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IJCST Vol. 3, ISSue 1, Jan. - MarCh 2012ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print)
w w w . i j c s t . c o m InternatIonal Journal of Computer SCIenCe and teChnology 353
Abstract
Different types of models have been proposed in the recent years 
to examine different problems associated with induction motors. 
These models are from the simple equivalent circuit to complex 
d, q models and abc models which allow the inclusion of different 
forms of impedance and/or voltage unbalance. In the recent past, 
hybrid models have been developed which allow the inclusion 
of supply side unbalance but with the computational economy 
of the d, q models. Recently, there are so many applications in 
which induction motors are fed by static frequency inverters. Such 
applications are growing fast and a significant work in this field 
has already been done. However, still there are a lot of scopes 
left which may be used in this applications. This paper presents a 
dynamic model using PWM inverter and mathematical modelling 
of the motor. By using this model induction motor may be used 
as variable speed applications unlike conventional induction 
motors. The utilization of squirrel cage induction motors with 
electronic inverters presents greater advantages on cost and energy 
efficiency, compared with other industrial solutions for varying 
speed applications. The dynamic simulation of the small power 
induction motor is one of the key steps in the validation of the 
design process of the motor drive system and it is needed for 
eliminating in advertent design mistakes and the resulting error in 
the prototype construction and testing. This model is successfully 
used in the fault detection of rotor broken bar for the induction 
machines. This paper demonstrates the simulation of steady-state 
performance of three phase squirrel cage induction motor and 
detection of rotor broken bar fault by MATLAB program. 
Keywords
Squirrel Cage Induction Motor, Pulse Width Modulation (PWM), 
Time Domain, Modelling and Simulation Rotor Fault Identification, 
MATLAB
I. Introduction
The controls of high-performance induction motor drives in 
industry application and production automation have received 
more interests in the recent years. Three–phase squirrel cage 
induction motor is widely used motor in the industrial applications 
for its simple design, reliable operation, rugged construction, 
low initial cost, easy operation and simple maintenance, high 
efficiency and having simple control gear for starting and speed 
control [1-3].
Induction motors are the most widely used motors for appliances, 
industrial control, and automation; hence, they are often called 
the workhorse of the motion industry. When power is supplied to 
an induction motor at the recommended specifications, it runs at 
its rated speed. However, many applications need variable speed 
operations. For example, a washing machine may use different 
speeds for each wash cycle. Historically, mechanical gear systems 
were used to obtain variable speed. Recently, electronic power 
and control systems such as PWM inverter have matured to 
allow these components to be used for motor control in place of 
mechanical gears [8]. These electronics devices such as PWM 
not only control the motor’s speed, but can improve the motor’s 
dynamic and steady state characteristics. In addition, electronics 
devices can reduce the system’s average power consumption and 
noise generation of the motor. The utilization of static frequency 
inverters comprehends currently the most efficient method to 
control the speed of induction motors. Inverters transform a 
constant frequency constant amplitude voltage into a variable 
(controllable) frequency-variable (controllable) amplitude voltage. 
The variation of the power frequency supplied to the motor leads 
to the variation of the rotating field speed, which modifies the 
mechanical speed of the machine [6, 9].
Usually, the induction motor is widely used for constant speed 
applications but if we want induction motor to be used as 
variable speed applications then it is required to fed induction 
motor with a static PWM frequency inverter. The PWM static 
frequency inverter ought to be used in the supply side means 
in stator side [2,5,7]. Therefore, Induction motor may be used 
in some important applications in the place of D.C. machines. 
The most important feature which declares induction motor as 
a tough competitor to D.C. machines in the drives field is that 
its cost per KVA is approximately one fifty of its counter-part 
and it possesses higher suitability in hostile environment [4-5]. 
