This document presents research on understanding partial discharge activity in transformer oil under transient voltages using acoustic emission techniques. Three defects were studied: corona discharge, discharge from a floating particle, and discharge from particle movement. Acoustic emission signals were captured from these defects under standard lightning impulse voltages and analyzed using fast Fourier transforms. Ternary plots were generated from the FFT outputs to classify the discharges from different defects. The acoustic emission signals from discharges under AC voltages were also compared to those under lightning impulse voltages. Inception voltages were found to be lower under AC than lightning impulse voltages, and varied between the different defect types studied.

1. Understanding of Partial discharge activity in
transformer oil under transient voltages adopting
Acoustic emission technique
A. S. Prasanna Venkatesh2
, M. G. Danikas3
and R. Sarathi1
1
Department of Electrical Engineering, IIT Madras, Chennai- 600 036
2
Department of Electronics and Communication Engineering, SSNCE, Kalavakkam, Kancheepuram- 603 110
3
Department of Electrical and Computer Engineering, Democritus University of Thrace, GR-671 00 Xanthi, Greece
Abstract-- One of the causes for the failure of power
transformers is due to formation of partial discharges. Partial
discharge taking place in transformer oil under AC voltages
were studied by researchers worldwide in detail. But for the PD
formation under transient voltages, the results are scanty. In
the present work, three different defects were considered viz.
corona discharge, discharge initiated due to floating particle
and discharge formation due to particle movement and the
discharges initiated by these defects under standard lightning
impulse were studied adopting acoustic emission technique. The
FFT analysis of AE signal obtained due to different defects has
close resemblance and hence the ternary plots were obtained
using the FFT output of the AE signal and classified. MRSD
technique was adopted to remove the noise signal in the AE
signal formed due to the discharges. The AE signal obtained
due to discharges under AC voltages were compared with the
signals obtained under standard lightning impulse voltage.
Index Terms— Acoustic Emission, corona, FFT, Lightning
impulse, Partial Discharge, Transformer oil.
I. INTRODUCTION
Transformer is one of the most important and expensive
equipments in the electrical power system network. The
insulation of the transformers consists of the transformer oil
with solid insulating materials such as pressboard, paper
insulation, bakelite, etc. One of the major causes for failure
of transformer insulation is due to formation of partial
discharges (PD) [1]. These partial discharges can be formed
due to any conducting or non conducting particle present in
the transformer insulation, corona discharge from the
protrusions in the current carrying conductor or in the ground
electrode or by the discharges initiated due to floating
conducting particles. The floating conducting particle can be
due to any dropout of metal from the surface of the conductor
during manufacturing.
The presence of any defect in the insulation structure,
under normal operating voltages can cause local field
enhancement near the defect site initiating discharges,
thereby releasing certain amount of energy in the form of
burst/impulsive pulses (acoustic energy) that radiate in all
directions [1, 2]. The released energy can be detected by
mounting a transducer over the surface of the structure. This
process is known as “Acoustic Emission” (AE). The signals
detected are called acoustic signals, which are used for
diagnostic study [3]. Acoustic emission technique’s use for
identification of defects and its application in the high voltage
field is significant. Considerable research work was carried
out to understand the partial discharge activity in transformer
oil insulation under AC and DC voltages [6, 7]. In the
present work, in addition to the normal operating AC voltage,
the transformer insulation is subjected to transient voltage
formed due to lightning or due to any switching operation.
Most of the work carried out in transformer oil is to
understand the partial discharges under the AC/DC voltages.
The partial discharge formed due to lightning impulse
voltage, for various defects were studied.
Hence the author has carried out a methodical experimental
study to understand the partial discharge activity due to
various defects in transformer oil, under lightning impulse
voltage, adopting Acoustic emission technique. The
influences of polarity of the applied voltage on the PD
formation were studied. It is essential to classify the
discharges initiated due to different defects and in the present
study ternary plots were obtained by using the FFT output of
the AE signals measured during discharges, for classification.
