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Molecular and Quantum Acoustics vol. 25, (2004) 177
DETERMINING THE REPEATABILITY OF ACOUSTIC EMISSION GENERATED BY
THE HSU-NIELSEN CALIBRATING SOURCE
Tomasz BOCZAR, Marcin LORENC
Technical University of Opole, Department of Electrical
Engineering and Automatic Control31 K. SosnkowskiegoStr., 45-272 ,
Opole, POLAND
e-mail: [email protected], [email protected]
This paper characterizes the idea of calibrating measurement
paths, which make the measurement of the acoustic emission (AE )
pulses generated by partial discharges (PDs) in insulation of power
appliances possible, by using the Hsu-Nielsen method. It also
presents the results of the analyses done in the time and frequency
domains of the measured AE pulses generated by the Hsu-Nielsen
calibrating source. The measurement and analysis of the AE pulses
were performed on the lid of the distributive transformer tub, for
various distances between the source of calibrating signals and a
measurement transducer in the range from 2.5 to 10 cm. The analysis
of the results obtained was carried out based on a series of
selected descriptors characterizing the AE signals measured,
separately for the time and frequency domains.
Moreover, the paper presents the results of parametric and
non-parametric tests of goodness of fit, which were carried out to
determine the probability distribution of the AE pulses measured
and to examine the repeatability of the frequency analysis results
obtained for a given distance between the transducer and the source
of calibrating signals. Statistical analyses were carried out based
on the values of three descriptors: shape coefficient, peak
coefficient and median frequency, which make it possible to
identify basic PD forms occurring in insulation oil.
Keywords: Hsu-Nielsen calibration methods, partial discharges,
time and frequency analyses of AE pulses, repeatability of the
measurement results
1. INTRODUCTION
Recent years have witnessed a dynamic development of the AE
method. It finds a
wider and wider application in many industrial branches, e.g.:
raw materials, materials,
machines, electronics, and power engineering [1]. Very important
applications of the AE
method in power appliance diagnostics are detection, measurement
and location of PDs in
power transformer insulation, high-voltage transformers, bushing
insulators, SF6 switching
stations. [2]. The main factor influencing progress in the AE
measurements is the
improvement of methods and measuring apparatus as well as
deepening the knowledge of
physical processes accompanying generation and propagation of
the AE signals.
The results of the AE measurements provide electrical quantities
(e.g. voltage) the
values of which do not make it possible to determine the
absolute value of a pulse registered.
mailto:[email protected]
-
178 Boczar T., Lorenc M.
It often happens that it is not possible to measure the size of
an AE signal in the place of its
generation. It is usually so because the source of the AE is as
a rule inside the dielectric under
study, which causes that when a signal reaches a transducer it
is suppressed and reflected
many times. Moreover, the medium coupling a transducer with an
insulation system under
study can cause the suppression of the primary signal. Also the
measuring system introduces
some indeterminacy of the signal registered in relation to the
signal in the place of generation.
All these are incentives for taking quantitative measurements of
the AE based on relative
measurements. Quantitative measurements consist in comparing the
pulses under study with
model signals generated by artificial sources. A theoretical
study of this issue was given by
Breckenridge [3].
Since the AE can be either continuous or discrete, the attempts
to produce model
signals have been made, which for discrete signals correspond
with delta Dirac function and
in the case of continuous emission with white noise. As an
impulse model source breaking a
glass capillary was suggested [4]. McBride and Huchison proposed
a method consisting in
the outflow of gas from a nozzle for calibration of apparatus
for registration of continuous AE
[5]. The calibration signal should be characteristic of the
parameters determined in the time
and frequency domains and be as close to the AE signal as
possible. The most proper
calibration methods are the methods that make it possible to
produce a pulse of strictly
determined and repeatable AE parameters, which are easy to
produce in laboratory conditions.
They provide the possibility to compare the results obtained in
various laboratories dealing
with measurements and analyses of the AE signals. Calibration of
the apparatus also becomes
vital when the AE measurements are taken in a costly or
unrepeatable experiment.
