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On-line wear monitoring using acoustic emission
605
Wear, 162-164 (1993) 605-610
Short Communication On-line wear monitoring using acoustic emission Kaoru Matsuoka*, Ming-Kai Tse
David
Forrest
and
Tribologv Research Program, Department of Mechanical Engineering Massachusetts Institute of Technology, Cambridge, MA 02139 (USA)
Abstract On-line estimation of the wear rate of materials subjected to abrasion has been accomplished using acoustic emission (AE) sensing. The energy in the AE signal is directly related to the energy required for material removal in the abrasion process. The technique has been successfully applied to monitoring the wear of magnetic recording head materials using lapping tapes over a wide range of wear rates. A methodology has been developed to calibrate the AE monitoring system on line and to estimate the total wear volume. Such a system provides a very powerful quantitative measurement technique for tribological studies, as well as for on-line machine or process diagnostic applications.
AE has been used to analyze the surface of floppy and hard disks [6-81. In the sliding process, Belyi et al. [9] concluded that the AE energy is indicative of the mass loss by wear of the surfaces. Tse [lo] and Tse and Gu [ll] proposed the use of AE for surface characterization (“triboacoustics”) and Tse [12, 131 also considered its use for in-process measurement and control (“tribosensing”). Lingard and Ng [14] suggested that the possibility of AI%wear correlation should not be precluded, although they did not fmd any consistent relationship between cumulative AE count and wear rate. Boness and McBride [15] obtained an empirical relationship between the integrated AE r.m.s. signal and the wear volume removed from the test ball in a ballon-cylinder test apparatus. Although a great deal of effort has been made to advance AE technology in tribological applications, the correlation between the AE signal and wear rate has not been firmly established. The present paper aims at identifying such a correlation and developing the methodology for applying the monitoring technique on line, if such a correlation exists. Finally, the efficacy of the proposed wear-monitoring technique is demonstrated in the accelerated wear testing of magnetic head materials.
1. Introduction 2. Experimental details Tribological problems of mechanical components are among the most common problems encountered during machine development or operation. Accordingly, accelerated testing methods for the prediction of the wear life of mechanical components, and techniques for diagnosis of deterioration due to wear are both very important in the development and operation of mechanical systems. Furthermore, in-process sensing techniques for monitoring wear, deterioration and failure in real time are desired because conventional methods that rely on post-mortem analysis are of limited value in providing information on the dynamics of the wear processes. To monitor the friction and wear of mechanical components in sliding contact in real time, the use of acoustic emission (AE) generated by the interacting surfaces has been considered by many investigators. Many studies have applied AE to monitor cutting tool wear [l-5]. In the field of magnetic storage systems, *Present address: Matsushita Electric Industrial Co., Ltd., Osaka, Japan.
0043-X48/93/$6.00
2.1. Materials Two types of the single-crystal manganese zinc ferrite widely used as the read-write heads in magnetic storage devices were used in this study. Although they differ in the volume ratio of each ingredient, the two types of head have nearly identical mechanical properties. Each test specimen was shaped as a square pillar with one rounded surface against which all sliding occurred. Abrasives used iu this study were commercial polyester-backed aluminum oxide (Al,O,) lapping tapes, which were wound on the reel hubs of tape cassettes t in wide. The nominal grit sixes of the aluminum oxide abrasives ranged from 0.3 to 60 pm and were conllrmed by scanning electron microscopy observation and surface profilometry. 2.2. Apparatus The AE instrumentation and the test apparatus shown in Fig. 1 were used in this investigation. The specimen was supported by the holder mounted on the strain ring. Its relative position against the lapping tape was
0 1993 - Elsevier Sequoia. Ah rights reserved
606
K. Matsuoka et al. ! On-line wear monitoring using AE
Motor 8. Controller
Tape End Detector
Fig. 1. Schematic
diagram of the AE test apparatus:
A/D, analog-to-digital.
