- Email: [email protected]
Effects of Tool Geometry on Acoustic Emission Intensity
Effects of Tool Geometry on Acoustic Emission Intensity Dr. M. Lee, Dr. D. G. Wildes, Mr. S. R. Hayashi and Dr. B. Keramati; GE Corporate Research and Development Center - Submitted by Dr. B. F. von Turkovich (1) Received on January 18,1988
ABSTRACT A natural consequence of tool wear is a change of tho tool-chip interface geometry. Therefore, any sensor which responds to a geometric change of the cutting edge is a potential in-process tool wear monitor. In this study, the average acoustic emission energy from various metal cutting processes was monitored along with the cutting power and the cutting forces. The results show that the average acoustic energy is a strong function of the rake angles and the metal removal rate. If other sensors are used to compensate for changes in the metal removal rate, the average acoustic energy can be a reliable tool wear indicator.
KEY WORDS
tool wear, sensor, acoustic emission, machining, tool geometry
1. Introduction Most physical phenomena, either microscopic or macro related to the wear processes of metal cutting tools generate acoustic e n e r T t 3 . In principle, most of these acoustic emission(AE) events should be emitting detectable signals. However, currently there are no technical means to isolate the specific signal from a particular microscopic event from the complex acoustic noise of the overall cutting activity. Monitoring the progress of tool wear through tracking signals from any specific microscopic wear event, therefore, is not possible. An alternative approach is to search for a readily detectable signal associated with the accumulated consequences of many microscopic wear events in time. A natural consequence of tool wear is the change of the cutting edge and the toolchip contact interface geometry. Therefore, any cutting tool sensor which is sensitive to the geometric change of cutting edge is a potential candidate for an inprocess tool wear monitor. In this study, average AE energy from lathe turning operations of metallic alloys was monitored over an intermediate frequency band along with the cutting power and the cutting forces. The objectives were to observe the effect of geometric modifications of cutting edges and the resulting variations of tool-chip and tool-workpieceinterface conditions on the total AE signal. Experimental variables include different workpiece and cutting tool materials. A Limited number of experiments were carried out on different machine tools. Also, some controlled experiments were performed under orthogonal machining conditions and attempts were made to identify specific events in the observed AE signal and correlate the observations with physical events monitored by a high speed video system. The goal of this study was to obscrvc signal variations under broad range of operating conditions and to identify common patterns which might be useful for in-process monitoring of cutting edge conditions. 2 Erpenments 2.1 Equipment and Procedures A Mazak Slant Turn 30 NC lathe with a GE Mark Century 2000 control was used
for most of the experiments. The machine is equipped with a spindle-power monitor, a three-axis dynamometer, and a vibration sensor with a resonant frequency of about 70 kHz. The vibration signal is high pass filtered at 30 kHz. For the analysis of AE signal energy variation in time domain, the signal from the sensor was processed through an envelope detector followed by a SO0 hertz low pass filte Details of this experimental procedure are described in an earlier publkation('). The orthogonal machining apparatus is a modified horizontal milling machine to allow for low speed (4pfmin.) operation. Thin workpiece plates are mounted on the table, while an indexable tool holder is mounted on the machine frame at a stationary position. The tool holder is attached to a rotating fixture for rake angle adjustment. A threeaxis piezoelectric dynamometer under the workpiece monitors the forces. Two AE sensors are mounted on the system, one on the tool holder and another on the workpiece. Also,two low frequency vibration sensors with proper band pass filters, one ranging from 150 Hz to 20 kHz and another ranging from 20 kHz to 100 KHz, are attached to the tool holder. The AE signals are passed through 100 kHz high pass filters before recording. In addition, a high speed, 2000 frames per second video system (Spin Physics SP2OOO Motion Analysis System) with hvo cameras is used to record both the cross-sectional view of the chips and an overall view of the cutting process. S i a l pulses from the video system identifying each frame of the picture are recorded on a magnetic tape (Honeywell 101), along with the force and vibration signals. Therefore, the system can identify specific changes in force components and vibration signals within various frequency ranges, and can correlate these changes with corresponding particular cutting events observed with the video system. For a quick screening of signals from either experiment, a dual-channel signal analyzer (Hewlet Packard Model 356%) and a digital oscilloscope are used. Because the limiting frequency of the signal analyzer is 100 kHz,slower playback tape speed (1/16) is used to examine higher frequency signals. For detailed analysis, a Preston AID converter with an analog anti-aliasing filter from Precision Filters is available for the digitization of the taped signals, and a PerkinElmer Model 3210 minicomputer is used for further signal processing. A signal processing and graphics software package (SPAGS) developed by Cranfield Data Systems Ltd. is available for detailed signal analysis.