If thermal forces are applied on the rotor bar of the induction 
machine then rotor bar may be broken, on that account if rotor bar 
is broken, the other component of induction motor is consequently 
damaged. Therefore, this fault becomes more catastrophic if it 
would not diagnose at time [6-8]. Induction machine modelling 
has continuously attracted the attention of researchers not only 
because such machines are made and used in largest number of 
applications but also due to their varied modes of operation both 
under steady state and dynamic states. In electric drive system 
elements, such machines is a part of the control system elements, 
if we want to control dynamic behavior of Induction Motor (IM) 
then dynamic model of IM has to be considered. The dynamic 
model considers the instantaneous effects of varying voltage/
currents, stator frequency and torque disturbance. In this paper 
dynamic model of IM is derived by using d and q variables with 
PWM inverter in a stationary rotating reference frame [9-15].
Induction motor is simply an electric transformer whose magnetic 
circuit is separated by an air gap into two relative movable 
portions, one carrying the primary and the other the secondary 
winding. Alternating current supplied to the primary winding 
from an electric power system induces an opposing current in the 
secondary winding, when the latter is short-circuited or closed 
through external impedance. Relative motion between the primary 
and secondary structure is produce by the electromagnetic forces 
corresponding to the power thus transferred across the air gap by 
induction. The essential features which distinguish the induction 
machine from other type of electric motors is that the secondary 
currents are created solely by induction, as in a transformer instead 
of being supplied by a dc exciter or other external power sources, 
as in synchronous and dc machines [1-6]. 
There are various faults occur in the induction motor such as 
broken rotor bar fault, short winding fault, bearing fault, air-gap 
eccentricity fault and load fault but the rotor broken bar fault is 
more catastrophic because if this fault occur, this can damage the 
Modelling and Detection of Rotor Broken Bar Fault using 
Induction Motor Fed PWM Inverter
1Khadim Moin Siddiqui, 2Dr. V.K. Giri
1,2Madan Mohan Malaviya Engineering College, Gorakhpur, UP, India
IJCST Vol. 3, ISSue 1, Jan. - MarCh 2012 ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print)
w w w . i j c s t . c o m354 InternatIonal Journal of Computer SCIenCe and teChnology 
other components of the induction motor. It has been stated that 
this fault is only occur 10 percent of total faults takes place in 
induction motor [7-8].
Induction motors are a critical component of many industrial 
processes and are frequently integrated in commercially available 
equipment and industrial processes. Motor-driven equipment 
often provide core capabilities essential to business success and 
to safety of equipment and personnel. There are many published 
techniques and many commercially available tools to monitor 
induction motors to ensure a high degree of reliability uptime. In 
spite of these tools, manycompanies are still facing unexpected 
system failures and reduced motor life. Environmental, duty, and 
installation issues may combine to accelerate motor failure far 
sooner than the designed motor lifetimes. Critical induction motor 
applications are found in all industries and include all motors of 
different horse powers ratings. It has been found that many of 
the commercial products to monitor induction motors are not 
cost effective when deployed on typical low- to medium-horse 
power ratings induction motors. Advances in sensors, algorithms, 
and architectures should provide the necessary technologies for 
effective incipient failure detection [16-19].
II. Mathematical Modelling of The Motor
In electrical engineering, direct-quadrature-zero (or dq0) 
transformation or zero-direct-quadrature (or 0dq) transformation 
is a mathematical transformation used to simplify the analysis of 
three-phase circuits. In the case of balanced three-phase circuits, 
application of the dq0 transform reduces the three AC quantities to 
two DC quantities. Simplified calculations can then be carried out 
on these imaginary DC quantities before performing the inverse 
transform to recover the actual three-phase AC results. It is often 
used in order to simplify the analysis of three phase induction 
machines or to simplify calculations for the control of three-phase 
inverters. The simulink model of and corresponding mathematical 
analysis of the model are as shown in fig. 1 and fig. 2.
Fig. 1:(a). q-Axis Diagram of IM
Fig. 1: (b). d-Axis Diagram of IM
The stator voltage on the q-axis and d-axis are given in equation 
1 and 2. The equations from (1 to 7) come into the category of 
Electrical system.
Vqs = Rsiqs + Ψqs + ωΨds, where, Ψqs= Lsiqs+ Lmíqr (1)
Vds = Rsids + Ψds- ωΨqs, where, Ψds=Lsids+Lmídr (2)
The rotor voltage on q-axis and d-axis are given in equation 3 
and 4.
