Download PD Acoustic Response in Oil-Filled Transformers

PD Acoustic Response in Oil-Filled Transformers
Juraj KURIMSKÝ∗
Abstract
In oil-filled transformers, partial discharges generate electromagnetic impulses which energy is transformed
into mechanical energy in the form of pressure waves. For the purpose of power transformer diagnostics,
several different approaches are used to partial discharges in insulating system. Theory of acoustic waves,
generated by partial discharges (PDs) in power transformers, and the PD acoustic emission and methods of
detection are described. Two types of waves are discussed, which can be used for non-destructive testing of
power transformer insulating system. The principle of PD source localization by means of acoustic range wave
detection is described. Experimental procedure applied to 110 kV power transformer and results are
presented.
Keywords: partial discharges, acoustic emission, power transformer
1. Introduction
There are several methods developed to
examine operational conditions of crucial
systems of oil-immersed transformers during
the life-time [1, 2, 3, 4]. They are based on
specific physical phenomena which are
transformed into the observable variable or
parameter. The 'specific' above means that
nature of these effects can be physical,
chemical, electric, etc. For the purpose of
power transformer diagnostics, three different
approaches are used to asset partial
discharges in insulating system. There are:
electric methods, dissolved gas analysis and
acoustic emission measurements. Electric
methods are based on electromagnetic field
change detection and electric current pulses
measurements, respectively. The last one
provides the ability to quantify the apparent
charge of PD and determine the amount of
degradation
energy.
Generally,
the
measurements can be performed either online or off-line.
The maintenance of power transformers
became very important work for utility
companies [5]. Many aspects of operational
parameters are analyzed to produce relevant
results. Due to chemical decomposition,
partial discharges produce the change
chemical properties of insulating oil. Dissolved
Gas Analysis (DGA) is effective tool widely
used to determine operational safety of power
transformers [6]. By means of DGA it can be
distinguished if operation is normal or near to
∗
Juraj KURIMSKÝ: PhD., Technical University of Košice,
Mäsiarska 74, 04001 Košice, Slovakia, [email protected]
a fault condition. There are three stages DGA:
taking a sample of oil (sampling), gas
chromatography and, finally, the analysis. The
state of the art overcomes classical analysis
moreover they are used modern data mining
methods and forecasting of gases content in
transformer oil [7, 8].
The method of acoustic emission detection
is useful for assessing the activity of partial
discharges during operation and is based on
detecting and locating sources of pressure
waves caused by electric discharge in the fluid
of insulating oil. The origins of the application
of this method are in the sixties of the 20th
century. There are several comprehensive
publications
on theory and practical
considerations of acoustic emission, e.g. [9,
10, 11].
2. PD acoustic emission in oil-filled
transformers
In oil-filled transformers, partial discharges
generate electromagnetic impulses which
energy is transformed into mechanical energy
in the form of pressure waves. The
transformation of the energy from one form to
another one is not able to be described by a
simple function as it depends on many
parameters, e.g. the kind and intensity of
partial
discharge,
dielectrics
nature,
surrounding properties, etc.
Depending on these parameters, the
duration of the pressure wave can vary. The
wave is distributed through the oil medium
until its front touches the transformer tank or
a solid object, which is the part the
transformer skeleton. There are several ways
ELECTROTEHNICĂ, ELECTRONICĂ, AUTOMATICĂ, vol. 62 (2014), nr. 1
to use this phenomenon for diagnostic
measurements. The acoustic wave generated
by pressure field is expressed by a second
order differential formula
(1)
where p is the pressure field, ∇ is the Laplace
operator, v is the velocity of sound in the
medium and t is the time.
There are five basic parameters that
quantify the acoustic pressure wave are:
− sound speed v (m/s)
2
− the intensity of sound waves I (W/m )
− sound pressure p (Pa)
− sound intensity LI (dB) and
− sound pressure level LP (dB).
Acoustic waves spread through the oil
medium in all directions. This type of pressure
waves are also called spherical wave and
location of partial discharge creates an
acoustic point-source. Generally, there are
longitudinal and share wave types in real
environments. Whilst longitudinal waves cause
the medium moving in the direction of
propagation, the shear waves produce the
motion transverse to the direction of
propagation. Several physical mechanisms are
applied:
spatial
attenuation,
acoustic
absorption,
scattering,
reflection
and
refraction. The spatial attenuation for
spherical wave is given as
(2)
where I0 is the intensity of the generated
sound pressure and Ir is the intensity of sound
pressure level at distance r from the source
wave-front. Acoustic absorption is caused by
the mechanical energy conversion into the
heat. It can be expressed as with the optical
absorption, the Lambert law:
47
striking the front of pressure waves to the
wall of the transformer tank, two types of
waves are excited in the steel material of
transformer tank. There is longitudinal vl and
shear Ls waves, which have different
velocities. The values are in the Table 1.