The scope of the research work carried out, the results of which
are presented in this
paper, comprised the measurements of the AE signals generated by
calibrating heads made
according to the guidelines defined by Hsu-Nielsen and the
analysis of the AE signals
measured in the time and frequency domains. Moreover, the
influence of the distance between
the calibrating head position and the measuring transducer on
the obtained descriptor values
characterizing time and frequency runs of the AE signals
measured was examined. Using
statistical tests the repeatability of the calibrating signals
generated was tested. The evaluation
of the repeatability was carried out for selected descriptors
characterizing frequency spectra
measured for a given distance between the source and the
transducer of the AE signals
generated by the Hsu-Nielsen calibrating source.
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Molecular and Quantum Acoustics vol. 25, (2004) 179
2. THE IDEA OF CALIBRATION USING THE HSU-NIELSEN METHOD
The Hsu-Nielsen method was elaborated at the beginning of the
1980s [6]. It is a
simple and easy method to apply and it does not require any
complex auxiliary apparatus or
training people taking the measurements. The calibrating device
comes down to making a
proper head, automatic pencil and marking points of 2H hardness
and the gauge of 0.5 mm.
The calibration signal is generated in the Hsu-Nielsen system at
the moment of breaking a
sensitive graphite pin cased by a properly adapted tip put on
the automatic pencil. The head
and the marking point pulled out to 3 mm ensure the same
breaking angle at each test, which
also means generation of a repeatable acoustic surface wave.
This method is classified as one
of the pulse calibration methods. The process of breaking gives
the AE pulse congenial with
the signal obtained in the process of breaking the glass
capillary. There is, however, some
difference between them, which consists in the occurrence of an
inconsiderable minimum in
the initial phase of the run. It results from the fact that the
breaking of the marking point is
done by a manual pressing of the pencil which is of a dynamic
character. The point of the
pencil presses the surface directly in one point. This method
found its application in
calibration of the AE detectors in the process of their
production. Owing to its simplicity it is
used for calibration of measuring systems installed in technical
conditions. It was also
standardized [7].
3. TECHNICAL PRODUCTION OF THE CALIBRATION SOURCE AND SELECTION
OF THE MEASURING SYSTEM
The calibration head was made based on the data from the
literature [7]. The draft of
the head is shown in Fig. 1. Following the draft the head was
made from methyl
polymethacrylate. This material guaranties durability and
constancy of the required shape and
measurements of the head. The head was turned from a rod of the
diameter of 7 mm. After
giving the head the required shape and measurements, a
concentric opening of the diameter of
0.9 mm was bored. Such calibration heads comply with the
requirements described by the
French standard [7].
Since the main aim of the measurement taking was the selection
of the way of
calibrating the systems for measuring the AE generated by PDs,
the fundamental tests were
done on a transformer of the following parameters:
- type TP 60/110,
- upper voltage of 110 kV,
- total mass of 345 kg.
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180 Boczar T., Lorenc M.
4
3
0 , 92
0,5 7
Fig. 1. Draft of the Hsu-Nielsen calibration head
The transducers calibrated were placed on the upper lid of a
transformer tub assuming
four different distances between the model AE source and the
transducer. To ensure an
effective mechano-electrical coupling the transducer was fixed
to the transformer through a
layer of cup grease. Fig. 2 shows an overall view of the
transducer calibrated and installed on
the transformer.
Fig 2. Overall view of the transducer calibrated by the
Hsu-Nielsen method, installed on a transformer
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Molecular and Quantum Acoustics vol. 25, (2004) 181
4. COLLECTIVE LISTING OF THE RESULTS
The AE signals generated during calibration were registered by
the apparatus
described in the papers [8 ]. For each distance assumed the
calibration test was repeated five
times. Based on the results obtained criterion calibration
descriptors were determined and
defined [8]. For the particular measurement series the following
statistical parameters were
also determined: average value, standard deviation and variance.
The measurement results are
listed in Tables 1 through 4. Table 1. shows parameters
characterizing time runs of the signals
registered such as: the length of a signal, the sum of the AE
counts, and the sum of transitions
through a selected level of the discrimination threshold. During
the whole experiment the PD
discrimination threshold was adopted at the level of PD = 0.2
V.
Table 1Listing of the descriptor values calculated for the time
runs of the AE signals generated by the Hsu-Nielsen method
Distance between the
transducer and the generation
place [mm]
Statistical quantitiesSignal length[ms]
Sum of the AE counts [n.imp.]
Sum of transitions through the
adopted discrimination level [n.imp.]