II. EXPERIMENTAL STUDIES
The basic experimental setup used in the present study is
shown in Fig. 1. The experimental setup could be sectioned
into three parts. The first, second and third parts of the
experimental setup include a high voltage source, an oil test
chamber with an acoustic emission sensor mounting (Test
apparatus) and a pre-amplifier with a data acquisition system
for post analysis of the acquired acoustic signals.
A. High Voltage source
The high AC voltage is produced from a 100kV, 5kVA, 50
Hz test transformer. The applied voltage was measured using
a capacitance voltage divider with peak voltmeter. The
standard lightning impulse voltage was generated using single
step impulse generator (140kV) and the generated voltage
was measured using capacitance divider.
2011 6th International Conference on Industrial and Information Systems, ICIIS 2011, Aug. 16-19, 2011, Sri Lanka
98
978-1-61284-0035-4/11/$26.00 ©2011 IEEE

2. Fig. 1 Experimental setup
B. Test Electrode Configuration
The stainless steel leak-proof test cell with dimensions of
12x12x12 cm of rectangular cross section, fitted with a high
voltage bushing at the top and bottom side of the chamber,
filled with transformer oil is used for the experiment. To
simulate the corona effect a needle-plane configuration was
used in the above mentioned test cell. To simulate the PD
activity due to the presence of floating particle, an
arrangement was made such that a conducting particle
(copper wire of dimension 5mm x 1mm) remains exactly
midway between the top electrode and the ground electrode.
For this purpose a pressboard (thickness 2mm) was used to
keep the particle midway and a small hole was drilled and the
wire was inserted. Thus the floating particle effect was
simulated. To simulate the PD activity due to movement of
the conducting particle (particle movement), a 2mm diameter
aluminium ball was placed on a slightly concave ground
electrode and the distance between the particle and the top
electrode was kept as 5 mm. The acoustic sensor is mounted
on the sidewalls of the test cell so that the longitudinal signal
energy of the acoustic signals produced due to the discharge
is transferred to the input of the AE sensor.
C. Acoustic Emission Instrumentation
The AE sensors are piezoelectric transducers, which
convert the acoustic signal into corresponding electric
signals. The partial discharge signals are wide band signals.
When a signal propagating in the medium hits the walls, it is
partly reflected and partly transmitted because of the low
absorption coefficient of the wall material. The partial
discharge inception voltage is identified as the voltage at
which the first acoustic emission signal is captured for the
defined conditions.
In the present work, a wide band sensor with frequency
response in the range 100KHz – 1MHz was used.
Optimization between the bandwidth and sensitivity is an
important factor. To get a maximum sensitivity, the sensor
must be attached to the test specimen in such a manner that
acoustic energy passes into the transducer with minimum loss
at the transducer material. The required contact was achieved
by applying a thin layer of gel between the sensor and the
surface of the chamber.
The AE signal generated by the sensor has to be amplified
to the required voltage magnitude. This is accomplished with
a pre-amplifier placed close to the sensor to minimize the
pickup of electromagnetic interference. The pre-amplifier has
a wide dynamic range and can drive the signal over a long
length of cable near the data acquisition system. Pre-
amplifiers inevitably generate electronic noise, and it is the
noise that sets the sensitivity of the acoustic emission system.
The gain of the integrated pre- amplifier is set to 40 dB with a
1 MHz bandwidth. In the present study, PCI-2, a 2 channel
acoustic emission system of Physical Acoustic Corporation
was used [8, 9]. The acquired AE signals were processed to
eliminate noise signal by adopting multi-resolution signal
decomposition technique (MRSD).
III. RESULTS AND DISCUSSION
Fig. 2 shows variation in discharge inception voltages due to
various defects (which includes corona activity, floating
particle and by the movement of conducting particle) under
different voltage profiles. The incipient discharges under LI
were generated by applying 80% of the breakdown voltage
that is calculated for the gap with the defect especially for the
floating conductor and the electrode gap with a spherical
particle. If the applied voltages were less than the 80% of the
breakdown voltage of the electrode gap, no discharges were
observed. Thus the inception voltage for the two defects
especially for the floating particle and the particle sitting on
the ground electrode were taken to be 80% of the breakdown
voltage. For each input voltage, the test was carried out eight
times and the AE signals were captured due to the discharge.
