The main driver behind developing advanced condition monitoring (CM) systems for the wind energy industry is the delivery of improved asset management regarding the operation and maintenance of the gearbox and other wind turbine components and systems. Current gearbox CM systems mainly detect faults by identifying ferrous materials, water, and air within oil by changes in certain properties such as electrical fields. In order to detect oil degradation and identify particles, more advanced devices are required to allow a better maintenance regime to be established. Current technologies available specifically for this purpose include Fourier transform infrared (FTIR) spectroscopy and ferrography. There are also several technologies that have not yet been or have been recently applied to CM problems. After reviewing the current state of the art, it is recommended that a combination of sensors would be used that analyze different characteristics of the oil. The information individually would not be highly accurate but combined it is fully expected that greater accuracy can be obtained. The technologies that are suitable in terms of cost, size, accuracy, and development are online ferrography, selective fluorescence spectroscopy, scattering measurements, FTIR, photoacoustic spectroscopy, and solid state viscometers.

References

1.
European Wind Energy Association (EWEA)
, 2009,
Wind Energy—The Facts
,
Earthscan
,
London
.
2.
Tavner
,
P. J.
,
van Bussel
,
G. J. W.
, and
Spinato
,
F.
, 2006,
“Machine and Converter Reliabilities in Wind Turbines,”
Proceedings of the 3rd IET International Conference on Power Electronics
,
Machines and Drives
, pp.
127
130
.
3.
McNiff
,
B.
, 2007,
“The Gearbox Reliability,”
Proceedings of the 2nd Sandia National Laboratories Wind Turbine Reliability Workshop
.
4.
Ensslin
,
C.
,
Durstewitz
,
M.
,
Hahn
,
B.
,
Lange
,
B.
, and
Rohrig
,
K.
, 2005,
German Wind Energy Report
,
ISET
,
Kassel
.
5.
Burton
,
T.
,
Sharpe
,
D.
,
Jenkins
,
N.
, and
Bossananyi
,
E.
, 2003,
Wind Energy Handbook
,
John Wiley and Sons
,
Chichester
.
6.
Musial
,
W.
,
Butterfield
,
S.
, and
McNiff
,
B.
, 2007, “
Improving Wind Turbine Gearbox Reliability
,”
European Wind Energy Conference, Conference Paper NREL/CP-500-41548
,
Milan, Italy.
8.
Crabtree
,
C. J.
, 2010,
“Survey of Commercially Available Condition Monitoring Systems for Wind Turbines,”
Durham University
. http://www.supergen-wind.org.uk/docs/Survey%20of%20commercially%20available%20CMS%20for%20WT.pdfhttp://www.supergen-wind.org.uk/docs/Survey%20of%20commercially%20available%20CMS%20for%20WT.pdf.
9.
McMillan
,
D.
, and
Ault
,
G. W.
, 2007, “
Quantification of Condition Monitoring Benefit for Offshore Wind Turbines
,”
Wind Eng.
,
31
(
4
), pp.
267
285
.
10.
Zhan
,
Y.
, and
Makis
,
V.
, 2006, “
A Robust Diagnostic Model for Gearboxes Subject to Vibration Monitoring
,”
J. Sound Vib.
,
290
(
3–5
), pp.
928
955
.
11.
Gelman
,
L.
,
Zimroz
,
R.
,
Birkel
,
J.
,
Leigh-Firbank
,
H.
,
Simms
,
D.
,
Waterland
,
B.
, and
Whitehurst
,
G.
, 2005, “
Adaptive Vibration Condition Monitoring Technology for Local Tooth Damage in Gearboxes
,”
Insight: Non-Destr. Test. Cond. Monit.
,
47
(
8
), pp.
461
464
.
12.
Lekou
,
D. J.
,
Mouzakis
,
F.
,
Anastasopoulos
,
A.
, and
Kourousis
,
D.
, 2009,
“Emerging Techniques for Health Monitoring of Wind Turbine Gearboxes and Bearings,”
Proceedings EWEC, Scientific Track—Operation and Maintenance,
Marseille, France.
