Abstract

Bearing failure in the heavy rotating machines results in shut down of many other machines and affects the overall cost and quality of the product. Condition monitoring of bearing systems acts as a preventive and corrective measure as it avoids breakdown and saves maintenance time and cost. This research paper proposes advanced strategies for early detection and analysis of taper rolling bearings. In view of this, mathematical model-based fault diagnosis and support vector machining (SVM) are proposed in this work. A mathematical model using dimension analysis by the matrix method (Dimension Analysis Method (DAMM)) and SVM is developed that can be used to predict the vibration characteristic of the rotor-bearing system. Types of defects are created using electrical discharge machining (EDM) and analyzed, and correlation is established between dependent and independent parameters. Experiments were performed to evaluate the rotor dynamic characteristic of healthy and unhealthy bearings. Experimental results are used to validate the model obtained by the DAMM and SVM. Experimental results showed that the vibration characteristic could be evaluated by using a theoretical model and SVM. Efforts have been made to extend the service life of the machines and the assembly lines and to improve their efficiency, so as to reduce bearing failure; what provides novelty to these efforts is the use of four machine learning techniques. Thus, an automatic online diagnosis of bearing faults has been made possible with the developed model based on DAMM and SVM.

References

References
1.
Li
,
B. W.
, and
Zhang
,
Y.
,
2011
, “
Supervised Locally Linear Embedding Projection for Machinery Fault Diagnosis
,”
Mech. Syst. Signal Process.
,
25
(
8
), pp.
3125
3134
.
2.
Tandon
,
N.
, and
Choudhury
,
A.
,
1997
, “
An Analytical Model for the Prediction of the Vibration Response of Rolling Element Bearings Due to Localized Defect
,”
J. Sound Vib.
,
205
(
3
), pp.
275
292
.
3.
Tandon
,
N.
, and
Choudhury
,
A.
,
1998
, “
A Theoretical Model to Predict Vibration Response of Rolling Bearings to Distributed Defects Under Radial Load
,”
ASME J. Vib. Acoust.
,
120
(
3
), pp.
214
220
.https://doi.org/10.1115/1.2893808
4.
McFadden
,
P. D.
, and
Smith
,
J. D.
,
1984
, “
Model for Vibration Produced by a Single Point Defect in a Rolling Element Bearing
,”
J. Sound Vib.
,
96
(
1
), pp.
69
82
.
5.
McFadden
,
P. D.
, and
Smith
,
J. D.
,
1985
, “
Vibration Produced by Multiple Point Defects in a Rolling Element Bearing
,”
J. Sound Vib.
,
98
(
2
), pp.
263
273
.
6.
Igarashi
,
T.
, and
Kato
,
J.
,
1985
, “
Studies on the Vibration and Sound of Defective Rolling Bearings. Third Report: Vibration of Ball Bearing With Multiple Defects
,”
Bull. JSME
,
28
(
237
), pp.
492
499
. https://doi.org/10.1299/jsme1958.28.492
7.
Choudhury
,
A.
, and
Tandon
,
N.
,
2006
, “
Vibration Response of Rolling Element Bearing in a Rotor Bearing System to a Local Defect Under Radial Load
,”
ASME J. Tribol.
,
128
(
2
), pp.
252
261
. https://doi.org/10.1299/jsme1958.28.492
8.
Patil
,
M. S.
,
Mathew
,
J.
,
Rajendrakumar
,
P. K.
, and
Desai
,
S.
,
2010
, “
A Theoretical Model to Predict the Effect of Localized Defect on Vibrations Associated With Ball Bearing
,”
Int. J. Mech. Sci.
,
52
(
9
), pp.
1193
1201
.
9.
Sopanen
,
J.
, and
Mikkola
,
A.
,
2003
, “
Dynamic Model of a Deep-Groove Ball Bearings Including Localized and Distributed Defects. Part 1: Theory
,”
Proc. Inst. Mech. Eng., Part K
,
217
(3), pp.
201
211
.
10.
Sopanen
,
J.
, and
Mikkola
,
A.
,
2003
, “
Dynamic Model of a Deep-Groove Ball Bearings Including Localized and Distributed Defects. Part 2: Implementation and Results
,”
Proc. Inst. Mech. Eng., Part K