25Average value
Standard deviationVariance
2,68 1169 209
0,30 172 31
0,09 29563 959
37Average value
Standard deviationVariance
2,40 932 191
0,31 66 18
0,09 4318 340
62Average value
Standard deviationVariance
2,84 829 148
0,47 170 36
0,22 28766 1281
100Average value
Standard deviationVariance
2,45 713 155
0,40 145 24
0,16 21060 559
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182 Boczar T., Lorenc M.
Table 2Listing of the descriptor values calculated for the time
runs of the energy of the AE signals generated by the Hsu-Nielsen
method
Distance between the
transducer and the generation
place [mm]
Statistical quantitiesAverage
amplitude[V]
ARMS value[V]
Surfaceabove the
average value[V2]
Peak coefficient[ - ]
25Average value 0,48 0,30 132,60 5,38
Standard deviation 0,03 0,06 30 0,69Variance 1,14E-03 3,78E-03
921 0,47
37Average value 0,47 0,26 85,75 5,31
Standard deviation 3,85E-02 0,02 14 0,58Variance 1,48E-03
5,59E-04 188 0,34
62Average value 0,42 0,26 74,40 4,93
Standard deviation 0,03 0,03 20 0,46Variance 1,20E-03 1,04E-03
392 0,21
Average value 0,397 0,203 56,800 4,78Standard deviation 0,032
0,033 16 0,745
Variance 0,001 1,10E-03 271 0,555
Table 3Listing of the descriptor values calculated for the
spectral amplitude density of the AE signals generated by the
Hsu-Nielsen method
Distance between the transducer
and the generationplace [mm]
Statistical quantities
Max. value of
the spectral
line in the spectrum
[V]
Average value of
the spectral
line in the spectrum
[V]
Frequency for the max.
amplitude density[kHz]
ARMS value
Peak coefficient
[ - ]
Median frequency
[kHz]
25
Average value 5,10 0,08 5,46 0,33 15,36 15,90
Standard deviation 0,39 0,01 0,80 0,04 2,28 2,44
Variance 0,156 1,41E-04 0,64 1,80E-03 5,20 5,94
37
Average value 4,24 0,07 4,88 0,27 15,52 17,78
Standard deviation 1,11 0,00 0,00 0,02 3,52 2,11
Variance 1,22 7,00E-06 0,00 6,18E-04 12,41 4,44
62
Average value 4,29 0,06 5,37 0,27 15,58 15,90
Standard deviation 0,98 0,01 0,00 0,03 2,38 3,67
Variance 0,96 6,07E-05 0,00 1,03E-03 5,65 1,48
100
Average value 2,79 0,046 5,71 0,215 12,38 15,8
Standard deviation 0,58 0,007 0,32 0,037 0,79 1,30
Variance 0,34 4,25E-05 0,10 1,40E-03 0,62 1,80
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Molecular and Quantum Acoustics vol. 25, (2004) 183
Table 4Listing of the descriptor values calculated for the
spectral energy density of the signal energy generated by the
Hsu-Nielsen method
Distance between the transducer
and the generationplace [mm]
Statistical quantities
Max. value of
the spectral
line in the spectrum
[V]
Average value of
the spectral
line in the spectrum
[V]
Frequency for the max.
amplitude density[kHz]
ARMS value
Peak coefficient
[ - ]
Median frequency
[kHz]
25
Average value 24,30 0,09 5,76 1,50 41,70 6,93
Standard deviation 3,78 2,80E-02 0,80 2,03 6,77 1,04
Variance 14,30 7,84E-04 0,64 4,12 45,9 1,09
37
Average value 23,78 0,066 4,88 0,52 36,01 6,77
Standard deviation 1,55 1,22E-02 0,00 0,02 15,06 0,88
Variance 2,40 1,50E-04 0,00 5,52E-04 226,90 0,77
62
Average value 19,30 0,07 5,37 0,52 36,15 6,10
Standard deviation 9,85 1,79E-02 0,00 0,04 16,47 0,39
Variance 97,08 3,21E-04 0,00 1,36E-03 271,39 0,15
100
Average value 7,18 0,04 5,71 0,46 15,27 7,03
Standard deviation 2,85 1,27E-02 0,33 0,04 4,98 0,11
Variance 8,10 1,61E-04 0,11 1,46E-03 24,75 0,01
5. THE ANALYSIS OF THE RESULTS OBTAINED
Table 1. shows the values descriptors determined for the time
runs that were calculated
for four distances between the model source and the measuring
transducer. The increase of the
distance did not influence significantly the time of the signals
registered. The values
determined were in the range from 2.45 ms to 2.84 ms. In the
case of the other two descriptors
the influence of the distance change on the values obtained was
observed. With the increase
of the length of the signal the values of the sum of the counts
and the sum of transitions
through a selected discrimination threshold decrease. This is
caused by the influence of the
object configuration in which the AE signals generated
propagate. The upper part of the
transformer is of a non-homogenous structure. The increase of
the distance between the
source and the transducer causes the shortening of a free path.
