2s
‘No Deterioration i
20 | 20
Vay Mismatch Predictor $ Vay Mismatch Predictor shang
> E ae
€15 + Yar Mismatch Predictor x10 & ig) + Yar Mismatch Predictor x10 e
§ 2 Negative Sequence Current x10 a ea
2 3 “Le
Fro i 10 -
3 ae
# LF
sf 3,
ce “ro = = ‘a
ol °
e $ z > zy . °

Voltage Unbalance Factor, %

Figure 2. Illustration of the insensitivity of the voltage
mismatch predictors to different levels supply unbalances
for a nondeteriorated induction motor.

in each predictor is very small and there is no trend or large
variability in the predictors due to different levels of voltage
supply unbalance,

The next aspect of the mismatch predictors to be
investigated was their sensitivity to simulated winding
deterioration. Figures 3 and 4 illustrate two typical results.
(Note in these figures, and all figures where the mismatch

re

qj Mismatch Predictor

f+ Var Mismatch Predictor x10 ra

Negative Sequence Current x10 a

Voltage Mismatch, V: Current, A

of 02 0s 0a 08
Deterioration Leaks

CY ey
Current, pu

Figure 3. Illustration of changes in the voltage mismatch
predictors and negative-sequence current with increasing
motor deterioration for an induction motor operating at a
small voltage supply unbalance.

oor 02 03 04 0606 07 08 09 1
Detertoration Leakage Current, pu

Figure 4. Illustration of changes in the voltage mismatch
predictors and negative-sequence current with increasing
motor deterioration for an induction motor operating at a
large voltage supply unbalance.

predictors are plotted, the same scale is used for accurate
comparison of the results.) Figure 3 shows results for the
ULM operating at the 0.5% VUF, and we observe that both
mismatch predictors increase significantly with the level of
leakage current. Figure 4 illustrates the results for the ULM
operating with the 5.2% VUF. We observe that the changes
in the predictors are almost identical to those presented in
Figure 3, in spite of the large difference in the level of
negative-sequence current, In addition, closer inspection of
Figure 4 reveals that the level of negative-sequence current
actually decreases with increasing deterioration severity for
chat series of tests. In other words, the combination of supply
anbalance, inherent motor asymmetry, and the deterioration
send to balance the motor currents. This is the type of
situation where the effective negative-sequence impedance
nay initially increase at very low levels of deterioration and
decrease at higher levels of deterioration [10]. However, we
observe that the mismatch predictors are not affected by the
anbalance caused by the voltage supply or the inherent motor
asymmetry. The predictors change only in response to the
increasing deterioration.

The final aspect of the mismatch predictors to be
investigated was whether or not changes in them provide any
indication of the level of deterioration severity, especially in
situations where the voltage supply unbalance changes. This
was evaluated by combining all of the test results and plotting
the voltage mismatch versus leakage current, The results
presented in Figure 5 show that the predictors increase in
proportion to the leakage current despite the large variability
in the voltage supply unbalance present during the different
tests. This is particularly encouraging when we consider that


determining the z-matrix. Once the z-matrix is determined,
the mismatch predictors can be computed for any level of
voltage unbalance, including a perfectly balanced system.
ULM speed control was achieved by setting the appropriate
resistance load on the generator and adjusting the output
voltage of the generator using the field rheostat. Speed was
measured with a digital tachometer.

After the two runs used to determine the z-matrix were
completed, a series of runs was conducted to evaluate the
ability of the mismatch predictors to detect - simulated
deterioration in the ULM. Tests were conducted at a wide
range of supply unbalances with the ULM operating under
several levels of deterioration.

Stator winding deterioration was simulated by connecting
a conductive path between the terminals of one stator coil
(the smallest portion of the stator winding accessible on the
ULM). Various levels of deterioration severity were
simulated by inserting different values of resistance in this
leakage path. Effort was taken to simulate small levels of
deterioration during the experiments; however, because each
phase of the stator is composed of only four coils, the
smallest portion of the winding accessible is 25% of one
phase winding. Therefore, the leakage current was limited to
very low values. In the most severe level of deterioration
simulated the leakage current was less than the rated input
current of the ULM.

