International Journal of Advancements in Research & Technology, Volume 2, Issue 7, July-2013
ISSN 2278-7763
258
Fault detection of Induction Motor using Envelope Analysis*
RincyRaphael, Bipin PR
1
Applied Electronics, ICET, Ernakulam, India; 2Electronics, ICET, Ernakulam, India.
Email:rincyraphel@gmail.com.
ABSTRACT
This paper presents a new approach to diagnose broken rotor bar fault in induction motor using envelope analysis. A dynamic
model of induction motor is developed using MATLAB/SIMULINK. Wavelet Transform and envelope analysis used to obtain
statistical parameters maximum, median, minimum. Depending on these parameters, Support Vector Machine predicts the machine is healthy or not.
Keywords: Broken Rotor Bar, Envelope Analysis, Discrete Wavelet Transform, Support Vector Machine.
1 INTRODUCTION
I
NDUCTION motor is a most commonlyused industrial load
and guzzles a key part of overall electrical consumption.
Induction motors, especially the asynchronous motors, play
a vital part in the field of electromechanical energy conversion.The main advantages of induction motorsare costeffectiveness, reliability and higher efficiency. Electric induction motors have the ability to be connected directly to the AC
source. This can be an important cost savernotonly in household uses but also in industrial uses. An induction motor is
easy to program for its numerous uses. The initial cost of installing will be high, but it will save money in the long term
because of the low maintenance cost and durability of the
product. Moreover, it is a flexible design which allows innovations and newer technologies to be incorporated easily without incurring extra costs.
Different fault occurs in induction motorbecause of environmental stress and many other reasons. Induction motors
are commonly controlled by contactors, which are electromagnetic switches that are highly sensitive to voltage depressions and momentary service interruptions. Voltage depressions are huge problems for many industries, and it is probably the major pressing power quality problems today. The
Voltage depressions caused by faults on the system affect the
performance of induction motors, in terms of the production
of both transient currents and transient torques [1]. It is essential to minimize the effect of the voltage dip on both the induction motor and more significantly on the process where the
motor is used. Large torque peaks may cause damage to the
shaft or equipment connected to the shaft. Some common reason for voltage depressions are lightning strikes in power
lines, equipment failures, accidental contact power lines, and
electrical machine starts. Despite being a short duration between 10 milliseconds to 1 second event during which are duction in the RMS voltage magnitude takes place, a small reduction in the system voltage can cause serious consequences
.This unexpected interruption at the industrial plant disturbs
the cost, product quality and safety. Thus any fault affecting
induction motor has a drastic effect. Hence fault detection and
diagnosis have much importance. It is highly essential to protect the induction motor against failures. It is better to detect
faults before motor crashes completely.
Hugh Douglas, Pragasen Pillay, andAlireza K. Ziarani discussed about a new algorithm which is introduced to do motor current signature analysis of induction machines operating
during transients [3].The algorithm is able to extract the amplitude, phase andfrequency of a single sinusoid embedded in a
nonstationary waveform. The algorithm is applied to the detection of broken rotor bars in induction machines during
startup transients. The fundamental component of current,
which varies in amplitude, phase, and frequency, is extracted
using the algorithm. The residual current is then analyzed
using wavelets for the detection of broken rotor bars. This
method of condition monitoring does not require parameters
such as speed or number of rotor bars, is not load dependent
and can be applied to motors that operate continuously in the
transient mode.
BurakOzpineci, Leon M Tolbert they proposed a modular
Simulink implementation of an induction machine model is
described in a step-by-step approach [8]. With the modular
system, each block solves one of the model equations. All of
the machine parameters are accessible for control and verification purposes. After the implementation, examples are given
with the model used in different drive applications, such as
open-loop constant V/Hz control and indirect vector control.