The elastic wave when
propagating in a non-homogeneous medium can be subject to
reflection or refraction. The
wave motion consists in propagation of a spherical disturbing
wave which causes particle
-
0
20
40
60
80
100
I
II
III
IV
- 25 mm
- 37 mm
- 62 mm
- 100 mm
Average amplitude
Surface above the average value
Peak coefficient
ARMS
value
184 Boczar T., Lorenc M.
deflection from the state of equilibrium. At some point the
primary wave and the wave
formed through transformation reach the same point of the
medium. Each of them causes
deflection characteristic for its kind, i.e. such deflection as
it would cause if the other wave
did not exist. The resultant deflection from the state of
equilibrium of the medium point under
study is equal to the geometrical sum of constituent
deflections. This law is binding in the
range of the Hookes Law applicability i.e. in the range in which
the whole experiment was
carried out. In consequence, it causes the increase of the
maximum amplitude, the sum of
counts and the sum of transitions through a selected
discrimination threshold. Fig. 2 shows an
exemplary run of the model signals registered, generated from
the Hsu- Nielsen source.
2000 4000 6000 80002.5
1.25
0
1.25
2.5
pip
ip
Fig. 2. An exemplary time run of the model AE signal generated
by the Hsu-Nielsen source
The effect of elastic waves transformation is also noticeable
for time runs it has an
effect on the decrease of the average amplitude value and the
size of the surface determined
above the average value. With the increase of the pulse duration
time the value of the energy
derivatives such as the root-mean-square value ARMS and the peak
coefficient also decrease
with the increase of the distance.
Fig. 3. Relative changes of the descriptors of derivative time
runs determined for the AE signal generated in the Hsu-Nielsen
system
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Molecular and Quantum Acoustics vol. 25, (2004) 185
Analyzing the descriptor values obtained in the frequency domain
calculated for the
spectral amplitude density and the spectral energy density the
influence on the medium values
obtained in which the propagation of waves took place is also
observable. An exemplary
amplitude spectrum of a model AE signal is shown in Fig. 4.
0 50 100 150 200 250 300 350 400 450 500100
80
60
40
20
0
ff1k
frk
Fig. 4. Amplitude spectrum of the model AE signal shown in Fig.
2
The shortening of the free path, on which the wave propagates,
caused the decrease of
the value of the maximum spectral line and the ARMS value. The
geometry of the medium did
not influence the frequency of the maximum spectral line, the
value of which was from 4.88
kHz to 5.71 kHz. The values of the median frequency showed
similar trends, which means
that the division of the power transferred by the particular
harmonics is unchanging. However,
the values of the peak coefficient were fluctuating
significantly due to considerable changes
of the energy values for those runs.
Fig. 5. Relative descriptor values calculated for the spectral
amplitude density of the AE signals generated in the Hsu-Nielsen
system
Maximum value in a spectrum
Average value in a spectrum
Frequency for the maximum
spectral density
ARMS
value Peak coefficient
Median frequency
0
20
40
60
80
100
I
II
III
IV
- 25 mm
- 37 mm
- 62 mm
- 100 mm
-
186 Boczar T., Lorenc M.
Fig. 6 shows an exemplary energy spectrum of a signal. The main
portion of the
energy is transferred by the waves of the frequency in the range
from 0 to 10 kHz. In the
group of descriptors determined for the spectral energy density
there could be observed
analogous changes as for the descriptors determined based on the
amplitude spectrum.
Relative values of descriptors for the spectral energy density
are shown in Fig. 7.