13.
Toms
,
L. A.
, 2008,
Machinery Oil Analysis—Methods, Automation & Benefits
, 3rd ed.,
STLE
,
Virginia Beach.
14.
Christensen
,
J. J.
,
Andersson
,
C.
, and
Gutt
,
S.
, 2009,
“Remote Condition Monitoring of Vestas Turbines,”
Technical Track—Operation & Maintenance, Proceedings EWEC
,
Marseille
,
France
.
15.
Gear Foundation Course Notes, 2009, Version 2, David Brown Gear Academy.
16.
Neale
,
M. J.
, 2001,
Lubrication and Reliability Handbook
,
J. W. Arrowsmith
,
Bristol
.
17.
Walsh
,
D. P.
, 2005, “
Oil Analysis 101
,”
Orbit
,
25
(
2
), pp.
50
55
.
18.
Li
,
D.
,
Sedman
,
J.
,
García-González
,
D. L.
, and
van de Voort
,
F. R.
, 2009,
“Automated Acid Content Determination in Lubricants by FTIR Spectroscopy as an Alternative to Acid Number Determination,”
J. ASTM Int.
,
6
(
6
), Paper ID JAI 102110, http://www.thermal-lube.com/Publications/Automated%20Acid%20Content%20Determination%20in%20Lubricants%20by.pdfhttp://www.thermal-lube.com/Publications/Automated%20Acid%20Content%20Determination%20in%20Lubricants%20by.pdf.
19.
Ebbing
,
D. D.
, and
Gammon
,
S. D.
, 2009,
General Chemistry
, 9th ed.,
Houghton Mifflin
,
Boston
.
20.
Gracia
,
N.
,
Thomas
,
S.
,
Bazin
,
P.
,
Duponchel
,
L.
,
Thibault-Starzyk
,
F.
, and
Lerasle
,
O.
, 2009, “
Combination of Mid-Infrared Spectroscopy and Chemometric Factorization Tools to Study the Oxidation of Lubricating Base Oils
,”
Catal. Today
,
155
(
3–4
), pp.
255
260
.
21.
Seeton
,
C. J.
, 2006, “
Viscosity-Temperature Correlation for Liquids
,”
Tribol. Lett.
,
22
(
1
), pp.
67
78
.
22.
Viswanath
,
D. S.
, and
Natarajan
,
G.
, 1989,
Data Book on the Viscosity of Liquids
,
Hemisphere
,
New York
.
23.
ASTM D2422–97, 2007, Standard Classification of Industrial Fluid Lubricants by Viscosity System, ASTM International.
24.
Rudnick
,
L. R.
, 2009,
Lubricant Additives: Chemistry and Applications
,
CRC Press
,
Boca Raton, Florida
.
25.
Mortier
,
R. M.
, and
Orszulik
,
S. T.
, 1997,
Chemistry and Technology of Lubricants
, 2nd ed.,
Blackie Academic and Professional
,
London
.
26.
Pawlak
,
Z.
, 2003,
Tribochemistry of Lubricating Oils
,
Elsevier
,
Amsterdam
.
27.
Aqua Star – Karl Fischer Titration Basics, 2010, EMD Chemicals, http://www.emdchemicals.comhttp://www.emdchemicals.com.
28.
Wieland
,
G.
, and
Fischer
,
K.
, 1987,
Water Determination by Karl-Fischer Titratio: Theory and Practice
,
GIT
,
Darmstadt
.
29.
InTech Website, http://www.isa.orghttp://www.isa.org accessed on September 1, 2010.
31.
Stuart
,
B.
, 2004,
Infrared Spectroscopy: Fundamentals and Applications
,
John Wiley and Sons
,
Chichester
.
32.
Párkányi
,
C.
, 1998,
Theoretical Organic Chemistry
,
Elsevier Science
,
Amsterdam
.
33.
Machinery Lubrication, accessed from http://www.machinerylubrication.comhttp://www.machinerylubrication.com on September 9, 2010.
34.
Poljanîsek
,
I.
, and
Krajnc
,
M.