V́qr = Ŕ rí qr + Ψq́r + (ω – ωr) Ψd́r, where, Ψq́r = Ĺr íqr +Lmiqs (3)
V́ dr = Ŕ rídr + Ψd́r + (ω – ωr) Ψq́r , where, Ψd́r = Ĺr ídr +Lmids (4) 
Ls = Lls + Lm (5) 
Ĺr=Ĺ1r+ Lm (6) 
The Electromagnetic Torque is given in equation
Te = 1.5 p(Ψdsiqs – Ψqsids) (7)
The equations for the mechanical system are as shown below:
 ωm = ( Te - F ωm – Tm) (8)
θm=ωm (9)
 
The Machine block parameters (all quantities are referred to the 
stator side) are as following:
Rs , Lls Stator resistance and leakage inductance
Rr , Lr Rotor resistance and leakage inductance
Lm Magnetizing inductance
Ls , Lr Total stator and rotor inductances
Vqs , iqs q axis stator voltage and current
Vqr , iqr q axis rotor voltage and current
Vds , ids d axis stator voltage and current
Vdr, idr d axis rotor voltage and current
Ψqs , Ψds Stator q and d axis fluxes
Ψqr , Ψdr Rotor q and d axis fluxes
p Number of pole pair
ωm Angular velocity of the rotor
θm Rotor angular position
ωr Electrical angular velocity(ωm X p)
θr Electrical rotor angular position (θm X p)
Te Electromagnetic torque
Tm Shaft mechanical torque
J Combined rotor, load inertia coefficient set to 
 infinite to simulate locked rotor.
H Combined rotor, load inertia constant set to 
 infinite to simulate locked rotor.
F Combined rotor and load viscous friction 
 coefficient.
There are two torques, one is Electromagnetic Torque (Te) and other 
is Shaft mechanical Torque (Tm). The difference between in both 
is Shaft mechanical torque (Tm) is the input Torque which applies 
on the motor and Electromagnetic torque (Te) is the output torque 
which produces due to the induction. The quadrature axis d-axis 
and q-axis which are obtained form to abc to dq conversion. 
A. abc to dq Reference Frame
The following relationships describe the abc-to-dq reference frame 
transformations applied to the Induction Machine phase-to-phase 
voltages 
= (10)
`
IJCST Vol. 3, ISSue 1, Jan. - MarCh 2012ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print)
w w w . i j c s t . c o m InternatIonal Journal of Computer SCIenCe and teChnology 355
= (11) 
In the preceding equations, θ is the angular position of the reference 
frame, while β = θ - θr is the difference between the position 
of the reference frame and the position (electrical) of the rotor. 
Because the machine windings are connected in a three-wire Y 
configuration, there is no homopolar (0) component. This also 
justifies the fact that two line-to-line input voltages are used inside 
the model instead of three line-to-neutral voltages.
B. dq to abc Reference Frame
The following relationships describe the dq-to-abc reference 
frame transformations applied to the Induction Machine phase 
currents.
 (12) 
 = (13)
 
ics = - ias – ibs (14)
ícr = -íar – íbr (15)
Where, ias, ibs, ics are the stator currents in different phases. íar, 
́ibr, ícr are the rotor current in different phases.
III. Proposed Simulation Model of 3- Phase Squirrel Cage 
Induction Motor
This Squirrel cage Induction machine block can be operates in 
generator as well as motor mode. It depends upon the sign of 
mechanical torque (Tm). If Tm is positive as shown in fig. 2, 
machine acts as motor and if Tm is negative it acts as generator. 
