CONDITION MONITORING OF INDUCTION MOTOR USING
VIBRATION ANAYLYSIS”
FINAL DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT
FOR
THE AWARD OF THE DEGREE OF
Master of Technology (M.Tech)
In
Mine Electrical Engineering
BY
RAHUL
KUMAR
17MT00xxxx
UNDER THE GUIDENCE OF
Dr. Dr. Ananda Shankar Hati
Assistant Professor
Department of Mining Machinery Engineering
Department
of Mining Machinery Engineering
INDIAN INSTITUTE OF TECHNOLOGY
(INDIAN SCHOOL OF MINES)
DHANBAD - 826004
CERTIFICATE
This is to certify that Mr. RAHUL KUMAR (17MT00xxxx), a student of M.Tech. (Mine Electrical
Engineering), Department Of Mining Machinery Engineering, Indian Institute of
Technology (Indian School of Mines), Dhanbad has worked under my guidance and
completed his Dissertation entitled "CONDTION MONITORING OF INDUCTION MOTOR USING VIBRATION
ANALYSIS" in
partial fulfillment of the requirement for award of degree of M.Tech. in
Department of mining machinery from Indian Institute of Technology (Indian
School of Mines), Dhanbad.
This work has not been submitted for any other
degree, award, or distinction elsewhere to the best of my knowledge and belief. He is solely responsible for the technical data and
information provided in this work.
Dr. xxxxxxxx
Assistant Professor and Guide
Department of MME
Indian
Institute of Technology
(Indian School of Mines), Dhanbad.
FORWARDED BY:
Head of
the Department,
Department
of MME
Indian
Institute of Technology
(Indian
School of Mines), Dhanbad
DECLARATION
The Dissertation titled “CONDTION
MONITORING OF INDUCTION MOTOR USING VIBRATION ANALYSIS” is a presentation of my original research work and is not copied
or reproduced or imitated from any other person's published or unpublished
work. Wherever contributions of others are involved, every effort is made to
indicate this clearly, with due reference to the literature, and
acknowledgement of collaborative research and discussions, as may be
applicable. Every effort is made to give proper citation to the published/unpublished
work of others, if it is referred to in the Dissertation.
To
eliminate the scope of academic misconduct and
plagiarism, I declare that I have read and understood the UGC (Promotion of Academic Integrity and
Prevention of Plagiarism in Higher Educational Institutions) Regulations, 2018.
These Regulations have been notified in the Official Gazette of India on 31st
July, 2018.
I
confirm that this Dissertation has been checked with the online plagiarism
detector tool Turnitin (http:///www.turnitin.com) provided by IIT (ISM) Dhanbad
and a copy of the summary report/report, showing Similarities in content and
its potential source (if any), generated online through Turnitin is enclosed at
the end of the Dissertation. I hereby declare that the Dissertation shows less
than 10% similarity as per the report generated by Turnitin and meets the
standards as per MHRD/UGC Regulations and rules of the Institute regarding
plagiarism.
I further state that no part of the Dissertation and its data will
be published without the consent of my guide. I also confirm that this
Dissertation work, carried out under the guidance of Dr. Ananda Shankar Hati, Assistant
Professor, Department of Mining Machinery Engineering, has not been previously submitted for assessment for the
purpose of award of a Degree either at IIT (ISM) Dhanbad or elsewhere to the
best of my knowledge and belief.
RAHUL KUMAR
M.Tech. (Mine Electrical
Engineering)
Department of Mining
Machinery Engineering
Admission No.: 17MT0xxxxx
Forwarded
by
(Dr.
