A data-driven approach for analyzing faults in wind turbine gearbox is developed and tested. More specifically, faults in a ring gear are predicted in advance. Time-domain statistical metrics, such as jerk, root mean square (RMS), crest factor (CF), and kurtosis, are investigated to identify faulty components of a wind turbine. The components identified are validated with the fast Fourier transformation (FFT) of vibration data. Fifty neural networks (NNs) with different parameter settings are trained to obtain the best performing model. Models based on original vibration data, and transformed jerk data are constructed. The jerk model based on multisensor data outperforms the other models and therefore is used for testing and validation of previously unseen data. Short-term predictions of up to 15 time intervals, each representing 0.1 s, are performed. The prediction accuracy varies from 91.68% to 94.78%.

References

References
1.
Larder
,
B. D.
,
1992
, “
An Analysis of HUMS Vibration Diagnostic Capabilities
,”
J. Am. Helicopter Soc.
,
45
(
1
), pp.
1
6
.
2.
Samuel
,
P. D.
, and
Pines
,
D. J.
,
2005
, “
A Review of Vibration-Based Techniques for Helicopter Transmission Diagnostics
,”
J. Sound Vib.
,
282
(
1–2
), pp.
475
508
.10.1016/j.jsv.2004.02.058
3.
Hameed
,
Z.
,
Hong
,
Y. S.
,
Cho
,
Y. M.
,
Ahn
,
S. H.
, and
Song
,
C. K.
,
2009
, “
Condition Monitoring and Fault Detection of Wind Turbines and Related Algorithms: A Review
,”
Renewable Sustainable Energy Rev.
,
13
(
1
), pp.
1
39
.10.1016/j.rser.2007.05.008
4.
Garcia
,
M. C.
,
Sanz-Bobi
,
M. A.
, and
Pico
,
J.
,
2006
, “
SIMAP: Intelligent System for Predictive Maintenance: Application to the Health Condition Monitoring of a Wind Turbine Gearbox
,”
Comput. Ind.
,
57
(
6
), pp.
552
568
.10.1016/j.compind.2006.02.011
5.
Yang
,
X.
,
Tavner
,
P. J.
,
Crabtree
,
C. J.
, and
Wilkinson
,
M.
,
2010
, “
Cost-Effective Condition Monitoring for Wind Turbines
,”
IEEE Trans. Ind. Electron.
,
57
(
1
), pp.
263
271
.10.1109/TIE.2009.2032202
6.
Tavner
,
P. J.
,
2008
, “
Review of Condition Monitoring of Rotating Electrical Machines
,”
IET Electr. Power Appl.
,
2
(
4
), pp.
215
247
.10.1049/iet-epa:20070280
7.
Cusido
,
J.
,
Romeral
,
L.
,
Ortega
,
J. A.
,
Rosero
,
J. A.
, and
Garcia
,
A. E.
,
2008
, “
Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition
,”
IEEE Trans. Ind. Electron.
,
55
(
2
), pp.
633
643
.10.1109/TIE.2007.911960
8.
Atat
,
H. A.
,
Siegel
,
D.
, and
Lee
,
J.
,
2011
, “
A Systematic Methodology for Gearbox Health Assessment and Fault Classification
,”
Int. J. Prognostics Health Manage.
,
2
, pp.
1
16
.
9.
Zheng
,
H.
,
Li
,
Z.
, and
Chen
X.
,
2002
, “
Gear Fault Diagnosis Based on the Continuous Wavelet Transform
,”
Mech. Syst. Signal Process.
,
16
(
2–3
), pp.
447
457
.10.1006/mssp.2002.1482
10.
Tse
,
P. W.
,
Peng
,
Y. H.
, and
Yam
,
R.
,
2001
, “
Wavelet Analysis and Envelope Detection for Rolling Element Bearing Fault Diagnosis-Their Effectiveness and Flexibilities
,”
ASME J. Vib. Acoust.
,
123
(
3
), pp.
303
310
.10.1115/1.1379745
11.
Kusiak
,
A.
, and
Shah
,
S.
,
2006
, “
A Data-Mining-Based System for Prediction of Water Chemistry Faults
,”
IEEE Trans. Ind. Electron.
,
53
(
2
), pp.
593
603
.10.1109/TIE.2006.870706
12.
Song
,
Z.
, and
Kusiak
,
A.
,
2007
, “
Constraint-Based Control of Boiler Efficiency: A Data-Mining Approach
,”
IEEE Trans. Ind. Inf.
,
3
(
1
), pp.