adjusted by the dual-axis stage. Two strain gauge bridges attached to the strain ring as shown in Fig. 1 allowed independent measurements of the applied normal force and the resultant tangential force. The analog outputs of the strain gauge bridges were amplified and filtered. The filtered signals were digitized and acquired by a microcomputer at 100 Hz. Tape speed and tape tension were controlled by the take-up motor and the supply motor respectively. The tape speed, from 1 to 9 m SK’, was controlled and computed from the rotational speed of the supply motor spindle, which was monitored with an optical tachometer. The wear tests were done at relatively low tape speeds of 2-3 m s-l in order to eliminate the air-bearing effect between the specimen and the lapping tape which occurs at higher tape speeds. To simulate wear conditions in an actual video tape recorder, tape travel over the specimen was limited to one direction. This was accomplished by lifting the tape off the specimen before reversing the direction when the tape on the supply reel was exhausted. Transparent tapes attached to either end of the abrasive tapes enabled detection of the tape ends using a light-emitting device and a photo-transistor. The AE signal was detected by means of an AE transducer (Physical Acoustics Corporation) with a resonant frequency of 500 kHz. The transducer was attached to the side surface of the specimen by means of a low melting point crystal (phenyl salicylate), as shown in Fig. 1. The AE signal was amplified with a pre-amplifier and a main amplifier. The amplified AE signal was processed through an r.m.s. voltmeter (HP
3400A) with a bandwidth of 1 MHz to obtain the r.m.s. signal, and a high speed digitizer (Signatec DASP25A) to capture the AE waveforms. Overall signal amplification was maintained at 56 dB with a bandwidth from 20 kHz to 1 MHz. All data on the normal force, tangential force, tape speed, AE r.m.s. and AE waveforms were digitized and processed by a microcomputer. The mass loss of a specimen over some period of time was measured to determine the volume removed by means of a balance with a resolution of 0.01 mg. The wear coefficient k of the material under test was calculated from Archard’s equation k=E
(1)
where V is the volume of material removed, H is the hardness of the specimen, N is the applied normal load and S is the distance slid between the tape and the specimen. The attenuation of the stress waves through all specimens tested was also measured by an ultrasonic pulseecho method. 3. Results and discussion 3.1. Correlation between the acoustic em&ion and wear rate
signal
In an abrasion process, the rate of external work done can be measured in terms of the frictional power as Wfriction
=
cLNv
(2)
607
R h4atsuoka et al. I On-line wear monitoring using AE
where p is the friction coefficient, N is the applied normal force and v is the sliding speed. This power is required for material deformation and removal which also generate heat, audible noise and AE (bulk stress waves) in the process. Several investigators have attempted to find a correlation between AE and the frictional power [16]. However, no clear correlation has yet been found, as observed by Tse and Lewis [6] and in this study. As previously mentioned, a portion of the frictional power is consumed by the process of material removal. The energy IV, required to remove a volume V of material with hardness H can be approximated by [17] W,=W
(3)
If we substitute eqn. (1) into eqn. (3) and differentiate with respect to time, the material removal power W, is obtained as p _ r
dJJ5 _ -dww dt
dt
(4)
= kNv
where v is the relative sliding speed. In this study, a clear correlation was found between the material removal power W, and AE measured in terms of AE r.m.s. voltage, as shown in Figs. 2 and 3. This finding may be explained in terms of the mechanism of AE. Acoustic stress waves result from the rapid release of stored strain energy. The shear strain involved in material removal is likely to be much greater than the shear strain associated with material deformation. Therefore, although both material deformation and material removal processes produce AE, the power in the AE signal is dominated by the latter process. As a first approximation, this correlation can be modeled by a linear dependence between AE! power and the material removal power, i.e.
v-ms. - P>’=
kNv
(5)
Z
1
0
0.05
”
j
8
1
0.1 d Material
”
”
1 ”
”
0.15 Removal
1
0.2 Power
”
1
0.25
‘.
0.3
(W”‘)
Fig. 2. AE r.m.s. signal as a function of the square root of material removal power for type A manganese zinc ferrite.
8 x 1O’3 7 6 & F .a CA
5 4
0 4 Material
Removal
Power
(W”‘)
Fig. 3. AE r.m.s. signal as a function of the square root of material removal power for type B manganese zinc ferrite.
whereKm., is the AE r.m.s. voltage, Z is the impedance of the measurement system and p is the “noise” in this system. The AE r.m.s. value can be expressed explicitly in terms of the other variables by rewriting eqn. (5) as Vr.m.s.
=
cu(kNvY
+
P
or VT.ln.S. = aWrln
(7)
where LYis the square root of Z. In Figs. 2 and 3, the experimental results of AE r.m.s. voltage are plotted against the square root of material removal power from wear tests using lapping tape with A&O, abrasive grits of 0.3-60 pm. In the figures, the broken lines show the relationship of eqns. (6) and (7). The experimental results in Figs. 2 and 3 show good agreement with the theoretical model for all tests, which involved material removal power ranging over four orders of magnitude. 3.2. Adjusted acorcstic emission r.m.s. signals The difference between the magnitudes of the AE r.m.s. signals of type A and type B is considerable, although the material removal power is similar as shown in Figs. 2 and 3. This difference is caused by the material-dependent attenuation of the acoustic wave travelling through the different materials. To account for this difference, the attenuation of acoustic waves for each material was measured using an ultrasonic pulse-echo method..The ultrasonic test results for type A and type B of manganese zinc ferrite are shown in Fig. 4. It is clear that the attenuation for type B (which contains a higher percentage of ferrite) is much larger than that for type A.
