MODELING OF INDUCTION
MOTOR AND FAULT ANALYSIS
ABSTRACT
Motor
current signature analysis is the reference method for the diagnosis of
induction machines faults in vector control technique, the special reference
frames, electromagnetic torque of the smooth air gap machine is similar to the
expression for the torque of the separately excited DC machine. Variable speed
drives applications are common in the aerospace, appliance, railway, and
automotive industries and also electric generators for wind turbines. In this
paper, a simple and effective technique is presented that allows the diagnosis
of machines faults for induction machines drives in vector control technique.
In case of induction machines the control is usually preformed in the reference
frame (d-q) attached to the rotor flux space vector. Simulation and
experimental results are shown to validate the scheme.
Keywords:
Induction motor, vector control, Simulink, Matlab, fault analysis, parameter.
INTRODUCTION
Introduction
motors are widely used in industrial applications for their intrinsic
ruggedness and reduced cost. Recently, the use of adjustable speed drives has
spread in many applications. Most of the industrials motors are used today are
in fact induction motors. Induction motors have been used in the past mainly in
applications requiring a constant speed because conventional methods of their
speed control have either been expensive or highly inefficient. This type of
control scheme uses more mathematical calculations and algorithms, which
involves heavy computing and needed efficient and costly controllers. Here we
introduce a novel theory to improve the performance of the motor running it at
optimum voltage and frequency for optimum motor efficiency at different points.
This is an offline method and not for online and real time control. In some applications,
where continuous operation is a key item, such as railway applications. And a
wind generator, The need for a preventive fault diagnosis is an extremely
important point. In this paper, fault detection and the prognosis of rotor
faults are critical for industrial applications, although rotor Faults share
only about20% of the overall induction machine faults. In fact, the breakage of
a bar leads to high current in adjacent bars, thus leading to potential further
breakage and stator faults as well.
PERFORMANCE OF INDUCTION MOTOR
Energy
supplied to the induction motor is distributed in the two parts, the first is in the form of mechanical output
and second one is in the form of losses. For the high performance of the motor
the motor losses should be small, so the output of motor goes high. An
efficient motor not only saves the energy, hence money, but will also generate
Less internal heat, and run cooler and more quietly. It is also likely to last
longer and more reliable than a less efficient motor. The better performance of
the motor is related to the maximum efficiency of the motor. There are
different methods to improve the performance of the induction motor. Variable
speed drive (VSD) is most applicable technology for the improvement of motor
performance. VSD is used to regulate the speed of a motor to suit with the load
demand. A VSD offers the reduce power, wider speed, torque and power ranges,
and shorter response time. Induction motor efficiency is dependent on many
motor parameters; however it is a function of the operating speed and applied
voltage, frequency.
CONTROL OF INDUCTION MACHINEDRIVES
Nowadays,
common solutions for high-power applications are based on drives that include a
voltage source inverter (VSI) feeding an induction motor or a permanent magnet
synchronous motor. However, old-fashioned solutions based on a current source
inverter or on thyristors are still employed, whereas old schemes based on dc
series motors or direct dc motors are no longer used.
Different
control schemes are adopted and tailored to the specific application.
Typically, variable structure controls are used for high-performance traction
drive systems that change according to the operating conditions, particularly
according to the speed and flux levels. The basic structure is a direct rotor
flux field-oriented vector control, whose scheme is shown in Fig. 1. The vector
control algorithm consists of two current loops for flux and torque regulation.
Moreover, an external rotor flux loop is used to set the flux level by means Of
the direct stator reference current. A similar control structure is used in
high-power applications, where transient operations often occur.
Direct
and inverse Clark transformations are represented by blocks D and D-1,
respectively. Standard PI regulators with anti-windup systems are used for the
control loops in a (d-q) reference frame that is synchronous with the
rotor flux. The rotor flux is estimated through a stator-model-based observer
obtained by integrating the stator voltage equation and taking into account the
leakage flux as
..................(1)
Where
Lm is the magnetizing inductance, Lr is the rotor inductance and Ls is the
stator inductance. ns And is are the
space vectors of the stator voltage and current, respectively; 
this corresponds
to the voltage–current observer block in Fig. 1.In the actual implementation of
(1), a low-pass filter is used instead of a pure integrator. This choice
reduces drifts due to errors and offsets in the acquired signals. However, the
uses of low-pass filter results in a wrong computation of the rotor flux space
vector in terms of magnitude and angle. An estimate of the stator pulsation is
used to compensate for these errors, i.e.,
......................(2)
Where
wr
is the measured mechanical speed, p is the pole pairs number, iq* is the
reference value for the torque current, fr* is the
reference value for the rotor flux, and Rr is the rotor resistance.
