International conference on Signal Processing, Communication, Power and Embedded System (SCOPES)-2016

Condition Monitoring of Induction Motors

: - A Review
Rudra Narayan Dash, Sangeeta Sahu, Bidyadhar Subudhi
Chinmoy Ku. Panigrahi Department of Electrical Engineering
School of Electrical Engineering NIT Rourkela
KIIT University Odisha
Bhubaneswar, Odisha
rudra.dashfel@kiit.ac.in

Abstract— The electrical motor condition monitoring is a Both the primary and secondary kinds of faults are
growing technology to detect the fault of an induction motor. It subjected in an induction machine. The different sources of
detects the unexpected faults of a critical system. Definite fault in an induction motor are as shown in figure 1 (a). The
harmonic signals of the line current are located by a popular classification of different internal and external faults of an
method known as motor current signature analysis. Different induction machine depicts in Fig. 1(b) and Fig. 1(c). The total
faults of an induction motor such as rotor, stator, bearing, fault in an induction motor is roughly classified by its internal
vibration, air gap eccentricity and their different diagnosis or external condition. The fault may be classified as
techniques are also explored. In fact, the actual fault detection by mechanical or electrical faults according to its origin.
using the human involvement is widely replaced by the According to the location a fault may be classified as rotor
automated technology, namely fuzzy-logic-based systems, genetic
fault [1] or stator fault. The faults in an induction machine can
algorithm, neural networks, wavelet technique, Vienna
monitoring etc. It is truly evident that the scope of this area is
be broadly classified as rotor faults, stator faults, air gap
vast. Hence, acknowledging the need for future research, this eccentricity fault, mechanical vibration fault, bearing fault etc.
review paper presents a bird’s eye view on different types of
faults and their diagnostics’ schemes.

Keywords— Condition monitoring, Induction Motors, fault

diagnosis, review.

I. INTRODUCTION
The fault diagnosis and protection of electrical machines is
an old concept. Initially, the producers and operators of
electrical machines depended on simple and uncomplicated
protection such as over current, overvoltage, earth-fault, etc. to
ensure safe and reliable operation. Nevertheless, the work
performance of the machines grew increasingly complicated, Fig.1 (b) Schemetic diagram of the Internal Faults
fault diagnosis became very essential. Currently, it has
become very essential to diagnose faults at their very inception
else it may lead to unscheduled machine downtime which in
turn may lead to heavy financial
losses.

Fig.1 (c) Schemetic diagram of the External Faults

Fig.1 (a) Sources of Machine Faults

978-1-5090-4620-1/16/$31.00 ©2016 IEEE

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International conference on Signal Processing, Communication, Power and Embedded System (SCOPES)-2016