During the tests, there was no effort made to calibrate the
sensors or other components of the data acquisition system.
It was recognized that any bias error in the sensors would be
accounted for in the 2-matrix determination, provided that the
sensors were not switched to different phases in subsequent
experiments,

IV, RESULTS

The tests were conducted to address three specific aspects
of the mismatch predictors. The first was to determine if the
predictors are well-behaved (i.e., unaffected) in situations
where the motor is supplied by a variable, unbalanced voltage
supply and/or the motor itself has minor construction
asymmetries that are unrelated to deterioration, Both of these
unbalanced conditions are very common and can create the
appearance of winding deterioration even though neither is
actually related to deterioration. The second area to be
evaluated was whether or not the predictors are sensitive to
low levels of deterioration. Although it is difficult to
quantify exactly what is meant by low-level, the deterioration
that was simulated had no perceptible affect on motor
operation and the motor could be run indefinitely with the
deterioration in place. The third aspect to be evaluated was
whether changes in the predictors could be associated with
level of deterioration severity. This is one of the limitations
of Zorg. Although Zaz does change with deterioration, it

does not change in a predictable manner under certain
operating conditions [1, 10].

A total of 14 experiments were conducted for the results
presented in this paper. Six different levels of voltage
unbalance were used during the experiments. Two were used
to determine the z-matrix, the other four were used in the
evaluation of the mismatch predictors. They include a
voltage unbalance factor (VUF) of approximately 0.5%,
2.1%, 2.7%, and 5.2%. (Here, voltage unbalance factor is
defined as the absolute value of the ratio of the negative-
Sequence voltage to positive-sequence voltage, expressed in
percent.) Note that the 0.5% VUF was as close to balanced
as could be conveniently attained with the experimental
setup. Three different states of motor condition were
simulated: no deterioration, a leakage current of
approximately 0.45pu (per unit), and a leakage current of
approximately 0.90pu.

The values obtained for the z-matrix are given in (8).

22.1/18,39° —1.01/- |

**|0.0493/=28.64° 3.31/51.60°

(8)

In general, the off-diagonal terms of the z-matrix should be
very close to zero; and they would, of course, be equal to zero
for a perfectly symmetrical motor/sensor system. Inspection
of (8), however, reveals that the z-matrix obtained in our
experiments contains fairly large off-diagonal terms,
indicating a relatively large level of system asymmetry in the
nondeteriorated. state. Note that this inherent asymmetry
includes effects that are caused by mismatched sensors as
well as motor construction asymmetry. There was no
attempt made to determine how much of this asymmetry was
due to sensors and how much was due to motor construction.
In fact, it is fortunate that this high level of inherent
asymmetry existed because it represented a potentially
problematic condition for the predictors that we wanted to
evaluate.

The first aspect of the mismatch predictors to be evaluated
was whether inherent motor asymmetry and/or changes in
supply unbalance would mimic deterioration. This was
accomplished by running the ULM in the nondeteriorated
state under a wide range of supply unbalances and calculating
the mismatch predictors. Ideally, the mismatch for this type
of situation would be zero because the changes in voltage and
current are not related to motor deterioration. Figure 2
presents the results obtained from our experiments with a plot
of the voltage mismatch versus level of supply unbalance at
the four different levels of voltage unbalance factor
previously described. (Note that because the magnitude of
the negative-sequence voltage is much smaller than the
positive-sequence voltage, ten times the V,2 mismatch
predictor is plotted.) These results indicate that the mismatch


28

\+

Vai Mismatch Predictor a

Vay Mismatch Predictor x10

EN

Voltage Mismatch, V
\
N

& 7
“|

04 08 06 07 08 09+
Hon Leakage Current, pu

Figure 5. Changes in the voltage mismatch predictors with
increasing motor deterioration for an induction motor
operating under a wide range of voltage supply unbalances.

the system exhibited a significant asymmetry in the
nondeteriorated state.

