of “damage-free” surfaces. The research focussed on identifying advanced monitoring techniques to enable the calculation of comprehensive AE sensory measures that can be applied independently and/or in conjunction with other sensory signals (e.g. force) to respond to the following technical requirements: (i) to identify time domain patterns that are independent from the tool path; (ii) ability to “calibrate” AE sensory measures against the gradual increase of tool wear/force signals; (iii) capability to detect workpiece surface defects (anomalies) as result of high energy transfer to the machined surfaces when abusive milling is applied.Although some drawbacks exist due to the amount of data manipulation, the results show good evidence that the proposed AE sensory measures have a great potential to be used in flexible and easily implementable solutions for monitoring tool and/or workpiece surface anomalies in milling operations.     

Analysis of the electrochemical behaviors of WC–Co alloy for micro ECM

Micro electrochemical machining (ECM) of tungsten carbide with cobalt binder (WC–Co) was studied using ultrashort pulses. In ECM, the machining characteristics were investigated according to machining conditions such as electrolyte, workpiece potential, and applied voltage pulse. Using a mixture of sulfuric acid and nitric acid, microstructures with a sharp edge and good surface quality were machined on tungsten carbide alloy. The potentials of workpiece electrode and tool electrode were determined by considering the machining rate, machining stability, and surface quality of products. With the negative potential of the workpiece electrode, oxide formation was successfully prevented and shape with good surface quality in the range from R_a 0.069 μm to 0.075 μm were obtained by electrochemical machining. Moreover, the performance of ECM, which includes machining gap, tapering, surface roughness, and machining time, without tool wear was compared with that of electrical discharge machining (EDM). Microstructures of WC–Co with a sharp edge and good surface quality were obtained by electrochemical milling and electrochemical drilling. Micro electrochemical turning was also introduced to fabricate micro shafts.     

高速铣削加工中刀具监测系统研究

在铣削加工中,在刀具急剧磨损的初级阶段,表征刀具磨损的信号较弱,而此时工件精度已早有明显变化。小波神经网络虽能有效处理各种频段信号,但对较弱信号还是存在漏检现象。开发针对高速铣削的刀具在线监测系统,通过监测工件表面精度的变化,及时修正小波变换参数,提高了监测微弱信号的能力,有效降低了刀具监测的漏检、误报率。     

型孔电解加工阴极优化试验研究

为解决电解加工型孔的加工稳定性和形状精度等问题,建立了异形孔电解加工稳定过程中加工间隙数学模型,分析了工具阴极结构对加工区域和非加工区域的电场及其均匀性以及其对电流密度与加工效果的影响,通过优化工件结构改善了加工间隙内的电场分布,使工件形状精度显著提高,并进行相关试验对仿真结果进行验证。得出结论:在相同的电解加工参数下,工具电极的结构对工件的形状精度有着显著的影响,通过优化工具电极结构,改善加工间隙内的电场分布与电流密度,让加工间隙内的流场更为稳定,使工件侧壁垂直度提高,提高了电解加工的形状精度与加工稳定性。     

薄壁筒车削颤振稳定性预测

切削颤振是制约薄壁筒工件加工质量和效率的主要因素之一。采用半离散法对含有时滞项的动力学方程进行稳定性预测分析,结合薄壁筒工件切削振动试验,研究刀具、工件动力学参数匹配关系变化对切削加工稳定性的影响。通过仿真分析得出:随着刀具刚度或固有频率的提升,切削系统稳定性呈上升趋势,但过度提升刀具刚度并不会有效提升切削稳定性;在刀具与工件固有频率接近处,切削系统的稳定性较差;适当调整刀具动态特性参数有利于提高柔性工件切削加工的稳定性;切削过程中,时变的切削位置和工件尺寸会引起切削系统动态特性的变化。根据时变稳定性预测图,从稳定性分析角度解释了一次走刀切削试验中薄壁筒工件表面出现不同加工形貌的原因。     

An automated monitoring solution for avoiding an increased number of surface anomalies during milling of aerospace alloys