II. VARIOUS TYPES OF FAULTS IN INDUCTION a) Frame: includes vibration, circulating currents, earth
MACHINE faults and loss of coolants
Extreme efforts have been taken to diagnose the Induction b) Lamination: includes core slackening and core hot spot
machine fault. Subject to the region of fault occurrence,
c) Stator windings fault: includes end winding portion
induction motor faults are primarily put under the following
(fretting of insulation, turn-to-turn faults, local damage to
five types. insulation, discharge erosion of insulation, oil or dirt, damage
to connectors, contamination of insulation by moisture,
The total induction machine faults may be classified as displacement of conductors, cracking of insulation and so on)
follows: and slot portion which includes displacement of conductors,
insulation fretting.
stator faults due to the abnormal stator windings
connection and short circuiting or opening of a stator phase
C. Rotor Faults
winding;
Rotor faults are electrical failures relating to a bar defect or
rotor fault due to rotor field winding short circuiting or bar breakage or mechanical failures such as bearing failure. In
broken rotor bar or rotor end-rings cracked; large motors, during start-up transient operations the bar
air-gap irregularities - static and/or dynamic defect develops from thermal stresses, hot spots, or fatigue
stresses. Torque is changed notably by a broken bar and
dynamic eccentricity similar to bent shaft which can result becomes harmful to the steady operation and safety of electric
in a rub between the rotor and stator machines. Air gap eccentricity is another type of rotor fault in
gearbox and bearing faults induction motors which is a commonly related to an array of
mechanical problems such as shaft misalignment or load
From the above faults, the stator faults, bearing faults, unbalance. Long-term load unbalance can impact symmetry of
rotor broken bar faults and the eccentricity related faults are air gap, damage the bearings and the bearing housing. Shaft
the most dangerous faults and thus more attention is required. misalignment between a shaft and coupled load can be
vertical, horizontal or radial. With these misalignments, due to
A. Bearing Faults constant radial force, the rotor will be distorted from its
Usually, a bearing with rolling-element comprises of two original position.
concentric rings which is a set of rollers spin or balls in the
raceways between inner ring and outer ring. Bearing faults D. Eccentricity Faults
may be classified as “distributed” or “local” [1]. Distributed Air gap eccentricity is the result of uneven air gap between
faults encompass waviness, rough surface, off-size rolling rotor and stator of induction motor. Its two types are the static
elements, and misaligned races. Localized faults encompass air-gap eccentricity and the dynamic air-gap eccentricity.
pits, spalls and cracks on the rolling surfaces. When a running Mixed eccentricity is a combination of static and dynamic air-
roller passes over the fault surface, it generates a streak of gap eccentricity and inclined air-gap eccentricity is the axial
vibration impacts at that very instant. The period and non uniformity of air gap. The minimal radial air-gap length is
amplitude of the impact are calculated by the anomaly’s fixed in space for static air gap eccentricity while the rotor’s
position, speed and bearing dimension. Mechanical vibrations center and the center of rotation never coincide for dynamic
are at the rotational speed of every component and are eccentricity. While commissioning of induction motor, a
produced by the flawed bearings. The characteristic faulty positioning of the stator or rotor may result in static
frequencies associated to the raceways and the balls or rollers eccentricity. Dynamic eccentricity is due to bearing wear and
are determined by the rotational speed and bearing dimension tear, bent in shaft, or mechanical resonances at critical speeds.
of the machine and it also determines the bearing condition E. Vibration Faults
using mechanical vibration analysis techniques.
The oscillation in the mechanical parts of the motors is
known as vibrations and can be observed in the external
system attached with the machine shaft. A unique machine
related frequency spectrum is generated for a normal motor
B. Stator Faults which changes with each motor fault and can be compared
Most induction motor stator faults is subjected to several with the reference spectrum to perform fault detection and
stressful operating conditions like environmental, electrical, diagnosis.
thermal, and mechanical. Stator winding faults namely open
circuit, turn-to-turn, phase-to-phase, coil-to-coil, and coil-to- III. TYPES OF FAULT AND FAULT DETECTION
ground, are the most frequent and potentially disastrous faults. TECHNIQUE
If timely diagnosis is not done, then it may ultimately cause
Till date, various fault detection techniques have been
terrible motor failure. The three main divisions of stator faults
developed in diagnosing the fault-related signals. These
are the following.
methods include the following fields of science and
technology:

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1) electromagnetic field monitoring, coils wound around five phase motors can performed with phase open circuit faults
motor shafts (axial flux-related detection) and search coils; and discreet design of machine can reduce the detrimental
2) infrared recognition; effects of ripple in torque. If the fault is detected and the field
is decreased by control of id, a vector controlled machine can
3) temperature measurements; operate successfully for a shorter period with shorted
4) chemical analysis; windings.

5) radio-frequency (RF) emissions monitoring;