Relationship (2) is represented in Fig. 1 by the stator frequency estimation
block and is used for three main purposes. It is used as the feed-forward
compensation in the phase-locked loop (PLL) block used for the tracking of the
flux angle. As stated previously, it is used to compensate for errors in the
magnitude and the angle of the rotor flux caused by the low pass filter used
for the integration. Eventually, it is used in the decoupling terms that are
blocked together with the magnitude of the rotor flux estimated by (1) and the
measured currents in the synchronous reference frame to compute the dynamic
back electromotive- force compensation terms
..........................(3)
........................(4)
The
magnitude of the estimated flux is eventually used as a feedback signal for the
outer loop. The output of the PLL block, which is the tracked and corrected
rotor flux angle, is used for the reference frame matrix transformations p(Qs)
and p-1(Qs).
The value of the reference quadrature stator current is obtained from the
reference torque and the reference flux signal through the following equation:
..............................(5)
Where
= (2Lr /3pLm ). On the other hand, the reference flux is obtained
by relying on the nominal values for the torque and the rotor flux, i.e.,
..........................(6)
This
choice keeps the slip frequency quite constant, providing better robustness of
the control system against speed errors and reducing the losses at low torque.
This is suited to traction applications, where high-torque dynamics are not
requested, and it does not prevent reaching the maximum torque at low speed
when needed. In this paper, reference is made to an induction motor drive fed
by a pulse width modulation (PWM) VSI insulated-gate bipolar transistor
inverter. Typically, in traction drive systems, the switching frequency is very
low, making the detection of the faults through the signal injection strategy
impossible. Moreover, industries are particularly interested in diagnostic
techniques that do not require additional sensors. This paper proposes a simple
processing technique that exploits already available control signals for the
rotor fault diagnosis.
VECTOR CONTROL
Vector
control is the most popular control technique of AC induction motors. In
special reference frames, the expression for the electromagnetic torque of the
smooth-air-gap machine is similar to the expression for the torque of the
separately excited DC machine. In the case of induction machines, the control
is usually performed in the reference frame (d-q) attached to the rotor flux
space vector. That’s why the implementation of vector control requires
information on the modulus and the space angle (position) of the rotor flux
space vector. The stator Currents of the induction machine are separated into
flux- and torque-producing components by utilizing transformation to the d-q
coordinate system, whose direct axis (d) is aligned with the rotor flux
space vector. That means that the q-axis component of the rotor flux
space vector is always zero.
Fig. 1 2500 kW, 3 kV, 24,000 rpm
induction motor
Fig.2 Complete block diagram of vector control
method
To
perform vector control, follow these steps:
·
Measure the motor quantities (phase
voltages and Currents)
·
Transform them to the 2-phase system (α,
β) Using a Clarke transformation
·
Calculate the rotor flux space vector
magnitude And position angle
·
Transform stator currents to the d-q
coordinate System using a Park transformation
·
The stator current torque- (isq) and
flux- (isd) Producing components are separately controlled
·
The output stator voltage space vector
is calculated using the decoupling block
·
An inverse Park transformation
transforms the Stator voltage space vector back from the d-q Coordinate System
to the 2-phase system fixed with the stator
·
Using the space vector modulation, the
output 3-Phase voltage is generated
The
components isa and isb , calculated with a Clarke transformation, are attached to the stator
reference frame α, β in vector control; all quantities must be expressed in the
same reference frame. The stator reference frame is not suitable for the
control process. The space vector is rotating at a rate equal to the angular
frequency of the phase Currents. The components isa and isb depend on time and speed. These components can be
transformed from the stator reference frame to the d-q reference frame rotating
at the same speed as the angular frequency of the phase currents. The isq and
isd components do not then depend on time and speed. The isd component is
called the direct axis Component (the flux-producing component) and isd is
called the quadrature axis component (the torque-producing component). They are
time invariant; flux and torque control with them is easy.
Knowledge
of the rotor flux space vector magnitude and position is key information for AC
induction motor vector control. With the rotor magnetic flux space vector, the
rotational coordinate system (d-q) can be established. There are several
methods for obtaining the rotor magnetic flux space vector. The flux model
Implemented here utilizes monitored rotor speed and stator voltages and
currents. It is calculated in the stationary reference frame (α, β) attached to
the stator. The error in the calculated value of the rotor flux, influenced by
the changes in temperature, is negligible for this rotor flux model. For
purposes of the rotor flux-oriented vector control, the direct-axis stator
current isd (the rotor flux-producing component) and the quadrature axis stator
current isd (the torque producing component) must be controlled independently.