73
83
.10.1109/TII.2006.890530
13.
Kusiak
,
A.
, and
Song
,
Z.
,
2006
, “
Combustion Efficiency Optimization and Virtual Testing: A Data-Mining Approach
,”
IEEE Trans. Ind. Inf.
,
2
(
3
), pp.
176
184
.10.1109/TII.2006.873598
14.
Li
,
W.
,
Joos
,
G.
, and
Belanger
,
J.
,
2010
, “
Real-Time Simulation of a Wind Turbine Generator Coupled With a Battery Super Capacitor Energy Storage System
,”
IEEE Trans. Ind. Inf.
,
57
(
4
), pp.
1137
1145
.10.1109/TIE.2009.2037103
15.
Patil
,
M. S.
,
Mathew
,
J.
, and
RajendraKumar
,
P. K.
,
2008
, “
Bearing Signature Analysis as a Medium for Fault Detection: A Review
,”
ASME J. Tribol.
,
130
(
1
), pp.
1
6
.10.1115/1.2805445
16.
Sassi
,
S.
,
Badri
,
B.
, and
Thomas
,
M.
,
2006
, “
“TALAF” and “THIKAT” as Innovative Time-Domain Indicators for Tracking Ball Bearings
,”
Proceedings of the 14th Seminar on Machinery Vibration
, Vancouver, Canada, October 24–27, pp.
404
419
.
17.
Kusiak
,
A.
, and
Zhang
,
Z.
,
2010
, “
Analysis of Wind Turbine Vibrations Based on SCADA Data
,”
ASME J. Sol. Eng.
,
132
(
3
), p.
031008
.10.1115/1.4001461
18.
Guo
,
Z.
,
Chang
,
L.
, and
Xue
,
Y.
,
2009
, “
Cogging Torque of Permanent Magnet Electric Machines: An Overview
,”
Canadian Conference on Electrical and Computer Engineering (CCECE)
, St. John's, Canada, May 4–6, pp.
1
8
.
19.
Kudo
,
T.
, and
Matsumoto
,
Y.
,
2004
, “
A Boosting Algorithm for Classification of Semi-Structured Text
,”
Proceedings of EMNLP
, Barcelona, Spain, July 25–26, pp.
301
308
.
20.
Hinton
,
G.
, and
Sejnowski
,
T. J.
,
1999
,
Unsupervised Learning: Foundations of Neural Computation
,
MIT Press
,
Cambridge, MA
.
21.
Sikonja
,
M. R.
, and
Kononenko
,
I.
,
1997
, “
An Adaptation of Relief for Attribute Estimation in Regression
,”
14th International Conference on Machine Learning
, Nashville, TN, pp.
296
304
.
22.
Hall
,
M. A.
,
1999
, “Correlation-Based Feature Subset Selection for Machine Learning,” Ph.D. thesis, University of Waikato,
Hamilton
,
New Zealand
.
23.
Broyden
,
C. G.
,
1970
, “
The Convergence of a Class of Double-Rank Minimization Algorithms
,”
J. Inst. Math. Appl.
,
6
(
1
), pp.
76
90
.10.1093/imamat/6.1.76
24.
Fletcher
,
R.
,
1970
, “
A New Approach to Variable Metric Algorithms
,”
Comput. J.
,
13
(
3
), pp.
317
322
.10.1093/comjnl/13.3.317
25.
Goldfarb
,
D.
,
1970
, “
A Family of Variable Metric Updates Derived by Variational Means
,”
Math. Comput.
,
24
, pp.
23
26
.10.1090/S0025-5718-1970-0258249-6
26.
Shanno
,
D. F.
,
1970
, “
Conditioning of Quasi-Newton Methods for Function Minimization
,”
Math. Comput.
,
24
(
111
), pp.
647
656
.10.1090/S0025-5718-1970-0274029-X
27.
Moller
,
M. F.
,
1993
, “
A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning
,”
Neural Networks
,
6
(
4
), pp.
525
533
.10.1016/S0893-6080(05)80056-5
28.
Zweiri
,
Y. H.
,
Whidborne
,
J. F.
, and
Sceviratne
,
L. D.
,
2002
, “
A Three-Term Backpropagation Algorithm
,”
Neurocomputing
,
50
, pp.
305
318
.10.1016/S0925-2312(02)00569-6
29.
Yee
,
P. V.
, and
Haykin
,
S.
,
2001
,
Regularized Radial Basis Function Networks: Theory and Applications
,
John Wiley & Sons
, New York.
You do not currently have access to this content.