A latest model is presented specifically for squirrel-cage
6) noise and vibration monitoring; induction machines in which the stator and rotor faults are
7) acoustic noise measurements; identified and detected [7]. First, the interturn short-circuit
winding have been modelled by a short-circuit element and
8) motor-current signature analysis (MCSA); then a new equivalent Park’s rotor resistance has been
suggested to allow the reduction of the of rotor bars count in
9) model, artificial intelligence, and neural-network-based faulty situation. Parameter estimation method is used for fault
techniques.
detection and localization. The stator fault of a three phase
Table 1. Comparison of various fault detection techniques electrical machine is diagnosed by a fully automatic on-line
Fault Detection Detected Faults system using an unsupervised Hebbian- based neural network-
Techniques based algorithm [8]. From the stator current alpha-beta
MCSA Bearing, Rotor, Stator components, unsupervised Hebbian-based neural network
and Vibration Faults derives the principal components (main directions) of the
induction motor stator currents. With the obtained
Park’s Transform Bearing and Stator Faults
eigenvectors, severity index is calculated by projecting the
Artificial Neural Networks Bearing and Rotor Faults
stator currents into the new eigenvector state space. The
Wavelet Analysis Bearing, Rotor, Stator directions of eigenvectors in the neural network indicate the
and Vibration Faults faulted phase and the relation between the eigenvector space
Finite Element Method Rotor, Stator and components shows if the motor is normal or faulted, and the
Vibration Faults extend of the fault if it is faulted. Subhasis Nandi et al.
Vibration Testing and Bearing and Vibration discussed a novel stator inter-turn fault detection scheme in
Analysis Faults which immediately after switching off an induction motor
Concordia Transform Bearing Faults certain harmonics are present at the terminal voltages [9].
External Magnetic Field Rotor Faults
Analysis For detecting stator winding faults in three-phase synchronous
Multiple Reference Frames Eccentricity and asynchronous motors, a new method based on the spectral
Theory analysis of the current Park’s Vector modulus is introduced
Power Decomposition Stator Faults [10]. For induction machines, Tian Han et al. has introduced
Technique an online fault detection system with the amalgamation of
KU Transformation Stator Faults discrete wavelet transform (DWT), genetic algorithm (GA),
Theory feature extraction, and neural network (ANN) techniques [11].
Zero Crossing Time Stator Faults The stator current signal features are extracted from electric
Method motor by means of discrete wavelet transform and feature
Modal Analysis Method Vibration Faults extraction techniques.
Xu Boqiang Li Heming Sun Liling [12] discussed the
methods to extract the inter-turn short circuit fault signals in
A. Stator Fault: the induction motor stator windings. It shows that as a fault
Author F. Duan and R. Zivanovic presents a unique feature signal, preference is given to the phase difference of
parameter estimation technique for the detection of stator the stator three-phase winding current. Moreover, an
winding short circuit fault condition in induction motors [4]. innovative feature signal of the inter-turn short circuit fault, in
Faults in induction motor will disturb electrical balance and other words, the derivation of phase difference of the cross-
lead to changes of some electrical parameters, called fault correlation of the stator winding voltage and current.
parameters. Hence, by monitoring these fault parameters, the Likewise , the stray flux has been used to detect the stator
motor faults can be detected. Stator fault detection is achieved fault in a three-phase squirrel-cage induction motor [13].
by manipulating the fault parameters from voltages and Motor Current Signature Analysis (MCSA) technology can
currents readings at power supply terminal of the machine [5]. be applied to monitoring an induction motor. This Method is
Both the local (gradient descent and nonlinear least squares) widely used in the heavy industrial machinery as it provides a
and the global (pattern search) search methods are applied in selective, highly sensitive, and cost-effective for online
the parameter estimation method. monitoring. This method has been also used to improve the
The ability of vector controlled induction-motor drives is to motor bearing fault assessment during plant operation. The
remain operating even if the stator winding has various Motor Current Signature Analysis (MCSA) technology can be
numbers of shorted turns in one coil [6]. Smooth operation of used in addition with the motor circuit analysis technique to