Ananda Shankar Hati)
Assistant
Professor
CERTIFICATE
ACKNOWLEDGEMENT…………………………………………………………..……….03
DECLARATION……………………………………………………………………………..04
ABSTRACT…………………………………………………………………………………..05
Chapter 1
1. INTRODUCTION…………………………….……………….…………………………11
1.1) Overview…………………………………………………………….........11
1.2) Objective……………………………………………………………….....13
1.3) Thesis scope……………………………………………………………....13
Chapter 2
2. LITERATURE REVIEW ………………………………………………………….…..14
2.1)
Bearing faults………………………………………………………….….14
2.2) Unbalanced Magnetic Force (UMF) ……………………………………..15
2.3) Bearing problem due to electrical
erosion………………………………..15
2.4) Vibration ranges of machines according to ISO 2372……………………16
Chapter 3
3. FAULTS AND ITS CAUSES…………………………………………………………...18
3.1) Main types of faults ……………………………………………………18
3.2) Major causes of faults………………………………………………….19
Chapter 4
4. TYPES OF CONDITION
MONITORING……………………………………………20
4.1)
RUN TO BREAK …………………………………………………...…20
4.2)
PREVENTIVE
MAINTENANCE …………………………………….21
4.3)
CONDITION BASED
MAINTANANCE………………………….….23
4.3.1) Lubricant analysis………………….………………………..…24
4.3.2)
Thermal Monitoring……………………………………...……24
4.3.3) Partial
Discharge……………………………………………....25
4.3.4) Wavelet Analysis……………………………………………...25
4.3.5)
Vibration analysis…………………………………….…….…25 4.4) Advantage of
condition monitoring………………..…..……………………26
4.5) Advantage of Vibration
Analysis……………………………………………27
4.6) Disadvantage Vibration
Analysis……………………………………………27
4.7) Condition Monitoring Process……………………………………………….28
Chapter 5
5. TRANSDUCERS AND SIGNAL PROCESSING
5.1) Types Vibration Transducers………………………………………..…….29
5.1.1) Proximity Probes……………………………………………..…….29
5.1.2) Velocity
Transducers……………………………………………….29
5.1.3) Accelerometers……………………………………………………...29
5.1.4) Laser Vibrometers…………………………………………………..29
5.1.5)
ADXL326 Three
Axis Accelerometer……………………………...30
5.2) Signals Generated
by Rotating Machines…………………………………30
5.2.1) Signals
generated…………………………………………………………..30
5.2.2) Bearing fault characteristic frequencies………………………….….31
5.3) Basic Signal
Processing Techniques……………………………………....31
5.3.1) Fourier Series…………………………………………………….....32
5.3.2) Fast Fourier Transform……………………………………………..32
5.3.3) Convolution………………………………………………………...32
5.3.4) Lab view
application……………………………………………….33
CHAPTER 6
6. EXPERIMENT AND RESULT………………………………………………………34
6.1) Experiment setup…………………………………………………………….34
6.2) Observation Data………………………………………………………….....35
6.3) Graph………………………………………………………………………...42
Chapter 7
Result &
Discussion……………………………………………………………46
7.1) Result…………………………………………………………………………………..46
7.2) CONCLUSION…………………………………………………………………….......47
7.3) FUTURE
PROSPECTS……………………………………………………………..…47
REFERENCES……………………………………………………………………………….48
List
of Figure
S.no.
Title Page
No.
1. Faults categories
in Motor…………………………………………..13
2. Condition
monitoring process………………………………………28
3. Specification of bearing……………………………………………..35
4. Bearing mounting technology………………………………………..36
5. Experimental setup…………………………..………………………50
6. sensor mounted in motor……………………………………….……40
7. DAQ…………………………………………………………………41
8. Faulty bearing used for experiment…………………………………41
9. Rotor removed from
motor…………………………………………..42
10. Faulty bearing fitted in rotor shaft……………………………………42
11. Vibration magnitude in healthy case………………………………….43
12. Vibration magnitude
in faulty case……………………………….…..43
13. Vibration spectrum of
healthy bearing……………………………….44
14. Vibration spectrum of
faulty bearing………………………..……….44
15. Comparison between
healthy and faulty case………………..………45
ABBRIVIATIONS
IM
- Induction Motor
PD
- Partial Discharge
BRBs – Broken Rotor Bars
BPFI - Ball Pass Frequency of
Inner Race
BPFO - Ball Pass Frequency of
Outer Race
BSF - Ball Spin Frequency
FTF- Cage defect frequency
UMP - Unbalanced Magnetic Pull
CM- Condition Monitoring
RBE- Rolling bearing element
DAQ Card – Data Acquisition Card
DFT – Discrete Fourier Transform
DTFSC – Discrete-Time Fourier Series
Coefficients DQ – Direct-Quadrature
FFT – Fast Fourier Transform
FS – Fourier Series
FSC - Fourier Series Coefficients
IPM – Intelligent Power Module
LR – Locked Rotor
NEMA – National Electrical Manufacturers
Association
PCB – Printed Circuit Board
PWM – Pulse Width Modulation
CHAPTER 01
----------------------------------------------------------------------------------------------------
INTRODUCTION
1.1
Overview
Induction motors are the most widely used machine in
any modern industry. Induction machines consumes up to 70 percent of total
energy consumed in an industry .Because of these reasons numerous studies and
research work have been carried out for decades, to enhance the performance and
reliability of induction motors . In industries where induction motors plays
vital role, an reliable and effective condition monitoring scheme is most
desired to predict any incipient fault in the induction motor and also for
their efficient utilization on the workplace. The condition monitoring can be
used to rule out the predictive maintenance which sometimes results in
unnecessary shutdown of machine and unintended fault due to unwanted
maintenance. In large and costly machine the condition monitoring technique
becomes more critical for timely identification of any incipient fault in the
motor components.