608
K. Matsuoka et al. / On-line wear monitoring using AE 1 st Echo
200
01
Time
(ps)
400
1 0
r
0.05
0.1
-/Material
0.15
02
025
03
Removal Power (W”‘)
Fig. 5. AE r.m.s. signal as a function of the square root of material removal power for manganese zinc ferrite type A and type B. Type B is adjusted for its high acoustic attenuation.
0
400
200 Time
Fig. 4. Ultrasonic type B.
outputs for manganese
The attenuation coefficient expressed as [18] ad=20
600
(ps)
zinc ferrite type A and
a of a material
can be
v,
()
log,, 7
where d is the distance traveled by the ultrasonic wave, and V, and V are the acoustic pressure levels for two successive echoes. On the basis of this equation, the relationship between the AE of the two materials may be expressed as v* = lO’“B-nA)dlZOVg
(9)
where uA and aB are the attenuation coefficients for type A and type B respectively. Using eqn. (9), all AE r.m.s. values were adjusted to reflect the difference in acoustic attenuation. The correlation between the adjusted AE r.m.s. signals and material removal power is shown in Fig. 5. Again, the result supports the validity of the model depicted in eqn. (6). 3.3. On-line wear monitoring It is impossible to measure the instantaneous wear coefficient directly during sliding wear. However, an indirect measurement can be made by a simple evaluation of the AE r.m.s. signals, as shown in Fig. 5. For example, using the quantitative relationship between the AE signal and wear rate in eqn. (6), the wear coefficient of a specimen may be estimated in real time by monitoring easily controlled or measured quantities
including the normal force, sliding speed and AE r.m.s. signal. Equation (6) includes two terms which characterize the measurement system: (Yand p. The term /3 simply corresponds to the AE r.m.s. level due to all sources except material removal. This includes AE due to background noise and elastic deformation etc. The term (Y is related to the proportionality constant between material removal power and the resulting AE r.m.s. level. Therefore (Yis inversely related to the attenuation coefficient of the test material. Many other factors (e.g. sample size, AE sensor characteristics, sensor location and amplifier characteristics) contribute to the value of (Yin very complicated combinations so that theoretical prediction of its value is impractical, if not impossible. Therefore, in practice, the terms (Yand /3 in eqn. (6) can best be determined empirically for the materials and instrumentation of a given system. Note that at least two sets of measured wear coefficient, AE r.m.s. value, normal force and speed are required for this calibration. For the system illustrated in Fig. 1, LYand p remained reasonably constant throughout the entire range of tests, as represented by the broken line in Fig. 5, where (Y=1.83 X low2 V Win and p = 4.80 X 10e4 V. Once the terms Q and p have been defined, the instantaneous wear coefficient of any specimen in the system can be estimated using eqn. (6). Even better wear coefficient estimations can be made by determining a specific (Yand p for each individual wear test. Figure 6 illustrates this technique. Note that the wear coefficient and the AE r.m.s. level together decrease dramatically during the first several tape passes. Accordingly, these early tape passes are ideal for the determination of the terms (Y and p. In Fig. 6, the broken curves are fitted to the first three data points (see individual plots) to determine the constants LYand
l
: Measured
-
:Predicted
wear coefficient #ear coefficient
for 0.5pm grit
li
.
for 0.5pm grit
-
Number of tape passes
e
-
: Measured
:Predicted
for 9pm grit
_ .
SI 50
(cl
rlr
-
: Measured
:Predicted
wear coefficient wear coeffident
*
r
s
.
-
.
.
.
I 100
Number of tape passes
Cd)
t
for 30pm grit
.
for 12pm grit for 12pm grit
50
0
100
Number of tape passes
:Measured wear coefficient :PredIcted wear coefficient
-
01 0
for 3pm grit for 3pm grit
Number of tape passes
@I
wear coefficient for 9pm grit wear coefficient
wear coefficient wear coefficfent
50
1OQ
50
:Measured :Predicted
l
: Measured
wear coefficient
for 6Opm gri
for 30gm grit
i
00 0
09 Fig. 6. Measured
50
100
50
Numbar of tape passes
and predicted
wear coefficients
~3. The wear coefficient prediction based r.m.s. level, represented by the full curves computed from eqn. (6). The measured show good agreement with the predicted ficient.