Table 1. Wave speed in transformer oil and steel
When analyzing the PD acoustic emission
and detection in the power transformers, the
next important element has to be taken into
account. Pressure waves, as they impact the
wall of the transformer tank, are responsible
for tank wall waves generation and motion.
Steel plate vibration belongs to mechanical
vibrations. The analysis is more complex
according the nature of steel plate. The
Kirchhoff-Love theory and the MindlinReissner theory are basics of plate motion.
Plates can be excited in so called modes,
which can be of order zero or higher orders,
too. Let us consider zero order excitation, see
Figure 1, where symmetrical (case a) and
asymmetrical (case b) waves are shown.
Figure 1. The steel plate vibrations
It should be supposed that parameters of
waves are depended on many mechanical and
structural parameters. That is true. For
instance, when steel plate of thickness of
1 cm is taken into account, the dependency of
angle of incidence on wave frequency vary for
both asymmetrical (a0) and symmetrical wave
of zero order (s0) (see Figure 2).
(3)
where β is the coefficient of absorption.
Scattering — the diffraction — occurs in
non-homogeneous materials. In the oil, there
may be gas bubbles or coagulated particles in
the volume. Scattering appears as absorption,
but losses due to scattering can be much
larger. Reflection and refraction of pressure
waves occur at the interface of two
environments. In different environments, the
pressure wave spreads at different speeds.
Applied here can be the principles of Huygens
law as well as Snell law of refraction, which
are known from optics.
In the oil medium, the only longitudinal
waves are taken into account. After they are
Figure 2. The steel plate Steel plate excitation [12]
3. The analysis of acoustic wave motion
in power transformer
Travelling, the acoustic wave front can be
analytically derived [12, 13, 14]. According
[12], simple model of real situation is given in
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ELECTROTEHNICĂ, ELECTRONICĂ, AUTOMATICĂ, vol. 62 (2014), nr. 1
locations. The most important path is this
one, which wave travelling takes minimal time
to reach the sensor in.
the Figure 3.
4. Experiment
Figure 3. The model for acoustic wave emission in
power transformer
The above facts show that the direct path
of the acoustic wave from source to the
sensor may not be the fastest, due to the
different velocities of acoustic waves in two
main physical environments – the oil and the
steel. In fact, there are many paths with
different angles of impact Φ to the
transformer tank wall by which the ultrasonic
signal can reach the sensor.
Suppose that the angle among the paths of
PD source-sensor and the path of PD-sourcetank, that is perpendicular to the plane, is Ψ.
Then the time that takes the travelling of the
wave-front from PD-source to the acoustic
sensor is:
(4)
There are several methods which can be
used for PD localization experiment by means
of acoustic emission measurements. Let us
mention two of them. The first one is simpler.
It is based on AE signal measurements in
several various places regarded to PD source.
The magnitude of acoustic emission, signal
shape and transformer design are crucial
factors for source position analysis. The
second method is running in real-time.
Acoustic signals are recorded from several
sensors. Data are processed and position of PD
source can be calculated by, e.g., triangular
method.
Previous experimentation has shown that
efficient measurement of acoustic emission
due to PD activity can be done in the
frequency range from 100 kHz up to 200 kHz.
Therefore acoustic sensors confirming this
condition have been selected with top
frequency about 160 kHz. Acoustic emission
signal response of used sensors is in the
Figure 4.
The minimal time span of acoustic wave
front arrives to the sensor can be found as
extreme solution for dt/dr =0. Just then from
formula (4) follows:
Figure 4. Acoustic sensor for PD detection response
(5)
where α is the critical incidence angle Φ of
the wave-front impact to the transformer
tank. By substituting the numbers from the
Table 1 in equation (4), we obtain a value
α=13.727°.
Two cases of impact angle are needed to
be analyzed. The first one is the case of Ψ>α.
The time tl taken to wave front arrive the
sensor is:
The model of the transformer oil tank with
PD source has been created. PD source was
placed in a known position of the source of
partial discharge of a known amount of
apparent charge. On the wall of the tank
there were placed acoustic sensors, see
Figure 5.
