超声振动切削刀具设计

介绍频率40kHz,振幅在(10～35)μm范围可调的振动刀具的设计过程,该刀具选用通用信号发生器作为超声波信号源,对其(0～5)V正弦电压信号进行放大,输出幅值(0～350)V用于激励压电换能器,将超声电振荡转换成机械振动,对振动信号再经变幅杆机械放大,使刀具振动幅值达到(10～25)μm以上进行切削。利用该刀具切削工件的精度和表面粗糙度达到精密切削的效果,并且已进行了天然金刚石精细切削不锈钢零件的实验,切削后的刀具磨损量明显降低。     

An automatic system based on vibratory analysis for cutting tool wear monitoring

The aim of this work is to develop a new, simple to use and reliable automatic method for detection and monitoring wear on the cutting tool. To achieve this purpose, the vibratory signatures produced during a turning process were measured by using a three-axis accelerometer. Then, the mean power analysis was proposed to extract an indicator parameter from the vibratory responses, to be able to describe the state of the cutting tool over its lifespan. Finally, an automatic detector was proposed to evaluate and monitor tool wear in real time. This detector is efficient, simple to operate in an industrial environment and does not require any protracted computing time.     

The design of a single-chip tool monitoring system for on-line turning operation

Tool condition monitoring systems play an important role in a FMS system. By changing the worn tool before or just at the time it fails, the loss caused by defect product can be reduced greatly and thus product quality and reliability is improved. To achieve this, an on-line tool condition monitoring system using a single-chip microcomputer for detecting tool breakage during cutting process is discussed in this paper. Conventionally, PC-based monitoring systems are used in most research works. The major shortcoming of PC-based monitoring systems is the incurred cost. To reduce costs, the tool condition monitoring system was built with an Intel 8051 single-chip microprocessor and the design is described in this paper. The 8051 tool monitoring system uses a strain gauge for measuring cutting force; according to the force feature, the tool monitoring system can easily recognize the breakage of the cutting tool with its tool breakage algorithm. The experimental results show that the low-cost 8051 tool monitoring board can detect tool breakage in three successive products successfully.     

Real-time tool condition monitoring method based on in situ temperature measurement and artificial neural network in turning

Tool failures in machining processes often cause severe damages of workpieces and lead to large quantities of loss, making tool condition monitoring an important, urgent issue. However, problems such as practicability still remain in actual machining. Here, a real-time tool condition monitoring method integrated in an in situ fiber optic temperature measuring apparatus is proposed. A thermal simulation is conducted to investigate how the fluctuating cutting heats affect the measuring temperatures, and an intermittent cutting experiment is carried out, verifying that the apparatus can capture the rapid but slight temperature undulations. Fourier transform is carried out. The spectrum features are then selected and input into the artificial neural network for classification, and a caution is given if the tool is worn. A learning rate adaption algorithm is introduced, greatly reducing the dependence on initial parameters, making training convenient and flexible. The accuracy stays 90% and higher in variable argument processes. Furthermore, an application program with a graphical user interface is constructed to present real-time results, confirming the practicality.     

高速切削加工刀具材料的性能分析及合理化选择

阐述各种高速切削加工刀具材料的性能,并分析其物理特性和化学特性以及不同的成分合成对机械加工性能的影响.通过比较,并考虑切削刀具材料与加工对象的力学性能、物理性能和化学性能的匹配情况,合理地选择高速切削加工刀具的材料.     

State-of-the-art methods and results in tool condition monitoring: a review

This paper presents a review of the state-of-the-art in sensors and signal processing methodologies used for tool condition monitoring (TCM) systems in industrial machining applications. The paper focuses on the technologies used in monitoring conventional cutting operations, including drilling, turning, end milling and face milling, and presents important findings related to each of these fields. Unlike existing reviews, which categorize results according to the methodology used, this paper presents results organized according to the type of machining operation carried out. By extensively reviewing and categorizing over one hundred important papers and articles, this paper is able to identify and comment on trends in TCM research, and to identify potential weaknesses in certain areas. The paper concludes with a list of recommendations for future research based on the trends and successful results observed, thus facilitating the cross-fertilization of ideas and techniques within the field of TCM research. An erratum to this article can be found at     

A probabilistic neural network applied in monitoring tool wear in the end milling operation via acoustic emission and cutting power signals