100
Number of tape passes
against A&Cl3 for manganese
on the AE in Fig. 6, is data points wear coef-
4. Conclusions As a result of this study, the following conclusions can be drawn.
zinc ferrite:
(a)-(c)
type A, (d)-(f)
type l3.
(1) The power in the AE signal is directly proportional to the power required for material removed in the abrasion process. (2) There is no direct correlation between the AE power and the total external power supplied to the sliding system. (3) The wear coefficient can be estimated and monitored indirectly on line using the AE r.m.s. signal without direct measurement of the wear volume. Such a system provides a very powerful quantitative wear measurement technique for tri%ological studies, as well as for on-line machine or process diagnostic applications.
610
K. Matsuoka et al. I On-line wear nronitoting using AE
(4) In accelerated wear testing of magnetic head materials, calibration of the AE monitoring method requires direct measurements of wear from the first few tape passes of a wear test. The normal force and the sliding velocity are also needed for wear prediction. (5) The AE r.m.s. signals for different materials may only be compared directly after properly accounting for the effect of acoustic attenuation. The attenuation coefficient can be measured using an ultrasonic pulseecho method.
Acknowledgments This research Industrial Co., Jirou Kajino of for his support
was supported by Matsushita Electric Ltd. The authors wish to thank Mr. Matsushita Electric Industrial Co., Ltd. and valuable suggestions.
References 1 M. K Tse, and J. C. Briggs, In-process tool wear sensing by acoustic emission, Proc. ltth World Conf. on Non-destructive Testing, Vol. 1, American Society for Non-Destructive Testing, Columbus, OH, 1985, pp. 70-77. 2 E. Kannatey-Asibu and D. A. Domfeld, Quantitative relationship for acoustic emission from orthogonal meta cutting, J. Eng. Znd., IO.? (1981) 330-340. 3 E. Kannatey-Asibu and A. Dornfeld, A study of tool wear using statistical analysis of metal-cutting acoustic emission, Wear, 76 (1982) 247-261. 4 T. Bulm and I. Inasaki, A study on acoustic emission from the orthogonal cutting process, J. Eng. Ind., 112 (1990) 203-211.
5 T. Moriwaki and M. Tobito, A new approach to automatic detection of life of coated tool based on acoustic emission measurement, J: Eng. Ind., 112 (1990) 212-218. 6 M. K. Tse and A. F. Lewis, Triboacoustics of nonwoven fabric/floppy disk dynamic contact, Tribal. Mech. Magn. Storage Syst., SP-21 (1986) 63-71. 7 J. C. Briggs, M.-K. Chang and M. K. Tse, High frequency slider vibrations during asperity impacts in rigid magnetic disk systems, Adv. Znform. Storage Sysr., 4 (1992) 181-194. 8 J. C. Briggs and M. K. Tse, Impact force identification using extracted modal parameters and pattern matching, Int. .I Impact Eng., 12 (3) (1992) 361-372. 9 V. A. Belyi, 0. V. Kholodilov and A. I. Sviridyonok, Acoustic spectrometry as used for the evaluation of tribologicai systems, Wear, dP (1981) 309-319. new tool for surface charac10 M. K. Tse, Triboacoustics-a terization, 29th Acoustic Emission Working Group Meet., Kingston, Ont., 1986. 11 M. K. Tse and P. Y. Gu, Surface analysis by triboacoustic emission. World Meet. on Acoustic Emission, Charlotte, NC, March 20-23, 1989. 12 M. K. Tse, Tribosensing: a new tool for in-process nondestructive evaluation, Ttibo~ogy Research Frogram, National Science Foundation Grantee’s Co& Atlanta, GA, August 1987. and 13 M. K. Tse, Triboacoustic for in-process measurement control, 31st Acoustic Emission Working Group Meet., Los Angeles, CA, 1988. 14 S. Lingard and K. K. Ng, An investigation of acous?ic emission in sliding friction and wear of metals, Wear, 130 (7989) 367-379. 15 R. J. Boness and S. L. McBride, Adhesive and abrasive wear studies using acoustic emission techniques, Wear, 149 (1991) 41-53. 16 C. L. Jiaa and D. A. Dornfeld, Experimental studies of sliding friction and wear via acoustic emission signal analysis, Wear, 139 (1990) 403-424. 17 M. C. Shaw, Metal C&ring Priwples, 3rd edn., MIT Press, Cambridge, MA, 1954. 18 J. Krautkrgmer and H. Krautkrlmer, Attenuation of ultrasonic waves in solids, Ultrusonic TestDtgofMaterialx, Springer, Berlin, 1983.