, 2005, “
Characterization of Phenol-Formaldehyde Prepolymer Resins by In Line FT-IR Spectroscopy
,”
Acta Chimica Slovenica
,
52
, pp.
238
244
.
35.
Toms
,
L. A.
, 2008,
Machinery Oil Analysis Methods, Automation and Benefits
, 3rd ed.,
STLE
,
Virginia Beach
.
36.
SpectroInc. QinetiQ North America, FluidScan Q1000, accessed from http://www.spectroinc.com/products-fluidscan.htmhttp://www.spectroinc.com/products-fluidscan.htm on August 25, 2010.
37.
Linden
,
J. C.
,
Tranter
,
G. E.
, and
Homes
,
J. L.
, 2000,
“Photoacoustic Spectroscopy, Theory,”
Encyclopaedia of Spectroscopy and Spectrometry
, 2nd ed.,
Academic
,
London
.
38.
Fodor
,
P.
, and
Ipolyi
,
I.
, 2005, “
Atomic Absorption Spectrometry, Electrothermal
,”
Encyclopedia of Analytical Science
, 2nd ed., pp.
174
180
Elsevier Academic Press
,
Amsterdam
.
39.
Foster
,
N. S.
,
Amonette
,
J. E.
,
Autrey
,
T.
, and
Ho
,
J. T.
, 2001, “
Detection of Trace Levels of Water in Oil By Photoacoustic Spectroscopy
,”
Sensors and Act.
,
77
, pp.
620
624
.
40.
MICEPAS: Miniaturised Cell Enhanced Photoacoustic Spectroscopy, 2009, accessed from http://www.micepas.basnet.by/http://www.micepas.basnet.by/ on August 10, 2010.
41.
Firebaugh
,
S. L.
,
Jensen
,
K. F.
, and
Schmidt
,
M. A.
, 2001,
“Miniaturization and Integration of Photoacoustic Detection with a Microfabricated Chemical Reactor System,”
J. Microelectromech. Syst.
,
10
(
2
), pp.
232
237
.
42.
Stachowiak
,
G. W.
, and
Batchelor
,
A. W.
, 2005,
Engineering Tribology
,
Elsevier
,
Oxford.
43.
Viswanath
,
D. S.
, 2007,
Viscosity of Liquids: Theory, Estimation, Experiment and Data
,
Springer
,
Dordrecht, Netherlands.
44.
Kereme
,
D.
, 2004,
“Solid-state Viscometer for Oil Condition Monitoring,”
Practicing Oil Analysis
, November Edition, http://65.38.6.88/Magazine/Issue/Practicing%20Oil%20Analysis/11/2004http://65.38.6.88/Magazine/Issue/Practicing%20Oil%20Analysis/11/2004.
45.
Lakowicz
,
J. R.
, 1991,
Topics in Fluorescence Spectroscopy, Principle
, Vol.
2
,
Plenum
,
New York
.
46.
Sotelo
,
F. F.
,
Pantoja
,
P. A.
,
López-Gejo
,
J.
,
Le Roux
,
G. A. C.
,
Quina
,
F. H.
, and
Nascimento
,
C. A. O.
, 2008,
“Application of Fluorescence Spectroscopy for Spectral Discrimination of Crude Oil Samples,”
Brazilian J. Pet. Gas
,
2
(
2
), pp.
63
71
.
47.
Liang
,
T. K.
,
Friedrich
,
M.
,
Lala
,
D.
, and
Ozanyan
,
K. B.
, 2004, “
Portable Fluorescence Sensor for On-line Monitoring of Lubricant Oils
,” Sensors,
Proceedings of IEEE
,
1
(
24–27
), pp.
8
11
.
48.
Patra
,
D.
, and
Misha
,
A. K.
, 2002, “
Total Synchronous Fluorescence Scan Spectra of Petroleum Products
,”
Anal. Bioanal. Chem.
,
373
, pp.
304
309
.
49.
Smith
,
S.
, 2008,
ADS Workshop: Sensing a Defence Requirement, Sensor Activity in the Scottish Engineering Research Partnerships
,
Proceedings of University of Edinburgh Sensor Workshop
.