Inspection of Figure $ shows that the Vqy mismatch is
approximately 7.5V for a 0.45pu leakage current and 15Vfor
a leakage current of 0.90pu; the corresponding mismatch in
Vq2 is approximately 1,0V and 2,0V and both are independent
of the changing voltage unbalance.

V. CONCLUSIONS

Results from the experiments are very encouraging. Both
of the mismatch predictors are sensitive to the stator
deterioration that was simulated, their performance is not
affected by supply unbalances - or _ inherent
machine/monitoring system asymmetry, and changes in them
appear to be indicative of level of deterioration severity. In
addition, no special sensors or calibration procedures were
Tequired to obtain these results. The negative-sequence
voltage mismatch predictor appears to be slightly more
sensitive to increasing deterioration severity; however, the
absolute changes in the positive-sequence voltage mismatch
predictor are larger.

Future research will include more exhaustive tests on
numerous induction motors to better define the ability of each
mismatch predictor to indicate deterioration. In addition,
correlation between the predictor and deterioration severity
will be developed as appropriate.

REFERENCES

iI] J. Sottile, and J. L. Kohler, “An on-line method to detect
incipient failure of tum insulation in random-wound motors,”
IEEE Transactions on Energy Conversion, vol. 8, no. 4, pp.
762-768, 1993,

J, Sottile, An Analysis of Induction Motor Incipient-Failure

Prediction and the Development of Systems Concepts for

Electrical Diagnostics in Mining Industry Applications, Ph.D.

dissertation, The Pennsylvania State University, 1991.

33] M. Arkan, and P. J. Unsworth, “Stator fault diagnosis in
induction motors using power decomposition,” Record of the
34" IEEE Industry Applications Society Conference, 1999.

‘AJR. R. Schoen and T. G, Habetler, “A new method of current-
based condition monitoring in induction machines operating
under arbitrary load conditions,” Electric Machines and Power
‘Systems, vol. 25, pp. 141-152, 1997,

‘S]_ M.A. Cash and T. G. Habetler, “Insulation failure detection in
the stator windings of ASD-driven induction machines using
standard deviation of line currents,” Record of the 33° IEEE
Industry Applications Society Conference, 1998.

(6] A. J. Marques Cardoso, 8. M. A. Cruz, and D. S. D. Fonseca,
“Inter-turn stator winding fault diagnosis in three-phase
induction motors by Park’s vector approach,” JEEE
Transactions on Energy Conversion, vol. 14, no. 3, pp. 595-
598, 1999,

(7] G, B. Kliman, W. J. Premerlani, R. A. Koegl, and D. Hoeweler,
“A new approach to on-line turn fault detection in ac motors,”
Record of the 31" IEEE Industry Applications Society
Conference, 1996,

[8] M.A. Cash and T. G. Habetler, and G. B. Kliman, “Insulation
failure prediction in induction motors using line-neutral
voltages,” Record of the 32 IEEE Industry Applications
Society Conference, 1997,

[9] J. L, Kohler, J. Sottile, and F.C. Trutt, “Alternatives for
assessing the electrical integrity of induction motors," [EEE
Transactions on Industry Applications, vol. 28, no. 5, pp. 1109-
1117, 1992,

[10] J. L. Kohler, J. Sottile, and F. C. Trutt, “Condition-based
maintenance of electrical machines,” Record of the 34" IEEE
Industry Applications Society Conference, 1999.

[11] J. Penmen, H. G, Sedding, B. A. Lloyd, and W. T. Fink,
“Detection and location of interturn short circuits in the stator
windings of operating motors,” IEEE Transactions on Energy
Conversion, vol. 9, no. 4, pp. 652-658, 1994.

[12] F. Ding and F. C. Trutt, “Calculation of frequency spectra of
electromagnetic vibration for wound-rotor induction machines
with winding faults,” Electric Machines and Power Systems,
vol. 14, pp. 137-150, 1988,

[13] C. F. Wagner and R. D. Evans, Symmetrical Components,
Krieger Publishing Company, 1982, pp. 345-349.