The demand for automated machining systems to enable the increase of process productivity and quality in milling of aerospace safety critical components requires advanced on-line monitoring and supervision systems to identify and reduce the number of workpiece surface anomalies caused by faulty tooling. It is well known that chipping or breakage of only one tooth of a milling cutter can lead to extensive damage to the machined surface. Therefore, implementing a process monitoring solution that can detect workpiece surface anomalies associated with the cutting tooth that generated them could be beneficial for proposing more efficient process supervision systems. The system presented in this paper is directed towards real-time control of the contact length of each tooth of a milling cutter with the scope of reducing the amount of workpiece surface anomalies. The proposed control solution consists of: (i) an automated process monitoring part, that, through signal analysis, automatically improves the reliability of fault detection; (ii) a signal based decision and supervision system for the avoidance of surface anomalies or tool malfunctions. The novelty of this supervision system comes from the fact that it is automatically acquiring Acoustic Emission (AE) and cutting forces, adjusts the monitoring parameters accordingly and transmits decision commands to the machine. The supervision system makes use of the sensor fusion and an original methodology for the detection of process malfunctions, to control the movement of the tool. This is directed towards the adjustment of the individual feed per tooth for each cutting edge, and if necessary reduce it to zero for a cutting tooth that is creating the surface damage. The efficiency of the proposed process supervision system is proven to avoid the generation of surface anomalies in milling of a Ni-based alloy used for the manufacture of parts for gas turbine engines.     

氧化锆陶瓷大抛光模磁流变抛光试验研究

目的研发一种高效、高质量氧化锆陶瓷超光滑表面加工技术。方法采用大抛光模磁流变抛光方式加工氧化锆陶瓷,利用自主研发的磁流变平面抛光装置,配制含有金刚石磨粒的磁流变抛光液,通过设计单因素实验,研究抛光时间、工作间隙、工件转速和抛光槽转速等主要工艺参数对氧化锆陶瓷平面磁流变加工性能的影响,并对材料去除率和表面粗糙度进行分析。结果在工作间隙为1.4 mm、工件转速为100 r/min、抛光槽转速为25 r/min的工艺条件下,表面粗糙度在达到饱和之前随时间的增加而降低。抛光30 min达到饱和,表面粗糙度Ra达到0.7 nm。继续延长抛光时间,表面粗糙度不再改善。氧化锆陶瓷的材料去除率随着工件转速和抛光槽转速的增加而增大,随着工作间隙的增大而减小。当工件转速为300 r/min时,材料去除率可以达到1.03 mg/min;抛光槽转速为25 r/min时,材料去除率可以达到0.80 mg/min;工作间隙为1.0 mm时,材料去除率最高可达0.77 mg/min。结论采用大抛光模磁流变抛光方法可以提高氧化锆陶瓷的材料去除率,同时获得纳米级表面粗糙度,实现氧化锆陶瓷的高效超光滑表面加工。     

Optimization of Abrasive Powder Mixed EDM of Aluminum Matrix Composites with Multiple Responses Using Gray Relational Analysis

Abrasive powder-mixed electrical discharge machining (APM-EDM), a hybrid manufacturing process involving the use of a dielectric fluid mixed with abrasive powder, combines the benefits of mechanical and thermal interactions. The aim of this article is to use a new approach of performance evaluation, gray relational analysis (GRA), to evaluate the effectiveness of optimizing multiple performance characteristics of APM-EDM of 6061Al/Al₂O_3p/20p aluminum matrix composites (AMCs). The considered process parameter includes the seven control factors namely pulse current (A), pulse ON time (μs), duty cycle (%), gap voltage (V), time interval of tool lift (s), abrasive powder concentration (g/L), abrasive particle size (μm), and a noise factor, aspect ratio (shape of tool electrode). The combination of L18 (2¹ × 3⁷) orthogonal array design of experiment with GRA enables to determine the optimal parameters for multiple responses. GRA is used to obtain a single performance index, gray relational grade through gray relational coefficient to optimize the APM-EDM process with lower tool wear rate, surface roughness, and higher material removal rate. In addition, analysis of variance (ANOVA) for the GRC is also utilized.     

铍铜合金铣削过程刀具黏附现象对切削颤振影响分析

为了满足高精密铍铜件表面的加工要求,研究刀具表面黏附过程对切削系统和已加工表面的影响,有利于提高加工质量和加工效率。通过建立二自由度切削颤振系统,结合工件材料特性、黏结过程和断续切削过程,采用单因素高速铣削实验方法,解析刀具损伤、切削颤振和已加工表面的内在联系,并通过电镜扫描和白光干涉对刀具表面和已加工表面进行对比分析。切削速度和黏附程度的差异性,极大地影响了切削过程的稳定性,导致已加工表面缺陷的产生。不同黏附环境往往导致了不同的切削状态,尤其是高黏附率环境下的刀具表面黏附有利于维持切削刃形态和减缓加工颤振现象。     