The Simulink block input is the mechanical torque at the machine’s 
shaft. The simulink output block has one output but that contains 
21 signals. We can demultiplex these signals by the Bus Selector 
block provided by the simulink library.
wm* S tep
(p.u. )
va b (V )
v+-
va b
-K -
rpm
-K -
pu2ra dpersec
Continuous
pow ergui
-K -
pea k2rms
ir, is (A)
s -
+
V bc
s -
+
V a b
sin
11.9
T e (N.m)
R ela yC
R ela yB
R ela yA
220.5
R MS V a b volta ge
N (rpm)
rem
Ma th
F unction
L ook-Up
T a ble
s ignal
magnitude
angle
F ourier
Demux
Demux
1/1980
2*pi/3*[ 0, -1,1 ]
C lock
 
m
A
B
C
T m
0.5 HP - 415 V
50 Hz - 1725 rpm
 
<E lec tromagnetic torque Te (N *m)>
<R otor c urrent ir_a (A)>
<S tator c urrent is _a (A)>
<R otor s peed (wm)>
Fig. 2: Simulation Model of Three Phase Squirrel Induction 
Motor
Note that the neutral connections of the stator and rotor windings 
are not available; three-wire Y connections are assumed. The 
proposed simulation model of the three phase induction motor 
shown in fig. 2. The input mechanical torque is applied on the 
shaft i.e. 11.9 N-m as the full load torque. There are five scope 
blocks which is used for results displaying purpose. They give 
Rotor current, Stator current, Rotor speed, Electromagnetic torque 
and output of PWM inverter respectively. The node voltage is 
extracted by the Fourier block which gives 220.7 Volt as shown 
in fig. 2.
A three-phase motor rated 0.5 HP, 415 V; 1725 rpm is fed by a 
sinusoidal PWM inverter considered. The base frequency of the 
sinusoidal reference wave is 50 Hz while the triangular carrier 
wave’s frequency is set to 1980 Hz. The Maximum time step has 
been limited to 10 µs. This is required due to the relatively high 
switching frequency (1980 Hz) of the inverter. The PWM inverter 
is built entirely with standard Simulink blocks. Its output goes 
through Controlled Voltage Source blocks before being applied to 
the Squirrel cage induction machine block’s stator windings.
The machine’s rotor is short-circuited. Its stator leakage inductance 
L1s is set to twice its actual value to simulate the effect of a 
smoothing reactor placed between the inverter and the machine. 
The load torque applied to the machine’s shaft is constant and 
set to its nominal value of 11.9 N.m. The motoris started from 
standstill condition. The speed set point is set to 1.0 pu, or 1725 
rpm. This speed is reached after 0.9 s. Observe that the rotor and 
stator currents are quite “noisy,” despite the use of a smoothing 
reactor. The noise introduced by the PWM inverter is also observed 
in the electromagnetic torque waveform Te. However, the motor’s 
inertia prevents this noise from appearing in the motor’s speed 
waveform. The RMS value of the fundamental component of the 
line voltage at the machine’s stator terminals is extracted with 
a Fourier block. There are three reference frame is possible in 
the three phase induction motor, in our case we have considered 
stationary reference frame. For the stationary reference frame the 
value of rotor angle is set to 0 and the value of β is set to - θr.
The descriptions of the elements are used in Simulink block is 
shown as following:
Rotor Type Squirrel Cage
Reference Frame Stationary
Motor 0.5 HP
Rated Speed 1725
Line-Line Voltage 415V
Node voltage rms 220.5V
Frequency 50Hz
Stator Resistance 0.435 ohm
Stator Inductance 2*2.0e-3H
Rotor Resistance 0.816ohm
Rotor Inductance 2.0e-3H
Mutual Inductance 69.31e-3
Inertia 0.089
Pairs of poles 2
After an extensive simulation on the developed model some 
limitations have been observed such as:
The Squirrel Cage Induction Machine block (used in simulink) does 
not include a representation of iron losses and saturation. We must 
be careful when we connect ideal sources to the machine’s stator. 
If we choose to supply the stator via a three-phase Y-connected 
infinite voltage source, we must use three sources connected in 
Y. However, if we choose to simulate a delta source connection, 
we must use only two sources connected in series.
When we use Squirrel Cage Induction Machine block in discrete 
systems, we might have to use a small parasitic resistive load, 
connected at the machine terminals, in order to avoid numerical 
oscillations. Large sample times require larger loads. The minimum 
resistive load is proportional to the sample time.