(14] S.A. Nasar, and F.C. Trutt, Electric Power Systems, CRC
Press, 1999, pp, 124-125.

2



Experimental Investigation of On-Line Methods for Incipient Fault Detection

Joseph Sottile
University of Kentucky
Lexington, KY

Abstract - Condition-based maintenance (CBM) of
industrial equipment is generally recognized as being the
most cost-effective means for improving equipment
availability. | However, prerequisite to successful
implementation of CBM is a reliable detector of failing
components. One such detector, termed the effective
negative-sequence impedance, had previously been
identified as an indicator of induction motor stator
winding degradation. However, a limitation of this
detector is that it does not change in a predicable manner
under certain motor operating conditions. This paper
presents an experimental investigation of an improved
technique for on-line detection of induction motor stator
winding degradation. The paper begins with a brief
description of the detectors, followed by a detailed
description of the experimental setup, the experiments
conducted, and results,

I. INTRODUCTION

Condition-based maintenance of induction motors is
accepted as being the most effective method for scheduling
motor repairs and replacements provided that deteriorating
components can be detected in a timely manner. Reasonably
teliable techniques now exist for detecting bearing
deterioration and, more recently, cracked and broken rotor
bars, and improvements continue to be made in both of these
areas. One component that is more problematic to monitor
and detect incipient failure is the stator winding. Early stages
of deterioration are difficult to detect, and certain types of
stator faults can progress rapidly, causing motor failure with
very little warning. In spite of these difficulties, a great deal
of progress is being made in incipient stator-winding fault
detection. The approaches generally involve monitoring and
analysis of voltage, current, and magnetic flux [1-11] and
electrically excited vibrations [12].

Methods that use voltage and current measurements offer
several advantages over test procedures that require the
machine to be taken off-line or techniques that require special
sensors to be mounted on the motor. Hardware requirements
are easily met; there is no need to modify the motor or to
supply external signals to motor windings. In addition,
insulation is not subjected to any unnecessary stress during
the evaluation process. Finally, condition monitoring can be
conducted nearly continuously if voltage and current sensors
can be mounted permanently and if processing requirements

Frederick C. Trutt
University of Kentucky
Lexington, KY

Jeffery L. Kohler
NIOSH
Pittsburgh, PA

are not demanding. A continuous monitoring system is
particularly advantageous when we consider the speed at
which deterioration can progress.

A technique that has long been applied to various types of
failure detection is negative-sequence current monitoring.
The approach is easy to apply; all that is required is
measurement of the three line currents. Unfortunately,
supply voltages and the motor itself are frequently
unbalanced, and induction motors exhibit a low impedance to
negative-sequence current. Therefore, most power systems
will always have a measurable negative-sequence current (/,2)
Present ranging from a fraction of a percent to several
percent, In addition, the level of /,2 will change as the supply
unbalance changes due to switching of single-phase loads or
for other reasons unrelated to incipient failure. This
condition coupled with the fact that motor deterioration
produces very small changes in /,2 makes the negative-
sequence current alone an unreliable predictor of incipient
failure. There is however, one group of researchers that has
developed techniques that overcome the shortcomings of
simple negative-sequence current monitoring for incipient
stator-winding fault detection. As would be expected with a
more advanced procedure, the technique requires additional
information and a brief training period prior to
implementation [7].

One concept that was developed in an attempt to satisfy
the implementation issues mentioned above is the detection
of the loss of motor construction symmetry due to
deterioration [1, 2]. The rationale for this approach can be
understood by examining the sequence voltage and current
relationships for a general symmetrical, nonstatic network:

Val [2% 9 Of} [to
Va \=/0 2 OIL, qa)

Ya} (0 0 a} Un
where,
2 = zero-sequence impedance,

21 = positive-sequence impedance, and
22 = negative-sequence impedance.


