Acoustic emission signatures of electrical discharge machining

Acoustic emission signatures of electrical discharge machining

International Academy for Production Engineering66th 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

http://www.sciencedirect.com/science/journal/00078506

Page 2© WZL/Fraunhofer IPT

Acknowledgements5

Conclusions and outlook4

Results of sequential discharge experiments3

Results of single discharge experiments2

Introduction and experimental setup1

Outline


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


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 bubbleoriginating 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


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


Acknowledgements5





Outline


Correlations between AE, Force and High-Speed-Images

0 100 200 300 400-3

0

3

6

9

forc

e / V

time / µs

on-time

1st collapse

2nd collapsepressure 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

ad

fec

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


(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 imagingTime 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


Spectrogram of AE burst and time evolution at 330 kHz

600

400500

300200100

0

frequ

ency

/ kH

z

-60

-65

-70

-75

-80

-85dB

0 100 200 300 4000.000.150.300.450.60

ampl

itude

/ V

time / µs

EMI pressurepulse

2nd collapse3rd 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


Correlation between Peak Force and Peak AE signals

0.0 1.5 3.0 4.5 6.0 7.5 9.00.00

0.75

1.50

2.25

3.00

peak

AE

/ 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


Dynamics of bubble collapse in EDM gap spaceexpansion compression split impingement

bubble

(a) 150 µs (b) 200 µs

0.4 mm

bubbledebris

Jet impingement may change removal mechanism for on-times exceeding ~100 µs


Acknowledgements5





Outline


Correlations between process parameters and RMS AE I/II

100 150 200 2500.04

0.05

0.06

0.07

0.08

0.09

AE R

MS

/ 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


Correlations between process parameters and RMS AE II/II

10 1000.03

0.04

0.05

0.06

0.07

0.08

0.09

AE R

MS

/ V

pulse on-time / µs

workpiece cathode

workpiece anode

2 5 20 50 100 200 300 4000.027

0.028

0.029

0.030

0.031

λ / (W/mK)

brassaluminum

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 theanode

For water dielectric, red curve stays above the blue one with no crossover


Acknowledgements5





Outline


Conclusions and outlook

AE sensor

AE signal

gas bubble plasma channel

shock waves

tool

workpiece

(a) 150 µs

bubbledebris

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


Acknowledgements5





Outline


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