S.K. Ahamed, ArghyaSarkar, M.Mitra and S. Senguptaexplains that errors may creep in when broken rotor bar fault of
induction motor is detected using conventional FFT based
approach as small sideband harmonics are completely masked
by the power frequency [10]. This paper unveils a new wavelet
transform and envelope analysis based broken rotor bar fault
detection technique, free from above mentioned drawback.
Wavelet transform has been performed onthe windowed
steady state current signal at no-load to obtain detailed and
approximate coefficients at different spectral bands. Then the
envelopes of the reconstructed signal corresponding to spectral bands below 50Hz were determined using Hilbert transform. It has been observed that faulty motor produces higher
statistical parameters- mean, standard deviation, median of
the envelopes than those for the healthy one.
IJOART
Copyright © 2013 SciResPub.
IJOART
International Journal of Advancements in Research & Technology, Volume 2, Issue 7, July-2013
ISSN 2278-7763
KhalafSalloumGaeid and Hew Wooi Ping proposed a
method which explains that the wavelet is considered as powerful tools in the fault detection and diagnosis of induction
motors [9]. Many wavelet classes can be generated by different
kinds of mother wavelets and can be constructed by filters
banks. The improvement of fault detection and diagnosis can
be exploiting the wavelet properties to get high detection and
diagnostics effectiveness. Theories of wavelet need to be
pushed forward to insure best choosing of mother wavelet.
The wavelet index can distinguish correctly between the faults
and healthy induction motor. Matlab/Simulink package for
both simulations and practical experiments in the diagnostic
of induction machines with wavelet.
A variety of faults can occur within three phase induction
motor during a course of normal operation. These faults can
lead to a potentially catastrophic failure if undetected. The
common internal faults can be mainly categorized in to two
groups [7].
Mechanical faults:
• Broken rotor bars
• Bearing damage
• Dynamic eccentricity
Electrical Faults
• Single or multiple phase short circuits.
• Open phase.
• Abnormal connections.
In this paper broken rotor bar or cracked rotor end ring are
analyzed with the help of signal processing techniques. The
first step to detect the broken rotor bar fault is to develop
analysis techniques that can be used to diagnose the observed
current signal to get useful information [4].Data acquisition is
carried out by running the simulation. The data acquisition
phase is followed by a sequence of steps consisting of signal
processing, envelope analysis and classification process. The
statistical parameters of the rotor current signal in frequency
domain are obtained and the parameters which can represent
the fault features well are extracted. Then classification of fault
is done with the help of Support Vector Machine.
259
the stationary frame to the synchronously rotating frame (dq)
using (2). In place of voltages there may be currents or flux
linkages.Where ‘ϒ’ is the transformation angle.
(1)
(2)
2. 2phase to 3-phase (dq-abc) conversion: This conversion does the
opposite of the abc-dq conversion for the current variables
using (3) and (4) respectively by following the same implementation techniques as before.
(3)
IJOART
(4)
The dynamic equations in arbitrary reference frame which
is rotating at speed ω in the direction ofrotor rotation.
1. When ω is equal to zero, the reference frame is fixed in the
stator (qs-ds ref. frame).
2. When ω is equal to ωe, the reference frame is fixed on the
synchronously rotating referenceframe.
3. When ω is equal to ωr, the reference frame is fixed in the
rotor. That is, the reference frame isrotating at speed of ω r .
The dynamic equations used are:
Electrical system equations:
(5)
2 MODELING OF INDUCTION MOTOR
Induction motor is modeled using mat lab / simulink program. This model is described in space vector formulation in
synchronously rotating arbitrary d-q reference frame associated with the frequency of the stator excitation.
This model is obtained considering the induction motor as
6 magnetically coupled circuits [1]. Under balanced conditions, the sum of stator currents as well as rotor currents is
zero. The induction motors are modeled in d-q variables. The
d-q model [6] uses two windings for each stator and rotor of
the induction motor. Only four independent variables are
needed to model the induction motor. A transformation of
variables can be used. The power invariant two-axes transformation is used and is defined as:
1.3-phase to 2-phase (abc-dq) conversion: To convert 3-phase voltages to voltages in the 2-phase synchronously rotating frame,
they are first converted to 2-phase stationary frame (α β) or in
the movement with an arbitrary speed using (1) and then from
Copyright © 2013 SciResPub.
