A series of continuous vibration measurements in 14 upwind wind turbines of the same model and belonging to the same wind farm have been conducted. The data were acquired over a period lasting approximately half a year. The tower axial vibration acceleration has been monitored in the frequency band from 0 to 10 Hz with an accelerometer mounted on the gearbox casing between the intermediate and the high-speed shafts. It has been observed that the average frequency spectrum is dominated by the blade passing frequency in all the wind turbines. The evolution of the vibration magnitudes over the entire range of operating conditions is also very similar for all the wind turbines. The root-mean-square (rms) acceleration value has been correlated with the wind speed, and it has been found that a linear fit with a positive slope is a useful model for prediction purposes.

References

References
1.
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
.
2.
Hameed
,
Z.
,
Ahn
,
S. H.
, and
Cho
,
Y. M.
,
2010
, “
Practical Aspects of a Condition Monitoring System for a Wind Turbine With Emphasis on Its Design, System Architecture, Testing and Installation
,”
Renewable Energy
,
35
(
5
), pp.
879
894
.
3.
Gray
,
C. S.
, and
Watson
,
S. J.
,
2010
, “
Physics of Failure Approach to Wind Turbine Condition Based Maintenance
,”
Wind Energy
,
13
(
5
), pp.
395
405
.
4.
Tian
,
Z.
,
Jin
,
T.
,
Wu
,
B.
, and
Ding
,
F.
,
2011
, “
Condition Based Maintenance Optimization for Wind Power Generation Systems Under Continuous Monitoring
,”
Renewable Energy
,
36
(
5
), pp.
1502
1509
.
5.
Kusiak
,
A.
, and
Li
,
W.
,
2011
, “
The Prediction and Diagnosis of Wind Turbine Faults
,”
Renewable Energy
,
36
(
1
), pp.
16
23
.
6.
Zaher
,
A.
,
McArthur
,
S. D. J.
, and
Infield
,
D. G.
,
2009
, “
Online Wind Turbine Fault Detection Through Automated SCADA Data Analysis
,”
Wind Energy
,
12
(
6
), pp.
574
593
.
7.
Ozbek
,
M.
,
Rixen
,
D. J.
,
Erne
,
O.
, and
Sanow
,
G.
,
2010
, “
Feasibility of Monitoring Large Wind Turbines Using Photogrammetry
,”
Energy
,
35
(
12
), pp.
4802
4811
.
8.
Ghoshal
,
A.
,
Sundaresan
,
M. J.
,
Schulz
,
M. J.
, and
Pai
,
P. F.
,
2000
, “
Structural Health Monitoring Techniques for Wind Turbine Blades
,”
J. Wind Eng. Ind. Aerodyn.
,
85
(
3
), pp.
309
324
.
9.
Tang
,
B.
,
Liu
,
W.
, and
Song
,
T.
,
2010
, “
Wind Turbine Fault Diagnosis Based on Morlet Wavelet Transformation and Wigner-Ville Distribution
,”
Renewable Energy
,
35
(
12
), pp.
2862
2866
.
10.
Yang
,
W.
,
Tavner
,
P. J.
, and
Wilkinson
,
M. R.
,
2009
, “
Condition Monitoring and Fault Diagnosis of a Wind Turbine Synchronous Generator Drive Train
,”
IET Renewable Power Gener.
,
3
(
1
), pp.
1
11
.
11.
Gasch
,
R.
, and
Twele
,
J.
, eds.,
2012
,
Wind Power Plants: Fundamentals, Design, Construction and Operation
,
Springer-Verlag
,
Berlin
.
12.
Oerlemans
,
S.
,
Sijtsma
,
P.
, and
López
,
B. M.
,
2007
, “
Location and Quantification of Noise Sources on a Wind Turbine
,”
J. Sound Vib.
,
299
(
4–5
), pp.
869
883
.
13.
McNerney
,
G. M.
,
van Dam
,
C. P.
, and
Yen-Nakfuji
,
D. T.
,
2003
, “
Blade-Wake Interaction Noise for Turbines With Downwind Rotors
,”
ASME J. Sol. Energy Eng.
,
125
(
4
), pp.
497
505
.
14.
Hau
,
E.
,
2006
,
Wind Turbines: Fundamentals, Technologies, Application, Economics
,
2nd ed.
,
Springer-Verlag
,
Berlin
.
15.
Hogeon
,
K.
,
Seungmin
,
L.
, and
Soogab
,
L.
,
2011
, “
Influence of Blade-Tower Interaction in Upwind-Type Horizontal Axis Wind Turbines on Aerodynamics
,”
J. Mech. Sci. Technol.
,
25
(
5
), pp.
1351
1360
.
16.
Kusiak
,
A.
, and
Zhang
,
Z.
,
2010
, “
Analysis of Wind Turbine Vibrations Based on SCADA Data
,”
ASME J. Sol. Energy Eng.
,
132
(
3
), p.
031008
.
You do not currently have access to this content.