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Acoustic emission signatures of
electrical discharge machining
International Academy for Production Engineering
66th General Assembly – Guimaraes, Portugal, Aug. 21-27, 2016
CIRP Annals - Manufacturing Technology Volume 65, Issue 1, 2016, Pages 229 - 232
A. Klink, M. Holsten, S. Schneider & P. Koshy
Page 2© WZL/Fraunhofer IPT
Acknowledgements5
Conclusions and outlook4
Results of sequential discharge experiments3
Results of single discharge experiments2
Introduction and experimental setup1
Outline
Page 3© WZL/Fraunhofer IPT
Acoustic Emission (AE) in the context of EDM
 AE – transient elastic waves in
response to mechanical loading:
– Inherently generated in cutting
processes
– Generated also during EDM, but not
well understood
 Availability of process information
[1,2]
 Monitoring of gap phenomena
using AE is possible
[1] Smith C, Koshy P (2013) Applications of Acoustic Mapping in Electrical Discharge Machining. CIRP Annals – Manufacturing Technology 62:171–174.
[2] Goodlet A, Koshy P (2015) Real-Time Evaluation of Gap Flushing in Electrical Discharge Machining. CIRP Annals – Manufacturing Technology 64:241–244.
What unique information can be extracted from AE acquired during EDM?
AE sensor
workpiece
disk tool
Page 4© WZL/Fraunhofer IPT
Possible sources of Acoustic Emission in EDM
AE sensor
AE signal
gas
bubble plasma channel
shock
waves
tool
workpiece
Possible sources for AE:
 Plasma channel
 Gas bubble
originating from the
rapid vaporization of
the liquid dielectric in
the vicinity of the
plasma channel
 Shock waves
emanating from the
formation, implosion
and rebound of the
gas bubble
Discharges in dry EDM do not yield significant AE: the plasma channel
can therefore be excluded as a source
Page 5© WZL/Fraunhofer IPT
Analysis on source of signal generation
0 40 80 120 160
-1.0
-0.5
0.0
0.5
1.0
AE/V
time / µs
sensor 1
sensor 1disk tool
sensor 2
sensor 2
AE during EDM can be attributed to the dynamics of gas bubbles
Experimental trial
with two identical
AE sensors:
 In contrast to
Sensor 1, the
second sensor
that only detects
the shock wave,
registers much
weaker signals
 Swapping of
sensors reveals
same results
Page 6© WZL/Fraunhofer IPT
Acknowledgements5
Conclusions and outlook4
Results of sequential discharge experiments3
Results of single discharge experiments2
Introduction and experimental setup1
Outline
Page 7© WZL/Fraunhofer IPT
Correlations between AE, Force and High-Speed-Images
0 100 200 300 400
-3
0
3
6
9
force/V
time / µs
on-time
1st collapse
2nd collapse
pressure
pulse
3rd collapse
-0.6
-0.3
0.0
0.3
0.6
AE/V
EMI
time delay
pressure pulse
1st collapse
2nd collapse
3rd collapse
a
d
fe
c
g h i
(A)
(B)
 Interpretation of the AE signal
by referring to the discharge
force signal
 Signals span ~200 times the
discharge on-time
Single discharge between wire electrode and force sensor
Page 8© WZL/Fraunhofer IPT
(f) 175 µs
(g) 200 µs (h) 230 µs (i) 270 µs
(a) 0.5 µs (c) 50 µs
(d) 100 µs (e) 112 µs
0.5 mm
bubble
electrode
dielectric
force
sensor
bubble inception
first collapse first rebound
second reboundsecond collapse third collapse
maximum
bubble
volume
bubble implosion
Stages of bubble expansion from high speed imaging
Time steps:
 inception and rapid
growth of the gas bubble
 maximum expansion
 bubble compression,
leading to its first collapse
 first rebound
 second collapse
 second rebound
 third collapse
Page 9© WZL/Fraunhofer IPT
Spectrogram of AE burst and time evolution at 330 kHz
600
400
500
300
200
100
0
frequency/kHz
-60
-65
-70
-75
-80
-85
dB
0 100 200 300 400
0.00
0.15
0.30
0.45
0.60
amplitude/V
time / µs
EMI pressure
pulse
2nd collapse
3rd collapse
1st collapse
 Extraction of additional
information through
examination of
spectrogram
 A slice of the spectrogram
at a frequency of 330 kHz
that corresponds to the
maximum amplitude:
Accentuation of features
such as second and third
collapse which were not
as readily apparent in the
AE signal before
Page 10© WZL/Fraunhofer IPT