As we know, in a typical induction motor there is a
stationary part known as stator and also there is a rotating part known as
rotor, a supporting metal rod which supports the rotor known as shaft, bearing
for smooth rotation. Induction machine components may get damaged while in
operation due to numerous reasons like ageing, improper lubrication,
misalignment, excessive electrical and mechanical stresses. Investigation have
been shown that the bearing fault accounts for approximately 76 percent of
total faults in small and medium rating motors while for large machines about
42 percent of faults are due to the problem in the bearing. Also there are
other defects like broken rotor bars that accounts for about 13 percent of
motor defects, stator faults(inter turn short circuit) , shaft misalignment and
single phasing are also responsible for the motor failures.
Induction motor performs from simple to
critical tasks in an modern industry. Failures in the machines results in
increased downtime and production loss. Replacing the faulty parts of the motor
increases the total monetary loss, also these faults can be catastrophic and it
is not acceptable in any industrial process .the most typical failures in the
induction motor have been found using fault surveys and have been categorized
according to location or component where they occur, the major faults are
bearing related (42%), stator winding faults (36%) and others (9%). The
application of condition monitoring technique for the electrical motors is
growing very rapidly because more reliability and less production loss is
desired. these days, online condition
monitoring is increasing in order to rule out any unwanted fault and increased
maintenance costs for the motor.
In last few decades the condition motor of electrical machines has
received immense attention. Many papers related to condition monitoring written
till now. Due to extensive use of induction motor online condition monitoring
is a must. Earlier human expertise is used to monitor electrical machines condition.
But nowadays steps are being taken to minimize the dependence on human experts
and more emphasis is given on computerized online condition monitoring .in our
work we have used the researches of many years experiences in this particular
area of vibration analysis on electrical motors.
Fig 15: Comparison between healthy and
faulty case
|
SPEED OF MOTOR (rpm) |
Rotational frequency(Hz) |
Theoretical computed fault frequency (Hz) |
Experimental obtained fault frequency (Hz) |
||||||
|
1480 |
24.66 |
Fcage |
Fouter |
Finner |
Fball |
Fcage |
Fout |
Finner |
Fball |
|
9.84 |
88.8 |
133.2 |
118.08 |
-- |
85 |
130 |
-- |
||
Table 4: Comparison of theoretical and experimental values
CHAPTER 07
RESULT & DISCUSSION
==========================================================
7.1 RESULT
Multiple fault
has been observed while analysis the data. The FFT of the data has been
obtained and plotted to find the frequency spectrum. Through the vibration
frequency spectrum, we got two faults in our bearing that is fault in inner
race and outer race. From the above table we can compare it with the
theoretical computed fault frequency with the experimental obtained fault
frequency. The peak overshoot in the spectrum confirms our result. The fault
frequency for inner race is 130 Hz and for the outer race it is 85 Hz which is
nearly close to the theoretical value we have calculated from the given
formulas in (5.2.2)
7.2 CONCLUSION
The present work deals with the faults related to motor bearing. Multiple
faults in bearing can be diagnosed with the help of MEMS accelerometer
effectively. In this paper a healthy bearing vibration spectrum is taken and it
has been compared with the faulty bearing vibration spectrum which is obtained
by replacing the healthy bearing from the rotor with the faulty one. After
comparing the two data we found the two faults in the bearing that is the bearing
is having fault in its inner and outer races.
So we can conclude that the vibration signal spectrum analysis
shows the overall health of the machine components. By monitoring a vibration,
we can analyses the life of the machines. Vibration analysis is helpful for maintenance
of the machines before it damages completely. Though in this report we have
detected bearing fault but can also be used to detect other faults (broken
rotor bar, air gap eccentricity) for the Induction Motor.