IV. Simulation Results for Healthy and Faulty Motor
The simulation results in healthy motor condition of the motor are 
as shown in fig. 3. There are four motor parameters those are rotor 
IJCST Vol. 3, ISSue 1, Jan. - MarCh 2012 ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print)
w w w . i j c s t . c o m356 InternatIonal Journal of Computer SCIenCe and teChnology 
current, stator current, rotor speed and electromagnetic torque. In 
the healthy mode of the motor the slip is set at 1(s=1) and input 
mechanical torque is 11.9 N-m. It is observed that from the results, 
all the parameters are reached in the steady state condition after 
0.8seconds. If we change the physical parameters of the motor 
such as slip and electromagnetic torque then the motor rotor bar 
behave like broken IM.
0 2 4 6 8 10 12
x 10
4
-100
-80
-60
-40
-20
0
20
40
60
80
100
time(s )
R
o
t
o
r
 c
u
r
r
e
n
t
(A
)
R otor current res pons e in healthy condition
 
0 2 4 6 8 10 12
x 10
4
-100
-80
-60
-40
-20
0
20
40
60
80
100
time(s )
S
t
a
t
o
r
 c
u
r
r
e
n
t
(A
)
S tator current res pons e in healthy condition
 (a ) (b) 
 
0 2 4 6 8 10 12
x 10
4
-200
0
200
400
600
800
1000
1200
1400
1600
1800
time(s )
R
o
to
r 
s
p
e
e
d
(r
p
m
)
R otor s peed res pons e in healthy condition
 
0 2 4 6 8 10 12
x 10
4
-40
-20
0
20
40
60
80
100
time(s )
E
le
c
tr
o
m
a
g
n
e
ti
c
 t
o
rq
u
e
(N
-m
)
E lectromagnetic torque res pons e in healthy condition
 (c) (d) 
Fig. 3: Healthy Condition of the Motor, (a). Rotor Current, (b). 
Stator Current, (c). Rotor Speed, (d). Electromagnetic Torque
The simulation results for faulty motor (5-broken bar) are as shown 
in fig 4. These results are for 5-broken bar motor condition. It is 
already stated that the rotor bar is broken by the varying of some 
physical parameters of the motor such as slip and input mechanical 
torque. The results shown in fig. 4, are for the full load 5-broken 
bar motor condition therefore, no variation is made in the load 
torque only slip is being changed. The slip is set at s=0.08. It 
is observed from the fig. 4, all the parameters of the motor get 
disturbed if the rotor bar is broken. The transient time of all the 
parameters is decreased and the motor is not reached in the steady 
state condition. Therefore, motor is reached in the unstable mode 
unexpectedly. The results obtained in the faulty motor condition 
are completely different from the healthy motor condition. Thus, 
it is a non-invasive technique to find out the rotor fault broken 
bar detection using time domain analysis.
0 2 4 6 8 10 12
x 10
4
-100
-80
-60
-40
-20
0
20
40
60
80
100
time(s )
R
o
to
r 
cu
rr
e
n
t(
A
)
R otor current res pons e at full load
 0 2 4 6 8 10 12x 104
-100
-80
-60
-40
-20
0
20
40
60
80
100
time(s )
S
ta
to
r 
cu
rr
e
n
t(
A
)
S tator current res pons e at full load
 (a ) (b) 
0 2 4 6 8 10 12
x 10
4
1300
1350
1400
1450
1500
1550
1600
1650
1700
1750
time(s )
R
o
to
r 
sp
e
e
d
(r
p
m
)
R otor s peed res pons e at full load condition
 0 2 4 6 8 10 12x 104
-60
-40
-20
0
20
40
60
80
100
time(s )
E
le
ct
ro
m
ag
n
e
ti
c 
to
rq
u
e
(N
-m
)
E lectromagnetic torque res pons e at full load
 (c) (d)
Fig. 4: Faulty Conditions (5-broken bar at full load), (a). Rotor 
Current, (b). Stator Current, (c). Rotor Speed, (d). Electromagnetic 
Torque
The comparison in healthy motor and faulty motor (5-broken 
bar) is shown in Table 1 for different loading conditions. It may 
be observed that the stator current, rotor current and rotor speed 
is decreased if load is decreased but electromagnetic torque is 
slightly increased.
