实验方法
辐射黑色体理论（Chao et al., 1961）和切削表面理论（Friedman and Lenz, 1970）。随着敏感的红外感光胶片的发展，在一个可被记录切削侧面温度场的工具（Boothroyd, 1961）和电视型红外线敏感的视频设备已被哈里斯等人使用（1980年），以热传感和半导体量子吸收的原则为基础的红外线传感器的不断发展，使得这些传感器的第二敏感性大于第一次，其时间常数很小太 - 在微秒到毫秒的范围之内。图5.21显示了最新使用的第二类的例子。有两个传感器以及开始投入使用，一个是在1毫米至5毫米的波长范围的敏感型锑化铟，另外一个是从6毫米至13毫米的敏感型碲镉汞类型，通过与两个不同的探测器信号比较可以使用温度测量更敏感的方法。大部分金属切削温度已进行了调查和了解使得更好地了解这个过程。原则上，温度测量可能用于条件监测，例如，警告说如果是天气太热导致切割刀具后刀面磨损，然而，尤其是辐射能尺寸，在生产条件，校准问题以及确保辐射能量途径从伤口区到探测器不被打断的困难，使得以温度测量为目的方法不够可靠切削的另一种方式是监测声发射，这虽然是一个间接的方法，但研究过程的状态是一个值得考虑未来。
5.4 声发射
材料的活跃形变—例如裂缝的增长，变形夹杂物，快速塑性剪切，甚至晶界，位错运动都是伴随着弹性应力波的排放而产生。这就是声发射（AE）。排放的发生在一个很宽的频率范围内，但通常是从10万赫到1兆赫。虽然波幅度很小，但是他们可以被检测到，通过强烈的压电材料如钛酸钡或压电陶瓷传感器制造从，（Pb（ZrxTi1–x）O3; x = 0.5 to 0.6）。图5.22显示了传感器的结构。声波传送到压力传感器造成直接的压力E（△L/L），其中E是传感器的杨氏模量，L是它的长度，△L是它的长度变化。应力产生电场
T = g33E(△L/L)（5.7a）
g33是传感器材料的压电应力系数。传感器两端的电压是TL，然后
V= g33E△L（5.7b）
g33和E的典型值分别是24.4 × 10-3Vm/ N和58.5GPa，以检测电压高达0.01毫伏，这是可能的。将这些值代入方程（5.7b）导致了检测△L的长度变化的可以小到7 × 10-15米：对于一个L = 10毫米的传感器来说，即相当于拥有7 × 10-13
图5.22显示的是声发射传感器的结构
实验理论方法
的最小应变，使用应变传感要比使用钢丝应变计更敏感，敏感的最低检测应变约为10-6。一个AE传感器电信号处理可分为两个阶段。第一个是通过使用一个低噪声前置放大器和一个带通滤波器（≈100千赫到1兆赫）。由此产生的信号通常具有的基础上的复杂形式，如图5.23所示，在处理的第二阶段，提取信号的主要特征，例如事件的数量，电压超过某一阈值VL，最大电压VT，或信号能量的脉冲频率使用声发射来进行状态监测具有许多优点。一小部分传感器，处于策略性部署，能调查整个机械系统。一个发射源可以通过不同次数的排放以到达不同的传感器。它的高灵敏度已经被提到。这也是很容易被记录的;并且声发射测量仪器重量轻而且体积小。然而，它也有一些缺点。这些传感器必须直接连接到被监视系统：这会导致长期的可靠性问题。在嘈杂的条件下可以使之成为不可能孤立的事件。声发射是很容易受被监视材料的状态的影响，例如热处理，预应变和温度。此外，由于声发射事件和被监视的系统状态两者关系的特点并不明显，甚至比热辐射测量需要更多的校准或压力测量系统。
在加工过程中，声发射信号的主要来源是剪切带，片工具和工具的工作接触区域，切屑的破碎与碰撞，及其切削工具的特征。声发射信号的功率比较大，一般见于范围100千赫至300千赫。其基本性能的研究和检测磨损工具的使用，并且切削已经成为大量调查的主题，例如Iwata和Moriwaki（1977），Kakino（1984），Diei和Dornfeld（1987）。声发射的使用潜力可以在图5.24看出来。它显示了一个后刀面磨损VB和振幅水平之间的关系
那就是AE信号会转化0.45％的普通碳素钢（Miwa，1981）。较大的侧面磨损，较大的声发射信号，而与具有耐磨变化切削条件的信号的变化率有关，例如切割速度。
参考文献
Boothroyd, G.（1961）金属切削温度的测定摄影技术。
英国J. Appl.物理学. 12，238-242.