Tool condition monitoring, which is very important in machining, has improved over the past 20 years. Several process variables that are active in the cutting region, such as cutting forces, vibrations, acoustic emission (AE), noise, temperature, and surface finish, are influenced by the state of the cutting tool and the conditions of the material removal process. However, controlling these process variables to ensure adequate responses, particularly on an individual basis, is a highly complex task. The combination of AE and cutting power signals serves to indicate the improved response. In this study, a new parameter based on AE signal energy (frequency range between 100 and 300 kHz) was introduced to improve response. Tool wear in end milling was measured in each step, based on cutting power and AE signals. The wear conditions were then classified as good or bad, the signal parameters were extracted, and the probabilistic neural network was applied. The mean and skewness of cutting power and the root mean square of the power spectral density of AE showed sensitivity and were applied with about 91% accuracy. The combination of cutting power and AE with the signal energy parameter can definitely be applied in a tool wear-monitoring system.     

FPGA-based reconfigurable system for tool condition monitoring in high-speed machining process

We present a reconfigurable system to detect and indicate online and in real time, the cutting tool conditions in high-speed face milling. It consists of a data acquisition system (DAS) and a hardware signal processing (HSP) unit. The DAS acquires and digitalizes the cutting vibration signals generated from machining tests performed under different tool conditions and cutting parameters. The HSP unit processes the digitalized vibration signals using reconfigurable IIR band-pass digital filter and statistical techniques, designed and implemented into a single field-programmable gate array (FPGA) and coefficients read-only memories. The system operation is divided into learning and monitoring modes. The tool condition is indicated by an alarm signal, one LED indicator, and a message shown on four-digit seven-segment displays. In all experiments, the system correctly detected the tool condition. The proposed system is fast, compact, reliable, and economical, and no modification of the machine-tool structure is required.     

Effects of the cutting feed, depth of cut, and workpiece (bore) diameter on the tool wear rate

Most published studies on metal cutting regard the cutting speed as having the greatest influence on tool wear and, thus, tool life, while other parameters and characteristics of the cutting process have not attracted as much attention in this respect. This is because of the existence of a number of contradicting results on the influence of the cutting feed, depth of cut, and workpiece (bore) diameter. The present paper discusses the origin of the aforementioned contradicting results. It argues that, when the optimal cutting temperature is considered, the influence of the aforementioned parameters on tool wear becomes clear and straightforward. The obtained results reveal the true influence of the cutting feed, diameter of the workpiece, and diameter of the hole being bored on the tool wear rate. It was also found that the depth of cut does not have a significant influence on the tool wear rate. The obtained results provide methodological help in the experimental assessment and proper reporting of the tool wear rates studied under different cutting conditions.     

Study of cutting force and surface roughness in the turning of polytetrafluoroethylene composites with a polycrystalline diamond tool

Despite the importance of the polytetrafluoroethylene (PTFE) composites in many industrial applications, especially for space industry, very little is known about the machinability of these composites. This paper presents an investigation into the turning of PTFE composites using a polycrystalline diamond tool in order to analyze the effect of the cutting parameters and insert radius on the cutting force and surface roughness. A strain gauge based dynamometer for the main cutting force measurement in turning was constructed. The force signals were captured and processed using a strain data acquisition system based on the Sider8 and CATMAN software. Cutting force and surface roughness were measured through longitudinal turning, according to the experimental plan developed based on the Taguchi methodology. The signal-to-noise ratio and the analysis of variance were applied to the experimental data in order to determine the effect of the process variables on the surface roughness and cutting force, and predictive models have been derived.     

Tool wear monitoring system for CNC end milling using a hybrid approach to cutting force regulation

A tool wear monitoring system is indispensable for better machining productivity, with the guarantee of machining safety by informing of the time due for changing a tool in automated and unmanned CNC machining. Different from monitoring methods using other signals, the monitoring of the spindle current has been used without requiring additional sensors on the machine tools. For reliable tool wear monitoring, only the current signal from tool wear should be extracted from the other parameters to avoid exhaustive analyses on signals in which all of the parameters are fused together. In this paper, the influences of force components from different parameters on the measured spindle current are investigated, and a hybrid approach to cutting force regulation is employed for tool wear signal extraction from the spindle current. Finally, wear levels are verified with experimental results by means of real-time feedrate aspects, varied to regulate the force component from tool wear.     

