This paper proposes new seismic-based methods for use in the wind energy industry with a focus on wind turbine condition monitoring. Fourteen Streckeisen STS-2 Broadband seismometers and two three-dimensional (3D) sonic anemometers are deployed in/near an operating wind farm to collect the data used in these proof-of-principle analyses. The interquartile mean (IQM) value of power spectral density (PSD) of the seismic components in 10 min time series is used to characterize the spectral signatures (i.e., frequencies with enhanced variance) in ground vibrations deriving from vibrations of wind turbine subassemblies. A power spectral envelope approach is taken in which the probability density function (PDF) of seismic PSD is developed using seismic data collected under normal turbine operation. These power spectral envelopes clearly show the energy distribution of wind-turbine-induced ground vibrations over a wide frequency range. Singular PSD lying outside the power spectral envelopes can be easily identified and is used herein along with supervisory control and data acquisition (SCADA) data to diagnose the associated suboptimal turbine operating conditions. Illustrative examples are given herein for periods with yaw misalignment and excess tower acceleration. It is additionally shown that there is a strong association between drivetrain acceleration and seismic spectral power in a frequency band of 2.5–12.5 Hz. The long-term goal of the research is development of seismic-based condition monitoring (SBCM) for wind turbines. The primary advantages of SBCM are that the approach is low-cost, noninvasive, and versatile (i.e., one seismic sensor monitoring multiple turbine components).

References

References
1.
DOE and NREL
,
2008
, “
20% Wind Energy by 2030, Increasing Wind Energy's Contribution to U.S. Electricity Supply
,” National Renewable Energy Laboratory, Golden, CO, Report No.
DOE/GO-102008-2567
.http://www.nrel.gov/docs/fy08osti/41869.pdf
2.
TPWind
,
2008
, “
Strategic Research Agenda and Market Deployment Strategy–From 2008 to 2030
,” European Wind Energy Technology Platform, Brussels, Belgium, accessed July 18, 2016, http://www.windplatform.eu/fileadmin/ewetp_docs/Bibliography/Executive_summary.pdf
3.
Walford
,
C. A.
,
2006
, “
Wind Turbine Reliability: Understanding and Minimizing Wind Turbine Operation and Maintenance Costs
,” Sandia National Laboratories, Albuquerque, NM, Sandia Report No.
SAND2006-1100
.http://prod.sandia.gov/techlib/access-control.cgi/2006/061100.pdf
4.
Hatch
,
C.
,
2004
, “
Improved Wind Turbine Condition Monitoring Using Acceleration Enveloping
,”
Orbit
,
61
, pp.
58
61
.https://www.orbit-magazine.com/wp-content/uploads/2014/07/2q04windturbcondmon.pdf
5.
Lu
,
B.
,
Li
,
Y.
,
Wu
,
X.
, and
Yang
,
Z.
,
2009
, “
A Review of Recent Advances in Wind Turbine Condition Monitoring and Fault Diagnosis
,”
Power Electronics and Machines in Wind Applications
(
PEMWA
), Lincoln, NE, June 24–26, pp.
1
7
.
6.
Wymore
,
M. L.
,
Van Dam
,
J. E.
,
Ceylan
,
H.
, and
Qiao
,
D.
,
2015
, “
A Survey of Health Monitoring Systems for Wind Turbines
,”
Renewable Sustainable Energy Rev.
,
52
, pp.
976
990
.
7.
Zaher
,
A.
,
McArthur
,
S.
,
Infield
,
D.
, and
Patel
,
Y.
,
2009
, “
Online Wind Turbine Fault Detection Through Automated SCADA Data Analysis
,”
Wind Energy
,
12
(
6
), pp.
574
593
.
8.
Tchakoua
,
P.
,
Wamkeue
,
R.
,
Ouhrouche
,
M.
,
Slaoui-Hasnaoui
,
F.
,
Tameghe
,
T. A.
, and
Ekemb
,
G.
,
2014
, “
Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges
,”
Energies
,
7
(
4
), pp.
2595
2630
.
9.
Yang
,
W.
,
Court
,
R.
, and
Jiang
,
J.
,
2013
, “
Wind Turbine Condition Monitoring by the Approach of SCADA Data Analysis
,”
Renewable Energy
,
53
, pp.
365
376
.
10.
Faulstich
,
S.
,
Hahn
,
B.
, and
Tavner
,
P. J.
,
2011
, “
Wind Turbine Downtime and Its Importance for Offshore Deployment
,”
Wind Energy
,
14
(
3
), pp.
327
337
.
11.
Tavner
,
P.
,
Spinato
,
F.
,
Van Bussel
,
G.
, and
Koutoulakos
,
E.
,
2008
, “
Reliability of Different Wind Turbine Concepts With Relevance to Offshore Application
,”
European Wind Energy Conference
(
EWEC
), Brussels, Belgium, Mar. 31–Apr. 3, pp. 2311–2319.https://community.dur.ac.uk/supergen.wind/Phase1/docs/Tavner,%20Spinato,%20van%20Bussel,%20Koutoulakos-EWEC2008.pdf
12.
Westwood
,
R. F.
,
Styles
,
P.
, and
Toon
,
S. M.
,
2015
, “
Seismic Monitoring and Vibrational Characterization of Small Wind Turbines: A Case Study of the Potential Effects on the Eskdalemuir International Monitoring System Station in Scotland
,”
Near Surf. Geophys.
,
13
(
2
), pp.
115
126
.
13.
Saccorotti
,
G.
,
Piccinini
,
D.
,
Cauchie
,
L.
, and
Fiori
,
I.