Chao, B. T., Li, H. L. 和 Trigger, K. J.（1961）对刀腹的表面温度分布的实验研究Trans. ASME J. Eng. Ind. 83, 496–503.
Diei，EN和Dornfeld，D. A.（1987）从端面铣削过程的声发射—过程变量的影响。Trans ASME J. Eng. Ind. 109, 92–99.
Friedman, M. Y. and Lenz, E.（1970）切屑表面温度场的测定。
机械工程研究所19（1），395-398.
实验理论方法
Harris, A., Hastings, W. F.和Mathew, P.（1980）切削温度的试验测量。
见于：Proc. Int. Conf. on Manufacturing Engineering,墨尔本，8月25-27日，第30-35。
Iwata, I. and Moriwaki, T.（1977）对声发射中的应用工具传感进程的
磨损。机械工程研究所26（1），21-26。
Kakino, K.（1984）金属切削和磨削过程声发射监测3，108-116。
Miwa,Y., Inasaki, I. and Yonetsu, S.（1981）用声发射信号故障检测工具的过程，Trans JSME 47, 1680–1689.
Reichenbach, G. S.（1958）实验的金属切削温度分布测量。
Trans ASME 80, 525–540.
Schwerd, F. (1933) Uber die bestimmung des temperaturfeldesbeimspanablauf. Zeitschrift VDI 77,
211–216.
Shaw, M. C. (1984) 金属切削原理。牛津：Clarendon出版社。
Trent, E. M. (1991) 金属切削第三版。牛津：北海海涅曼。
Ueda, T., Sato, M. and Nakayama, K. (1998) 单晶钻石刀具温度的转变。 CIRP 47(1), 41–44.
Williams, J. E, Smart, E. F. and Milner, D. (1970)冶金的加工，第一部分. Metallurgia
6
力学进展
6.1简介
第2章介绍了最初的机械，热及摩擦学加工过程的报告。演示实验的报告研究表明，在剪切面角，摩擦角和前角之间没有独特的的关系;证据表明这部分可能受主剪切带加工硬化;切削速度与高温之间的关系和高应力条件下使摩擦面的摩擦角条件不足的影响。3至5章集中描述了工件和刀具材料的性能，刀具磨损和故障的本质和加工后的实验方法过程。这使得针对描述力学进展的背景下，导致有能力来预测从机械加工行为和物理性质的工作及其工具。
本章安排了除本介绍之外的三个部分：滑移线场模型，从而使成连续切屑形成具有很大的启示，但这最终是令人沮丧的，因为它最终没有提供去删除以上所指非唯一性的办法;考虑到建模的工作流引入应力变化的影响这消除了非唯一性，即使只通过一个近似的方式；第一个实例，以对切屑形成的正交模型来扩展更多的一般的三维（非正交）的条件。这是一个第2章与现代数值（有限元）制作经典材料之间的过渡章节第7章。
6.2滑线场模拟
第2章介绍了两个早期的平面的剪切角依赖摩擦和斜角的理论。根据Merchant（1945）（方程（2.9））切屑的形成发生在一个给定摩擦最低能量的条件下。据Lee和Shaffer（1951年）（方程（2.10）），剪切面的夹角是由在第二剪切带相关的塑性流动摩擦角规则。Lee和Shaffer的贡献首次是在slipline的切屑形成磁场模型。
6.2.1 滑移线场理论
滑移线场理论适用于平面应变（二维）的塑性流动。材料的力学性能被简化为刚性，完全塑料。这就是说，它的弹性模量被认为是不定的（刚性）及其塑性流动时发生的应用是最大剪应力达到某一临界值，k，它不随条件，如应变，应变率和温度流动的变化而变化。对于这样一个在平面上的理想化材料，应变塑性状态，滑移线场理论发展的压力和速度如何可以改变规则。这些被认为是在详细附录1之中。一个简短的部分在这里给出了摘要，足以使该理论应用到加工中。
首先：什么是滑移线和滑移线场;以及他们有用吗？一个平面材料的应力应变加载的分析结论是，在任何一点上都有两个正交方向，其中剪应力方向为最大值。此外，在这些方向直接应力是平等的（和平等的静水压力）。然而，这些方向可以从一个点到另一个点而改变。如果材料是加载塑性，应力状态完全是所描述的最大剪应力常数K值，以及方向和静水压力各不相同的点。 A线，一般弯曲，沿其长度最大剪应力方向都被称为滑移线。一个滑移线是正交曲线滑移在塑料地带现有生产线配套。滑线场理论是构建在特定情况下的滑移线场（例如规则加工）和计算领域内的静水压力的变化之上。
该文章摘自：Metal MachiningTheory and Applications
Thomas Childs
University of Leeds,UK
Katsuhiro Maekawa
Ibaraki University,Japan
Toshiyuki Obikawa
Tokyo Institute of Technology,Japan
Yasuo Yamane
Hiroshima University,Japan
http://www.arnoldpublishers.com
Copublished in North,Central and South America by
John Wiley & Sons Inc.,605 Third Avenue,
New York,NY 10158–0012
Experimental methods
(Chao et al.,1961) and on the chip surface (Friedman and Lenz,1970). With the development of infrared sensitive photographic film,temperature fields on the side face of a chipand tool have been recorded (Boothroyd,1961) and television type infrared sensitive video equipment has been used by Harris et al. (1980).