Annals of the ClRP Vol. 37/1/1988
Cutting tools used for the orthogonal machining experiments were mostly steel cutting grade cemented carbide indexable inserts. Some of these tools were coated with Tic, Tfi, and 0 by a chemical vapor deposition process. Workpieces were SAE 1045 stee303stainless steel, Ti-6AI-4V. 70/30 brass, and gray cast iron. A thin ledge (1.5 mm) with less than 5 mm height was machined on each workpiece plate to ensure that light cuts could be made with reasonable lateral rigidity. Most cuts were 15 cm long at 4 meters per minute and down feed per pass was 0.25 to 0.4 mm. Several type of ceramic tools were also used in the case of the lathe turning tests depending upon the particular workpieEe materials. Workpiece materials used in the lathe experiments include International Nickel AUoy 718, Ti-6-4, 304 stainless steel, gray cast iron, low carbon steels, and chilled Gist iron. 2.2 Results 22.1 Lathe Turning Tests Since there are no references to estimate the expected magnitude of AE signal energy depending upon the change of cutting conditions or workpiece materials, some experiments were carried out to establish relative variations of AE energy amplitude in relation to various machining conditions. First four workpiece materials with significantly ditferent machining characteristics were turned on a lathe using 1.27 cm square inserts in a tool holder with -5 degree back rake, -5 degree side rake, and 15 degree side cutting edge angle. The objective of this series of tests was to identify a material property, or combination of properties, which could be used as an approximate indicator of the expected AE signal intensity. As shown in Table 1, the four workpieces chosen have a fairly wide range of hardness, and significantly ditferent specific power requirements for inaclhing. ThTqccXic cutting power for the materials was from the machining data handbook and they are substantially independent of cutting condtions. The cutting speed used for each test was 92 meters per minute, and the depth-ofcut and feed per revolution were 2.54 mm and 0.2 mm, respectively. The AE energy listed is an average value of several experiments on each material. It should be noted, however, that the AE signal was processed in several steps as described earlier and the listed magnitude of AE energy is useful only for relative comparison of results listed on the table. The results show that materials with high hardness and, hence, requiring high specific power for machining generate high energy level AE. The results also showed that materials normally forming highly segmented chips tend to be a more active source of AE. TABLE 1 AVERAGE AE ENERGY AND SPECIFIC POWER FOR MACHINING
TOOL
SPEED DEPTHOFCUT: FEEDPERREV
1.27cm, 15' LEAD 91 mfmin. 2.54mm 2mm
AVERAGE NOLT)
SPECIFIC POWER FOR MACYNING WAITSICM /MIN
1045 STEEL (Rc-30)
0.07
so
TITANIUM 6Al-4V (Rc-38)
0.35
55-64
INCO 718
0.5
91-114
2.5
155
AE ENERGY MATERIAL
(Rc-43) CHILLED CAST IRON (Rc-58)
The physical properties of workpiece materials have a strong influence on the AE activity of cutting and the degree of dependence of AE activity on specific cutting parameter is also related to the characteristics of the workpiece. For example, materials which generate high intensity AE from cutting seem to show a very strong connection between the depth of cut and the intensity of the AE. As shown
57
in Figure 1, the average AE from machining INCO alloy 718 increases very rapidly with increasing depth-of-cut, but the average AE from machining 1015 steel increases relatively little over the same range of depth-of-cut. AU tests shown in the Figure 1 were done with square inserts with the same tool holder (described earlier), and the cutting speed was 183 surface meters per minute. Use of a clamp-we chip breaker increased the level of average AE intensity somewhat, as shown in the figure. Under the same machining conditions, changing the side cutting edge angle (lead angle) showed a significant effect on the average AE intensity. As shown in Figure 2, a square tool with 45 degree lead angle generates much higher average AE than one with 15 degree lead angle. For a straight cutting edge, increasing the lead angle increases the length of the cutting edge engaged and the width of the chip, Magnitude of this difference increases with increasing depth of cut. However, the AE energy from machining with round insert was mostly lower than the AE energy from straight edge cuts of equivalent depth of cut, although the actual length of cutting edge engaged in cutting for the round tool for the same depthof-cut is longer than that of the straight edges over the entire range of depth-of-cut studied. In a normal cutting state, if some dynamic variations occur in the specific cutting conditions, both the average A E intensity and the magnitude of the average cutting power change in the same general manner. However, when the cutting edge starts to degrade abruptly, the relationship between the AE intensity and the cutting power becomes unpredictable. Figure 3 shows a strip chart trace of the average AE output and corresponding cutting power recorded simultaneously while machining an IN 718 alloy using a ceramic cutting tool on a vertical turret lathe. At about the midpoint of the recorded cut, the cutting edge started to break-up gradually by small fragments, but the process was continued until the end of the planned cut. As shown in the figure, gradual break-up of the cutting edge caused an erratic, but gradual, decrease of the average AE,whereas the cutting power increased somewhat at the same time. The gentle slope in the power curve is due to a gradual increase of motor speed in order to maintain constant cutting speed over a decreasing workpiece diameter. One possible cause of the decrease in the AE intensity is an effective decrease of the rake angle as a result of the partial edge break-up. Such a result can decrease the average AE while increasing the cutting horsepower, according to a quantitative mod.@f AE emission from machining proposed by Kannatey-Asibu,Jr. and Dornfeld , Although this model is based on a simple orthogonal machining case, there is no clear physical reason why the same trend should not hold for other more complex cutting geometries. To verify the possible effect of the rake angle in the laboratory, several series of experiemnts were carried out. Ordinarily the rake angles are determined by the specific tool holders used. Since only a limited range of rake angles are used in commercial practice. n o experimental approaches were followed to generate a range of rake angles for this study. In the fist approach, the bottom of a commercial tool holder was ground to produce -10 degree side rake angle. The holder also had -5 degree back rake which was not modified. Therefore, the net rake angles are slightly different from the angles measured on the side of tool holder. Several wedges were ground with 5 degree increment and these wedges were used to shim under the tool holder to create appropriate side rake angles. The second approach consisted of grinding the rake face of inserts to create the desired rake angles. However, generating accurate rake angles by this approach was extremely difficult. Instead, the approach was modified by using a set of 1.27ci-n diameter round ceramic inserts which were cylindrically ground to form a rake face in the shape of a truncated cone. N inserts had negative rake angles ranging from -5 to -30 degrees in 5 degree interVal. A series of turning experiments was performed using the tilted tool holder to establish the effect of very large negative rake angles on the magnitude of the AE signal. Using 1.27 cm square C-2 grade cemented carbide inserts, an INCO 718 alloy bar was machined at a speed of 61 surface meters per minute with 1.9 mm depth of cut and 0.18 mm feed per revolution. The measured average amplitude of the AE signal and the total cutting power are plotted against the nominal rake angles in Figure 4. As the results show, it was difficult to extract the clear trend of the AE signal from these experiments, although there seem to be a general decrease of AE energy with decreasing rake angle. The cutting power, however, continuously increased with decreasing rake angle. This series of experiments had two complications. The wedges which were inserted under the tool holder changed the transfer characteristics of AE signal through the fixture, making it difficult to reproduce the results consistently. Simply tilting the tool holder around the axis of the holder with a finite lead angle also moved a portion of the cutting edge below the center line of the workpiece but what effect it had on the AE activity is not known.
To avoid the problem of removing the tool holder between tests, the preground set of tools were used on a fixed tool holder. The workpiece was INCO 718 alloy, the tool material was aluminum oxide and the cutting speed was 213 meters per minute. The depth-of-cut and the feed per revolution were 1.8 mm and 0.18 m respectively. The average AE for various rake angles and the corresponding average cutting power values are shown in Figure 5. As shown in the figure, significant variations of the AE amplitude from test to test under the same machining conditions were observed for the -10 degree rake angle. The results in general were, however, much more reproducible than those using the tilted tool holders and were consistent for rake angles below -15 degrees. An interesting feature of this figure is the drastic shift of both the AE amplitude and the power from the -5 degree cut to the -10 degree cut. The AE amplitude increased significantly from -5 to -10 degrees while the cutting power decreased over the same range. Between -10 and -20degrees, the A E amplitude seems to decreases slightly, but the cutting power increases. After -20 degree, both the AE amplitude and the cutting power increased with further decrease of rake angle.