Correlation between Peak Force and Peak AE signals
0.0 1.5 3.0 4.5 6.0 7.5 9.0
0.00
0.75
1.50
2.25
3.00
peakAE/V
peak force / V
 Remarkable linear
correlation between
peak discharge
force and peak AE
amplitude
 Range of
experiments
including variation
of
– Discharge current
– Open circuit voltage
– On-time
Peak force may be
estimated from the AE
signal
Page 11© WZL/Fraunhofer IPT
Dynamics of bubble collapse in EDM gap space
expansion compression split impingement
bubble
(a) 150 µs (b) 200 µs
0.4 mm
bubble
debris
Jet impingement may change removal mechanism for on-times exceeding ~100 µs
Page 12© WZL/Fraunhofer IPT
Acknowledgements5
Conclusions and outlook4
Results of sequential discharge experiments3
Results of single discharge experiments2
Introduction and experimental setup1
Outline
Page 13© WZL/Fraunhofer IPT
Correlations between process parameters and RMS AE I/II
100 150 200 250
0.04
0.05
0.06
0.07
0.08
0.09
AERMS/V
open circuit voltage / V dielectric
oil water
0.00
0.02
0.04
0.06
At a higher gap width due to increased open circuit voltage, the bubble does less work against the
surrounding fluid as it initially expands and it assumes a larger volume: higher bubble pressure and a
larger contact area yields higher AE. This hypothesis is verified by higher AE RMS corresponding to
lower kinematic viscosity of the dielectric fluid (water: 1 mm²/s vs. oil: 3.8 mm²/s).
AE correlates with the energy available for bubble dynamics
 RMS AE increases
with the open circuit
voltage although
discharge energy and
the resulting MRR are
constant
 RMS AE depends
strongly on gap width
and dielectric viscosity
Page 14© WZL/Fraunhofer IPT
Correlations between process parameters and RMS AE II/II
10 100
0.03
0.04
0.05
0.06
0.07
0.08
0.09
AERMS/V
pulse on-time / µs
workpiece cathode
workpiece anode
2 5 20 50 100 200 300 400
0.027
0.028
0.029
0.030
0.031
λ / (W/mK)
brass
aluminum
copper
500
Crossover in oil can be explained by carbon formation on anode at large pulse on-times > ~20 µs that
apportions more energy into the gas bubble. Thermal conductivity of electrode material further
determines energy in the gas bubble. The greater the thermal conductivity of anode, less energy is
available in the bubble and lower the AE
 Polarity effect for
MRR in oil:
– Long pulse:
workpiece cathode
– Short pulse:
workpiece anode
 More energy
partition to the
anode
 For water dielectric,
red curve stays
above the blue one
with no crossover
Page 15© WZL/Fraunhofer IPT
Acknowledgements5
Conclusions and outlook4
Results of sequential discharge experiments3
Results of single discharge experiments2
Introduction and experimental setup1
Outline
Page 16© WZL/Fraunhofer IPT
Conclusions and outlook
AE sensor
AE signal
gas bubble
plasma channel
shock waves
tool
workpiece
(a) 150 µs
bubble
debris
 Conclusions
– The AE signal was shown to essentially
reflect the energy available within the
gas bubble
– It comprises features pertaining to the
pressure pulse from the rapid expansion
of the gas bubble, followed by several
collapse and rebound cycles
– Jet impingement was identified to
contribute to removal for discharges
with long pulse on-times (> ~100 µs)
– Sequential discharge results are in line
with new theories regarding pyrolytic
carbon deposition, which depends on
the polarity and dielectric fluid used and
the pulse on-time
 Outlook
– There is a high potential for AE enabling
further unique insights into EDM
Page 17© WZL/Fraunhofer IPT
Acknowledgements5
Conclusions and outlook4
Results of sequential discharge experiments3
Results of single discharge experiments2
Introduction and experimental setup1
Outline
Page 18© WZL/Fraunhofer IPT
Acknowledgements
 German Research Foundation (DFG), Collaborative
Research Center SFB/TRR 136 “Process Signatures”
(Bremen, Aachen, Oklahoma) sub project F02.
 Alexander von Humboldt Foundation – Alumni Program,
Support for: Fundamental Investigations Into Acoustic
Emission From Electrical Discharge Machining,
Professor Philip Koshy, McMaster University, Canada.