Infrared sensors have continued to develop,based on both heat sensing and semiconductor quantum absorption principles. The sensitivity of the second of these is greater than the first,and its time constant is quite small too in the range of ms to ms. Figure 5.21 shows a recent example of the use of the second type. Two sensors,anInSb type sensitive in the 1 mm to 5 mm wavelength range and a HgCdTetype,sensitive from 6 mm to 13 mm, were used:more sensitive temperature measurements may be made by comparing the signals from two different detectors.
Most investigations of temperature in metal cutting have been carried out to understand the process better. In principle,temperature measurement might be used for condition monitoring,for example to warn if tool flank wear is leading to too hot cutting conditions. However,particularly for radiant energy measurements and in production conditions,calibration issues and the difficulty of ensuring the radiant energy path from the cutting zone to the detector is not interrupted,make temperature measurement for such a purpose not reliable enough. Monitoring the acoustic emissions from cutting is
Fig. 5.21 Experimental set-up for measuring the temperature of a chip’s back surface at the cutting point, using a diamond tool and infrared light, after Ueda et al. (1998)
Acoustic emission 155
anotherway,albeit an indirect method,to study the state of the process,and this is considered next.
5.4Acoustic emission
The dynamic deformation of materials – for example the growth of cracks,the deformation of inclusions,rapid plastic shear,even grain boundary and dislocation movements is accompanied by the emission of elastic stress waves. This is acoustic emission (AE).Emissions occur over a wide frequency range but typically from 100kHz to 1MHz.Although the waves are of very small amplitude,they can be detected by sensors madefrom strongly piezoelectric materials,such as BaTiO3 or PZT (Pb(ZrxTi1–x)O3; x = 0.5 to0.6).
Figure 5.22 shows the structure of a sensor. An acoustic wave transmitted into thesensor causes a direct stressE(DL/L) where E is the sensor’s Young’s modulus, L is itlength and DL is its change in length. The stress creates an electric field
T = g33E(DL/L)(5.7a)
where g33 is the sensor material’s piezoelectric stress coefficient. The voltage across thesensor,TL,is then
V = g33EDL (5.7b)
Typical values of g33 and E for PZT are 24.4 × 10–3 Vm/N and 58.5GPa. It is possible,withamplification,to detect voltages as small as 0.01 mV. These values substituted intoequation (5.7b) lead to the possibility of detecting length changes DL as small as 7 × 10–15m:for a sensor with L = 10mm,that is equivalent to a minimum strain of 7 × 10–13. AE
Fig. 5.22 Structure of an AE sensor
156 Experimental methods
Fig. 5.23 An example of an AE signal and signal processingstrain sensing is much more sensitive than using wire strain gauges,for which the minimum detectable strain is around 10–6.
The electrical signal from an AE sensor is processed in two stages. It is first passedthrough a low noise pre-amplifier and a band-pass filter (≈100kHz to 1MHz). The resulting signal typically has a complicated form,based on events,such as in Figure 5.23. In thesecond stage of processing,the main features of the signal are extracted,such as thenumber of events,the frequency of pulses with a voltage exceeding some threshold valueVL,the maximum voltage VT,or the signal energy.