58
2.2.2 Orthogonal Machining Expenmen& In addition to the effect it has on the average energy level of the continuous portion of AE si worn cutting edges
v%
often increase the density of pulse events in the AE signal . However, very little is known about the sources of the randomly occuringAE pulses. By combining a high speed video recording system with the AE signal monitoring system, a series of experiments was conducted to identify the AE pulses with visually identifiable physical events. One problem encountered in this experiment was that the pulse signals have a widely varying range of energy level and that fully recording the high energy pulse events simultaneouslywith low energy continuous AE signal was extremely difficult. Therefore, the signal amplifer was adjusted to record only the desirable portion of signals useful for comparison with other equivalent cases. In ordcr to dctermine the desired level of amplification necessary for the AE kip.
nals from each sensor, screening experiments were carried out. During these experiments, the amplified output of the sensed signal was traced with an oscilloscope,and one camera of the video system was aimed at the screen of the oscilloscope. By adjusting the oscilloscope to trigger every time a pulse signal is received, the cutting process can be viewed on the screen of the video system while the AE pulse trace on the oscilloscope is projected on the small window on the same video screen. With the electronic gain in the sensing system set at a low level, only high energy pulse events were detected. Examinations of the recorded video tapes showed that the high energy AE pulses were not accompanied by any observable physical event. Many clearly observable discrete cutting events, such as chip breaking and chip-tool collisions, were not accompanied by sufficient energy AE pulse detectable at the low level setting of the signal amplifier. To eliminate the possibility that these high energy AE pulses might be originating from any moving or damaged parts in the machine tool, a polymer (PMMA) plate was mounted on the machine and the edge of the plate was ploughed over by a small PMMA plate mounted on the tool holder, simulating the motion and the force fluctuation similar to the light machining condition. No high energy AE pulses were detected during this experiment, indicating that the previously observed AE pulses originate from the cutting process itself. When the coated cutting tools were used, occasional packs of pulses appeared in the signal. Examination of the edge after the cut revealed damaged coating. However, the video tape segment corresponding to the AE pulse packs showed no observable significantphysical events.
To examine the effect of built-up edge formation on the AE signal, a cold rolled steel plate was machined with 0.38 mm down feed. These cuts created very severe built-up edges and caused extreme plastic deformation and occasional cracking in the workpiece ahead of the cutting edge, as observed by the video image of the cut. The cutting force also fluctuated along with the buildt-up and the break-away cycles of the chip. However, the AE signal from this cut was not intense and needed significantly higher amplificationfor recording. The AE signal from these severely fluctuating cuts showed fewer pulses than more smooth cuts of the same workpiece with 0.25 mm down feed. The relationship between the specific morphology of chips and the corresponding AE signal was evaluated further using grey cast iron and titanium-6Al-4V alloy. Cast irons form very fragmented chips, essentially by a brittle fracture process, and chips gcnerdly undeigo veiy little ductile deformation. Because the chips arc formed by a series of fragmentation processes, the AE signal from cast iron cuts showed almost a continuous series of pulses. Compared with equivalent cuts of cold rolled steel, the cutting force of cast iron cuts were low. However, average amplitude of the AE signal from cast iron was much higher than the signal from the equivalent cuts of cold rolled steel. It was apparent from the comparison of video recordings and corresponding segments of the sensor signals that intense plastic deformation during the cutting process has a strong effect on the cutting forces but a relatively insignificanteffect on the intensity of the AE signal. Because of their particular physical properties, titanium alloys form severely segmented chips. However, in contrast to cast iron, where chips are formed by a fracture process, the titanium alloy chips are formed by a highly localized cyclic shear deformation process. Examining the video record of a titanium alloy cut, the AE signal corresponding to first several chip segments was identified. The AE signal covering this section of cut is shown in Figure 6. The figure shows the > 100 kHz portion of the AE signal over the first 20 chip segments. Video images corresponding to the formation of the first three chip segments following the collision of chip with the chip breaker are shown in Figure 7. The graphs are generated using the dynamic signal analyzer in the time capture mode. The AE signal shows one packet of AE pulses per each chip segment with precise time correspondence between the two. The large packet at the end of the signal segment occured when the chip fractured and began lift off the rake face of tool as shown in the video image. The AE signal recorded through a sensor mounted on the workpiece was essentially the same as the signal observed by the sensor on the tool holder. Results of this study show that all discrete events in the chip forming process generate burst of AE signal. AU the specific events that were pursued, such as chip segmentation and chip/tool couision did correspond with an AE pulse trace. However, most of these signals. including the AE pulses from chip breaking and chip collision, are low energy AE events and their detection system requires high sensitivity. The number of potential sources of AE pulse at this high level of sensitivity, however, is very large. For example, when a stream of lubricant mist from an aerosol can was sprayed on the cutting tool, the generated AE noise was much more intense than the chip segmentation or chip breakage noise, overshadowing the entire signal. 3. Diwussionr
The relationship between cutting forces and the state of the cutting prooess is one of the most frequently investigated subjects of metal cutting science. If the cutting forces are readily measurable or even the net cutting power can be accurately
measured, the information can be very valuable for on-line diagnosis of metal cutting. Since monitoring of AE signal from cutting processes is simply accomplished for most machine tools, it could be very useful if a dependable relationship could be established between the net power consumed for cutting and the corresponding AE signal energy. Results of this study show some very useful information concerning this relationship. The relationship between specific physical and mechanical parameters of cutting with the AE energy and the net cutting energy is complex; some parameters have a similar qualitative &ect in both cases, but others have opposite effect. Under similar conditions, materials requiring high specific cutting power will generate higher energy AE during cutting. In this respect, materials with higher hardness are likely to generate higher energy AE. It is important to note that the AEpower relationship is with the total net cutting power and that the specific power requirement for a specific material is only a good comparative indicator with other materials under similar conditions. AU cutting parameters which have positive relationship with the material removal rate and with the net power consumption also have positive relationship with the AE energy. These are depth of cut, feed, and cutting speed. The magnitude of the specific cutting power necessary for a given material is a qualitative indicator of how strong an effect these parame ters would have in each case. Over m practical cutting speed range the cutting forces decrease with increasing speed . The effect of cutting speed on the AE energy is, therefore, the opposite of the effect on the cutting forces.