However, the equations of the stator voltage components are coupled. The direct
axis component vsd also depends on isd and the quadrature axis component vsd also
depends on isq. The stator voltage components vsd and vsq cannot be
considered as decoupled control variables for the rotor flux and
electromagnetic torque. The stator Currents isd and isq can only be
independently controlled (decoupled control) if the stator voltage equations
are decoupled and controlling the terminal voltages of the induction motor
indirectly controls the stator current components isd and isq.
FAULTS DETECTION TECHNIQUES
Modem
measurement techniques in combination with advanced computerized data
processing and acquisition show new ways in the field of induction machines
monitoring by the use of spectral analysis of operational process parameters
(e.g. temperature, pressure, steam flow, etc.). Time domain analysis using
characteristic values to determine changes by trend setting, spectrum analysis
to determine trends of frequencies, amplitude and phase relations, as well as
cepstrum analysis to detect periodical Components of spectra are used as
evaluation tools. In many situations, vibration monitoring methods were
utilized for incipient fault detection. However, stator current monitoring was
found to provide the same indication without requiring access to the motor. In
what follows, some of the main stator current signature based technique is
presented.
·
The Classical
Fast Fourier Transform (FFT)
·
Wavelet Analysis
·
Current park‟s
vector approach
·
Power spectral
density analysis
DEVELOPMENT OF SIMULINK MODEL
The
block model of the induction motor system with the controller was developed
using the power system, power electronics, control system, signal processing
toolboxes & from the basic functions available in the Simulink library in
Matlab / Simulink. The entire system modeled in Simulink is a closed loop
feedback control system consisting of the plants, controllers, samplers,
comparators, feedback systems, the mux, de-mux, summers, adders, gain blocks,
multipliers, clocks, sub-systems, integrators, state-space models, subsystems,
the output sinks (scopes), the input Source etc.
Voltage
equations
Current
equations
Fig. 3. Induction motor with supply
Fig.4.Spectral power density
RESULTS
Extensive
research activities were carried out to model rotor asymmetries to accurately
predict the behavior of the machine under faulty conditions. Here, the
procedure was validated with a machine model, whose parameters are taken from
the machine used for the experiments. Specifically, a 7.5-kW three-phase
two-pole pair’s induction machine was used to verify the agreement between
simulations. The rotor fault is one broken bar that was modeled increasing the
resistance of one squirrel cage rotor bar.
Fig.5.Healthy motor torque
Fig. 6. Three phase stator currents vs
time
Fig. 7.Speed for healthy motor
WAVELET OUTPUTS HEALTHY MOTOR CURRENT SIGNAL (ia)
Fig.8.Approximation signal for healthy
induction motor
Fig.9.Details coefficients for healthy
induction motor
ONE BAR BROKEN CURRENT SIGNAL (ia)
Fig.10.Approximation signal for one
broken bars induction motor
Fig.11.Details coefficients for one
broken bars induction motor
PARK’S CURRENT VECTOR APPROACH
Fig.12.park’s current vector approach
for healthy broken induction motor
Fig.13.park’s current vector approach
for one bar induction motor
Fig.14.Spectral power density for
healthy induction motor
Fig.15.Spectral power density for one
bar broken induction motor
SHORT TIME FOURIER TRANSFORMATIONS
Fig.16.STFT coefficients for healthy
motor induction motor
Fig.17.STFT coefficients for one bar
broken induction motor
CONCLUSION
We
have seen the simulation circuit and simulation results of induction machine.
This method has been tailored to control rotor flux field oriented control
drives in transient conditions. During transient condition, torque, speed
varies, preventing the use of vector control technique for an effective
diagnosis of rotor faults. The obtained analytical frequencies in the stator
spectrum can be related to the experimental ones of normal operation and under
rotor bar faults. Stator current of healthy and fault motors are analyzed by using
wavelet daudechies 6-level decomposition technique, park’s current vector
approach, spectral power density and short time Fourier transformations. This
analysis shows the difference between healthy, single and double broken rotor
bar and three bar broken rotor of induction motor.
APPENDIX
The
induction motor is 10hp having following parameters
No.
of poles = 4
Rated
power = 7.5kw
Rated
stator voltage = 380 V
Nominal
Stator current = 15.3 A
Rated
frequency = 50 Hz
Rated
speed = 1440 rpm
Stator
resistance = 0.54 ohm
Rotor
resistance = 0.58 ohm
Stator
inductance = 88.4mH
Rotor
inductance = 83.3mH
Magnetizing
inductance = 81.7mH
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