In this paper, fault diagnosis of high speed rolling element bearings due to localized defects using response surface method has been done. The localized defects as spalls on outer race, on inner race, and on rolling elements are considered for this study. The mathematical formulation accounted for tangential motions of rolling elements and inner and outer races with the sources of nonlinearity such as Hertzian contact force and internal radial clearance. The nonlinear stiffness is obtained by the application of Hertzian elastic contact deformation theory. The mathematical formulation predicts discrete spectrum having peaks at the characteristic defect frequencies and their harmonics. Experimentation has also been performed to validate the results obtained from the mathematical model and it shows that the model can be successfully used to predict amplitude ratios among various spectral lines with localized surface defects. Combined parametric effects have been analyzed and their influence has been considered with design of experiments and surface response methodology is used to predict the dynamic response of a rotor bearing system.

1.
Chow
,
M.
,
Mangum
,
P. M.
, and
Yee
,
S. O.
, 1991, “
A Neural Network Approach to Real-Time Condition Monitoring of Induction Motors
,”
IEEE Trans. Ind. Electron.
0278-0046,
38
, pp.
448
453
.
2.
Alguindigue
,
I. E.
,
Loskiewicz-Buczak
,
A.
, and
Uhrig
,
R. E.
, 1993, “
Monitoring and Diagnosis of Rolling Element Bearings Using Artificial Neural Networks
,”
IEEE Trans. Ind. Electron.
0278-0046,
40
, pp.
209
217
.
3.
McCormick
,
A. C.
, and
Nandi
,
A. K.
, 1997, “
Classification of the Rotating Machine Condition Using Artificial Neural Networks
,”
Proc. Inst. Mech. Eng., Part C: J. Mech. Eng. Sci.
0954-4062,
211
, pp.
439
450
.
4.
McCormick
,
A. C.
, and
Nandi
,
A. K.
, 1997, “
Real-Time Classification of Rotating Shaft Loading Conditions Using Artificial Neural Networks
,”
IEEE Trans. Neural Netw.
1045-9227,
8
, pp.
748
757
.
5.
Tse
,
P. W.
, and
Atherton
,
D. P.
, 1999, “
Prediction of Machine Deterioration Using Vibration Based Fault Trends and Recurrent Neural Networks
,”
ASME J. Vibr. Acoust.
0739-3717,
121
, pp.
355
362
.
6.
Samanta
,
B.
, and
Al-Balushi
,
K. R.
, 2003, “
Artificial Neural Network Based Fault Diagnostics of Rolling Element Bearings Using Time-Domain Features
,”
Mech. Syst. Signal Process.
0888-3270,
17
(
2
), pp.
317
328
.
7.
Samanta
,
B.
, 2004, “
Gear Fault Detection Using Artificial Neural Networks and Support Vector Machines With Genetic Algorithms
,”
Mech. Syst. Signal Process.
0888-3270,
18
, pp.
625
644
.
8.
Jack
,
L. B.
, and
Nandi
,
A. K.
, 2002, “
Fault Detection Using Support Vector Machines and Artificial Neural Network, Augmented by Genetic Algorithms
,”
Mech. Syst. Signal Process.
0888-3270,
16
, pp.
373
390
.
9.
Samanta
,
B.
,
Al-Balushi
,
K. R.
, and
Al-Araimi
,
S. A.
, 2003, “
Artificial Neural Network and Support Vector Machine With Genetic Algorithm for Bearing Fault Detection
,”
Eng. Applic. Artif. Intell.
0952-1976,
16
, pp.
657
665
.
10.
Sugumaran
,
V.
,
Muralidharan
,
V.
, and
Ramachandran
,
K. I.
, 2007, “
Feature Selection Using Decision Tree and Classification Proximal Support Vector Machine for Fault Diagnostic of Roller Bearing
,”
Mech. Syst. Signal Process.
0888-3270,
21
(
2
), pp.
930
942
.
11.
Hu
,
Q.
,
He
,
Z.
,
Zhang
,
Z.
, and
Zi
,
Y.
, 2007, “
Fault Diagnosis of Rotating Machinery Based on Improved Wavelet Package Transform and SVM Ensemble
,”
Mech. Syst. Signal Process.
0888-3270,
21
(
2
), pp.
688
705
.
12.
Wang
,
W. Q.
,
Golnaraghi
,
M. F.
, and
Ismail
,
F.
, 2004, “
Prognosis of Machine Health Condition Using Neuro-Fuzzy Systems
,”
Mech. Syst. Signal Process.
0888-3270,
18
, pp.
813
831
.
13.
Wang
,
W.
,
Ismail
,
F.
, and
Golnaraghi
,
F.
, 2004, “
A Neuro-Fuzzy Approach to Gear System Monitoring
,”
IEEE Trans. Fuzzy Syst.
1063-6706,
12
, pp.
710
723
.
14.
Gallina
,
A.
,
Martowicz
,
A.
, and
Uhl
,
T.
, 2006, “
An Application of Response Surface Methodology in the Field of Dynamic Analysis of Mechanical Structures Considering Uncertain Parameters
,”
ISMA 2006 Conference
, Leuven, Belgium.
15.
Liang
,
X.
,
Lin
,
Z.
, and
Zhu
,
P.
, 2007, “
Acoustic Analysis of Damping Structure With Response Surface Method
,”
Appl. Acoust.
0003-682X,
68
, pp.
1036
1053
.
16.
Kankar
,
P. K.
,
Harsha
,
S. P.
,
Kumar
,
P.
, and
Sharma
,
S. C.
, 2009, “
Fault Diagnosis of a Rotor Bearing System Using Response Surface Method
,”
Eur. J. Mech. A/Solids
0997-7538,
28
, pp.
841
857
.
17.
Ghafari
,
S. H.
,
Golnaraghi
,
F.
, and
Ismail
,
F.
, 2008, “
Effect of Localized Faults on Chaotic Vibration of Rolling Element Bearings
,”
Nonlinear Dyn.
0924-090X,
53
(
4
), pp.
287
301
.
18.
Harsha
,
S. P.
, and
Kankar
,
P. K.
, 2005, “
Nonlinear Dynamic Analysis of a Complex Rotor Bearing System
,”
Int. J. Acoust. Vib.
1027-5851,
10
(
1
), pp.
33
39
.
19.
Harris
,
T. A.
, and
Kotzalas
,
M. N.
, 2007,
Advanced Concepts of Bearing Technology
,
CRC
,
New York
.
20.
Arslan
,
H.
, and
Aktürk
,
N.
, 2008, “
An Investigation of Rolling Element Vibrations Caused by Local Defects
,”
ASME J. Tribol.
0742-4787,
130
(
4
), p.
041101
.
21.
Myers
,
R. H.
, and
Montgomery
,
D. C.
, 2002,
Response Surface Methodology: Process and Product Optimization Using Designed Experiments
, 2nd ed.,
Wiley
,
New York
.
22.
Nayfeh
,
A. H.
, and
Balachandran
,
B.
, 1995,
Applied Nonlinear Dynamics: Analytical, Computational and Experimental Methods
,
Wiley
,
New York
.
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