The use of acoustic emission for condition monitoring has a number of advantages. Asmall number of sensors,strategicallyplaced,can survey the whole of a mechanicalsystem. The source of an emission can be located from the different times the emissiontakes to reach different sensors. Its high sensitivity has already been mentioned. It is alsoeasy to record; and acoustic emission measuring instruments are lightweight and small.However,it also has some disadvantages. The sensors must be attached directly to thesystem being monitored:this leads to long term reliability problems. In noisy conditions itcan become impossible to isolate events. Acoustic emission is easily influenced by thestate of the material being monitored,its heat treatment,pre-strain and temperature. Inaddition,because it is not obvious what is the relationship between the characteristics ofacoustic emission events and the state of the system being monitored,there is even moreneed to calibrate or train the measuring system than there is with thermal radiationmeasurements.
In machining,the main sources of AE signals are the primary shear zone,the chip–tooland tool–work contact areas,the breaking and collision of chips,and the chipping andfracture of the tool. AE signals of large power are generally observed in the range 100kHzto 300kHz. Investigations of their basic properties and uses in detecting tool wear andchipping have been the subject of numerous investigations,for example Iwata andMoriwaki (1977),Kakino (1984) and Diei and Dornfeld (1987). The potential of using AE
is seen in Figure 5.24. It shows a relation between flank wear VB and the amplitude level
References 157
Fig. 5.24 Relation between flank wear VB and amplitude of AE signal, after Miwa et al. (1981)of an AE signal in turning a 0.45% plain carbon steel (Miwa,1981). The larger the flankwear,the larger the AE signal,while the rate of change of signal with wear changes withthe cutting conditions,such as cutting speed.
References
Boothroyd,G. (1961) Photographic technique for the determination of metal cutting temperatures.British J. Appl. Phys. 12,238–242.
Chao,B.T.,Li,H.L. and Trigger,K.J. (1961) An experimental investigation of temperature distribution at tool flank surface. Trans. ASME J. Eng. Ind. 83,496–503.
Diei,E.N. and Dornfeld,D.A. (1987) Acoustic emission from the face milling process – the effectsof process variables. Trans ASME J. Eng. Ind. 109,92–99.
Friedman,M.Y. and Lenz,E. (1970) Determination of temperature field on upper
chip face. AnnalsCIRP 19(1),395–398.
158 Experimental methods
Harris,A.,Hastings,W.F. and Mathew,P. (1980) The experimental measurement of cutting temperature. In: Proc. Int. Conf. on Manufacturing Engineering,Melbourne,25–27 August,pp. 30–35.
Iwata,I. and Moriwaki,T. (1977) An application of acoustic emission to in-process sensing of toolwear. Annals CIRP 26(1),21–26.
Kakino,K. (1984) Monitoring of metal cutting and grinding processes by acoustic emission. J.Acoustic Emission 3,108–116.
Miwa,Y.,Inasaki,I. and Yonetsu,S. (1981) In-process detection of tool failure by acoustic emissionsignal. Trans JSME 47,1680–1689.
Reichenbach,G.S. (1958) Experimental measurement of metal cutting temperature distribution.Trans ASME 80,525–540.
Schwerd,F. (1933) Uber die bestimmung des temperaturfeldesbeimspanablauf. Zeitschrift VDI 77,211–216.
Shaw,M.C. (1984) Metal Cutting Principles. Oxford:Clarendon Press.Trent,E.M. (1991) Metal Cutting,3rd edn. Oxford:Butterworth Heinemann.Ueda,T.,Sato,M. and Nakayama,K. (1998)
The temperature of a single crystal diamond tool inturning. Annals CIRP 47(1),41–44.
Williams,J.E,Smart,E.F. and Milner,D. (1970) The metallurgy of machining,Part 1. Metallurgia
6
Advances in mechanics
6.1Introduction
Chapter 2 presented initial mechanical,thermal and tribological considerations of themachining process. It reported on experimental studies that demonstrate that there is nounique relation between shear plane angle,friction angle and rake angle; on evidence thatpart of this may be the influence of workhardening in the primary shear zone; on hightemperature generation at high cutting speeds; and on the high stress conditions on the rakeface that make a friction angle an inadequate descriptor of friction conditions there.Chapters 3 to 5 concentrated on describing the properties of work and tool materials,thenature of tool wear and failure and on experimental methods of following the machiningprocess. This sets the background against which advances in mechanics may be described,leading to the ability to predict machining behaviours from the mechanical and physicalproperties of the work and tool.
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