Wear, 162-164 (1993) 605-610
Short Communication On-line wear monitoring using acoustic emission Kaoru Matsuoka*, Ming-Kai Tse
David
Forrest
and
Tribologv Research Program, Department of Mechanical Engineering Massachusetts Institute of Technology, Cambridge, MA 02139 (USA)
Abstract On-line estimation of the wear rate of materials subjected to abrasion has been accomplished using acoustic emission (AE) sensing. The energy in the AE signal is directly related to the energy required for material removal in the abrasion process. The technique has been successfully applied to monitoring the wear of magnetic recording head materials using lapping tapes over a wide range of wear rates. A methodology has been developed to calibrate the AE monitoring system on line and to estimate the total wear volume. Such a system provides a very powerful quantitative measurement technique for tribological studies, as well as for on-line machine or process diagnostic applications.
AE has been used to analyze the surface of floppy and hard disks [6-81. In the sliding process, Belyi et al. [9] concluded that the AE energy is indicative of the mass loss by wear of the surfaces. Tse [lo] and Tse and Gu [ll] proposed the use of AE for surface characterization (“triboacoustics”) and Tse [12, 131 also considered its use for in-process measurement and control (“tribosensing”). Lingard and Ng [14] suggested that the possibility of AI%wear correlation should not be precluded, although they did not fmd any consistent relationship between cumulative AE count and wear rate. Boness and McBride [15] obtained an empirical relationship between the integrated AE r.m.s. signal and the wear volume removed from the test ball in a ballon-cylinder test apparatus. Although a great deal of effort has been made to advance AE technology in tribological applications, the correlation between the AE signal and wear rate has not been firmly established. The present paper aims at identifying such a correlation and developing the methodology for applying the monitoring technique on line, if such a correlation exists. Finally, the efficacy of the proposed wear-monitoring technique is demonstrated in the accelerated wear testing of magnetic head materials.
1. Introduction 2. Experimental details Tribological problems of mechanical components are among the most common problems encountered during machine development or operation. Accordingly, accelerated testing methods for the prediction of the wear life of mechanical components, and techniques for diagnosis of deterioration due to wear are both very important in the development and operation of mechanical systems. Furthermore, in-process sensing techniques for monitoring wear, deterioration and failure in real time are desired because conventional methods that rely on post-mortem analysis are of limited value in providing information on the dynamics of the wear processes. To monitor the friction and wear of mechanical components in sliding contact in real time, the use of acoustic emission (AE) generated by the interacting surfaces has been considered by many investigators. Many studies have applied AE to monitor cutting tool wear [l-5]. In the field of magnetic storage systems, *Present address: Matsushita Electric Industrial Co., Ltd., Osaka, Japan.
0043-X48/93/$6.00
2.1. Materials Two types of the single-crystal manganese zinc ferrite widely used as the read-write heads in magnetic storage devices were used in this study. Although they differ in the volume ratio of each ingredient, the two types of head have nearly identical mechanical properties. Each test specimen was shaped as a square pillar with one rounded surface against which all sliding occurred. Abrasives used iu this study were commercial polyester-backed aluminum oxide (Al,O,) lapping tapes, which were wound on the reel hubs of tape cassettes t in wide. The nominal grit sixes of the aluminum oxide abrasives ranged from 0.3 to 60 pm and were conllrmed by scanning electron microscopy observation and surface profilometry. 2.2. Apparatus The AE instrumentation and the test apparatus shown in Fig. 1 were used in this investigation. The specimen was supported by the holder mounted on the strain ring. Its relative position against the lapping tape was
0 1993 - Elsevier Sequoia. Ah rights reserved
606
K. Matsuoka et al. ! On-line wear monitoring using AE
Motor 8. Controller
Tape End Detector
Fig. 1. Schematic
diagram of the AE test apparatus:
A/D, analog-to-digital.