?4
The effect of the tool and the cutting geometry on the AE energy is quite different from the effect of other cutting parameters. Change of these geometric parameters showed significant effect on the AE energy, although it has no effect on the material removal rate. The most important pariyfeter is the rake angle. As reported first by Kannatey-Asibu and Dornfeld , increasing the rake angle increases the average AE energy. Results of this study also generally support the observation that the decreasing rake angle has a tendency to decrease the AE energy until the rake angle become severly negative. Over this range of rake angles, the AE energy level decreases while the forces and the cutting power increases. This relationship is very valuable since any in-process condition such as edge wear the resulting change of effective rake angle should have an opposing effect on the AE energy and other parameters indicating mechanical cutting energy. Furthermore, the indicator is only a relative variation of respective signals in time, not requiring specific knowledge on the absolute values of each signal. This point is particularly important since possible application of this approach will not require an accurate knowledge of equipment sensitivity or predetermined reference information as many force base tool monitoring systems do often require.
chip making activity and the average intensity of AE. For a relatively broad range of cutting edge angles and shapes, where most practical machining is done, change of conditions increasing the power consumption can reduce the AE intensity. Therefore, any change of cutting edge conditions related to these specific parameters can result in diverging trend of change in the mechanical power consumption and the AE intensity. Conditions increasing the severity and the magnitude of chip tool contact interface seem to increase the AE intensity. All discrete events in chip making action that were pursued generate AE pulses which can be detected with a sensing system of adequate sensitivity. The energy of each pulse depends on the rate of the event itself. Very fast events, such as brittle fracture and adiabatic shear, emit higher energy AE pulses than the slow rate periodic shear deformation of chips. These type of events, however, tend to decrease the werall energy consumed for the chip making action.
References [l]
Lee, M., Thomas, C. E., and Wild-,
D. G., 1987, "Prospects for In-Process Dngnosis of Metal Cutting by Monitoring Vibration Signals," Journal of Materials Science, 22( 11): 3821.
[2] Iwata, K and Moriwaki, M., 1971, "An Application of Acoustic Emission Measurement to In-Process Sensing of Tool," Annals of the CIRF', 2 5 2126. [3] Hayashi, S. R., Thomas, C. E., Davis, R. K, McKnight, W S.,and Roberts, C. R, 1985, "Automatic Tool Touch and Breakage Detection in Turning,'' Int. J. of Materials and Product Technology, vol. 1, no. 1: 113-129. [4]
Machining Data Handbook, 3rd Edition, Machinability Data Center, Metcut Research Associates Inc., Cincinnati, Ohio 1980.
IS] Kannatey-Asibu, Jr.. E. and Dornfeld, D., 1981, "Quantitative Relationships for Acoustic Emission from Orthogonal Metal Cutting," Trans. ASME Ser. E, Journal of Engineering for Industry, 103: 330-340. [6] Zorev, N. N., 1966, Metal Cutting Mechanics, Translated by H. S. H. Massey, Pergamon Press, New York.
Several results of this study also show that the chip-tool rake face contact conditions seem to have a very strong influence on the energy of AE signal. For example, increasing chiptool contact area by increasing the lead angle without changing other cutting parameters increased the AE energy level significantly (Fig. 2).
2$?
e effects of increasing the rake angle is increasing the chip-tool contact The positive relationship between the rake angle and the AE energy, therefore implies a similar relationship between the chiptool contact length and the AE energy Cnmpariron of cuts with the same depth of cut and feed using round and straight edge inserts shows that the curved underside chip formed by the round edge generates significantly lower energy AE signal compare with the straight edge cuts (Fig. 2), although the actual length of cuIting edge engaged is longer for the round tools. This observation implies that not only the size of the chip-tool contact area but the contact geoemtry also have strong effects on the AE energy. This point can be surported further by the results shown in Figure 5. Changing the f i t rake face of a round tool to a truncated conical shape drastically increased the AE energy as compared with the -5 and -10 degree cases shown in Figure 5. It should be very interesting to know if the apparent strong effect of the chip-tool interface on the AE signal energy is an indication of the interface being a significantsource of the AE. Orthogonal machining experiments showed that all physical discrete events in the cutting action generate packets of AE pulses. The energy content of each AE pulse packet is related to the rate of the event. Brittle fracture and addiabatic shear type events generate higher energy AE pulses compared with the slow rate shear deformation of steel. If the frequency of the events is very high, such as the fragmentingcast iron chips, the density of pulses is so high that the signal becomes nearly continuous and the resulting average AE level is high. These discrete events, however, make little contribution to the required mechanical cutting power. Conditions resulting in the thickeningof the shear zone and severe plastic deformation increase the cutting power requirement but have little effect on the AE energy. Excessive deformation of chips against the tool surface, such as cutting with very large negative rake angle tools, however, changes the chip-tool interface conditions significantly enough that the AE energy increases.
i
MPR14FQn (mm)
Figure 1.
Average AE signal amplitude vs Ihe depth-of-cutfor machining INCO AUoy 718 and AISI 1045 steel. WORKPIECE IN718 TOOL MATERIAL: KYON X K X )
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5
e
4. swnmory
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Effect of various physical and geometric parameters in machining on the acoustic emission activities of metal cutting was explored through a series of lathe turning and orthogonal machining experiments.
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In general, if the cutting edge shape and the cutting angles are unchanged, a positive correlation can be established between the mechanical energy consumed for the chip making activity and the average intensity of the AE signal during the cut. Therefore, machining parameters increasing the material removal rate such as speed, depth of cut, and feed will increase the average intensity of AE signal. Tough to machine materials such as high temperature alloys and hard steels requiring high cutting power generdy accompany high intcnsity AE. The degree of dependence of the average AE intensity on the material removal rate for these types of tough to machine materials is, therefore, also high. The shape of cutting edge or the cutting edge angles, however, can have significant effect on the relationship between the total energy consumed for the
4-
El
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/ 01 0
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1
I 2
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0EPTH.OF.CUT (mm)
Figure 2.
AverageAE amplitudevs depth-of-cutfor 1.27 cm square and round inserts.
59
CUTTING TIME(SEC0ND)
Figure 3.
A strip chart recording of the average AE and the corresponding cutting horse power for machining a INCO Alloy 718 using a ceramic insert. The cutting edge began to chip gradually at the point where the AE amplitude starts decrease.
1
1
2.01
-30
-20
0
-10
RAKE ANGLE (DEGREE)
Figure 4.
Average AE amplitude and cutting power vs the rake angle of 1.27 M square inserts machining INCO AUoy 718.
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Figure 5.
Average AE amplitude vs the rake angle of 1.27 cm diameter round ceramic inserts machining INCO Alloy 718. The rake face of inserts was ground cylindrically to form listed rake angleswith respect to the axis of the cylinder.
Figure 6.