7.3 FUTURE
PROSPECTS
Though the vibration
analysis is used for the monitoring of ball bearing fault detection, in future
work should be done to verify this method for other bearing specifications and type.
Works should be done to detect faults of very low level which cannot be
depicted artificially but they naturally occur in the industrial conditions.
Most of the existing researches have been focusing on the detection of rolling
ball bearings failures but not on sleeve bearing. The sleeve bearings require
addition work and analysis.
References:
[1] M. E. H. Benbouzid,
"A review of the induction motor signature analysis as a means of
detecting faults", IEEE Trans. Ind. Electron., Vol. 47, n. 5, pp. 984-993,
October 2000.
[2] A. H. Bonnett and G. C.
Soukup, "Cause and analysis of stator faults and rotor in three-phase
squirrel cage asynchronous motors", IEEE Trans. Ind. Appl., Vol. 28, n. 4,
pp. 921-937, July / August. 1992
[3] Mikhail Tsypkin,
"Monitoring the condition of the induction motor: vibration analysis
technique - a
Practical implementation
", International Conference on Electric Machines and IEEE Drives
(IEMDC) 2011, 15-18 May.
[4] Detection of broken broken
bars with induction motor by vibration analysis - A case study
Ž. Kanović, D. Matić, Z.
Jeličić, M. Rapaić, B. Jakovljević, M. Kapetina
[5] a new approach for
detecting broken broken bars using the vibration spectrum Alireza Sadoughi,
Mohammad Ebrahimi, Esmaeil Rezaei
[6] W. Wang and O. A. Jianu,
"An Intelligent Detection Unit for Measurement and Vibration
Monitoring", IEEE / ASME Trans. Mechatronics, vol. 15, no. 1
pp. 70-78, February 2010
[7] I. Y. Onel and M. E. H.
Benbouzid, "Detection and diagnosis of induction bearing failures: a
comparative study on Park and Concordia transformation approaches", IEEE /
ASME Trans. Mechatronics, vol. 13, no. 2, pp. 257-262, April 2008.
[8] J. Zarei and J. Poshtan,
"The vector approach of an advanced park for bearing failure
detection", Tribol. Int., Vol. 42, n. 2, pp. 213-219,
February 2009
[9] Modeling of a control
based on condition monitoring using mat-lab / simulink for rotating electrical
machines
Arunav Kabiraaj Thakur1, T.M.
Joardar2, Pranab K Dan3
[10] Fabio Immovili, Claudio
Bianchini, Marco Coconcelli, Alberto Bellini, Member, IEEE and Riccardo Rubini [11] Models for Bearing Damage Detection in Induction Motors Using
Stator Current Monitoring Martin Blödt, Member, IEEE, Pierre Granjon,
Bertrand Raison, Member, IEEE, and Gilles Rostaing
[12] Multisensor Wireless System for Eccentricity and Bearing Fault
Detection in Induction Motors
Ehsan
Tarkes Esfhani ; Shaocheng Wang and V. Sundararajan
[13] An Overview of Bearing Vibration Analysis
dararajan
Dr. S.J. Lacey
[14] A review of induction motors signature analysis
as a medium for faults detection
Author: M. El Hachemi Benbozid
[15] An
amplitude modulation detector for fault diagnosis in rolling element bearings
Author:
J.R. Stack ; R.G. Harley and T.G. Habetler
[16] An
Advanced Park's Vectors Approach for Bearing Fault Detection Author: Jafar
Zarei and Javad Poshtan
[17] Detection
of Localized Bearing Faults in Induction Machines by Spectral Kurtosis and
Envelope Analysis of Stator Current
Author: Valéria C. M. N. Leite ; Jonas Guedes Borges da Silva ; Giscard
Francimeire Cintra Veloso ; Luiz Eduardo
[18] A
Survey of Condition Monitoring and Protection Methods for Medium-Voltage
Induction Motors Author(s) Pinjia Zhang
; Yi Du ; Thomas G. Habetler ; Bin Lu
[19] A
comparison of some condition monitoring techniques for the detection of defect
in induction motor ball bearings
Author
links open overlay panelN.Tandon, G.S.Yadava and K.M.Ramakrishna
[20] Models
for Bearing Damage Detection in Induction Motors Using Stator Current
Monitoring Martin Blödt, Member, IEEE, Pierre Granjon, Bertrand Raison, Member,
IEEE, and Gilles Rostaing