adjusted by the dual-axis stage. Two strain gauge bridges attached to the strain ring as shown in Fig. 1 allowed independent measurements of the applied normal force and the resultant tangential force. The analog outputs of the strain gauge bridges were amplified and filtered. The filtered signals were digitized and acquired by a microcomputer at 100 Hz. Tape speed and tape tension were controlled by the take-up motor and the supply motor respectively. The tape speed, from 1 to 9 m SK’, was controlled and computed from the rotational speed of the supply motor spindle, which was monitored with an optical tachometer. The wear tests were done at relatively low tape speeds of 2-3 m s-l in order to eliminate the air-bearing effect between the specimen and the lapping tape which occurs at higher tape speeds. To simulate wear conditions in an actual video tape recorder, tape travel over the specimen was limited to one direction. This was accomplished by lifting the tape off the specimen before reversing the direction when the tape on the supply reel was exhausted. Transparent tapes attached to either end of the abrasive tapes enabled detection of the tape ends using a light-emitting device and a photo-transistor. The AE signal was detected by means of an AE transducer (Physical Acoustics Corporation) with a resonant frequency of 500 kHz. The transducer was attached to the side surface of the specimen by means of a low melting point crystal (phenyl salicylate), as shown in Fig. 1. The AE signal was amplified with a pre-amplifier and a main amplifier. The amplified AE signal was processed through an r.m.s. voltmeter (HP
3400A) with a bandwidth of 1 MHz to obtain the r.m.s. signal, and a high speed digitizer (Signatec DASP25A) to capture the AE waveforms. Overall signal amplification was maintained at 56 dB with a bandwidth from 20 kHz to 1 MHz. All data on the normal force, tangential force, tape speed, AE r.m.s. and AE waveforms were digitized and processed by a microcomputer. The mass loss of a specimen over some period of time was measured to determine the volume removed by means of a balance with a resolution of 0.01 mg. The wear coefficient k of the material under test was calculated from Archard’s equation k=E
(1)
where V is the volume of material removed, H is the hardness of the specimen, N is the applied normal load and S is the distance slid between the tape and the specimen. The attenuation of the stress waves through all specimens tested was also measured by an ultrasonic pulseecho method. 3. Results and discussion 3.1. Correlation between the acoustic em&ion and wear rate
signal
In an abrasion process, the rate of external work done can be measured in terms of the frictional power as Wfriction
=
cLNv
(2)
607
R h4atsuoka et al. I On-line wear monitoring using AE
where p is the friction coefficient, N is the applied normal force and v is the sliding speed. This power is required for material deformation and removal which also generate heat, audible noise and AE (bulk stress waves) in the process. Several investigators have attempted to find a correlation between AE and the frictional power [16]. However, no clear correlation has yet been found, as observed by Tse and Lewis [6] and in this study. As previously mentioned, a portion of the frictional power is consumed by the process of material removal. The energy IV, required to remove a volume V of material with hardness H can be approximated by [17] W,=W
(3)
If we substitute eqn. (1) into eqn. (3) and differentiate with respect to time, the material removal power W, is obtained as p _ r
dJJ5 _ -dww dt
dt
(4)
= kNv
where v is the relative sliding speed. In this study, a clear correlation was found between the material removal power W, and AE measured in terms of AE r.m.s. voltage, as shown in Figs. 2 and 3. This finding may be explained in terms of the mechanism of AE. Acoustic stress waves result from the rapid release of stored strain energy. The shear strain involved in material removal is likely to be much greater than the shear strain associated with material deformation. Therefore, although both material deformation and material removal processes produce AE, the power in the AE signal is dominated by the latter process. As a first approximation, this correlation can be modeled by a linear dependence between AE! power and the material removal power, i.e.
v-ms. - P>’=
kNv
(5)
Z
1
0
0.05
”
j
8
1
0.1 d Material
”
”
1 ”
”
0.15 Removal
1
0.2 Power
”
1
0.25
‘.
0.3
(W”‘)
Fig. 2. AE r.m.s. signal as a function of the square root of material removal power for type A manganese zinc ferrite.
8 x 1O’3 7 6 & F .a CA
5 4
0 4 Material
Removal
Power
(W”‘)
Fig. 3. AE r.m.s. signal as a function of the square root of material removal power for type B manganese zinc ferrite.
whereKm., is the AE r.m.s. voltage, Z is the impedance of the measurement system and p is the “noise” in this system. The AE r.m.s. value can be expressed explicitly in terms of the other variables by rewriting eqn. (5) as Vr.m.s.
=
cu(kNvY
+
P
or VT.ln.S. = aWrln
(7)
where LYis the square root of Z. In Figs. 2 and 3, the experimental results of AE r.m.s. voltage are plotted against the square root of material removal power from wear tests using lapping tape with A&O, abrasive grits of 0.3-60 pm. In the figures, the broken lines show the relationship of eqns. (6) and (7). The experimental results in Figs. 2 and 3 show good agreement with the theoretical model for all tests, which involved material removal power ranging over four orders of magnitude. 3.2. Adjusted acorcstic emission r.m.s. signals The difference between the magnitudes of the AE r.m.s. signals of type A and type B is considerable, although the material removal power is similar as shown in Figs. 2 and 3. This difference is caused by the material-dependent attenuation of the acoustic wave travelling through the different materials. To account for this difference, the attenuation of acoustic waves for each material was measured using an ultrasonic pulse-echo method..The ultrasonic test results for type A and type B of manganese zinc ferrite are shown in Fig. 4. It is clear that the attenuation for type B (which contains a higher percentage of ferrite) is much larger than that for type A.