The AE signal from machining titanium alloy at 4 meters per minute. Each packet of AE pulses corresponds to shear separation of individual chip scgmcnts.
60
Figure 7.
Video images of titanium chips corresponding to the beginniag and the end of the AE signal shown in Figure 6.
ABSTRACT A natural consequence of tool wear is a change of tho tool-chip interface geometry. Therefore, any sensor which responds to a geometric change of the cutting edge is a potential in-process tool wear monitor. In this study, the average acoustic emission energy from various metal cutting processes was monitored along with the cutting power and the cutting forces. The results show that the average acoustic energy is a strong function of the rake angles and the metal removal rate. If other sensors are used to compensate for changes in the metal removal rate, the average acoustic energy can be a reliable tool wear indicator.
KEY WORDS
tool wear, sensor, acoustic emission, machining, tool geometry
1. Introduction Most physical phenomena, either microscopic or macro related to the wear processes of metal cutting tools generate acoustic e n e r T t 3 . In principle, most of these acoustic emission(AE) events should be emitting detectable signals. However, currently there are no technical means to isolate the specific signal from a particular microscopic event from the complex acoustic noise of the overall cutting activity. Monitoring the progress of tool wear through tracking signals from any specific microscopic wear event, therefore, is not possible. An alternative approach is to search for a readily detectable signal associated with the accumulated consequences of many microscopic wear events in time. A natural consequence of tool wear is the change of the cutting edge and the toolchip contact interface geometry. Therefore, any cutting tool sensor which is sensitive to the geometric change of cutting edge is a potential candidate for an inprocess tool wear monitor. In this study, average AE energy from lathe turning operations of metallic alloys was monitored over an intermediate frequency band along with the cutting power and the cutting forces. The objectives were to observe the effect of geometric modifications of cutting edges and the resulting variations of tool-chip and tool-workpieceinterface conditions on the total AE signal. Experimental variables include different workpiece and cutting tool materials. A Limited number of experiments were carried out on different machine tools. Also, some controlled experiments were performed under orthogonal machining conditions and attempts were made to identify specific events in the observed AE signal and correlate the observations with physical events monitored by a high speed video system. The goal of this study was to obscrvc signal variations under broad range of operating conditions and to identify common patterns which might be useful for in-process monitoring of cutting edge conditions. 2 Erpenments 2.1 Equipment and Procedures A Mazak Slant Turn 30 NC lathe with a GE Mark Century 2000 control was used
for most of the experiments. The machine is equipped with a spindle-power monitor, a three-axis dynamometer, and a vibration sensor with a resonant frequency of about 70 kHz. The vibration signal is high pass filtered at 30 kHz. For the analysis of AE signal energy variation in time domain, the signal from the sensor was processed through an envelope detector followed by a SO0 hertz low pass filte Details of this experimental procedure are described in an earlier publkation('). The orthogonal machining apparatus is a modified horizontal milling machine to allow for low speed (4pfmin.) operation. Thin workpiece plates are mounted on the table, while an indexable tool holder is mounted on the machine frame at a stationary position. The tool holder is attached to a rotating fixture for rake angle adjustment. A threeaxis piezoelectric dynamometer under the workpiece monitors the forces. Two AE sensors are mounted on the system, one on the tool holder and another on the workpiece. Also,two low frequency vibration sensors with proper band pass filters, one ranging from 150 Hz to 20 kHz and another ranging from 20 kHz to 100 KHz, are attached to the tool holder. The AE signals are passed through 100 kHz high pass filters before recording. In addition, a high speed, 2000 frames per second video system (Spin Physics SP2OOO Motion Analysis System) with hvo cameras is used to record both the cross-sectional view of the chips and an overall view of the cutting process. S i a l pulses from the video system identifying each frame of the picture are recorded on a magnetic tape (Honeywell 101), along with the force and vibration signals. Therefore, the system can identify specific changes in force components and vibration signals within various frequency ranges, and can correlate these changes with corresponding particular cutting events observed with the video system. For a quick screening of signals from either experiment, a dual-channel signal analyzer (Hewlet Packard Model 356%) and a digital oscilloscope are used. Because the limiting frequency of the signal analyzer is 100 kHz,slower playback tape speed (1/16) is used to examine higher frequency signals. For detailed analysis, a Preston AID converter with an analog anti-aliasing filter from Precision Filters is available for the digitization of the taped signals, and a PerkinElmer Model 3210 minicomputer is used for further signal processing. A signal processing and graphics software package (SPAGS) developed by Cranfield Data Systems Ltd. is available for detailed signal analysis.
Annals of the ClRP Vol. 37/1/1988
Cutting tools used for the orthogonal machining experiments were mostly steel cutting grade cemented carbide indexable inserts. Some of these tools were coated with Tic, Tfi, and 0 by a chemical vapor deposition process. Workpieces were SAE 1045 stee303stainless steel, Ti-6AI-4V. 70/30 brass, and gray cast iron. A thin ledge (1.5 mm) with less than 5 mm height was machined on each workpiece plate to ensure that light cuts could be made with reasonable lateral rigidity. Most cuts were 15 cm long at 4 meters per minute and down feed per pass was 0.25 to 0.4 mm. Several type of ceramic tools were also used in the case of the lathe turning tests depending upon the particular workpieEe materials. Workpiece materials used in the lathe experiments include International Nickel AUoy 718, Ti-6-4, 304 stainless steel, gray cast iron, low carbon steels, and chilled Gist iron. 2.2 Results 22.1 Lathe Turning Tests Since there are no references to estimate the expected magnitude of AE signal energy depending upon the change of cutting conditions or workpiece materials, some experiments were carried out to establish relative variations of AE energy amplitude in relation to various machining conditions. First four workpiece materials with significantly ditferent machining characteristics were turned on a lathe using 1.27 cm square inserts in a tool holder with -5 degree back rake, -5 degree side rake, and 15 degree side cutting edge angle. The objective of this series of tests was to identify a material property, or combination of properties, which could be used as an approximate indicator of the expected AE signal intensity. As shown in Table 1, the four workpieces chosen have a fairly wide range of hardness, and significantly ditferent specific power requirements for inaclhing. ThTqccXic cutting power for the materials was from the machining data handbook and they are substantially independent of cutting condtions. The cutting speed used for each test was 92 meters per minute, and the depth-ofcut and feed per revolution were 2.54 mm and 0.2 mm, respectively. The AE energy listed is an average value of several experiments on each material. It should be noted, however, that the AE signal was processed in several steps as described earlier and the listed magnitude of AE energy is useful only for relative comparison of results listed on the table. The results show that materials with high hardness and, hence, requiring high specific power for machining generate high energy level AE. The results also showed that materials normally forming highly segmented chips tend to be a more active source of AE. TABLE 1 AVERAGE AE ENERGY AND SPECIFIC POWER FOR MACHINING