 Industrial Research Circle EAK (Arbeitskreis
Elektroerosive Bearbeitung): Support for pre-competitive
fundamental and applied research in the area of EDM
and vast support in re-building research capabilities and
infrastructure after the big fire at WZL in February 2016.
EAK

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Acoustic emission signatures of electrical discharge machining

  • 1. Acoustic emission signatures of electrical discharge machining International Academy for Production Engineering 66th General Assembly – Guimaraes, Portugal, Aug. 21-27, 2016 CIRP Annals - Manufacturing Technology Volume 65, Issue 1, 2016, Pages 229 - 232 A. Klink, M. Holsten, S. Schneider & P. Koshy
  • 2. Page 2© WZL/Fraunhofer IPT Acknowledgements5 Conclusions and outlook4 Results of sequential discharge experiments3 Results of single discharge experiments2 Introduction and experimental setup1 Outline
  • 3. Page 3© WZL/Fraunhofer IPT Acoustic Emission (AE) in the context of EDM  AE – transient elastic waves in response to mechanical loading: – Inherently generated in cutting processes – Generated also during EDM, but not well understood  Availability of process information [1,2]  Monitoring of gap phenomena using AE is possible [1] Smith C, Koshy P (2013) Applications of Acoustic Mapping in Electrical Discharge Machining. CIRP Annals – Manufacturing Technology 62:171–174. [2] Goodlet A, Koshy P (2015) Real-Time Evaluation of Gap Flushing in Electrical Discharge Machining. CIRP Annals – Manufacturing Technology 64:241–244. What unique information can be extracted from AE acquired during EDM? AE sensor workpiece disk tool
  • 4. Page 4© WZL/Fraunhofer IPT Possible sources of Acoustic Emission in EDM AE sensor AE signal gas bubble plasma channel shock waves tool workpiece Possible sources for AE:  Plasma channel  Gas bubble originating from the rapid vaporization of the liquid dielectric in the vicinity of the plasma channel  Shock waves emanating from the formation, implosion and rebound of the gas bubble Discharges in dry EDM do not yield significant AE: the plasma channel can therefore be excluded as a source
  • 5. Page 5© WZL/Fraunhofer IPT Analysis on source of signal generation 0 40 80 120 160 -1.0 -0.5 0.0 0.5 1.0 AE/V time / µs sensor 1 sensor 1disk tool sensor 2 sensor 2 AE during EDM can be attributed to the dynamics of gas bubbles Experimental trial with two identical AE sensors:  In contrast to Sensor 1, the second sensor that only detects the shock wave, registers much weaker signals  Swapping of sensors reveals same results
  • 6. Page 6© WZL/Fraunhofer IPT Acknowledgements5 Conclusions and outlook4 Results of sequential discharge experiments3 Results of single discharge experiments2 Introduction and experimental setup1 Outline
  • 7. Page 7© WZL/Fraunhofer IPT Correlations between AE, Force and High-Speed-Images 0 100 200 300 400 -3 0 3 6 9 force/V time / µs on-time 1st collapse 2nd collapse pressure pulse 3rd collapse -0.6 -0.3 0.0 0.3 0.6 AE/V EMI time delay pressure pulse 1st collapse 2nd collapse 3rd collapse a d fe c g h i (A) (B)  Interpretation of the AE signal by referring to the discharge force signal  Signals span ~200 times the discharge on-time Single discharge between wire electrode and force sensor
  • 8. Page 8© WZL/Fraunhofer IPT (f) 175 µs (g) 200 µs (h) 230 µs (i) 270 µs (a) 0.5 µs (c) 50 µs (d) 100 µs (e) 112 µs 0.5 mm bubble electrode dielectric force sensor bubble inception first collapse first rebound second reboundsecond collapse third collapse maximum bubble volume bubble implosion Stages of bubble expansion from high speed imaging Time steps:  inception and rapid growth of the gas bubble  maximum expansion  bubble compression, leading to its first collapse  first rebound  second collapse  second rebound  third collapse
  • 9. Page 9© WZL/Fraunhofer IPT Spectrogram of AE burst and time evolution at 330 kHz 600 400 500 300 200 100 0 frequency/kHz -60 -65 -70 -75 -80 -85 dB 0 100 200 300 400 0.00 0.15 0.30 0.45 0.60 amplitude/V time / µs EMI pressure pulse 2nd collapse 3rd collapse 1st collapse  Extraction of additional information through examination of spectrogram  A slice of the spectrogram at a frequency of 330 kHz that corresponds to the maximum amplitude: Accentuation of features such as second and third collapse which were not as readily apparent in the AE signal before