608
K. Matsuoka et al. / On-line wear monitoring using AE 1 st Echo
200
01
Time
(ps)
400
1 0
r
0.05
0.1
-/Material
0.15
02
025
03
Removal Power (W”‘)
Fig. 5. AE r.m.s. signal as a function of the square root of material removal power for manganese zinc ferrite type A and type B. Type B is adjusted for its high acoustic attenuation.
0
400
200 Time
Fig. 4. Ultrasonic type B.
outputs for manganese
The attenuation coefficient expressed as [18] ad=20
600
(ps)
zinc ferrite type A and
a of a material
can be
v,
()
log,, 7
where d is the distance traveled by the ultrasonic wave, and V, and V are the acoustic pressure levels for two successive echoes. On the basis of this equation, the relationship between the AE of the two materials may be expressed as v* = lO’“B-nA)dlZOVg
(9)
where uA and aB are the attenuation coefficients for type A and type B respectively. Using eqn. (9), all AE r.m.s. values were adjusted to reflect the difference in acoustic attenuation. The correlation between the adjusted AE r.m.s. signals and material removal power is shown in Fig. 5. Again, the result supports the validity of the model depicted in eqn. (6). 3.3. On-line wear monitoring It is impossible to measure the instantaneous wear coefficient directly during sliding wear. However, an indirect measurement can be made by a simple evaluation of the AE r.m.s. signals, as shown in Fig. 5. For example, using the quantitative relationship between the AE signal and wear rate in eqn. (6), the wear coefficient of a specimen may be estimated in real time by monitoring easily controlled or measured quantities
including the normal force, sliding speed and AE r.m.s. signal. Equation (6) includes two terms which characterize the measurement system: (Yand p. The term /3 simply corresponds to the AE r.m.s. level due to all sources except material removal. This includes AE due to background noise and elastic deformation etc. The term (Y is related to the proportionality constant between material removal power and the resulting AE r.m.s. level. Therefore (Yis inversely related to the attenuation coefficient of the test material. Many other factors (e.g. sample size, AE sensor characteristics, sensor location and amplifier characteristics) contribute to the value of (Yin very complicated combinations so that theoretical prediction of its value is impractical, if not impossible. Therefore, in practice, the terms (Yand /3 in eqn. (6) can best be determined empirically for the materials and instrumentation of a given system. Note that at least two sets of measured wear coefficient, AE r.m.s. value, normal force and speed are required for this calibration. For the system illustrated in Fig. 1, LYand p remained reasonably constant throughout the entire range of tests, as represented by the broken line in Fig. 5, where (Y=1.83 X low2 V Win and p = 4.80 X 10e4 V. Once the terms Q and p have been defined, the instantaneous wear coefficient of any specimen in the system can be estimated using eqn. (6). Even better wear coefficient estimations can be made by determining a specific (Yand p for each individual wear test. Figure 6 illustrates this technique. Note that the wear coefficient and the AE r.m.s. level together decrease dramatically during the first several tape passes. Accordingly, these early tape passes are ideal for the determination of the terms (Y and p. In Fig. 6, the broken curves are fitted to the first three data points (see individual plots) to determine the constants LYand
l
: Measured
-
:Predicted
wear coefficient #ear coefficient
for 0.5pm grit
li
.
for 0.5pm grit
-
Number of tape passes
e
-
: Measured
:Predicted
for 9pm grit
_ .
SI 50
(cl
rlr
-
: Measured
:Predicted
wear coefficient wear coeffident
*
r
s
.
-
.
.
.
I 100
Number of tape passes
Cd)
t
for 30pm grit
.
for 12pm grit for 12pm grit
50
0
100
Number of tape passes
:Measured wear coefficient :PredIcted wear coefficient
-
01 0
for 3pm grit for 3pm grit
Number of tape passes
@I
wear coefficient for 9pm grit wear coefficient
wear coefficient wear coefficfent
50
1OQ
50
:Measured :Predicted
l
: Measured
wear coefficient
for 6Opm gri
for 30gm grit
i
00 0
09 Fig. 6. Measured
50
100
50
Numbar of tape passes
and predicted
wear coefficients
~3. The wear coefficient prediction based r.m.s. level, represented by the full curves computed from eqn. (6). The measured show good agreement with the predicted ficient.