TOOL
SPEED DEPTHOFCUT: FEEDPERREV
1.27cm, 15' LEAD 91 mfmin. 2.54mm 2mm
AVERAGE NOLT)
SPECIFIC POWER FOR MACYNING WAITSICM /MIN
1045 STEEL (Rc-30)
0.07
so
TITANIUM 6Al-4V (Rc-38)
0.35
55-64
INCO 718
0.5
91-114
2.5
155
AE ENERGY MATERIAL
(Rc-43) CHILLED CAST IRON (Rc-58)
The physical properties of workpiece materials have a strong influence on the AE activity of cutting and the degree of dependence of AE activity on specific cutting parameter is also related to the characteristics of the workpiece. For example, materials which generate high intensity AE from cutting seem to show a very strong connection between the depth of cut and the intensity of the AE. As shown
57
in Figure 1, the average AE from machining INCO alloy 718 increases very rapidly with increasing depth-of-cut, but the average AE from machining 1015 steel increases relatively little over the same range of depth-of-cut. AU tests shown in the Figure 1 were done with square inserts with the same tool holder (described earlier), and the cutting speed was 183 surface meters per minute. Use of a clamp-we chip breaker increased the level of average AE intensity somewhat, as shown in the figure. Under the same machining conditions, changing the side cutting edge angle (lead angle) showed a significant effect on the average AE intensity. As shown in Figure 2, a square tool with 45 degree lead angle generates much higher average AE than one with 15 degree lead angle. For a straight cutting edge, increasing the lead angle increases the length of the cutting edge engaged and the width of the chip, Magnitude of this difference increases with increasing depth of cut. However, the AE energy from machining with round insert was mostly lower than the AE energy from straight edge cuts of equivalent depth of cut, although the actual length of cutting edge engaged in cutting for the round tool for the same depthof-cut is longer than that of the straight edges over the entire range of depth-of-cut studied. In a normal cutting state, if some dynamic variations occur in the specific cutting conditions, both the average A E intensity and the magnitude of the average cutting power change in the same general manner. However, when the cutting edge starts to degrade abruptly, the relationship between the AE intensity and the cutting power becomes unpredictable. Figure 3 shows a strip chart trace of the average AE output and corresponding cutting power recorded simultaneously while machining an IN 718 alloy using a ceramic cutting tool on a vertical turret lathe. At about the midpoint of the recorded cut, the cutting edge started to break-up gradually by small fragments, but the process was continued until the end of the planned cut. As shown in the figure, gradual break-up of the cutting edge caused an erratic, but gradual, decrease of the average AE,whereas the cutting power increased somewhat at the same time. The gentle slope in the power curve is due to a gradual increase of motor speed in order to maintain constant cutting speed over a decreasing workpiece diameter. One possible cause of the decrease in the AE intensity is an effective decrease of the rake angle as a result of the partial edge break-up. Such a result can decrease the average AE while increasing the cutting horsepower, according to a quantitative mod.@f AE emission from machining proposed by Kannatey-Asibu,Jr. and Dornfeld , Although this model is based on a simple orthogonal machining case, there is no clear physical reason why the same trend should not hold for other more complex cutting geometries. To verify the possible effect of the rake angle in the laboratory, several series of experiemnts were carried out. Ordinarily the rake angles are determined by the specific tool holders used. Since only a limited range of rake angles are used in commercial practice. n o experimental approaches were followed to generate a range of rake angles for this study. In the fist approach, the bottom of a commercial tool holder was ground to produce -10 degree side rake angle. The holder also had -5 degree back rake which was not modified. Therefore, the net rake angles are slightly different from the angles measured on the side of tool holder. Several wedges were ground with 5 degree increment and these wedges were used to shim under the tool holder to create appropriate side rake angles. The second approach consisted of grinding the rake face of inserts to create the desired rake angles. However, generating accurate rake angles by this approach was extremely difficult. Instead, the approach was modified by using a set of 1.27ci-n diameter round ceramic inserts which were cylindrically ground to form a rake face in the shape of a truncated cone. N inserts had negative rake angles ranging from -5 to -30 degrees in 5 degree interVal. A series of turning experiments was performed using the tilted tool holder to establish the effect of very large negative rake angles on the magnitude of the AE signal. Using 1.27 cm square C-2 grade cemented carbide inserts, an INCO 718 alloy bar was machined at a speed of 61 surface meters per minute with 1.9 mm depth of cut and 0.18 mm feed per revolution. The measured average amplitude of the AE signal and the total cutting power are plotted against the nominal rake angles in Figure 4. As the results show, it was difficult to extract the clear trend of the AE signal from these experiments, although there seem to be a general decrease of AE energy with decreasing rake angle. The cutting power, however, continuously increased with decreasing rake angle. This series of experiments had two complications. The wedges which were inserted under the tool holder changed the transfer characteristics of AE signal through the fixture, making it difficult to reproduce the results consistently. Simply tilting the tool holder around the axis of the holder with a finite lead angle also moved a portion of the cutting edge below the center line of the workpiece but what effect it had on the AE activity is not known.
To avoid the problem of removing the tool holder between tests, the preground set of tools were used on a fixed tool holder. The workpiece was INCO 718 alloy, the tool material was aluminum oxide and the cutting speed was 213 meters per minute. The depth-of-cut and the feed per revolution were 1.8 mm and 0.18 m respectively. The average AE for various rake angles and the corresponding average cutting power values are shown in Figure 5. As shown in the figure, significant variations of the AE amplitude from test to test under the same machining conditions were observed for the -10 degree rake angle. The results in general were, however, much more reproducible than those using the tilted tool holders and were consistent for rake angles below -15 degrees. An interesting feature of this figure is the drastic shift of both the AE amplitude and the power from the -5 degree cut to the -10 degree cut. The AE amplitude increased significantly from -5 to -10 degrees while the cutting power decreased over the same range. Between -10 and -20degrees, the A E amplitude seems to decreases slightly, but the cutting power increases. After -20 degree, both the AE amplitude and the cutting power increased with further decrease of rake angle.