(6)
(7)
Flux linkage-current relations:
(7a)
(7b)
IJOART
International Journal of Advancements in Research & Technology, Volume 2, Issue 7, July-2013
ISSN 2278-7763
Where
Mechanical system equations:
(8)
3 SIMULINK MODEL OF INDUCTION MOTOR
260
3.1 Model for Broken Bar Fault of Induction Motors
When the induction motor parameter changes there occur
interior faults. This paper provides one type of interior fault
model [5]. With the help of the quantitative relation among
machine parameters, fault types and fault extent, it is possible
to indirectly reflect interior faults by setting parameter changes of induction motor model. Considering the greatly possible
broken bar failure, a mathematical model is obtained. Suppose
that Z 2 is the number of rotor bars and n is the number of
broken bars. A cage rotor with n broken bars can be analyzed
as a three phase wound rotor with its impedance getting increased by ∆Z (∆Z = (∆R/s + j∆X)) dependent on the broken
bar number. This means that the difference in the mutual linkage inductance coefficients between different windings can be
neglected [2]. The transformation value of rotor resistance is
R’ 2 =R’ B +R’ R
The transformation value of rotor resistance after failure is
(9)
IJOART
(10)
Fig.1 Block diagram of induction motor model in the arbitrary frame
The model of the induction motor in d-q variables is represented by (5), (6), (7) and (8). Currents or flux linkages can be
used as state variables. In this paper the flux linkages are chosen as state variables and it was verified in the
Matlab/Simulink software environment. The block diagram of
a three-phase induction motor supplied by a three-phase
power supply is shown in Fig. 1. The variable ω = ω s represents the speed of the common reference frame used. This
speed is an arbitrary speed. It consists of five major blocks: the
3-phasevoltages, abc-dq conversion, dq-abc conversion, induction machine d-q model (Im_dq_model) and the mechanical
system (mech sys) blocks.
Fig.3. Faulty Model
4 PROPOSED TECHNIQUE
Fig.2. Simulink Model of Induction Motor
Copyright © 2013 SciResPub.
Rotor current is taken from the simulink model of induction motor. Then Discrete Wavelet Transform is performed on
the current signal with frequency below 50Hz using db6
mother wavelet. The statistical parameters are obtained by
envelop analysis. Then the envelopes of detailed coefficients
are obtained, it is observed that the faulty motor produces
higher statistical parameters maximum, median and minimum
than those for the healthy motor. Then the statistical parameters are classified with the help of support vector machine.Model of healthy and faulty induction motor are taken
IJOART
International Journal of Advancements in Research & Technology, Volume 2, Issue 7, July-2013
ISSN 2278-7763
as reference for training the Support Vector Machine.Envelope
analysis not only enhances the fault parameters, remaining
power frequency leakage if any is also removed.
Wavelets are functions that can be used to decompose signals, similar to how to use complex sinusoids in a Fourier
Transform to decompose signals. The wavelet transform computes the inner products of analyzed signals and a family of
wavelets. Wavelets are more suitable for analyzing nonstationary or transient signals, than time domain or frequency
domain analysis. DWT is well-suited for multi-resolution
analysis. The DWT decomposes high frequency components
of a signal with fine time resolution but coarse frequency resolution and decomposes low frequency components with fine
frequency resolution but coarse time resolution .DWT based
multi-resolution analysis help better understand a signal and
is useful in feature extraction application such as fault detection. Multi-resolution analysis also can help in removing unwanted components in the signal, such as noise. The family of
Daubechies wavelets was chosen as the basis functions for the
decomposition.