100
Number of tape passes
against A&Cl3 for manganese
on the AE in Fig. 6, is data points wear coef-
4. Conclusions As a result of this study, the following conclusions can be drawn.
zinc ferrite:
(a)-(c)
type A, (d)-(f)
type l3.
(1) The power in the AE signal is directly proportional to the power required for material removed in the abrasion process. (2) There is no direct correlation between the AE power and the total external power supplied to the sliding system. (3) The wear coefficient can be estimated and monitored indirectly on line using the AE r.m.s. signal without direct measurement of the wear volume. Such a system provides a very powerful quantitative wear measurement technique for tri%ological studies, as well as for on-line machine or process diagnostic applications.
610
K. Matsuoka et al. I On-line wear nronitoting using AE
(4) In accelerated wear testing of magnetic head materials, calibration of the AE monitoring method requires direct measurements of wear from the first few tape passes of a wear test. The normal force and the sliding velocity are also needed for wear prediction. (5) The AE r.m.s. signals for different materials may only be compared directly after properly accounting for the effect of acoustic attenuation. The attenuation coefficient can be measured using an ultrasonic pulseecho method.
Acknowledgments This research Industrial Co., Jirou Kajino of for his support
was supported by Matsushita Electric Ltd. The authors wish to thank Mr. Matsushita Electric Industrial Co., Ltd. and valuable suggestions.
References 1 M. K Tse, and J. C. Briggs, In-process tool wear sensing by acoustic emission, Proc. ltth World Conf. on Non-destructive Testing, Vol. 1, American Society for Non-Destructive Testing, Columbus, OH, 1985, pp. 70-77. 2 E. Kannatey-Asibu and D. A. Domfeld, Quantitative relationship for acoustic emission from orthogonal meta cutting, J. Eng. Znd., IO.? (1981) 330-340. 3 E. Kannatey-Asibu and A. Dornfeld, A study of tool wear using statistical analysis of metal-cutting acoustic emission, Wear, 76 (1982) 247-261. 4 T. Bulm and I. Inasaki, A study on acoustic emission from the orthogonal cutting process, J. Eng. Ind., 112 (1990) 203-211.
5 T. Moriwaki and M. Tobito, A new approach to automatic detection of life of coated tool based on acoustic emission measurement, J: Eng. Ind., 112 (1990) 212-218. 6 M. K. Tse and A. F. Lewis, Triboacoustics of nonwoven fabric/floppy disk dynamic contact, Tribal. Mech. Magn. Storage Syst., SP-21 (1986) 63-71. 7 J. C. Briggs, M.-K. Chang and M. K. Tse, High frequency slider vibrations during asperity impacts in rigid magnetic disk systems, Adv. Znform. Storage Sysr., 4 (1992) 181-194. 8 J. C. Briggs and M. K. Tse, Impact force identification using extracted modal parameters and pattern matching, Int. .I Impact Eng., 12 (3) (1992) 361-372. 9 V. A. Belyi, 0. V. Kholodilov and A. I. Sviridyonok, Acoustic spectrometry as used for the evaluation of tribologicai systems, Wear, dP (1981) 309-319. new tool for surface charac10 M. K. Tse, Triboacoustics-a terization, 29th Acoustic Emission Working Group Meet., Kingston, Ont., 1986. 11 M. K. Tse and P. Y. Gu, Surface analysis by triboacoustic emission. World Meet. on Acoustic Emission, Charlotte, NC, March 20-23, 1989. 12 M. K. Tse, Tribosensing: a new tool for in-process nondestructive evaluation, Ttibo~ogy Research Frogram, National Science Foundation Grantee’s Co& Atlanta, GA, August 1987. and 13 M. K. Tse, Triboacoustic for in-process measurement control, 31st Acoustic Emission Working Group Meet., Los Angeles, CA, 1988. 14 S. Lingard and K. K. Ng, An investigation of acous?ic emission in sliding friction and wear of metals, Wear, 130 (7989) 367-379. 15 R. J. Boness and S. L. McBride, Adhesive and abrasive wear studies using acoustic emission techniques, Wear, 149 (1991) 41-53. 16 C. L. Jiaa and D. A. Dornfeld, Experimental studies of sliding friction and wear via acoustic emission signal analysis, Wear, 139 (1990) 403-424. 17 M. C. Shaw, Metal C&ring Priwples, 3rd edn., MIT Press, Cambridge, MA, 1954. 18 J. Krautkrgmer and H. Krautkrlmer, Attenuation of ultrasonic waves in solids, Ultrusonic TestDtgofMaterialx, Springer, Berlin, 1983.