  • 10. Page 10© WZL/Fraunhofer IPT Correlation between Peak Force and Peak AE signals 0.0 1.5 3.0 4.5 6.0 7.5 9.0 0.00 0.75 1.50 2.25 3.00 peakAE/V peak force / V  Remarkable linear correlation between peak discharge force and peak AE amplitude  Range of experiments including variation of – Discharge current – Open circuit voltage – On-time Peak force may be estimated from the AE signal
  • 11. Page 11© WZL/Fraunhofer IPT Dynamics of bubble collapse in EDM gap space expansion compression split impingement bubble (a) 150 µs (b) 200 µs 0.4 mm bubble debris Jet impingement may change removal mechanism for on-times exceeding ~100 µs
  • 12. Page 12© WZL/Fraunhofer IPT Acknowledgements5 Conclusions and outlook4 Results of sequential discharge experiments3 Results of single discharge experiments2 Introduction and experimental setup1 Outline
  • 13. Page 13© WZL/Fraunhofer IPT Correlations between process parameters and RMS AE I/II 100 150 200 250 0.04 0.05 0.06 0.07 0.08 0.09 AERMS/V open circuit voltage / V dielectric oil water 0.00 0.02 0.04 0.06 At a higher gap width due to increased open circuit voltage, the bubble does less work against the surrounding fluid as it initially expands and it assumes a larger volume: higher bubble pressure and a larger contact area yields higher AE. This hypothesis is verified by higher AE RMS corresponding to lower kinematic viscosity of the dielectric fluid (water: 1 mm²/s vs. oil: 3.8 mm²/s). AE correlates with the energy available for bubble dynamics  RMS AE increases with the open circuit voltage although discharge energy and the resulting MRR are constant  RMS AE depends strongly on gap width and dielectric viscosity
  • 14. Page 14© WZL/Fraunhofer IPT Correlations between process parameters and RMS AE II/II 10 100 0.03 0.04 0.05 0.06 0.07 0.08 0.09 AERMS/V pulse on-time / µs workpiece cathode workpiece anode 2 5 20 50 100 200 300 400 0.027 0.028 0.029 0.030 0.031 λ / (W/mK) brass aluminum copper 500 Crossover in oil can be explained by carbon formation on anode at large pulse on-times > ~20 µs that apportions more energy into the gas bubble. Thermal conductivity of electrode material further determines energy in the gas bubble. The greater the thermal conductivity of anode, less energy is available in the bubble and lower the AE  Polarity effect for MRR in oil: – Long pulse: workpiece cathode – Short pulse: workpiece anode  More energy partition to the anode  For water dielectric, red curve stays above the blue one with no crossover
  • 15. Page 15© WZL/Fraunhofer IPT Acknowledgements5 Conclusions and outlook4 Results of sequential discharge experiments3 Results of single discharge experiments2 Introduction and experimental setup1 Outline
  • 16. Page 16© WZL/Fraunhofer IPT Conclusions and outlook AE sensor AE signal gas bubble plasma channel shock waves tool workpiece (a) 150 µs bubble debris  Conclusions – The AE signal was shown to essentially reflect the energy available within the gas bubble – It comprises features pertaining to the pressure pulse from the rapid expansion of the gas bubble, followed by several collapse and rebound cycles – Jet impingement was identified to contribute to removal for discharges with long pulse on-times (> ~100 µs) – Sequential discharge results are in line with new theories regarding pyrolytic carbon deposition, which depends on the polarity and dielectric fluid used and the pulse on-time  Outlook – There is a high potential for AE enabling further unique insights into EDM
  • 17. Page 17© WZL/Fraunhofer IPT Acknowledgements5 Conclusions and outlook4 Results of sequential discharge experiments3 Results of single discharge experiments2 Introduction and experimental setup1 Outline
  • 18. Page 18© WZL/Fraunhofer IPT Acknowledgements  German Research Foundation (DFG), Collaborative Research Center SFB/TRR 136 “Process Signatures” (Bremen, Aachen, Oklahoma) sub project F02.  Alexander von Humboldt Foundation – Alumni Program, Support for: Fundamental Investigations Into Acoustic Emission From Electrical Discharge Machining, Professor Philip Koshy, McMaster University, Canada.  Industrial Research Circle EAK (Arbeitskreis Elektroerosive Bearbeitung): Support for pre-competitive fundamental and applied research in the area of EDM and vast support in re-building research capabilities and infrastructure after the big fire at WZL in February 2016. EAK