Table: 1 Comparison in Faulty Motor Condition at Different Load 
(5-Broken Bar)
Motor 
Condition Slip Load
Rotor 
Current
(A)
Stator 
Current
(A)
Speed
(rpm)
EMT
(N-m)
Healthy 1 11.9 74.53 87.07 1725 90.64
1 BRB 0.04 11.9 54.56 77.74 1440 55.29
3 BRB .056 11.9 52.68 77.68 1416 55.59
5 BRB 0.08 11.9 49.02 77.52 1380 55.83
No-Load 0.01 0 59.83 78.02 1485 53.07
The comparison in faulty motor conditions for various broken 
bar is as shown in Table 2. This comparison clearly shows the 
difference between 1, 3, 5 broken bars in the motor parameters. 
The comparison is made from healthy motor parameters. The 
analysis is also done for no-load condition of the motor. It is 
observed from the table 2, when the rotor bar is broken at that 
time all the motor parameters are decreased but when the rotor 
broken bar is increased then the parameters of the motor is being 
decreased except electromagnetic torque.
Table 2: Comparison of Parameters for Various Broken Bar
Motor 
Condition Slip Load
RotorCurrent
(A)
Stator 
Current
(A)
Speed
(rpm)
EMT
(N-m)
Healthy 1 11.9 74.53 87.07 1725 90.64
1 BRB 0.04 11.9 54.56 77.74 1440 55.29
3 BRB .056 11.9 52.68 77.68 1416 55.59
5 BRB 0.08 11.9 49.02 77.52 1380 55.83
No-Load 0.01 0 59.83 78.02 1485 53.07
77.74 A whereas, in healthy condition it is more than the faulty 
stator current i.e. 87.07 A. If a bar broken is increased then fault 
will be severe and stator current will be further decreased. It is 
observed that all the mentioned signatures of the motor given in 
the Table 2, are decreased except electromagnetic torques value 
it is slightly increased. It is concluded that if the rotor fault severity 
is increased then electromagnetic torque also will be increased. 
The rotor speed is also decreased. Finally from the observation 
of above tables it may be stated that the signatures of the motors 
in the healthy condition is completely different from the faulty 
condition of the induction motor. The combined response of the 
three phase squirrel cage induction motor for healthy and faulty 
(5-broken bar) condition is as given in fig. 3(a) and fig. 3(b). It 
IJCST Vol. 3, ISSue 1, Jan. - MarCh 2012ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print)
w w w . i j c s t . c o m InternatIonal Journal of Computer SCIenCe and teChnology 357
shows clear variation between the signal magnitudes verses time 
for healthy and faulty motor.
0 2 4 6 8 10 12
x 10
4
-100
-50
0
50
100
150
200
time(s )
M
a
g
n
it
u
d
e
(p
u
)
R es pons e in the healthy condition
 
 
R otor current vs . time
S tator current vs . time
R oto s peed vs . time
Torque vs . time
 
0 2 4 6 8 10 12
x 10
4
-100
-50
0
50
100
150
200
time(s )
M
a
g
n
it
u
d
e
(p
u
)
R es pons es at full load condition
 
 
R otor current vs . time
S tator current vs . time
R otor s peed vs . time
Torque vs . time
 (a) (b)
Fig 5: Combined Response, (a). For Healthy Dondition, (b). For 
5 Broken Bar Condition at Full Load
Now, it is clear that using time domain responses it is possible to 
detect rotor faults in all load conditions and various broken bars. 
It has been observed from the fig 6, the responses and magnitude 
voltage i.e. 359.25 V is exactly same for the healthy and faulty 
motor. That means if we fed static frequency inverter in the stator 
side of the motor then there is no effect on the PWM inverter 
characteristic either rotor broken or not. Therefore, it is concluded 
that the PWM inverter is efficiently used in the speed control of 
the three phase induction motor. The output responses of PWM 
inverter for healthy and 5-broken bar faulty conditions are as 
shown in fig. 6.