(6)
If Ψ≤α, then acoustic wave front reach
travels by direct path to the sensor. The
propagation time for direct path is given as:
(7)
The real situation is more complex;
moreover, acoustic sensor is receiving all
interference waves incoming from all possible
Figure 5. Experimental setup
ELECTROTEHNICĂ, ELECTRONICĂ, AUTOMATICĂ, vol. 62 (2014), nr. 1
49
The question is: how many sensors need to
be used. The answer depends on object size
and internal body complexity. For laboratory
experiments form 2 to 6 sensors are good. In
power transformers, the acoustic wave
propagation is complex due to various
materials and barriers. AE signal is changed by
means of attenuation, reflexing, refraction,
etc. In such case, the more number of
sensors, the better PD source localization. The
number of 12 AE sensors seems to be minimal
for PD localization in large
power
transformers.
5. Results
For the purpose of signal processing, the
Spartan-AT multichannel system has been
used and independent data streams from AE
sensors have been recorded.
It was confirmed by the AE measurements
and signal analysis that the location of partial
discharge sources in the model is possible
when apparent charge overcomes hundreds of
pico-Coulombs. The response of such PD signal
is transduced into typical acoustic pulse
shape. The frequency spectra depends on AE
sensors parameters. Typical shape of AE signal
caused by PD source and result of 3D location
of PD source in transformer tank is in the
Figure 6.
Figure 6. Transduced PD signal in AE sensor and 3D
PD source localization
The concept was applied on serious task of
power transformer diagnostics. It seems to be
meaningful to apply the acoustic emission
measurements and direct electric method of
PD measurement and take advantage of
apparent charge magnitude determination and
significant sources of PD localization. Both
methods give different measures of PD source
activity. Electric method offers, e.g.
magnitude of apparent charge, PD phase
distributions of several parameters, etc. The
AE measurements can analyze acoustic energy
of pressure waves in time domain for each
sensor separately and total, too, the number
of above-threshold indications, dominant
magnitude versus time characteristics of AE
waves, the amplitude of the signal sensor by
sensor. Acoustic counts are a measure of the
number of threshold crossings per AE event.
More interesting details are in [11].
6. Discussion
Typically, in a power transformer the PD
source can generate acoustic signals from 20
to 30 dB above ambient background noise
level. Then, the level of AE signals is
detectable so the timing information for the
location of the discharge source was recorded.
When signal rate and acoustic energy of
signals are high, source location can be done.
The locations were done by multi-channel
analysis of acoustic wave arrival times. The
crucial for sufficient precision are right
positions of AE sensors. The strategy of sensor
positions should be based on transformer
design and construction knowledge. An
example can be seen in Figure 7, where
sensors positions on transformer wall are
shown.
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ELECTROTEHNICĂ, ELECTRONICĂ, AUTOMATICĂ, vol. 62 (2014), nr. 1
8. Acknowledgment
"This publication is the result of the Project
implementation:
University
Science
Park
TECHNICOM
for
Innovation
Applications
Supported by Knowledge Technology, ITMS:
26220220182, supported by the Research &
Development Operational Programme funded by
the ERDF."
9. References
Figure 7. AE sensors on power transformer for PD
localization
The situation was used for PD test.
Simultaneously, the electric PD measurements
were done. The magnitude of apparent charge
of 3500 pC was measured in the circuit of
phase L1 winding. This was sufficient
magnitude for successful PD localization.
7. Conclusions
Known the limitations of electric PD testing
in a substation environment can be overcome
by applying acoustic emission PD source
location, mainly wanted test for gassing
transformers. By analyzing the acoustic
emission the faults can be detected and
localized in the insulating system, moreover,
faults in the magnetic circuit of high voltage
transformers with oil medium can be
unleashed.
Discharges in the internal partial discharge
sources can be unstable, what can be solved
by means of the long-term measurements and
analysis of acoustic emission. When PD AE
signal is more than 20 dB above the noise
background, the location is done in several
minutes after test start. In real large systems
the accuracy of several centimeters can be
achieved. Experimental results can uncover
serious defect development. Detection of
partial discharge acoustic emission opens up
renewed possibilities in the diagnosis of high
voltage oil-filled transformers. The main
advantages are: immunity to electromagnetic
interference, possibility to monitor the
transformer during the operation and location
of partial discharges sources however signal
from PD toroid sensor is well suited for
acoustic system triggering with respect to
overvoltage circuit protection [15]. The
method is particularly useful in solving the
critical conditions in HV equipment; moreover
it is great tool for condition based monitoring.
