This document summarizes a study on sampling and analyzing grease from offshore wind turbine installations in Europe. The study aimed to develop reliable grease sampling and analysis methods to assess bearing condition and improve reliability. Researchers tested active grease sampling devices and analyzed samples for properties like ferrous debris, moisture, and consistency. Spatial sampling of two turbine bearings showed heterogeneity in grease properties. Analysis methods provided accurate wear and contamination data for condition monitoring and optimized maintenance. The study demonstrated that grease analysis is an important tool for monitoring wind turbine bearing health.

1. Grease Sampling and Analysis of Offshore Wind Installations
in Europe to Improve Asset Reliability
Richard N. Wurzbach
MRG Laboratories, York, Pennsylvania
Reliability of current and installed wind turbine platforms is essential to
future viability and growth of the windpower industry. Condition monitoring
has been identified as an important tool in enhancing wind turbine
reliability, and understanding dominant failure modes and root-causes.
Grease lubrication is utilized for most drivetrain components, and proper
lubrication is vital to reliable operation. Companies in the Danish wind
industry, recognizing these concerns, created a project team to research
methods and tools for obtaining grease samples from wind turbine main
bearings. Utilizing the principles of the Theory of Sampling by Professor
Pierre Gy, the team identified several tools and important methods in
ensuring that analysis of greases from wind turbines provides accurate
condition assessment and actionable data. Analysis methods utilizing
small grease volumes (approximately 1 gram) were shown to be effective
in differentiating bearing conditions, and providing accurate representation
of bearing and grease condition. This poster outlines the methods for
obtaining representative grease samples in wind turbines, and analysis
methods performed on these samples.
Objectives
There is considerable difference between RDE and FdM-Fe results, and
RDE significantly underestimates the amount of iron wear particles in all
grease samples in this project. The explanation for this is most likely that a
significant amount of wear particles in grease from main bearings in wind
turbines are larger than 6-8 μm which is at the limit of sensitivity of the
RDE instrument. A key to the success of the ferrous debris measurement
is the configuration of the FdMPlus unit, in that the entire sample is
introduced to the field of the Hall-effect sensor, thus cancelling any slight
localized variations in ferrous debris distribution in the grease
(heterogeneity), and providing an average value for trending and
comparison. The project demonstrates that reliable measurement of
ferrous wear in grease from wind turbine can only be achieved using the
FdMPlus or similar measuring instruments.
Generally, moisture has several negative effects in tribo-systems and
moisture should be kept as low as possible. Similar to the above
mentioned verification of FdM-Fe analysis in grease, it is documented that
the combination of Grease Thief sampling and Karl Fischer (KF) Oven
Method analysis of moisture is a very accurate and reliable method for
assessment of water in main bearing greases. Trend analysis of moisture
revealed some surprising variations. In Figure 4 trends for moisture in front
and rear bearings in two units are shown. It is quite clear in these trends
that these separate turbines are experiencing a similar change in moisture,
increasing from March until June (moisture level triples) after which it is
slightly decreased. The key point here to observe is that this is a tool for
accurate tracking of moisture in grease.
Conclusions
References
1. Grease sampling and analysis of wind turbine drivetrain components, R.
Wurzbach, AWEA Poster Presentation, Chicago, Illinois, May 7, 2013
2. Analysis of Grease in Wind Turbine bearing – a tool for condition monitoring,
Part 2, H. Møller, et.al., LUBMAT Conference Proceedings, Manchester, UK,
June 26, 2014
Wind energy is foreseen to play a very important role in EU in the future,
and many countries in Europe have launched ambitious investment plans.
Vattenfall Renewable and DONG Energy are the major players in Off-shore
wind farms and both companies operate a substantial number of wind
farms in the North Sea.
Maintenance and operation of off-shore wind farms is a great challenge as
accessibility is limited and unplanned maintenance is very expensive.
Condition monitoring of key components in a modern wind turbine is an
absolute prerequisite. This research project evaluated sampling and
analysis of grease in wind turbines as a tool to assess the condition of
pitch-, yaw-, main- and generator bearings, with special focus on main
bearings.
The project was comprised of two parts. I) Development of methods for
representative sampling of greases from bearings used in modern wind
turbines; the present contribution describes the methodology to be
developed and the results of the first research forays. II) Development of a
comprehensive set of grease tests for condition monitoring as well as
screening of a number of bearings in existing in turbines.
Representative grease sampling from a tribo-system is a complex
undertaking. The method and sampling equipment developed were
evaluated against the Theory of Sampling (TOS) and for implementation
testing of bias-free sampling tools for extraction of increments for analysis.
An important aspect was the mapping of grease spatial heterogeneity in
bearings.
A key goal of these studies was to understand the critical considerations in
obtaining grease samples to ensure that the results will inform the proper
decisions regarding optimized maintenance of grease lubricated drivetrain
components. Advanced notice of degraded lubrication conditions allows
for proactive management of bearings and gears to ensure maximum life
and performance.
The sampling methods tested here met the requirements for
representative sampling per the Theory of Sampling. In the first part of this
project it was shown that extraction of grease increments from main
bearings using the Grease Thief gave an unbiased sample. Comparison
with microscopic evaluation of the particles and observation of the several
bearings removed from service confirms that the precision is absolutely
satisfactory and with a low overall uncertainty, and this sampling and
analysis scheme for ferrous wear metals in greases is an effective tool for
trend analysis.