Thus comparing, it is observed that irrespective of type of
defect causing discharge, the discharge inception voltage is
less under AC voltage compared with the lightning impulse
voltage. In the present study, the discharge inception voltage
Fig. 2 Inception Voltages in kV for different defects
under different voltage profiles; PM-Particle Movement;
CD-Corona Discharge; FP-Floating Particle
2011 6th International Conference on Industrial and Information Systems, ICIIS 2011, Aug. 16-19, 2011, Sri Lanka
99

3. is defined as the voltage at which the first AE signal is
acquired. In case of the lightning impulse voltage, the
inception voltage is nearly the same for both polarities.
Among the three types of defects, the discharge inception
voltage (AC/LI) is high for the floating particle followed by
corona discharge and then by the discharge initiated due to
particle movement. Fig.3 shows typical AE signal generated
due to corona discharge in transformer oil under different
voltage profiles. It is observed that burst type or impulsive
type discharges can occur. It is observed that under AC
voltages, for Corona discharge, the FFT analysis of the AE
signal indicates that the maximum energy of the signal lies in
the frequency range between 400 kHz and 600 kHz. This
characteristic is the same under lightning impulse voltages.
Fig. 4 shows the AE signal measured due to discharges
initiated due to floating conducting particle under different
voltages. It is observed that the magnitude of AE signal is
high under AC voltage compared with the AE signal
generated due to discharge initiated under lightning impulse
voltage. The FFT analysis of the AE signal generated due to
floating electrode discharges indicates the energy content
spreads in the range 100 kHz to 600 kHz. The frequency
contents in the AE signal generated due to discharges
initiated by floating particle under LI is much different from
the AC voltage and the frequency contents are different for
positive and negative LI voltages. In general impulsive type
discharge occurs with AE signal generated under AC voltage
and burst type signal occurs under transient voltages
especially with discharge initiated due to floating particle and
movement of conducting particle.
Particle initiated partial discharge is one of the major
causes for the failure of transformer insulation. The particle
levitates once the force exerted by the particle is much higher
than the applied electric field [4]. Fig. 5 shows typical AE
signal generated due to particle initiated discharges under AC
and LI voltages. It is observed that impulsive type discharges
occurs under AC voltage and burst type discharge occurs
under LI voltage. The FFT analysis of AE signal generated
due to particle movement under AC voltage, the frequency
content of the AE signal lies in the entire range of 100kHz to
1MHz. Under LI voltage, irrespective of polarity of LI
voltage, the frequency content of AE signal formed lies in the
range 200-600 kHz. The MRSD technique was used to
remove the noise content from the obtained AE signal in
order to obtain the required AE signal.
The AE time domain signals acquired for different type of
discharges and with its corresponding FFT patterns, it is
observed that the frequency contents of the AE signals are
nearly the same and so difficult to classify the defect causing
AE signal. To understand the intricate details further the
frequency contents in the AE signal formed due to different
defects, the partial power analysis to the AE signal generated
Fig. 3 Typical AE signals generated due to corona discharge under different
voltages (I) AC (II) +LI (III) –LI (a) Time domain (b) its corresponding FFT
output
Fig. 4 Typical AE signals generated due to discharge initiated by floating
particle under different voltages (I) AC (II) +LI (III) –LI (a) Time domain
(b) its corresponding FFT output
Fig. 5 Typical AE signals generated due to particle movement under
different voltages (I) AC (II) +LI (III) –LI (a) Time domain (b) its
corresponding FFT output
2011 6th International Conference on Industrial and Information Systems, ICIIS 2011, Aug. 16-19, 2011, Sri Lanka
100

4. Fig. 6 Ternary diagram classifying the defects under various voltages (i) AC (ii) +LI (iii) -LI
due to discharges was carried out, which will be the input
data for generating the Ternary plot.
Partial Power is calculated by summing the power
spectrum in a specified range of frequencies and dividing it
by the total power. The power spectrum was calculated up to
800 kHz is split equally and the partial powers were
calculated in three zones (x= (200–400 kHz), y= (400-600
kHz) and z= (600-800 kHz)). The Triangle coordinates
corresponding to energy content be calculated as follows.