0 2 4 6 8 10 12
x 10
4
-400
-200
0
200
400
time(s )
O
u
t
p
u
t
 V
o
lt
a
g
e
(V
)
Output of P W M Inverter in Healthy C ondition
 (a)
0 2 4 6 8 10 12
x 10
4
-400
-200
0
200
400
time(s )
O
u
tp
u
t 
V
o
lt
a
g
e
(V
)
Output of P W M Inverter for F ive B roken B ar
 (a)
Fig. 6:(a). Response of PWM Inverter in Healthy Condition, (b). 
Response of PWM Inverter in Faulty Condition (5-broken bar)
V. Conclusions
It has been concluded that the rapid advancement of power 
electronics have allowed constant speed induction motor is used 
as variable speed induction drive systems by using static frequency 
inverter. For the variable speed induction motor the motor must 
be fed by static frequency inverter rather than directly by the 
sinusoidal power line. The utilization of squirrel cage induction 
motors with electronic inverters presents great advantages on cost 
and energy efficiency, compared with other industrial solutions 
for varying speed applications. Nevertheless, the PWM inverter 
affects the motor performance and might introduce disturbs into 
the main power line. But the increasing number of applications 
with induction motors fed by PWM inverters operating in variable 
speed duty. Thus, requires a good understanding of the whole 
power system as well as the interactions among its parts one 
another (power line-frequency inverter-induction motor-load). It is 
also concluded that this model efficiently used in the fault detection 
of rotor broken bar purpose. It may be stated that the time domain 
analysis may also be used for the rotor broken bar fault detection 
purpose efficiently. This model may also be used for the incipient 
of fault detection in combination with other methods such as Fast 
Fourier Transform (FFT), STFT, and Wavelet Transform.
References
[1] B. Liang,B.S.,Payne, A.D. Ball, S.D. Iwnicki,“Simulation 
and fault detection of three-phase induction motors”, Int. 
J. Mathematics and Computers in Simulation, pp. 1–15, 
2002.
[2] Meenakshi Mataray, Vinay Kakkar,“Asynchronous Machine 
Modelling Using Simulink Fed by PWM Inverter”, 
International Journal of Advances in Engineering & 
Technology, May 2011.
[3] Sung-Kuk Kim, Jul-Ki Seok,“High-Frequency Signal 
Injection-Based Rotor Bar Fault Detection of Inverter-Fed 
Induction Motors With Closed Rotor Slots”, IEEE Trans.
industry applications, Vol. 47, July-Aug,2011.
[4] Nyein Nyein Soe, Thet Thet Han Yee, Soe Sandar 
Aung,“Dynamic Modeling and Simulation of Threephase 
Small Power Induction Motor”, World Academy of Science, 
Engineering and Technology, pp. 421-424, 2008.
[5] P. Fritzson,“Principles of Object-Oriented Modeling and 
Simulation with Modelica 2.1. Piscataway”, NJ: IEEE Press, 
2004.
[6] Kim, K., Parlos, A.G.,“Model-Based Fault Diagnosis of 
Induction Motors Using Non-Stationary Signal Segmentation”, 
Int J. Mechanical Systems and Signal Processing, Vol. 16, 
pp. 223-253, 2002. 
[7] R. Krishnan,“Electric Motor Drives Modelling, Analysis, 
and Control”, Prentice Hall 2001.
[8] Khadim Moin Siddiqui, V.K. Giri,“Broken Rotor Bar 
Fault Detection in Induction Motors using Transient 
Current Analysis”, International Journal of Electronics and 
Telecommunications, Vol 2, Oct-Dec, 2011.
[9] Nur Hakimah Ab Aziz,“Three- Phase Squirrel-Cage Induction 
Motor Drive Analysis Using LabVIEW”, Master Thesis 
University of South Australia, 2006.
[10] Krause, P. C.,“Simulation of symmetrical induction 
machinery”, IEEE Trans. Power apparatus Systems, Vol. 
PAS-84, No. 11, pp. 1038–1053, 1965.
[11] Ghani, S. N.,“Digital computer simulation of three- phase 
induction machine dynamics a generalized approach”, IEEE 
Trans Industry Appl., Vol. 24, No. 1, pp. 106–114 (1988).