[1] BOGGS SA, “Partial discharge: overview and
signal generation”. in Electric Insulation
Magazine, IEEE. 1990; vol. 6 (no. 4): pp. 33–
39.
[2] CIMBALA R, “Dielectric spectroscopy of HV
insulation material in time and frequency
domain”. in EEEIC 2011, 10th International
Conference on Environment and Electric
Engineering, Conference proceedings, 8-11
May, 2011; Rome, Italy.
[3] DOLNIK B, Harmonic analysis of the leakage
current in surge arresters. Ph.D. Thesis.
Technical University of Košice, Slovak
Republic; 1996.
[4] BALOGH J, PETRAS J, “Inductive Sensor
Parameters Important for Partial Discharge
Measurement”. in EEA - Electrotehnică,
Electronică, Automatică. 2013; Vol. 61
(no.1): pp. 14-17.
[5] STACHO B, RUSEK S, GONO R, KRAL V,
RASKA T, “Maintenance optimisation of
transformers 110 kV/MV in distribution
networks”.
in
Proceedings
of
the
International Scientific Conference Electric
Power Engineering EPE 2007, June 2007.
VŠB-TU Ostrav; pp. 434-440, 2007.
[6] WANG Z, WANG X, YI X, LI S, HINSHAW, J.V.
“Gas generation in natural ester and
mineral oil under partial discharge and
sparking faults”. in IEEE Electric Insulation
Magazine. 2013; vol. 29 (no. 5), art. no.
6585858, pp. 62-70.
[7] YANN-CHANG HUANG, “A new data mining
approach to dissolved gas analysis of oilinsulated power apparatus”. in IEEE
Transactions on Power Delivery. 2003; vol.
18 (no. 4), pp. 1257–1261.
[8] LIAO RJ, BIAN JP, YANG LJ, GRZYBOWSKI S,
WANG YY, LI J, “Forecasting dissolved
gases content in power transformer oil
based on weakening buffer operator and
least square support vector machine–
Markov”. in Generation, Transmission &
Distribution. 2012; vol. 6 (no 2), 142–151.
[9] LUNDGAARD LE, Partial discharge. “XIII.
Acoustic partial
discharge detectionfundamental considerations”. in Electric
ELECTROTEHNICĂ, ELECTRONICĂ, AUTOMATICĂ, vol. 62 (2014), nr. 1
Insulation Magazine, IEEE. 1992; vol. 8 (no.
4), pp. 25–31.
[10] LUNDGAARD LE, “Partial discharge. XIV.
Acoustic partial
discharge detectionpractical application”. in Electric Insulation
Magazine, IEEE. 1992; vol. 8 (no. 5), pp. 34–
43.
[11] ELEFTHERION PM, “Partial discharge. XXI.
Acoustic emission based PD source location
in transformers”. in Electric Insulation
Magazine, IEEE. 1995; vol. 11 (no. 6), pp.
22–26.
[12] LUNDGAARD LE, HANSEN W, DURSUN K,
“Location
of
discharges
in
power
transformers
using
external
acoustic
sensors”. in Proc. 6th Int. Symp. High
Voltage Eng., New Orleans. 1989; paper no.
15.05.
[13] SKUBIS J, “A state of development of the
acoustic method for assesment of partial
discharges
and
directions
of
its
improvement”. in Proc. of 2nd I.C.D.I, High
Tatras, Slovakia. 2000; pp. 144–152.
[14] PHUNG BT, BLACKBURN TR, LIU Z, “Acoustic
measurements of partial discharge signals.
http://www.itee.uq.edu.au.
51
[15] DOLNIK B, GULAS R, “Sledovanie zmien
elektrických parametrov ZnO varistorov pre
siete nízkeho napätia počas urýchleného
starnutia”. in Starnutie elektroizolačných
materiálov. 2010; vol. 5 (no. 8), pp. 4–13.
10. Biography
Juraj KURIMSKY graduated the
Technical University of Košice,
Faculty of Electric Engineering in
Košice (Slovakia), in 1990. He
received the PhD degree in
electric engineering from the
Technical University of Košice, Faculty of
Electric Engineering in Košice (Slovakia), in
2003. He is assistant professor at the Technical
University of Košice, Faculty of Electric Power
Engineering (Slovakia). His research interests
concern: high voltage technique, diagnostics of
high voltage devices, physics of materials and
the material technology.