Mirror surface machining of high-alloy steels by elliptical vibration cutting with single-crystalline diamond tools: Influence of alloy elements on diamond tool damage

Elliptical vibration cutting with single-crystalline diamond tools is applied to mirror surface machining of high-alloy steels such as cold work die steels and high-speed tool steels with a hardness of more than 60 HRC. Although practical mirror surface machining of hardened die steels such as Stavax (modified AISI 420) with a hardness of 53 HRC has been realized with the elliptical vibration cutting, lives of single-crystalline diamond tools are not sufficiently long in machining of some high-alloy steels, that may be caused by a large amount of alloy elements. In order to clarify the influence of the alloy elements on the diamond tool damage, the elliptical vibration cutting experiments are conducted on six kinds of high-alloy steels and four kinds of pure metals which are the same as the alloy elements. Mechanical properties of the alloy steels, i.e. difference in hardness between carbides and matrices, and the number of small carbides, are measured, and their influence on the micro-chippings are investigated. The chemical states of the alloy elements in high-alloy steels are analyzed using an X-ray diffraction (XRD) and an electron probe micro analyzer (EPMA), and their influence on the tool wear is discussed. Based on the investigation, a mirror surface machining of DC53, which has a high hardness of 62.2 HRC and the best machinability in the tested high-alloy steels, is demonstrated, and a mirror surface with a roughness of Rt 0.05 μm is obtained successfully.     

基于Internet的嵌入式设备状态监测系统开发与研究

网络化的设备状态监测及故障诊断是企业设备状态监测的发展方向。本文介绍了一种基于Internet的嵌入式设备状态监测与故障诊断系统，利用嵌入式动态信号测试分析仪进行现场数据采集，通过Internet上传至服务器，实现了设备数据的集中化管理，专家通过网络可以对设备状态进行远程监控，并且服务器可以对客户端的连接进行在线监控，增强了系统的规范化管理和安全性。     

Development of a cutting tool with a nano/micro-textured surface—Improvement of anti-adhesive effect by considering the texture patterns

Demand for lightweight aluminum-based composites is rapidly increasing in the transport industry. Generally it is considered that aluminum alloys are easy-to-cut materials due to their low hardness. However, it is noted that some serious problems exist. Because of low lubricity against the cutting tool surface during deep-hole drilling, milling, and tapping, aluminum chips may adhere strongly to the cutting edge of the tool, leading to tool breakage. To solve this problem, a cutting tool with a nano/micro-textured surface utilizing femto-second laser technology was proposed in our previous research. A series of face-milling experiments for aluminum alloy showed that a nano/micro-textured surface promoted anti-adhesive effects at the tool–chip interface, although adhesion remained a problem. In this study, the ways to improve the anti-adhesive effect with nano/micro-textures were studied. Based on this, a cutting tool with a banded nano/micro-textured surface was newly developed and it was revealed that the surface significantly improved the anti-adhesiveness and lubricity.     

高速车削钛合金时硬质合金刀具和涂层刀具的寿命分析

采用硬质合金刀具和硬质合金TiMN涂层刀具对Ti-6Al-4V钛合金进行高速干车削正交试验,并通过多元线性回归分析得出硬质合金刀具和涂层刀具的寿命经验公式.分析表明:随着所选用的切削参数值的升高,刀具的使用寿命急剧减少,其中速度v对刀具使用寿命的影响最大.涂层刀具在低速切削加工钛合金时其寿命优于未涂层刀具,随着速度的提高,涂层刀具的优势迅速减小.当切削速度低于85 m/min,刀具寿命经验公式可以作为数控机床自动换刀的刀具寿命标准.     

The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery

The monitoring of progressive wear in gears using various non-destructive technologies as well as the use of advanced signal processing techniques upon the acquired recordings to the direction of more effective diagnostic schemes, is the scope of the present work. For this reason multi-hour tests were performed in healthy gears in a single-stage lab scale gearbox until they were seriously damaged. Three on-line monitoring techniques are implemented in the tests. Vibration and acoustic emission recordings in combination with data coming from oil debris monitoring (ODM) of the lubricating oil are utilized in order to assess the condition of the gears. A plethora of parameters/features were extracted from the acquired waveforms via conventional (in time and frequency domain) and non-conventional (wavelet-based) signal processing techniques. Data fusion was accomplished in the level of integration of the most representative among the extracted features from all three measurement technologies in a single data matrix. Principal component analysis (PCA) was utilized to reduce the dimensionality of the data matrix whereas independent component analysis (ICA) was further applied to identify the independent components among the data and correlate them to different damage modes of the gearbox. Finally heuristic rules based on characteristic values of the resulted independent components were set, realizing thus a health monitoring scheme for gearboxes.The integration of vibration, AE and ODM data increases the diagnostic capacity and reliability of the condition monitoring scheme concluding to very interesting results. The present work summarizes the joint efforts of two research groups towards a more reliable condition monitoring of rotating machinery and gearboxes specifically.     

