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Delegates are invited to meet and discuss with the poster presenters in this topic directly after the session 'On- and off-shore installation technologies' taking place on Wednesday, 12 March 2014 at 11:15-12:45. The meet-the-authors will take place in the poster area.

Patxi Etxaniz atten2, Spain
Co-authors:
Patxi Etxaniz (1) F P Eneko Gorritxategi (1) Jesús Terradillos (2)
(1) atten2, Eibar, Spain (2) IK4-Tekniker, Eibar, Spain

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Presenter's biography

Biographies are supplied directly by presenters at EWEA 2014 and are published here unedited

Mr. Etxaniz got his degree in Aeronautical Engineering at the Universidad Politécnica de Madrid. He has been working in Research Centers and Universities for more than 20 years. He is currently the Chief Executive Officer of atten2, a spin-off of IK4-Tekniker Research Center, for the development and marketing of online sensors for fluid monitoring.

Abstract

OIL CONDITION MONITORING SYSTEM FOR WIND TURBINE MONITORING

Introduction

Wind Energy association statistics says that changing from Preventive to Predictive maintenance, the reduction of maintenance costs is around 47%.
Predictive maintenance tries to assess the condition of machines scheduling maintenance actions just when is really necessary.

This presentation shows an innovative Oil Condition Monitoring System.
This new technological development measures the particle content, particle size and shape and classify wear particle depending on the root cause in order of early detection of failures.
Additionally the degradation of the oil is measured in order to ensure the proper lubrication within the machine.



Approach

Wind farms operate in exigent and extreme environmental conditions. This is especially important in offshore wind farms. In addition, these environmental conditions could reduce significantly the time interval for maintenance purposes. Therefore more attention is being paid on Operations and Maintenance (O&M) tasks.
In addition the current situation of renewable energies in Europe, makes that wind farms operators become more interested in reducing O&M costs.
Establishing of an appropriate Condition Monitoring System (CMS) allows knowing the real condition of the turbine, carrying out a prognosis or identification of future failures and at the same time entails a Predictive Maintenance (PdM), which allows a more efficient schedule of the maintenance strategy. With PdM is possible to increase the operating time, the productivity, and the availability and to reduce the failure risk. At the same time the maintenance cost is reduced because the maintenance tasks are done only if necessary.
One of the most critical components in a wind turbine is the gearbox where the lubricant oil is nowadays an element which is monitorized, and offers very interesting information about the status of the gearbox. The degradation and contamination of lubricating oil are the main causes of most of important failures, and because of that the monitoring of lubricating oil is extremely important. Historically the monitoring of lubricant oil has been carried out by means of periodically oil sampling which are analyzed in the laboratory. The actual procedures are changing fast towards intelligent systems integrated within the machine, which allow the continuous monitorization of the status of the oil. These systems provide information which allows the change from Preventive or Reactive Maintenance to Predictive Maintenance.



Main body of abstract

Current technology enables the online measurement of the most important parameters in the oil condition. These include the measurement of the degradation status of the oil and the presence of particles in the oil.
Oil degradation is the physical-chemical process by the oil loses its lubricating properties until it finally becomes more viscous and does not perform their functions properly.
Currently the oil change is done preventively. I.e. the oil is changed before it can present any problems. On the IK4-Tekniker oils laboratory we have found that with this procedure lubricating oil is replaced being in perfect conditions of use.
The maintenance managers we consulted are aware of this problem. But the laboratory analysis cannot ensure that the oil is going to continue in good condition until the following analysis. So the dilemma is how optimize oil change and do so safely.
The proposed solution is the online monitoring of the degradation of oil. OilHealth® is the perfect tool to optimize the oil change. OilHealth® gives real-time and reliable measure of oil degradation, since the oil is fresh until it is fully degraded. OilHealth® is an optical sensor that measures the absorbance changes in some spectral bands. We have correlated this spectrum with the degradation stage of the lubricant oil. The sensor gives a percentage value which indicates the remaining lifetime of the oil.
This technology has enough precision to provide a linear measure of the degradation that easily allows to make extrapolations about the future state of the oil and the time optimum time to make the change. And make this change safely. Our estimates are that it is possible to double the life of the oil, producing important benefits economic (for the cost of oil) and environmental (for recycling).