The concept of detecting loss of motor symmetry was
implemented by considering (1) and recognizing that the ratio
of Vaz to Jaz is nearly constant for a symmetrical induction
motor. Based on this relationship, the detector was defined,

2)

and was termed the effective negative-sequence impedance.
This detector has several advantages in a monitoring
application.. First, the method is very easy to implement
which is a very important requirement for the mining
industry. The only motor parameter that needs to be
determined is Zz2eg. Second, for a symmetrical induction
motor, the effective negative-sequence impedance is not very
dependent on operating speed [13]; therefore, Zazeg needs to
be determined at only a few different motor speeds and motor
speed need not be accurately measured in an application.
Third, Za2eg was shown to be sensitive to early stages of stator
winding deterioration.

However, the effective negative-sequence impedance has
several limitations. First, the relationship expressed in (1)
applies only to a symmetrical rotating machine; therefore, the
changes in 2,2 caused by deterioration are unpredictable and
they are not generally related to deterioration severity. (Note
that the relationship expressed in (1) does not account for the
interaction of different sequence components that occurs in
an unsymmetrical system such as a deteriorating motor.)
This limitation was originally recognized [1, 2], but it was
believed that the ease of use compensated for the lack of
predictable behavior. Second, minor construction
asymmetries mimic motor deterioration and reduce the ability
of Zazeg to be used to detect the inception of deterioration.
Finally, mismatched sensors also tend to mimic or mask
deterioration; therefore, sensors need to be calibrated to
eliminate this effect. (Note that the calibration process only
requires that the sensors in each phase match one’ another;
absolute accuracy is not necessary.) In the next section, the
theoretical development of the mismatch predictors will be
presented. As will be seen, these predictors overcome the
deficiencies of the effective negative-sequence impedance.

Il. THEORETICAL DEVELOPMENT

Consider a three-phase, wye-connected induction motor
connected to a three-phase, wye-connected power source as
shown in Fig. 1. If the power source or motor is in a delta
configuration, it is assumed that this component is
represented by its equivalent wye.

Let V's0, Vai, and Veg be the zero, positive and negative
sequence symmetrical components of the power source

Ie

Figure 1. Wye-connected power source and induction motor.

voltages measured with respect to the ground reference.
Similarly, we will define 120, Jat, and I,2 as the symmetrical
components of the line currents and Vig, Vai, and Vq2 as the
symmetrical components of the motor phase voltages
measured with respect to the junction point of its wye
connection. Note that the zero sequence voltages V9 and Vip
differ by the voltage at the junction point of the motor wye
connection measured with respect to the ground reference
(Vp) while the corresponding positive and negative sequence
power source and motor phase voltages are equal.

It may be shown that [14]

Veo = 200 Lap + Z01 [gi + 202 a2 GB)
Voy = 210 Lam +211 dat +212 Leg (4)
Vag = 220 Tay + 221 loi +222 Lea (5)

where the 2, parameters are functions of the motor design,
construction, any internal deterioration, and the operating
speed. In these equations, the zero sequence component of
the line currents is equal to zero if there is no ground fault in
the system. Such faults or deterioration involving ground
may be observed by standard techniques that monitor the
zero-sequence component of the line currents and are
relatively easy to detect. For the remainder of this paper, we
will assume that Jao = 0 (either no significant ground leakage
exists or it has been corrected) and concentrate on the more
difficult problem of detecting incipient deterioration that does
not involve ground such as coil-to-coil faults within one
motor phase or phase-to-phase deterioration.

With this assumption, (4) and (5) become
Ver = 211 dat +212 1 (6)

Von = Z21 Tai +222 Lon (7)


and it is then possible to determine 2); , 212 , z21 and 27 from
two separate tests on a motor conducted at any given motor
speed. In this way, a library of zy parameters may be
constructed for the range of motor operating speeds. Once
these parameters are known, it is then possible to monitor the
three-phase motor voltages and line currents from which Vai,
Vea, Iai, and Iq may be determined. Equations (6) and (7)
may then be used to calculate Vg) and Vg at the measured
motor operating speed and if no internal deterioration has
occurred, the calculated values will match the measured
values. If internal deterioration such as an interturn coil fault
or phase-to-phase leakage has developed, the zy parameters
will have changed from their normal values at that speed and
there will be a mismatch between the measured positive and
negative sequence voltages and the corresponding calculated
values. This mismatch may then be used as a measure of
internal motor deterioration.