0 10 20 30 400
10
20
30
40
fmk
frkFig. 6. Spectral energy density of the AE signal shown in
Fig. 2
Fig. 7. Relative descriptor values calculated for the energy
density spectrum of the calibrating signals generated in the
Hsu-Nielsen system
0
20
40
60
80
100
I
II
III
IV
- 25 mm
- 37 mm
- 62 mm
- 100 mm
Maximum value in a spectrum
Average value in a spectrum
Frequency for the maximum
spectral densityA
RMS value Peak
coefficientMedian
frequency
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Molecular and Quantum Acoustics vol. 25, (2004) 187
6. CHARACTERISTICS OF THE MEASUREMENT RESULTS OF CALIBRATING
SIGNALS GENERATED IN THE HSU-NIELSEN SYSTEM AS RANDOM VARIABLES
In order to determine the repeatability of the calibrating
signals generated by the Hsu-
Nielsen source the methods of statistical inference were used.
To carry out a statistical
analysis for the population of the results obtained there were
created samples consisting of
randomly selected elements that represented them. Statistical
tests were done for
measurements obtained at the distance of 10 cm between the
transducer and calibrating head.
That is the distance which can be used during the calibration of
measurement paths that
measure AE signals generated by PDs in paper-oil insulation of
power transformers.
For the designated random samples, function runs and density
probability cumulative
distribution functions were determined, where using histograms
the empirical distribution of
the values measured was presented, and using a continuous line
their theoretical distribution
was presented. In order to verify the statistical hypothesis of
equivalence of the probability
density of the AE pulses analyzed with the assumed theoretical
probability density a non-
parametric 2 text of goodness of fit was used. Within the
analyses carried out it was proved
that with a 5% tolerance of error making there are no bases for
rejecting the zero Ho hypothesis which assumes a normal type of
distribution of the AE pulses measured generated
in the Hsu-Nielsen system. The detailed results of the test
verifications carried out have been
presented, among others, in the works [9, 11, 12]. Moreover, in
order to verify graphically the
normal distribution probability of the random variables tested
probability diagrams of the
normal and semi-normal probability were used.
Figs 8-11 show in order the probability density and cumulative
density function, the
normal and semi-normal probability diagram for random samples
representing the AE pulses
generated in the Hsu-Nielsen system.
U [ V ]
frequ
ency
0
500
1000
1500
2000
2500
3000
3500
4000
-2,5 -2,0 -1,5 -1,0 -0,5 0,0 0,5 1,0 1,5 2,0 2,5
Fig. 8 Probability density functions (PDF) determined for the AE
pulses generated the
U [ V ]
frequ
ency
0100020003000400050006000700080009000
100001100012000130001400015000160001700018000
-2,5 -2,0 -1,5 -1,0 -0,5 0,0 0,5 1,0 1,5 2,0 2,5
Fig. 9 Cumulative density function determined for the AE pulses
generated the Hsu-Nielsen
-
188 Boczar T., Lorenc M.
Hsu-Nielsen system system
observed value
norm
al v
alue
-5
-3
-1
1
3
5
-3 -2 -1 0 1 2 3
Fig. 10 Normal probability plot determined for the AE pulses
generated the Hsu-Nielsen
system
observed value
norm
al v
alue
-0,5
0,5
1,5
2,5
3,5
4,5
-3 -2 -1 0 1 2 3
Fig. 11 Semi-normal probability plot determined for the AE
pulses generated the
Hsu-Nielsen system
7. TEST RESULTS OF THE MEASUREMENT REPEATIBILITY
The repeatability tests were done for three descriptors, i.e.
median frequency, peak
coefficient and shape coefficient, which can be used for
identification of basic PD forms
[10-13]. The measurement cycles took place in similar
environment conditions, e.g.
temperature, humidity and air pressure.