声发射监测技术在磨削加工中的应用

在磨削加工中,砂轮的工作状况是不断变化的,因此,对砂轮的修整及磨削过程进行监测是非常必要的。本文将声发射(AE)信号应用到对磨削过程的监测上,通过监测砂轮修整过程可以得到一致的砂轮表面质量。通过监测AE信号的幅值和频谱特征即可确定砂轮的寿命。用AE信号可以成功地检测出砂轮和工件的初始接触时间,为砂轮向工件进给时的准确对刀及高精度表面质量的获得提供了有效的方法。     

A time–frequency acoustic emission-based monitoring technique to identify workpiece surface malfunctions in milling with multiple teeth cutting simultaneously

In the view of implementing automated solutions for monitoring complex machining processes such as milling, the usage of acoustic emission (AE) in machining is regarded as a promising way for assessing machine tool condition and for in-process detection of workpiece malfunctions. Correlating AE signal events with the occurrence of workpiece surface anomalies (e.g. laps, material drag) can be a powerful method for scrap reduction of expensive components such as those employed in aerospace industry. This paper proposes new methods for supervising cutting processes with multiple teeth cutting simultaneously, i.e. milling, by use of AE signals backed-up by force data. This is done by taking into account signals patterns when one, two or three teeth are cutting simultaneously, situation that often occurs in real milling applications. The research shows for the first time that identification of milling conditions (i.e. cutting with one/two/three teeth) is possible using only AE signal in time–frequency (T–F) domain. Moreover, detection of surface anomalies, such as folded laps that are generated by damaged cutting edges can be successfully identified in various milling conditions. The paper demonstrates that time–frequency analysis of AE signals empowered with advanced processing techniques has great potential to be used in flexible and easily to implement monitoring solutions to enable milling of anomaly-free workpiece surfaces in difficult-to-cut aerospace materials.     

On-line monitoring of tool wear in turning using a neural network

Tool wear has long been identified as the most undesirable characteristic of the machining operations. Flank wear, in particular directly affects the workpiece dimensions and the surface quality. A reliable and sensitive technique for monitoring the tool wear without interrupting the process, is crucial in realization of the modern manufacturing concepts like unmanned machining centres, adaptive control optimization, etc. In this work an optoelectronic sensor is used in conjunction with a multilayered Neural Network for predicting the flank wear on the cutting tool. The gap sensing system consists of a bifurcated optical fibre, a laser source and a photodiode circuit. The output of the photodiode circuit is amplified and converted to the digital form using an A/D converter. The digitized sensor signal along with the cutting parameters form the inputs to a three layered, feed forward, fully connected Neural Network. The Neural Network, trained off-line using a backpropagation algorithm and the experimental data, is used to predict the flank wear. A geometrical relation is also used to correlate the flank wear on the cutting tool with the change in the workpiece dimension. The values predicted using the Neural Network and those calculated using the geometrical relation are compared with the actual values measured using a tool maker's microscope. Results showed the ability of the Neural Network to accurately predict the flank wear.     

On-machine three-dimensional monitoring technique using machining laser

An on-machine three-dimensional monitoring system has been developed that uses machining YAG laser as a source of light for monitoring. In the monitoring stage, the output of the laser is decreased. The reflected light from a workpiece is taken out with a beam sampler on the way of the optical system, and observed by CMOS image sensor. This system can measure both Z-direction depth and the position of X–Y-direction. Because the same laser and the optical system are used, the system has no gap of an optical axis between the measurement and the machining, and also has no limitation of viewing angle. Every three-dimensional shape which can be machined by laser beam can be measured. In this paper, system configuration, monitoring technique and the experimental results are described.     

Design and development of nanofinishing process for 3D surfaces using ball end MR finishing tool

A new precision finishing process for nanofinishing of 3D surfaces using ball end MR finishing tool is developed. The newly developed finishing process is used to finish ferromagnetic as well as nonmagnetic materials of 3D shapes using specially prepared magnetorheological polishing (MRP) fluid. The existing MR finishing devices and methods are likely to incapable of finish 3D intricate surfaces such as grooves in workpiece or complex in-depth profiles in the mold due to restriction on relative movement of finishing medium and workpiece. In this newly developed finishing device, the ball end MR finishing tool is used for finishing different kinds of 3D surfaces, as there is no limitation on relative movement of finishing medium and workpiece. It can finish the work surfaces similarly as the machining of 3D surfaces by CNC ball end milling cutter and open a new era of its applications in future. The developed process may have its potential applications in aerospace, automotive and molds manufacturing industries. A computer controlled experimental setup is designed and manufactured to study the process characteristics and performance. The magnetostatic simulations were done on ferromagnetic as well as nonferromagnetic materials of 3D surfaces to observe the ball end shape of magnetic field at the tip of the MR finishing tool. The experiments were performed on flat EN31 and groove surface of copper workpieces in the developed MR finishing setup to study the effect of finishing time on final surface roughness.     