An important advantage of this approach is that the
mismatch predictors should be independent of initial
construction imperfections and unbalances within the motor
itself as well as changes or unbalance that may develop in the
motor power supply system due to single phase loading or
other factors. In addition, the performance of the mismatch
predictors should not be affected by mismatched sensors;
therefore, no sensor calibration is necessary. The application
and robust nature of this monitoring approach will be
illustrated in the experimental study.

Til, EXPERIMENTAL STUDY

The first step in the experimental study consisted of
determining the elements of the impedance matrix defined by
(6) and (7) from two runs on a healthy induction motor.
After the impedance matrix was determined, additional runs
were conducted with the motor operating under various levels
of voltage supply unbalance and deterioration. Next, the
mismatch predictors were computed from the measured
currents and the impedance matrix for each run. These
values were compared with the positive-, and negative-
sequence voltages that were computed from the measured
line voltages. Finally, the results were analyzed. The
remainder of this paper will describe the experimental study
and the results of that study.

A, Experimental Machine and Data Collection

The experimental machine is a two-pole, uniform air-gap
universal laboratory machine (ULM) coupled to a de
generator, The output of the generator is connected to a bank
of ten resistors that can be individually controlled to provide
a wide range of loads for the ULM. An external rheostat is
connected in series with the generator field winding, allowing
very precise control of the generator output voltage. The
ULM has a rating of 2.0 kVA at 208 V. The stator is

composed of 24 slots, wound with 12, 26-tum coils. The
terminals of each stator coil are brought out to a large panel at
the front console of the machine. By making the appropriate
coil-to-coil connections at this terminal panel, the user can
connect the stator in either a delta or wye configuration. The
user can also connect the stator coils in either a series or
parallel circuit. Most important for this research is that the
user also has access to the terminals of each stator coil, which
provides a means for simulating internal deterioration (as will
be described later). The rotor of the ULM is a wound rotor
with brushes and slip rings that can be set to connect external
resistors to the rotor circuit or, alternatively, the brushes can
be set to short the rotor coils, thereby simulating a squirrel
cage rotor. In the experiments conducted for this research,
the ULM stator was wye connected, with the stator coils
connected in series,

Voltage signals were acquired by using voltage dividers
connected between motor terminals and ground. Current
signals were obtained by using current transformers (CT) in
conjunction with resistors. (The resistors were used to
convert each CT output to an appropriate voltage signal.)
The analog signals from the voltage dividers and CTs were
digitized with a 16-bit analog to digital converter (ADC).

Each experiment consisted of collecting 1024 points per
channel at a sample rate of 5128 points per second (for a
combined sample rate of 30,768 points per second for all six
channels), A fast Fourier transform (FFT) was used to
compute frequency domain information; subsequent
calculations used the 60-Hz component of each signal.

B. Experimental Procedures

The first step of the experimental procedure consisted of
tunning two tests on the ULM that were sufficient to
determine the elements of the impedance matrix defined by
(6). and (7). In order to accurately determine these terms,
specific operating parameters had to be observed. First,
because terms of the impedance matrix are speed dependent,
it was necessary to run the ULM at the same speed for both
tests, and for all subsequent tests. Second, it was necessary to
conduct the tests at two different levels of voltage supply
unbalance in order to obtain four independent equations.

Control of the supply unbalance was achieved by using a
three-phase variable-voltage transformer modified to allow
each phase voltage to be controlled independently of the
other two, Because near-zero values of J,2 and V2 are
problematic for determining the z-matrix, the transformer was
used to create a measurable level of unbalance in each of
these two runs. The procedure we used consisted of
increasing the phase a, voltage to approximately 10% above
the nominal for the first run and decreasing the phase a
voltage to approximately 10% below the nominal for the
second run. Note that such unbalances are only necessary for