This research has significantly strengthened the position that grease
analysis is a very important tool for conditioning monitoring of bearings in
wind turbines and it can serve as an effective and important routine
analysis in line with testing gear and hydraulic oils in wind turbines. This
project has also documented that appropriate sampling procedures and an
adequate test method should be used to provide correct values for level of
wear metals and moisture in greases.
Figure 2: Grease sampling from a damaged Main Bearing for 3-
dimensional sampling (Photo courtesy of DONG Energy)
Copyright 2013, York Laboratories, LLC
Abstract
Methods
Results
Sampling
The focus of this project was to evaluate methods to obtain meaningful
samples and apply analysis methods to those samples for wind turbine
main bearings. The methodologies for sampling collection was the
utilization of the active sampling devices described in ASTM D7718,
Standard Practice for Obtaining In-Service Samples of Lubricating Grease.
Two versions of these “grease thief” devices were used to produce an
approximate 1 gram sample. The first, as seen in the image below, was
inserted into an extension T-handle that allowed for remote actuation and
gathering of the sample in the area directly adjacent to the surface of the
moving bearing elements.
The second method was used to sample grease from the partially
disassembled main bearing for 3-dimensonal sampling. 3-dimensional
sampling involves taking multiple samples from various locations around
the bearing and comparing values to determine the distribution of the
measured properties and particles in the grease. This was performed
twice for this project, on two bearings that were removed from service after
a time in service in North Sea offshore wind farms. These samples were
obtained using a plastic spatula and syringe. The plastic spatula was used
to gather a series of 1-gram samples, placing them inside the opened
syringe, and then using the subsequently assembled syringe to inject the
sample into the grease sampler body used in the first sampling exercise.
This provided a uniform sample methodology in a standard sample
geometry, allowing for multiple analyses with this small sample size.
Analysis of Grease
Analysis of these small sized samples was enabled by the sampling device
itself, and the Die Extrusion process for grease consistency measurement
and sample preparation. First, the sampling device was placed into a Hall-
Effect sensor to measure the quantity of ferrous debris in the sample. This
provided a quantification in parts per million (ppm) of ferrous debris. The
sampling device was then threaded into a specially designed extrusion die,
which provided a flow channel for the grease as it exited the sampling
device. This extrusion was performed under controlled temperatures, and
a precisely varying rate to produce a load profile for a given sample. The
load profile, when compared to the new, fresh grease, provides an
assessment of the consistency of the grease and its flow dynamics,
important in ensuring proper lubrication. The extruded grease was
deposited as a thin-film on a plastic substrate for subsequent analysis.
The thin-film geometry allowed for multiple additional tests to be
performed, including tests to evaluate wear, consistency, contamination
and oxidation. The analysis methods included automated microscopic
particle counting, differential scanning colorimetry, Fourier-transform
infrared spectroscopy (FTIR), analytical ferrography, and colorimetric
analysis, among others.
Study of Samples
The 3-dimensional sampling, as shown in the image above, involves
collecting a spatially diverse set of samples from around the bearing
geometry, and evaluating the spatial variability of the grease analytes. The
purpose here was to note the heterogeneity of the grease in the housing.
In the case of the wind turbine main bearing, it is important that any
change in the grease or its constituents (wear particles, contaminants)
should be represented in the sample that is routinely taken from the
bearing. To evaluate this, two bearings were removed from service in off-shore
applications. The first was a bearing with a known bearing defect
as seen in the vibration signature for this bearing. The damage was
advanced, and the bearing was scheduled for replacement. The
opportunity was taken to carefully disassemble the bearing and
methodically gather samples from various locations from within the
housing. The second bearing was from a wind turbine that had suffered
known gearbox damage, but had no indications of bearing faults. This
bearing was sampled in a similar manner to obtain a 3-dimensional
sample. In both cases, the visual appearance of the bearing was noted,
and evidence of faults or damage on the bearing were recorded. It was
found that the first bearing had significant raceway damage, while the
second bearing had no appreciable fault or damage.
Among the analysis tests performed, statistical analysis was used to
evaluate trends and comparisons of values for both the ferrous debris
levels and the moisture levels seen in the target bearings. Ferrous debris
was compared by two methods, FdM (Hall-Effect), and Rotating Disk
Electrode (RDE), an atomic emission method. This comparison allowed
for insight into suitability of these common techniques used in liquid oil
analysis, and evaluate suitability and issues pertaining specifically to
grease. Moisture analysis is a difficult test for semi-solids like grease, yet
potentially a very important parameter. To achieve meaningful analysis,
the samples were extruded by a thin-film and exposed to a carrier gas in
an elevated temperature chamber (Oven Method) to quantify in a precise
and repeatable manner the moisture content in the analyzed grease
samples.
Acknowledgements
This project was made possible by the support of DONG Energy and Vattenfall,
and the participation of Hans Møller and Jan Ukonsaari of Vattenfall; Uffe Larsen,
Trine Giselsson, & Jan Jacobsen of DONG Energy; and Kim Esbensen of GEUS.
Figure 1: Grease sampling device and its use in extension T-handles to harvest
targeted grease samples (Photo at lower left courtesy of Oelcheck, Gmbh)
Figure 3: Comparison of FdM-Fe and RDE data.
Figure 4: Moisture in main bearing greases, Vestas V80 2 MW
(Grease: SKF LGWM 1)