[12] Wade, S., Dunnigan, M. W., Williams, B. W., “Modelling 
and simulation of induction machine vector control and rotor 
resistance identification”, IEEE Trans. Power Electronics, 
vol. 12, No. 3, pp 495–505 (1997).
IJCST Vol. 3, ISSue 1, Jan. - MarCh 2012 ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print)
w w w . i j c s t . c o m358 InternatIonal Journal of Computer SCIenCe and teChnology 
[13] Shi, K. L., Chan, T. F., Wong, Y. K.,“Modelling of the three-
phase induction motor using SIMULINK”, Record of the 
1997 IEEE International Electric Machines and Drives 
Conference, USA, pp. WB3-6 (1997).
[14] Shi, K. L., Chan, T. F., Wong, Y. K.,“Modelling and simulation 
of direct self control system”, IASTED International 
Conference: Modelling and Simulation, Pittsburgh, USA, 
pp.231–235, 1998.
[15] Using SIMULINK,“Dynamic System Simulation for 
MATLAB”, the Mathworks Inc. (2010).
[16] W. W. Tan, H. Huo,“A generic neuro fuzzy model-based 
approach for detecting faults in induction motors”, IEEE 
Transactions on Industrial Electronics, Vol. 52, pp. 1420–
1427, Oct. 2005.
[17] Benbouzid, M.E.H.,“Bibliography on induction motors faults 
detection anddiagnosis”, IEEE Trans.Energy Conversion, 
Vol. 9, No. 4, pp. 1065–1074, 1999.
[18] C. Kral, A. Haumer, F. Pirker,“A modelica library for the 
simulation of electrical asymmetries in multiphase machines 
- the extended machines library”, IEEE International 
Symposium on Diagnostics for Electric Machines, Power 
Electronics and Drives, The 6th, SDEMPED, Cracow, 
Poland, pp. 255–260, 2007.
[19] F. M. Discenzo, P.J. Tavner.,“Motor diagnostics: Technological 
drivers leading to 21st century predictive diagnostics”, in 
Proc. 1997 Int. Conf. Maintenance and Reliability, Vol. 1, 
Knoxville, TN, pp. 30.01–30.12, 1997.
Khadim Moin Siddiqui received his 
B.Tech degree in Electronics Engineering 
from Azad Institute of Engineering & 
Technology, Lucknow, India, in 2007, 
the M.Tech degree in Power Electronics 
& Drives from Madan Mohan Malaviya 
Engineering College, Gorakhpur, India, 
in 2011. He was a teaching, lecturer with 
Department of Electronics Engineering, 
Azad Institute of Engineering & 
Technology, in August 2008 to 2009. He 
worked as a trainee in NIIT, Bangalore, in 2007 to July 2008. His 
research interests include power and control, telecommunication. 
At present, He is working as Assistant Professor in JNU jaipur.
V.K.Giri obtained his B.E. (Electrical) 
Degree from REC, Surat (Gujrat) 
in 1988, M.E. (Measurement and 
Instrumentation) Hons. degree from 
University of Roorkee, Roorkee in 1997 
and Ph.D. degree from Indian Institute 
of Technology Roorkee, Roorkee 
in 2003. He joined the Electrical 
Engineering Department of M.M.M 
Engineering College, Gorakhpur (UP) 
in 1989 as lecturer. Presently, he holds 
the position of Professor in the same department since, 2008. He 
has published more than 30 research papers, guided 6 PG students; 
and supervising 3 Ph.D. theses. He has received many awards 
including the best paper awards of the Institution of Engineers 
(India) in 23rd Indian Engineering Congress in year 2008. He was 
elected as Fellow of the Institution of Engineers (I), Institution of 
Electronics and telecommunication. Engineers, and is a member 
of many professional bodies such as life member ISTE, member 
IEE and member CSI. He has also undertaken large number of 
consultancy, testing & sponsored projects from industries and 
government departments. His research interests include Digital 
Signal Processing, Measurement and Instrumentation, Biomedical 
Instrumentation, ECG Data Compression and Telemedicine.