58
2.2.2 Orthogonal Machining Expenmen& In addition to the effect it has on the average energy level of the continuous portion of AE si worn cutting edges
v%
often increase the density of pulse events in the AE signal . However, very little is known about the sources of the randomly occuringAE pulses. By combining a high speed video recording system with the AE signal monitoring system, a series of experiments was conducted to identify the AE pulses with visually identifiable physical events. One problem encountered in this experiment was that the pulse signals have a widely varying range of energy level and that fully recording the high energy pulse events simultaneouslywith low energy continuous AE signal was extremely difficult. Therefore, the signal amplifer was adjusted to record only the desirable portion of signals useful for comparison with other equivalent cases. In ordcr to dctermine the desired level of amplification necessary for the AE kip.
nals from each sensor, screening experiments were carried out. During these experiments, the amplified output of the sensed signal was traced with an oscilloscope,and one camera of the video system was aimed at the screen of the oscilloscope. By adjusting the oscilloscope to trigger every time a pulse signal is received, the cutting process can be viewed on the screen of the video system while the AE pulse trace on the oscilloscope is projected on the small window on the same video screen. With the electronic gain in the sensing system set at a low level, only high energy pulse events were detected. Examinations of the recorded video tapes showed that the high energy AE pulses were not accompanied by any observable physical event. Many clearly observable discrete cutting events, such as chip breaking and chip-tool collisions, were not accompanied by sufficient energy AE pulse detectable at the low level setting of the signal amplifier. To eliminate the possibility that these high energy AE pulses might be originating from any moving or damaged parts in the machine tool, a polymer (PMMA) plate was mounted on the machine and the edge of the plate was ploughed over by a small PMMA plate mounted on the tool holder, simulating the motion and the force fluctuation similar to the light machining condition. No high energy AE pulses were detected during this experiment, indicating that the previously observed AE pulses originate from the cutting process itself. When the coated cutting tools were used, occasional packs of pulses appeared in the signal. Examination of the edge after the cut revealed damaged coating. However, the video tape segment corresponding to the AE pulse packs showed no observable significantphysical events.
To examine the effect of built-up edge formation on the AE signal, a cold rolled steel plate was machined with 0.38 mm down feed. These cuts created very severe built-up edges and caused extreme plastic deformation and occasional cracking in the workpiece ahead of the cutting edge, as observed by the video image of the cut. The cutting force also fluctuated along with the buildt-up and the break-away cycles of the chip. However, the AE signal from this cut was not intense and needed significantly higher amplificationfor recording. The AE signal from these severely fluctuating cuts showed fewer pulses than more smooth cuts of the same workpiece with 0.25 mm down feed. The relationship between the specific morphology of chips and the corresponding AE signal was evaluated further using grey cast iron and titanium-6Al-4V alloy. Cast irons form very fragmented chips, essentially by a brittle fracture process, and chips gcnerdly undeigo veiy little ductile deformation. Because the chips arc formed by a series of fragmentation processes, the AE signal from cast iron cuts showed almost a continuous series of pulses. Compared with equivalent cuts of cold rolled steel, the cutting force of cast iron cuts were low. However, average amplitude of the AE signal from cast iron was much higher than the signal from the equivalent cuts of cold rolled steel. It was apparent from the comparison of video recordings and corresponding segments of the sensor signals that intense plastic deformation during the cutting process has a strong effect on the cutting forces but a relatively insignificanteffect on the intensity of the AE signal. Because of their particular physical properties, titanium alloys form severely segmented chips. However, in contrast to cast iron, where chips are formed by a fracture process, the titanium alloy chips are formed by a highly localized cyclic shear deformation process. Examining the video record of a titanium alloy cut, the AE signal corresponding to first several chip segments was identified. The AE signal covering this section of cut is shown in Figure 6. The figure shows the > 100 kHz portion of the AE signal over the first 20 chip segments. Video images corresponding to the formation of the first three chip segments following the collision of chip with the chip breaker are shown in Figure 7. The graphs are generated using the dynamic signal analyzer in the time capture mode. The AE signal shows one packet of AE pulses per each chip segment with precise time correspondence between the two. The large packet at the end of the signal segment occured when the chip fractured and began lift off the rake face of tool as shown in the video image. The AE signal recorded through a sensor mounted on the workpiece was essentially the same as the signal observed by the sensor on the tool holder. Results of this study show that all discrete events in the chip forming process generate burst of AE signal. AU the specific events that were pursued, such as chip segmentation and chip/tool couision did correspond with an AE pulse trace. However, most of these signals. including the AE pulses from chip breaking and chip collision, are low energy AE events and their detection system requires high sensitivity. The number of potential sources of AE pulse at this high level of sensitivity, however, is very large. For example, when a stream of lubricant mist from an aerosol can was sprayed on the cutting tool, the generated AE noise was much more intense than the chip segmentation or chip breakage noise, overshadowing the entire signal. 3. Diwussionr
The relationship between cutting forces and the state of the cutting prooess is one of the most frequently investigated subjects of metal cutting science. If the cutting forces are readily measurable or even the net cutting power can be accurately
measured, the information can be very valuable for on-line diagnosis of metal cutting. Since monitoring of AE signal from cutting processes is simply accomplished for most machine tools, it could be very useful if a dependable relationship could be established between the net power consumed for cutting and the corresponding AE signal energy. Results of this study show some very useful information concerning this relationship. The relationship between specific physical and mechanical parameters of cutting with the AE energy and the net cutting energy is complex; some parameters have a similar qualitative &ect in both cases, but others have opposite effect. Under similar conditions, materials requiring high specific cutting power will generate higher energy AE during cutting. In this respect, materials with higher hardness are likely to generate higher energy AE. It is important to note that the AEpower relationship is with the total net cutting power and that the specific power requirement for a specific material is only a good comparative indicator with other materials under similar conditions. AU cutting parameters which have positive relationship with the material removal rate and with the net power consumption also have positive relationship with the AE energy. These are depth of cut, feed, and cutting speed. The magnitude of the specific cutting power necessary for a given material is a qualitative indicator of how strong an effect these parame ters would have in each case. Over m practical cutting speed range the cutting forces decrease with increasing speed . The effect of cutting speed on the AE energy is, therefore, the opposite of the effect on the cutting forces.