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provide the complete health monitoring of the motor circuit. method. A novel approach is used to analyze the space vector
The result of MCSA provides a complete view of motor of voltages which is induced in the stator winding after
system health. Monia Ben Khader Bouzid et al. have been disconnection of the supply, to identify the rotor broken bars
proposed the motor current signature analysis (MCSA) with faults of a squirrel-cage induction motor. [27].
advanced signal-and-data-processing algorithms technique for
The space vector of the voltages induced in stator windings
the online diagnosis of an induction motor [14].
of an induction motor have been presented by MUSIC and
The stator inter-turn short circuit fault of an induction STMUSIC algorithms. The results obtained have been
motor can be locate and diagnose automatically by using the compared by using the standard FFT and STFFT algorithms.
neural network approach. In this case a feedforward The rotor asymmetries fault in an induction motor can be
multilayer-perceptron neural network (NN) trained by back diagnosed using the stator current by the application of the
propagation method to locate and detect the fault of an Discrete Wavelet Transform (DWT) [28]. The approximation
induction motor [15]. An impedance identification technique signal of the stator startup current reproduces the evolution of
was proposed to locate and detect the stator inter - turn fault in the left sideband harmonic during the startup process.
case of a multiple-motor drive system [16]. Fast and reliable Comparing the approximation signal with original
fault detection is achieved by utilizing the characteristics of characteristic waveform of the left sideband harmonic of the
current regulators in the motor controller. The stator inter – startup current is a reliable evidence of a rotor fault. The
turn fault detection by monitoring ΔZnp of an induction motor continuous short time fourier transform can be used to detect
which is fed by closed-loop motor drives is given. The above the bar breakage in the induction motor with rotor axial ducts
method is different from all the existing methods in such a and outer bar breakages of a double cage induction motor
way that it has the advantage of taking the current regulating [29]. Furthermore, unlike the DWT, the STFT has been
effect of the motor controller. proved for providing an accurate extraction of low-frequency
fault components, higher-order fault harmonics and
B. Rotor Fault: differentiation between fault related coexisting components.
Broken rotor bars fault using wavelet analysis can be In line connected induction motor the broken rotor bar can be
detected by decomposition of the transient current [17]. As for detected by complex wavelet by using the stator currents
as the fault detection performance is consider, greater during startup transients [30]. The fault related parameter in an
accuracy is achieved by multiple signature processing rather induction motor stator current vector can be detected by this
than single signature processing [18] and [21]. In addition, wavelets. The stator current vector also indicates the rotor bars
multiple signature processing has two schemes for fault data damage.
detection. One is monolith and the other is partition. The
finite element analysis which is useful in determining the C. Bearing Fault
broken bar effects demonstrate the performance of the motor Depending on the type of fault signatures that are
under fault condition [19]. As the number of broken bars produced, bearing faults are categorised as either single-point
increases, the fault degrades the steady-state torque-slip defects or generalized roughness [31]. The benefit of this
frequency characteristic progressively. The load torque- categorization is of two types. Firstly it overlooked the
induced harmonic coincides with rotor fault-induced generalized roughness fault. The most of the condition
harmonics when the position of the rotor varies the load monitoring schemes of the bearing fault in the literature focus
synchronously [20]. The state of actual machine can be on to detect the single point defects. While to detect the both
sensed using the real-time space-phasor models. The Vienna faults that is generalized roughness and single point defects of
Monitoring Method compares online a voltage model output the bearing of an induction motor. Secondly in a group of
with a current model and monitors the variation in a rotor faults, it gives the clear understanding to detect the different
fixed reference frame [22] and [23]. The traditional VMM faults. This provides improved insight into how bearing
processes measured voltages, currents, and a rotor position condition monitoring schemes should be designed and applied.
signal. Using the stator current the rolling element bearing fault of an
induction motors can be detected [32]. The related to air gap
A novel method for the diagnosis of an induction motor
length variations and change in load torque has been proposed
has been tested which is based on the global fault index by using a new fault model.
method. The above method which is used the line current and
instantaneous power signal gives the significant results to There is another method known as an ANFIS (adaptive
detect the rotor broken bars faults [24]. A comparison between neural fuzzy inference systems) approach to detect the two
the line current and instantaneous power signal gives the types of incipient faults, i.e., bearing faults and inter-turn short
detection of broken bar fault, if the global fault index of the circuit faults of a single phase induction motor [33]. Firstly,
instantaneous power with low frequency is used. A corrosion using the motor intake current and rotor speed the
model has been proposed to simulate the rotor bar faults of an performance of an induction motor can be tested. Later, the
induction motor [25]. The corrosion model of a rotor bar, temperature of the motor winding, the noise of the motor and
which was assumed as a rotor-bar-in fault progress was the bearing temperature were added. Recently rolling bearing
derived by electromagnetic theory. Finite element method is fault condition is monitoring by using the frequency response
used to detect the rotor bar fault of a squirrel cage induction analysis [34].
motor [26]. For the different fault condition the current
amplitude is different and are calculated by the proposed

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Use of this detector only requires machine vibration from IV. CONCLUSION
one sensor and knowledge of the bearing characteristic fault By doing the concise review of rotor, stator, eccentricity,
frequencies. vibration, and bearing faults and their different diagnosis
Motor current spectral analysis was applied for detecting techniques has been presented in this paper. It is concluded
the damage in induction motor rolling-element bearing [38]. from various literatures that the most preferred fault diagnosis
Vibration monitoring is performed to find the mechanical technique is MCSA. However, theoretical analysis and
bearing frequencies. It helps in detecting the presence of fault modelling of induction machine faults are also required to
in induction machine. The first step in detecting the bearing differentiate by using the frequency components from the
fault is to find the efficiency of current monitoring by other due to machine saturation, harmonics, etc. The different
correlating the vibration and the current frequency techniques for the detection of induction machine faults based
relationship. The author used machine vibration for detecting on fuzzy-logic, genetic algorithm, neural networks, wavelet
bearing inner race defect by developing a fault signature technique, Vienna monitoring etc. have also been discussed.
model and detection scheme [39]. The fault detection scheme
studies the vibration spectra of the machine with phase couple
side bands that occur at model predicted spacing. As
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