,
2011
, “
Seismic Noise by Wind Farms: A Case Study From the Virgo Gravitational Wave Observatory, Italy
,”
Bull. Seismol. Soc. Am.
,
101
(
2
), pp.
568
578
.
14.
Prowell
,
I.
,
Elgamal
,
A.
,
Uang
,
C.
, and
Jonkman
,
J.
,
2010
, “
Estimation of Seismic Load Demand for a Wind Turbine in the Time Domain
,”
European Wind Energy Conference
(
EWEC
), Warsaw, Poland, Apr. 20–23, pp. 4710–4717.http://nheri.ucsd.edu/projects/2010-wind-turbine/pubs/2010-nrel-prowell-elgamal-uang-jonkman.pdf
15.
Santangelo
,
F.
,
Failla
,
G.
,
Santini
,
A.
, and
Arena
,
F.
,
2016
, “
Time-Domain Uncoupled Analyses for Seismic Assessment of Land-Based Wind Turbines
,”
Eng. Struct.
,
123
, pp.
275
299
.
16.
Hu
,
W.
,
Pryor
,
S. C.
,
Letson
,
F.
,
Tytell
,
J.
, and
Barthelmie
,
R. J.
,
2017
, “
Investigation of Gust-Seismic Relationships and Applications to Gust Detection
,”
J. Geophys. Res.: Atmos.
,
122
(
1
), pp.
140
151
.
17.
Letson
,
F.
,
Hu
,
W.
,
Barthelmie
,
R. J.
,
Tytell
,
J.
, and
Pryor
,
S. C.
,
2017
, “
Wind Gust Quantification Using Seismic Measurements
,” 11th International Conference on Energy Sustainability, Charlotte, NC, June 26–29, Paper No. ES2017-3568.
18.
Pryor
,
S. C.
,
Conrick
,
R.
,
Miller
,
C.
,
Tytell
,
J.
, and
Barthelmie
,
R. J.
,
2014
, “
Intense and Extreme Wind Speeds Observed by Anemometer and Seismic Networks: An Eastern US Case Study
,”
J. Appl. Meteorol. Climatol.
,
53
(
11
), pp.
2417
2429
.
19.
McNamara
,
D.
, and
Buland
,
R. P.
,
2004
, “
Ambient Noise Levels in the Continental United States
,”
Bull. Seismol. Soc. Am.
,
94
(
4
), pp.
1517
1527
.
20.
Pryor
,
S. C.
,
Hu
,
W.
,
Letson
,
F.
, and
Barthelmie
,
R. J.
,
2016
, “
Applications of Seismic Analyses to the Wind Energy Industry
,” EnergyTech Magazine, Dubuque, IA, accessed July 18, 2017, http://www.energy-tech.com/advanced_energy/article_0b281b0c-a5f4-11e6-ad6e-4fcbdc8c0992.html
21.
Tytell
,
J.
,
Vernon
,
F.
,
Hedlin
,
M.
,
Hedlin
,
C. D. G.
,
Reyes
,
J.
,
Busby
,
B.
,
Hafner
,
K.
, and
Eakins
,
J.
,
2016
, “
The US Array Transportable Array as a Platform for Weather Observation and Research
,”
Bull. Am. Meteorol. Soc.
,
97
(
4
), pp.
603
619
.
22.
Ringler
,
A.
, and
Hutt
,
C.
,
2010
, “
Self-Noise Models of Seismic Instruments
,”
Seismol. Res. Lett.
,
81
(
6
), pp.
972
983
.
23.
Welch
,
P. D.
,
1967
, “
The Use of Fast Fourier Transform for the Estimation of Power Spectra: A Method Based on Time Averaging Over Short, Modified Periodograms
,”
IEEE Trans. Audio Electroacoust.
,
15
(
2
), pp.
70
73
.
24.
The MathWorks
,
2015
, “
Matlab Help
,” The MathWorks, Inc., Natick, MA.
25.
Diaz
,
J.
,
2016
, “
On the Origin of the Signals Observed Across the Seismic Spectrum
,”
Earth Sci. Rev.
,
161
, pp.
224
232
.
26.
Xi Engineering Consultants
,
2014
, “
Seismic Vibration Produced by Wind Turbines in the Eskdalemuir Region
,”
Xi Engineering Consultants Ltd.
, Edinburgh, UK, Document No. FMB_203_FINAL_V5R.
27.
Fiori
,
I.
,
Giordano
,
L.
,
Hild
,
S.
,
Losurdo
,
G.
,
Marchetti
,
E.
,
Mayer
,
G.
, and
Paoletti
,
F.
,
2009
, “
A Study of the Seismic Disturbance Produced by the Wind Park Near the Gravitational Wave Detector
,”
Third International Meeting on Wind Turbine Noise
, Aalborg, Denmark, June 17–19, pp. 570–594.
28.
Peterson
,
J.
,
1993
,
Observations and Modeling of Seismic Background Noise
, U.S. Department of Interior Geological Survey, Albuquerque, NM.
29.
Fleming
,
P.
,
Scholbrock
,
A.
,
Jehu
,
A.
,
Davoust
,
S.
,
Osler
,
E.
,
Wright
,
A.
, and
Clifton
,
A.
,
2014
, “
Field-Test Results Using a Nacelle-Mounted Lidar for Improving Wind Turbine Power Capture by Reducing Yaw Misalignment
,”
J. Phys. Conf. Ser.
,
524
(
1
), p.
012002
.
30.
Zhang
,
Z.
, and
Kusiak
,
A.
,
2012
, “
Monitoring Wind Turbine Vibration Based on SCADA Data
,”
ASME J. Sol. Energy Eng.
,
134
(
2
), p.
021004
.
You do not currently have access to this content.