?4
The effect of the tool and the cutting geometry on the AE energy is quite different from the effect of other cutting parameters. Change of these geometric parameters showed significant effect on the AE energy, although it has no effect on the material removal rate. The most important pariyfeter is the rake angle. As reported first by Kannatey-Asibu and Dornfeld , increasing the rake angle increases the average AE energy. Results of this study also generally support the observation that the decreasing rake angle has a tendency to decrease the AE energy until the rake angle become severly negative. Over this range of rake angles, the AE energy level decreases while the forces and the cutting power increases. This relationship is very valuable since any in-process condition such as edge wear the resulting change of effective rake angle should have an opposing effect on the AE energy and other parameters indicating mechanical cutting energy. Furthermore, the indicator is only a relative variation of respective signals in time, not requiring specific knowledge on the absolute values of each signal. This point is particularly important since possible application of this approach will not require an accurate knowledge of equipment sensitivity or predetermined reference information as many force base tool monitoring systems do often require.
chip making activity and the average intensity of AE. For a relatively broad range of cutting edge angles and shapes, where most practical machining is done, change of conditions increasing the power consumption can reduce the AE intensity. Therefore, any change of cutting edge conditions related to these specific parameters can result in diverging trend of change in the mechanical power consumption and the AE intensity. Conditions increasing the severity and the magnitude of chip tool contact interface seem to increase the AE intensity. All discrete events in chip making action that were pursued generate AE pulses which can be detected with a sensing system of adequate sensitivity. The energy of each pulse depends on the rate of the event itself. Very fast events, such as brittle fracture and adiabatic shear, emit higher energy AE pulses than the slow rate periodic shear deformation of chips. These type of events, however, tend to decrease the werall energy consumed for the chip making action.
References [l]
Lee, M., Thomas, C. E., and Wild-,
D. G., 1987, "Prospects for In-Process Dngnosis of Metal Cutting by Monitoring Vibration Signals," Journal of Materials Science, 22( 11): 3821.
[2] Iwata, K and Moriwaki, M., 1971, "An Application of Acoustic Emission Measurement to In-Process Sensing of Tool," Annals of the CIRF', 2 5 2126. [3] Hayashi, S. R., Thomas, C. E., Davis, R. K, McKnight, W S.,and Roberts, C. R, 1985, "Automatic Tool Touch and Breakage Detection in Turning,'' Int. J. of Materials and Product Technology, vol. 1, no. 1: 113-129. [4]
Machining Data Handbook, 3rd Edition, Machinability Data Center, Metcut Research Associates Inc., Cincinnati, Ohio 1980.
IS] Kannatey-Asibu, Jr.. E. and Dornfeld, D., 1981, "Quantitative Relationships for Acoustic Emission from Orthogonal Metal Cutting," Trans. ASME Ser. E, Journal of Engineering for Industry, 103: 330-340. [6] Zorev, N. N., 1966, Metal Cutting Mechanics, Translated by H. S. H. Massey, Pergamon Press, New York.
Several results of this study also show that the chip-tool rake face contact conditions seem to have a very strong influence on the energy of AE signal. For example, increasing chiptool contact area by increasing the lead angle without changing other cutting parameters increased the AE energy level significantly (Fig. 2).
2$?
e effects of increasing the rake angle is increasing the chip-tool contact The positive relationship between the rake angle and the AE energy, therefore implies a similar relationship between the chiptool contact length and the AE energy Cnmpariron of cuts with the same depth of cut and feed using round and straight edge inserts shows that the curved underside chip formed by the round edge generates significantly lower energy AE signal compare with the straight edge cuts (Fig. 2), although the actual length of cuIting edge engaged is longer for the round tools. This observation implies that not only the size of the chip-tool contact area but the contact geoemtry also have strong effects on the AE energy. This point can be surported further by the results shown in Figure 5. Changing the f i t rake face of a round tool to a truncated conical shape drastically increased the AE energy as compared with the -5 and -10 degree cases shown in Figure 5. It should be very interesting to know if the apparent strong effect of the chip-tool interface on the AE signal energy is an indication of the interface being a significantsource of the AE. Orthogonal machining experiments showed that all physical discrete events in the cutting action generate packets of AE pulses. The energy content of each AE pulse packet is related to the rate of the event. Brittle fracture and addiabatic shear type events generate higher energy AE pulses compared with the slow rate shear deformation of steel. If the frequency of the events is very high, such as the fragmentingcast iron chips, the density of pulses is so high that the signal becomes nearly continuous and the resulting average AE level is high. These discrete events, however, make little contribution to the required mechanical cutting power. Conditions resulting in the thickeningof the shear zone and severe plastic deformation increase the cutting power requirement but have little effect on the AE energy. Excessive deformation of chips against the tool surface, such as cutting with very large negative rake angle tools, however, changes the chip-tool interface conditions significantly enough that the AE energy increases.
i
MPR14FQn (mm)
Figure 1.
Average AE signal amplitude vs Ihe depth-of-cutfor machining INCO AUoy 718 and AISI 1045 steel. WORKPIECE IN718 TOOL MATERIAL: KYON X K X )
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5
e
4. swnmory
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Effect of various physical and geometric parameters in machining on the acoustic emission activities of metal cutting was explored through a series of lathe turning and orthogonal machining experiments.
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In general, if the cutting edge shape and the cutting angles are unchanged, a positive correlation can be established between the mechanical energy consumed for the chip making activity and the average intensity of the AE signal during the cut. Therefore, machining parameters increasing the material removal rate such as speed, depth of cut, and feed will increase the average intensity of AE signal. Tough to machine materials such as high temperature alloys and hard steels requiring high cutting power generdy accompany high intcnsity AE. The degree of dependence of the average AE intensity on the material removal rate for these types of tough to machine materials is, therefore, also high. The shape of cutting edge or the cutting edge angles, however, can have significant effect on the relationship between the total energy consumed for the
4-
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1
I 2
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3
4
0EPTH.OF.CUT (mm)
Figure 2.
AverageAE amplitudevs depth-of-cutfor 1.27 cm square and round inserts.
59
CUTTING TIME(SEC0ND)
Figure 3.
A strip chart recording of the average AE and the corresponding cutting horse power for machining a INCO Alloy 718 using a ceramic insert. The cutting edge began to chip gradually at the point where the AE amplitude starts decrease.
1
1
2.01
-30
-20
0
-10
RAKE ANGLE (DEGREE)
Figure 4.
Average AE amplitude and cutting power vs the rake angle of 1.27 M square inserts machining INCO AUoy 718.
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Figure 5.
Average AE amplitude vs the rake angle of 1.27 cm diameter round ceramic inserts machining INCO Alloy 718. The rake face of inserts was ground cylindrically to form listed rake angleswith respect to the axis of the cylinder.
Figure 6.
The AE signal from machining titanium alloy at 4 meters per minute. Each packet of AE pulses corresponds to shear separation of individual chip scgmcnts.
60
Figure 7.
Video images of titanium chips corresponding to the beginniag and the end of the AE signal shown in Figure 6.