261
TABLE II
CLASSIFICATION RESULTS USING SVM
TABLEIII
4 RESULTS
Using d and q variables in a synchronously rotating reference frame, a generalized dynamic model of an induction motor is developed. A mathematical model of the fault is obtained and is incorporated with the d-q model. A Support Vector Machine fault prediction is trained with the help of parameters obtained from healthy and faulty simulink models.
IJOART
TABLE I
CLASSIFICATION RESULTS USING NN
Copyright © 2013 SciResPub.
DWT-ENVELOPE ANALYSIS RESULTS
Comparison between ANN classification and SVM classi-
IJOART
International Journal of Advancements in Research & Technology, Volume 2, Issue 7, July-2013
ISSN 2278-7763
262
fication is carried out and is shown in table I and table II. In
both cases healthy and faulty models are considered. The table
I shows ANN classification is good for low value of rotor resistance and give wrong output for higher values. But SVM
classification is good for higher values of rotor resistance and
gives wrong output for lower values. In this paper provide
accurate result for both higher and lower rotor resistances
shown in table III.
5 CONCLUSION
In this present paper dynamic model of induction motor
has been developed using d and q variables in a synchronously rotating frame. The broken rotor bar fault is detected using
wavelet transform and envelope analysis. Support Vector Machine is used to determine whether induction motor is healthy
or not.
REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
B. ArunaKumari, K. Naga Sujatha, K. Vaisakh, Dept. of Electrical Engineering, “Assessment Of Stresses On Induction Motor Under Different Fault
Conditions”, Journal of Theoretical and Applied Information Technology,
Vol.50, 2009.
Y.amuna. K. Moorthy, Pournami S. Chandran, Rishidas S. Asst. Professor,
Dept of Electronics & Communication College of Engineering, Trivandrum
“Motor Current Signature Analysis by Multi-resolution Methods using Support Vector Machine”, 978-1-4244-9477-4/11/$26.00 ©2011 IEEE 096
H. Douglas, P. Pillay, A. K. Ziarani, “A new algorithm for transient motor
current signature analysis using wavelets”University of Cape Town Department of Electrical Engineering Rondebosch 7701 Cape Town, South Africa.
B. Ayhan, M. Y. Chow, and M. H. Song, “Multiple signature processingbased
fault detection schemes for broken rotor bar in induction motors”, IEEE Trans.
Energy Convers., vol. 20, no. 2, pp. 336343, Jun. 2005.
S.S.Mulukutla, E.M.Gulachenski, “A critical survey of considerations in maintaining process continuity during voltage dips while protecting motors with
reclosing and bustransferpractices,”IEEE, 1991.
J. Lee, P. Pillay And R. G. Harley, “D,Q Reference Frames for the Simulation
of Induction Motors”, Department of Electrical Engineering, University of Natal,Electric Power Systems Research, Regular Papers, 8 (1984/85).
Cusido, L. Romeral, A. Garcia, J.A. Rosero , J.A. Ortega, “Fault detection in
Induction Machines by using Continuous and Discrete Wavelet Decomposition” MCIA research group published in Power Electronics and Applications,
2007 European Conference on 2-5 Sept. 2007.
BurakOzpineci, M. Leon, Tolbert, “Simulink Implementation of Induction
Machine Model- A Modular Approach”, Department of Electrical and Computer Engineering the University of Tennessee IEEE Transactions on Power
Electronics 2003.
KhalafSalloumGaeid and Hew Wooi Ping, “Wavelet Fault Diagnosis of Induction Motor” University of Malaya MalaysiaMATLAB for Engineers –
Applications in Control, Electrical Engineering, ITand Robotics.
S.K. Ahamed1,* Arghya Sarkar2, M.Mitra3 and S. Sengupta4 “Broken Rotor
Bar Fault Detection of Induction Motor through Wavelet Transform and Envelope Analysis” Published in Computing, Electronics and Electrical Technologies (ICCEET), 2012 International Conference
IJOART
Copyright © 2013 SciResPub.
IJOART