Tool wear in friction drilling

This study investigates the tool wear in friction drilling, a nontraditional hole-making process. In friction drilling, a rotating conical tool uses the heat generated by friction to soften and penetrate a thin workpiece and create a bushing without generating chips. The wear of a conical tungsten carbide tool used for friction drilling a low carbon steel workpiece is studied. Tool wear characteristics are quantified by measuring its weight change, detecting changes in its shape with a coordinate measuring machine, and making observations of wear damage using scanning electron microscopy. Energy dispersive spectrometry is applied to analyze the change in chemical composition of the tool surface due to drilling. In addition, the thrust force and torque during drilling and the hole size are measured periodically to monitor the effects of tool wear. Results indicate that the carbide tool is durable, showing minimal tool wear after drilling 11,000 holes, but observations also indicate the progressively severe abrasive grooving on the tool tip.     

Polishing properties of tiny grinding wheel based on Fe3O4 electrorheological fluid

Experiments were conducted to reveal the polishing properties of the Fe₃O₄ electrorheological fluid, which was used to form a dynamical, instantaneous tiny grinding wheel to polish optical glass. The profile of the polished area of the glass surface indicates that the material removal process is dominated by the synergy of the applied pressure and the relative velocity between the abrasives and the workpiece to be polished. It is also found that the rate of material removal is proportional to the intensity of external electric field and decreases with the extension of the machining gap between the workpiece and the needle-like tool.     

Tool wear-dependent process analysis by means of a statistical online monitoring system

Simulating milling processes can provide numerous optimization possibilities regarding process stability and surface quality. In tool and die manufacturing often long-running processes are necessary. In contrast to very time-consuming Finite-Element-based approaches, geometric physically-based simulation systems allow predictions for such processes because of their relatively short runtime. The machining of hardened material and varying engagement conditions between the tool and the workpiece provoke a gradually increasing influence of tool wear on the cutting edges. To consider these alterations while simulating milling processes, different approaches can be used. Because of the complex characteristics of tool wear, methods, which result in an increased simulation runtime, have to be used for the geometric modeling of tool wear. In this paper, a novel approach for monitoring a milling process is presented, which utilizes an online-selection of pre-calculated simulation data to predict the process stability for different states of tool wear. To achieve this, measured data are compared to simulated data, which result from offline simulation conductions for each defined state of tool wear. As tool wear changes when the process is progressing, different simulation data for different states of tool wear have to be selected to ensure a valid stability prediction.     

基于复合工作液的高压喷液电火花线切割实验分析

阐述了基于复合工作液的高压喷液电火花线切割加工以提高切割效率和加工精度的方法：从理论上分析了电火花线切割加工过程中，工作液在极间的压力分布状况和冷却规律；对比了高压喷液与无高压喷液条件下加工工件的表面形貌；通过检测电流、电压波形反映了极间放电状况；分析了极间状态对加工工件表面形貌的影响。     

Pulse electrochemical finishing: Modeling and experiment

Surface quality of the workpiece has great influence on its service performance and lifespan. Pulse electrochemical finishing (PECF) provides an effective method for improving surface quality of the workpiece. In PECF, surface irregularities are removed by electrochemical dissolution rather than by cutting force. Due to non-contact nature of the process, there is no residual stress and thermal effect on the workpiece surface. For successful utilization of PECF, in present manufacturing, it still demands for more intensive research, including the mechanism of anodic smoothing. The anodic smoothing characteristics of PECF are analyzed through a developed mathematical model. The main influencing factors such as the finishing time, the interelectrode gap, the applied voltage and the rotational speed of electrode have been examined. The predictive values based on the developed mathematical model are found to be in reasonable agreement with the experimental values. The surface roughness Rz ranges from 3 μm to 1.22 μm. The research achievement through various parametric studies can be used as a guideline for the operation of a PECF system.