50.
Mignani
,
A. G.
, 2009, “
Optical Fiber Spectroscopy for Measuring Quality Indicators of Lubricant Oils
,”
Meas. Sci. Technol.
,
20
, pp.
7
13
.
51.
Harrington
,
J. A.
, 2004,
Infrared Fibers and Their Applications
,
SPIE
,
Washington
.
52.
Harrington
,
J. A.
, 2007
Infrared Fiber Optics: OSA Handbook
,
SPIE
,
Washington
.
53.
Olivieri
,
A. C.
, 2008, “
Analytical Advantages of Multivariate Data Processing
,”
Anal. Chem.
,
80
, pp.
5713
5720
.
54.
Lajunen
,
L. H. J.
, and
Perämäki
,
P.
, 2004,
Spectrochemical Analysis by Atomic Absorption and Emission
, 2nd ed.,
The Royal Society of Chemistry
,
Cambridge.
55.
Rao
,
B. K. N.
, 1996,
Handbook of Condition Monitoring
, 1st ed.,
Elsevier Advanced Technology
,
Oxford
.
56.
Ghosh
,
S.
,
Sarkar
,
B.
, and
Saha
,
J.
, 2005,
“Wear Characterization by Fractal Mathematics for Quality Improvement of Machine,”
J. Qual. Maint. Eng.
,
11
(
4
), pp.
318
332
.
57.
Goldstein
,
J.
,
Newbury
,
D.
,
Joy
,
D.
,
Lyman
,
C.
,
Echlin
,
P.
,
Lifshin
,
E.
,
Sawyer
,
L.
, and
Michael
,
J.
, 2003,
Scanning Electron Microscopy and X-ray Microanalysis
, 3rd ed.,
Plenum
,
New York
.
58.
“Scanning Electron Microscope,”
Purdue University
,
Department of Radiological and Environmental Management
, accessed from http://www.purdue.edu/rem/rs/sem.htmhttp://www.purdue.edu/rem/rs/sem.htm, on August 2, 2010.
59.
“Scanning Electron Microscopes,”
Popular Mechanics (
2010), accessed from http://www.popularmechanics.com/technology/gadgets/4218957http://www.popularmechanics.com/technology/gadgets/4218957 on August 8, 2010.
60.
Wu
,
T. H.
,
Mao
,
J. H.
,
Wang
,
J. T.
,
Wu
,
J. Y.
, and
Xie
,
Y. B.
, 2009,
“A New On-Line Visual Ferrograph,”
Tribol. Trans.
,
52
(
5
), pp
623
631
.
61.
Myshkin
,
N. K.
,
Markova
,
L. V.
,
Semenyuk
,
M. S.
,
Kong
,
H.
,
Han
,
H.-G.
, and
Yoon
,
E.-S.
, 2003,
“Wear Monitoring Based on the Analysis of Lubricant Contamination by Optical Ferroanalyzer, Wear,”
14th International Conference on Wear of Materials
,
255
(
7–12
), pp.
1270
1275
.
62.
Lord
,
C. J.
, 1991, “
Determination of Trace Metals in Crude Oil by Inductively Coupled Plasma Mass Spectrometry with Micro-emulsion Sample Introduction
,”
Anal. Chem.
,
63
, pp.
1594
1599
.
63.
Escobar
,
M. P.
,
Smith
,
B. W.
, and
Winefordner
,
J. D.
, 1996, “
Determination of Metallo-organic Species in Lubricating Oil by Electrothermal Vaporization Inductively Coupled Plasma Mass Spectrometry
,”
Anal. Chim. Acta
,
320
, pp.
11
17
.
64.
Aucelio
,
R. Q.
,
Souza
,
R. M.
,
Campos
,
R. C.
,
Miekeley
,
N.
, and
Silveira
,
C.
, 2007, “
The Determination of Trace Metals in Lubricating Oils by Atomic Spectrometry
,”
Spectrochim. Acta, Part B
,
62
(
9
), pp.