The conclusions from the analyses carried out were drawn based
on the test
of significance that is based on the variance analysis for many
averages of a single
classification [14-20]. This test is based on F Snedecor
distribution and the assumption that
there are given k populations of a normal distribution N(mi, i),
where i =1, 2, , k, or close
to a normal distribution, and the variances of all k populations
are equal, i.e. 12 = 22 = ... =
k2 = 2, but they do not have to be known. Hence, in order to
begin the test it was necessary
to check first whether the data of measurements were within a
normal distribution. Following
the earlier research, already published [9, 12, 13], it was
decided, based on the assumption of
the concord of the data with the distribution of a normal type,
to find out whether there also
occurs the equality of the variance of the data. A homogeneity
test of many variances [14-20]
is based on the distribution 2 and the assumption that there are
k normal populations N(mi,
i), where i = 1, 2, ..., k, of ni number. The selected
measurement data on which the
calculations were performed are presented in Table 5.
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Molecular and Quantum Acoustics vol. 25, (2004) 189
Table 5Comparative listing of coefficient values calculated for
the results obtained and read from the tables for 2 and F tests for
the peak, shape and median frequency coefficients calculated for
the amplitude spectrum and energy density of the AE pulses
generated by the Hsu-Nielsen calibration source.
DescriptorAverage
value Standard deviation 2 2
F F
Spec
tral a
mpl
itude
den
sity Peak
coefficient[ - ]
12,38 0,069 3,88
Shape coefficient [ - ] 4,15 0,045 2,66
Median frequency
[ kHz ] 15,80 0,987 7,13
Spec
tral e
nerg
y de
nsity Peak
coefficient[ - ]
15,27 0,191 3,92
Shape coefficient [ - ] 5,74 0,052 4,42
Median frequency
[ kHz ] 7,03 0,627 8,01
11,07
0,78
1,00
1,88
0,79
1,12
1,98
2,53
The hypotheses of the test assume, respectively:H0: 12 = 22 = 32
= 42 = 52 = 62; where is a variance of a given population,
H1 : not all variances of results are equal.
The calculated value of 2 distribution and the value of the
significance level = 0.05
readout from the table are presented in Table 5.
Since in each case there is the inequality 2 < , there are no
bases for rejecting the
Ho hypothesis which says that all variances of the descriptors
determined are equal to one
another. It should be added that the limitations of the paper
length do not make it possible to
present all the calculation results tested, i.e. for the
remaining three distances between the
transducer and the calibrating head. However, homogeneity tests
of many variances were
performed for all the data collected, and as a result of which
it was possible to state that there
are no bases for rejecting the H0 hypothesis.
Because the calculations presented in Table 5 can be described
by a normal
distribution and their variances are equal, it was possible to
carry out a test of variance
analysis for many averages in order to determine the
repeatability of the test results.
-
190 Boczar T., Lorenc M.
The test hypotheses assume, respectively:
H0 : m1 = m2 = m3 = m4 = m5; where m is the average from
population.
H1 : not all averages are equal to one another
The calculated value of distribution F and the value readout
from the table for the
significance level = 0.05 is presented in Table 5, respectively.
Since in each case the
inequality F < F takes place, there are no bases for
rejecting the Ho hypothesis which says
that all the selected descriptors are equal to one another. This
statement proves, at the same
time, that in the setup under study the repeatability of the
experiment results takes place with
a 5% error tolerance.
8. SUMMARY
Based on the statistical tests carried out it can be observed
that the AE signals
generated by breaking the marking point placed in the
Hsu-Nielsen calibrating head are
characteristic of the repeatability for a given distance between
the generation place and the
measuring transducer. This ascertainment is true with a 5% error
margin. Therefore this
method can be used for calibration of measuring paths applied in
the acoustic method of
evaluating the condition of power appliance insulation.
Acoustic emission is one of the non-destructive research methods
finding its wider and
wider application in practice. This paper offers another insight
into important issues dealing
with generation and propagation of the repeatable model AE
pulses. The results of the
analysis of the AE pulses generated in the Hsu-Nielsen system
refer to an actual transformer.
This fact is important as the AE method is more and more often
used in professional power
engineering for monitoring and diagnosing the condition of
insulation in high-power
transformers, high-power measuring transformer, flow insulators,
power capacitors and
switching stations with SF6. The AE method provides unique
information on the location and
intensity of PDs occurring in these appliances. In the
conditions of regular work the PD
measurement by electrical methods is not possible due to a
strong interaction of power
disturbances. The spectra of the pulses registered are not
always measured during tests
performed in technical conditions. The measurements are often
limited to determining basic
descriptors of time change derivatives. The authors of this
paper wanted to draw attention to
the fact that a signal occurring in the generation place differs
significantly from the pulse
received at the end of the measuring system.