Normalized energy content in the range 200-400 kHz = x/(x +
y + z); Normalized energy content in the range 400-600 kHz
= y /(x +y +z) and the normalized energy content in the range
600-800 kHz = z/(x + y + z). This normalisation technique is
identical to the process used to generate the gas in oil ratio
used to plot the Duval’s triangle. Fig. 6 shows the ternary
plot obtained for various defects under AC and lightning
impulse voltage. It is observed that the location in the ternary
plot is slightly different for the corona discharge under AC
and LI voltages. The location of discharge due to floating
particle and particle movement are nearly same under LI
voltages of both polarities. Further analysis is required for its
implementation in practice.
IV. CONCLUSIONS
The important conclusions acquired based on the present
study are the following.
(i) AE sensors could indentify PD generated under transient
voltages. Burst type and impulsive type AE signals are
generated due to partial discharges in transformer insulation.
(ii) The magnitude of AE signal is always high with AE
signals generated by discharges under AC voltages. It is also
noticed that impulsive type discharges occurs under AC
voltages and burst type discharge occurs under lightning
impulse voltage. Irrespective of the type of defect, the
duration of AE signal formed is high under negative LI
voltage compared with positive LI voltage.
(iii) The Frequency domain analysis of AE signal could help
one to identify the dominant frequency contents. But the
ternary plot obtained based on FFT output of the AE signal
helps one to classify the type of discharges. The results of
ternary plot indicates that the frequency content of AE signals
generated due to discharges under positive and negative
lightning impulse and AC voltages are different, indicating
that the mechanism of discharge formation under various
voltages are different.
(iv) Ternary diagram provides major location for variety of
discharges and is a simple visual technique for identification.
REFERENCES
[1] G. Koperundevi , M. K. Goyal, Sunil Das, N. K. Roy, R.
Sarathi, ” Classification of Incipient discharges in Transformer
Insulation using Acoustic Emission Signatures”, 2010 Annual
IEEE India Conference (INDICON).
[2] Ramanujam Sarathi, Prathap D. Singh, Michail G. Danikas,
“Characterization of Partial Discharges in Transformer oil
insulation under AC and DC voltage using Acoustic Emission
Technique”, Journal of ELECTRICAL ENGINEERING ,VOL 58,
NO. 2, 2007, pp.91-97
[3] Prasantha kundu, N. K. Kishore, A. K. Sinha,” Behavior of
Acoustic Partial Discharge In Oil-Pressboard Insulation System”,
2008 IEEE Region 10 and the third ICIIS, Kharagpur, INDIA
December 8-10, Paper Identification No: 88
[4] Boczar T.:” Identification of a Specific Type of PD from
Acoustic Emission Frequency Spectra”, IEEE Trans. Diel.
Electr. Insul. DEI-8 (2001), 598–606.
[5] Kennedy, W.: “Recommended Dielectric Tests and Test Proc
edures for Converter Transformers and Smoothing Reactors,
IEEE Trans. Power Deliv. PD-1 (1986), 161–166.
[6] Pompili, M, Mazzetti, C. Barnikas, R.: “Partial Discharge Pulse
Sequence Patterns and Cavity Development Times in Transformer
Oils under ac Conditions” , IEEE Trans. Diel. Electr. Insul. DEI-
12 (2005), 395–403.
[7] Cavallini A. Montanari,G.C.—CianiI,F.: “Analysis Of Partial
Discharge Phenomena in Paper Oil Insulation Systems as a Basis
for Risk Assessment Evaluation”, Proc. IEEE Intern. Conf. Diel.
Liquids, Coimbra, Portugal, 26 June–1 July 2005, 241–244.
[8] Pollock A. A.: ACOUSTIC Emission Inspection , Physical
Acoustic Corporation ,Technical Report TR-103-96-12/89.
[9] PCI-2 Based User’s Manual, Physical Acoustic Corporation.
(i) (ii)
(A)-Corona Discharge; (B)-Floating Particle; (C)-Particle movement
(i) (ii) (iii)
2011 6th International Conference on Industrial and Information Systems, ICIIS 2011, Aug. 16-19, 2011, Sri Lanka
101