Development and machining performance of a textured diamond cutting tool fabricated with a focused ion beam and heat treatment

This paper presents the fabrication method and machining performance of a textured diamond cutting tool. To improve the machining performance, a texture was fabricated on the rake face of the diamond tool with a depth of 43 nm and width of 1.8 μm by utilizing a focused ion beam (FIB) followed by heat treatment. In addition, a FIB-induced non-diamond phase that adversely affects the machining performance was removed. A machining experiment using aluminum alloy and nickel phosphorus was conducted to evaluate the proposed method. A significant decrease in friction was observed at the tool–chip interface after texturing. This corresponds to a reduced cutting force, which indicates that the machining performance of the tool was improved by texturing. The magnitude of the effect depends on the shape and direction of the texture. The textured tool was able to machine a surface topography similar to that with a non-textured tool, which indicates that the texture effect can be obtained while maintaining the quality of the machined surface by fabricating the texture far from the cutting edge.     

基于压缩体素模型的球头刀空间扫描体构造新方法及其应用

提出了一种基于压缩体素模型的球头刀空间扫描体构造新方法,将球头刀分解为相应球体部分和圆柱体部分,分别给出了球体和圆柱体空间扫描体构造公式并构造出其表面模型,利用RayCasting方法分别将球体和圆柱体空间扫描体表面模型进行离散,将其分别转化为压缩体素模型,通过布尔并操作生成球头刀空间扫描体压缩体素模型。该方法由于采用三个方向的Dexel模型表示体素模型,其计算机内部存贮空间得到了很大地压缩,并简化了布尔操作和提高了布尔操作速度;通过MarchingCubes方法提取数控加工仿真工件表面模型并进行图形显示,提高了显示质量和显示速度。该方法在《基于压缩Voxel模型的五坐标数控加工仿真系统》中得到了应用并完成了某叶轮的五坐标数控加工仿真,仿真结果三维信息完备,NC编程人员可从任意方向观察、验证仿真结果,克服了现有五坐标数控加工仿真方法和商品化软件系统的不足,该方法是虚拟数控加工的关键技术。     

Development of high water-content cutting fluids with a new concept: Fire prevention and environmental protection

Using water-insoluble cutting fluids, which are good in lubricity but easy to mist, always risks firing and environmental problems. On the other hand, the current water-soluble coolants fail to deliver sufficient lubricity to heavy cutting applications. This study has newly proposed and developed a high water-content cutting fluid, based upon a new concept of having high lubricity despite of its water-soluble nature. As compared to the commercialized water-insoluble cutting fluid, the new cutting fluids shows a better capability of preventing oil mist and is fully applicable into cutting of various metallic materials, particularly effective in cutting of S45C and SUS304. The study also reveals a fact that a sulfur-type extreme pressure agent is the key element to enhance the cutting performance at high temperature.     

Cutting tool condition monitoring by analyzing surface roughness,work piece vibration and volume of metal removed for AISI 1040 steel in boring

The vibration is one of the intensive problems in boring process. Machining and tool wear are affected more by vibration of tool due to length of boring bar. The present work is to estimate the effect of cutting parameters on work piece vibration, roughness on machined surface and volume of metal removed in boring of steel (AISI1040). A laser Doppler vibrometer (LDV) was used for online data acquisition and a high-speed FFT analyzer used to process the AOE signals for work piece vibration. A design of experiments was prepared with eight experiments with two levels of cutting parameters such as spindle rotational speed, feed rate and tool nose radius. Taguchi method has been used to optimize the cutting parameters and a multiple regression analysis is done to obtain the empirical relation of Tool life with roughness of machined surface, volume of metal removed and amplitude of work piece vibrations.