952
961
.
65.
Goncalves
,
I. M.
,
Murillo
,
M.
, and
González
,
A. M.
, 1998, “
Determination of Metals in Used Lubricating Oils by AAS using Emulsified Samples
,”
Talanta
,
47
, pp.
1033
1042
.
66.
Brown
,
R. J.
, 1983, “
Determination of Trace Metals in Petroleum and Petroleum Products Using an Inductively Coupled Plasma Optical Emission Spectrometer
,”
Spectrochim. Acta, Part B
,
38
(
1–2
), pp.
283
289
.
67.
Jansen
,
E. B. M.
,
Knipscheer
,
J. H.
, and
Nagtegaal
,
M.
, 1992,
“Rapid and Accurate Element Determination in Lubricating Oils Using Inductively Coupled Plasma Optical Emission Spectrometry,”
J. Anal. At. Spectrom.
,
7
(
2
), pp.
127
130
.
68.
Yaroshchyk
,
P.
,
Morrison
,
R. J. S.
,
Body
,
D.
, and
Chadwick
,
B. L.
, 2005, “
Quantitative Determination of Wear Metals in Engine Oils Using LIBS: The Use of Paper Substrates and a Comparison Between Single- and Double-pulse LIBS
,”
Spectrochim. Acta, Part B
,
60
, pp.
1482
1485
.
69.
Patel
,
B. M.
, and
Winefordner
,
J. D.
, “
Graphite Rod Atomization and Atomic Fluorescence for Simultaneous Determination of Silver and Copper in Jet-engine Oils
,”
Anal. Chim. Acta
,
64
, pp.
135
138
.
70.
Miller
,
R. L.
,
Fraser
,
L. M.
, and
Winefordner
,
J. D.
, 1971, “
Combination Flame Atomic Fluorescence Atomic Emission DC Spectrometer for Analysis of Trace Wear Metals in Jet Engine Oils
,”
Appl. Spectrosc.
,
25
, pp.
477
482
.
71.
Iwai
,
Y.
,
Honda
,
T.
,
Miyajima
,
T.
,
Yoshinaga
,
S.
,
Higashi
,
M.
, and
Fuwa
,
Y.
, 2010, “
Quantitative Estimation of Wear Amounts by Real Time Measurement of Wear Debris in Lubricating Oil
,”
Tribol. Int.
,
43
(
1–2
), pp.
388
394
.
72.
Machinery Lubrication, accessed from http://www.machinerylubrication.comhttp://www.machinerylubrication.com on September 10, 2010.
74.
Sandler
,
M. P.
,
Coleman
,
R. E.
, and
Patton
,
J. A.
, 2003,
Diagnostic Nuclear Medicine
,
Lippincott Williams & Wilkins
,
Philadelphia
.
75.
Crabtree
,
C. J.
, 2010,
Survey of Commercially Available Condition Monitoring Systems for Wind Turbines
,
Durham University
.
76.
Yoon
,
S.
,
Lee
,
S.
,
Lee
,
Y.
, and
Oh
,
J.
, 2006, “
A Miniaturized Magnetic Induction Sensor Using Geomagnetism for Turn Count of Small-Caliber Ammunition
,”
Sensors
,
6
, pp.
712
726
.
77.
Rajendran
,
A.
, and
Neelamegam
,
P.
, 2004, “
Microcontroller Based Dielectric Constant Measurement
,”
Sensors & Transducers Magazine
,
41
(
3
), pp.
181
190
.
78.
He
,
L. M.
,
Kear-Padilla
,
L. L.
,
Lieberman
,
S. H.
, and
Andrews
,
J. M.
, 2003, “
Rapid in Situ Determination of Total Oil Concentration in Water Using Ultraviolet Fluorescence and Light Scattering Coupled With Artificial Neural Networks
,”
Anal. Chim. Acta
,
478
(
2
), pp.
245
258
.
79.
Hair
,
J. F.
, 2009,
Multivariate Data Analysis: A Global Perspective
, 7th ed.,
Pearson Education
,
Upper Saddle River, NJ.
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