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Molecular and Quantum Acoustics vol. 25, (2004) 191
The size of these differences depends on the transition
function, which characterizes
each element of the path that a signal has to cover, and on the
medium in which it propagates.
The results presented in this paper confirm the thesis that the
Hsu-Nielsen source complies
with the conditions of the repeatable AE source, is easy to make
and be used in technical
conditions.
ACKOWLEDGEMENTS
The research was carried out within the grant KBN no. 3 T10A 031
27
REFERENCES
[1] Kaiser J.: Messung von Geruschen bei Zugbeanspruchung von
metallischen Werkstoffen, Arch. f. Eisenhttenwesen, 25, 43,
1953.
[2] Skubis J.: Emisja akustyczna w badaniach izolacji urzdze
elektroenergetycznych, IPPT PAN Warszawa, 1993
[3] Breckenridge F., Tschiegg C., Greenspan M.: Acoustic
emission: Some Application of Lambs Problem, J. Acoustic Soc.
Vol.57, No. 3, March 1975.
[4] Hsu N. N., Breckenridge F. R..: Characterization and
Calibration of Acoustic Emission Sensors, Mat. Evaluation, 39, 60,
1981.
[5] Mc Bribge S.L., Hutchison T.: Absolute Calibration of the
Helium Gas Jet Noise Source, Canadian J. of Phis., 56, 504,
1978.
[6] Brel & Kjael Technical Review, No 2, 38-40, 1981.
[7] Norma francuska Badania nieniszczce, sownictwo
wykorzystywane w EA, NF - A 09-350.
[8] Skubis J., Lorenc M.: Measurements and analysis of acoustic
emission standard impulses generated in Hsu-Nielsen source.
Archives of Electrical Engineering Vol. XLVII. No 1 pp. 13-24,
Warszawa 1998.
[9] Lorenc M.: Ocena powtarzalnoci sygnaw emisji akustycznej
generowanej przez rda wzorcowe testem Chi-kwadrat, KNT
Transformatory w eksploatacji; Sieniawa, 2002, pp.143-148
[10] T. Boczar: Identification of a Specific Type of Partial
Discharges form Acoustic Emission Frequency Spectra, IEEE
Transactions on Dielectrics and Electrical Insulation, Vol. 8, No 4
August 2001, pp. 598-606.
[11] T. Boczar., D. Zmarzy: Application of Wavelet Analysis to
Acoustic Emission Pulses Generated by Partial Discharges, IEEE
Transactions on Dielectrics and Electrical Insulation, Vol. 11, No
3, June 2004, pp. 433-449.
[12] T. Boczar, S. Wolny: Application of calculus of probability
for the randomness evaluation of acoustic emission signals
generated by partial discharges, 31st International
-
192 Boczar T., Lorenc M.
Conference Defektoskopie 2001, Czech Society for Nondestructive
Testing, Prague, Czech Republic, 2001, pp. 55-62.
[13] T. Boczar, S. Wolny: Application of statistical methods in
the analysis of the acoustic emission signals generated by partial
discharges, Proceedings Scientific Colloquium on High Voltage
Engineering, Slovakia, Kosice, 2002.
[14] R. Gnanadesikan: Methods for statistical data analysis of
multivariate observations, John Wiley and Sons, New York, 1997.
[15] M. Hollander, D. A. Wolfe: Nonparametric statistical
methods, John Wiley and Sons, New York, 1997.
[16] D. C. Montgomery, G. C. Runger: Applied statistics and
probability for engineers, John Wiley and Sons, New York, 1999.
[17] J. Neter, M. H Kutner, C. J. Nachtsheim, W. Wasserman:
Applied linear statistical models, Richard D. Irwin, Inc. and Times
Mirror Higher Education Group, Inc, Chicago, 1996.
[18] J. Stevens: Applied multivariate statistics for the social
sciences, Hillsdale Erlbau, new York, 1986.
[19] S. B. Vardeman: Statistics for engineering problem solving,
PWS Publishing Company, Boston, 1994.
[20] R. J. Van Brut: Stochastic properties of partial discharges
phenomena, IEEE Transactions on EL, vol. 26, no. 5, 1990, pp.
642-665.
REFERENCES