,
217
(
3
), pp.
213
223
.
11.
Dick
,
P.
,
Carl
,
H.
,
Nader
,
S.
,
Alireza
,
M. A.
, and
Sarabjeet
,
S.
,
2015
, “
Analysis of Bearing Stiffness Variations Contact Forces and Vibrations in Radially Loaded Double Row Rolling Element Bearing With Raceway Defect
,”
Mech. Syst. Signal Process.
,
50–51
(
1
), pp.
139
160
.
12.
Tomovic
,
R.
,
Miltenovic
,
V.
,
Banic
,
M.
, and
Miltenovic
,
A.
,
2010
, “
Vibration Response of Rigid Rotor in Unloaded Rolling Element Bearing
,”
Int. J. Mech. Sci.
,
52
(
9
), pp.
1176
1185
. https://doi.org/10.1016/j.ijmecsci.2010.05.003
13.
Desavale
,
R. G.
,
Venkatachalam
,
R.
, and
Chavan
,
S. P.
,
2013
, “
Antifriction Bearings Damage Analysis Using Experimental Data Based Models
,”
ASME J. Tribol.
,
135
(
4
), p.
041105
. https://doi.org/10.1115/1.4024638
14.
Desavale
,
R. G.
,
Venkatachalam
,
R.
, and
Chavan
,
S. P.
,
2014
, “
Experimental and Numerical Studies on Spherical Roller Bearings Using Multivariable Regression Analysis
,”
ASME J. Vib. Acoust.
,
136
(
2
), p.
021022
. https://doi.org/https://doi.org/10.1115/1.4026433
15.
Desavale
,
R. G.
,
Kanai
,
R. A.
,
Chavan
,
S. P.
,
Venkatachalam
,
R.
, and
Jadhav
,
P. M.
,
2015
, “
Vibration Characteristics Diagnosis of Roller Bearing Using the New Empirical Model
,”
ASME J. Tribol.
,
138
(
1
), p.
011103
. https://doi.org/10.1115/1.4024638
16.
Desavale
,
R. G.
,
2019
, “
Dynamics Characteristic and Diagnosis of a Rotor-Bearing’s System Through a Dimensional Analysis Approach: An Experimental Study
,”
ASME J. Comput. Nonlinear Dyn.
,
14
(
2
), p.
014501
. https://doi.org/10.1115/1.4041828
17.
Kanai
,
R. A.
,
Desavale
,
R. G.
, and
Chavan
,
S. P.
,
2016
, “
Experimental-Based Fault Diagnosis of Rolling Bearings Using Artificial Neural Network
,”
ASME J. Tribol.
,
138
(
3
), p.
031103
. https://doi.org/10.1115/1.4032525
18.
Jamadar
,
I. M.
, and
Vakharia
,
D. P.
,
2016
, “
A Numerical Model for the Identification of the Structural Damages in Rolling Contact Bearings Using Matrix Method of Dimensional Analysis
,”
ASME J. Tribol.
,
138
(
2
), p.
021106
. https://doi.org/10.1115/1.4031989
19.
Jamadar
,
I. M.
, and
Vakharia
,
D. P.
,
2017
, “
A New Damage Diagnostic Approach for Deep Groove Ball Bearings Having Localized Surface Defect in the Raceways
,”
ASME J. Tribol.
,
139
(
6
), p.
061103
. https://doi.org/10.1115/1.4036630
20.
Kankar
,
P. K.
,
Sharma
,
S. C.
, and
Harsha
,
S. P.
,
2011
, “
Fault Diagnosis of Ball Bearing Using Machine Learning Methods
,”
Expert Syst. Appl.
,
38
(
3
), pp.
1876
1886
.
21.
Janani
,
S. R.
, and
Tiwari
,
R.
,
2017
, “
Experimental Time-Domain Vibration Based Fault Diagnosis of Centrifugal Pumps Using SVM
,”
ASCE-ASME J. Risk Uncertainty Eng. Syst., Part B
,
3
(
1
), p.
044501
. https://doi.org/10.1115/1.4035440
22.
Janani
,
S. R.
, and
Tiwari
,
R.
,
2019
, “
Multi-Fault Diagnosis of Combined Hydraulic and Mechanical Centrifugal Pump Faults Using Continuous Wavelet Transform and Support Vector Machines
,”
ASME J. Dyn. Syst. Meas. Control.
,
141
(
11
), p.
111013
. https://doi.org/10.1115/1.4044274
23.
Gangsar
,
P.
, and
Tiwari
,
R.
,
2019
, “
Online Diagnostics of Mechanical and Electrical Faults in Induction Motor Using Multiclass Support Vector Machine Algorithms Based on Frequency Domain Vibration and Current Signals
,”
ASCE-ASME J. Risk Uncertainty Eng. Syst., Part B
,
5
(
1
), p.
031001
. https://doi.org/10.1115/1.4043268
24.
Patel
,
V.
,
Tandon
,
N.
, and
Pandey
,
R. K.
,
2010
, “
A Dynamic Model for Vibration Studies of Deep Groove Ball Bearings Considering Single and Multiple Defects in Races
,”
ASME J. Tribol.
,
132
(
4
), p.
041101
. https://doi.org/10.1115/1.4002333
You do not currently have access to this content.