The particles present in the oil can have two origins:
-External particles that pollute the oil. These particles may be very harmful for the machine if they are not properly filtered.
-Wear particles produced by the machine itself.
The detection of wear particles is very interesting because they allow to know the status of the machine and the early detection of possible failures. In fact monitoring the particles present in the oil is one of the methods that can detect the initial stages of failure of the machines before.

Currently, there are several technologies and products that enable online monitoring of the particles present in the oil. From lesser to greater complexity and price, the key technologies are:
- Magnetic: provides the global quantity of magnetic particles that are in the fluid.
- Optical counter: sees the shadow of the particles in a laser beam. This technology has the ability to count the particles by sizes according to standards like ISO 4406.
- Optical: performs a picture of oil and obtain measurement by digital processing. This technology allows to count the particles by sizes (ISO 4406) and to do the recognition of the root cause of the particles.
OilWear® sensor is a low cost device to detect particles within the lubricating oil and its classification according to the Standard ISO 4406, and to do the recognition of the root cause of the particles.
Our patented technology allows integrating in a one sensor two optical technologies: the measurement of the degradation and the optical measurement of the particles. In order to offer a complete diagnostic about two of the most important parameters of the lubricating oil: particle content and degradation.
Online devices never will offer the same quality in their measurements as laboratory techniques but the integration of technologies and measurements will offer a better understanding of the lubricant stage.



Conclusion

As published by BNEF, the costs of maintenance of wind farms in Spain have been reduced from €30.900 /Mw in 2008 to €19.200 /Mw in 2012. In order to continue with this reduction in costs the change in strategy is necessary. From a Preventive/Reactive Maintenance to a Predictive Maintenance.
For this change in strategy, it is imperative to have a Condition Monitoring System that provides precise, clear, useful and real-time information about the real state of the machines.
From all the elements that can be monitored in a wind turbine, oil is one that provides more useful information.
Currently, there are online low cost sensors with enough precision to make this change of maintenance strategy.
This article is focuses in two of the main parameters that can be measured in the oil:
-Degradation: the measurement of this parameter allows the improvement of procedures for the oil change. In this way it is possible to safely, optimize oil change prolonging, very significantly, its life.
- The presence of debris particles in the oil: by detecting the amount of particles produced by the machine and its root cause, is possible the early detection of failures, allowing early corrective actions with a significant reduction of maintenance costs.
The improvement of maintenance procedures, based in the information on online oil sensors, produces significant benefits:
-Reduce the costs of O&M since maintenance tasks are performed only when they are needed.
-Environmental benefits by reducing the amount of materials those need recycling.
- Increase machine operating time, productivity and availability, and reduce unplanned downtime.




Learning objectives
The online oil monitoring obtains key information that allows the improvement of maintenance procedures, from a Preventive/Reactive Maintenance to a Predictive Maintenance. This improvement of maintenance procedures produces significant benefits:
-Reduce the costs of O&M since maintenance tasks are performed only when they are needed.
-Environmental benefits by reducing the amount of materials those need recycling.
- Increase machine operating time, productivity and availability, and reduce unplanned downtime.




References
[1] D.C. Schalcosky et al. "Advances in real time oil analysis”. Practising Oil Analysis. Pag 28-37 Nov-December 2000
[2] A. Aranzabe, J. Terradillos, A. Arnaiz, S. Merino, D. Gomez. "Application of Microtechnologies in on-line condition monitoring of lubricants". Communication. Tribology and Lubrication Engineering January 13-15, 2004, Stuttgart/Ostfildern, Germany.