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

Dawid Janse van Vuuren Avago Technologies Fiber, Germany
Co-authors:
Dawid Janse van Vuuren (1) F P Magnus Ahlstedt (1)
(1) Avago Technologies Fiber, Regensburg, Germany

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Presenter's biography

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

1985-1989: Bachelor degree in Electronic engineering
1990-1994: Masters degree in Electronic engineering (Remote Spectroscopy with Optical fibers)
1996 Alcatel (STC Frequency Technologies):
Design Engineer

1996 -1999: Eloptro (PTY) LTD: (Eloptro later Carl Zeiss)
Senior Design Engineer
Responsible for Laser rangefinder and designator development.

1999 – 2012: Periseo (PTY) LTD:
Director
Responsible for product and business development.
Involved in various R&D projects.
Free space optical communication, Optical fiber communications, Optical sensors and related projects.


Current job
Avago Technologies Fiber GmbH (Regensburg):
Research and Development Engineer
Currently involved in the area of POF sensor development.

Abstract

POF sensor for wind turbine load control & monitoring

Introduction

Plastic Optical Fiber (POF) is an attractive medium for sensing applications; especially when used in wind turbine blades. The use of POF as sensing element is advantageous due to its low cost, ease of coupling and termination, high resistance to breakage and electromagnetic immunity.
The application of this technology for management and control of turbine and tower loading provides several advantages.


Approach

The Avago Optical Phase Interrogator (OPI) strain sensor system was already described in the past; presenting data in relation to prototyping and integration of this technology into wind blades. The performance of the system in the real application and the relationship between specific events during wind power plant operation versus sensor output has been demonstrated in 14m blades. Active load management applied to wind turbines present various significant benefits, such as the active control of overload conditions.


Main body of abstract

The expected lifetime of the turbine can be increased by preventing overload conditions.

An active blade pitch control system can be used for wind turbine and tower load management. A control system involves three basic elements: sensors to measure process variables, actuators to manipulate energy capture and component loading, and control algorithms to coordinate the actuators based on information gathered by the sensors.

Our focus is on POF based sensor technology; applied to the turbine blade, to measure the load variations. We present the sensor evaluation campaign for load control applications using larger wind turbine blades.

The POF sensor evaluation approach:
1) Static evaluation of the POF technology in 52 meter blades under various loading scenarios.
2) Installation into an operational two bladed wind turbine implementing active load control.

The static tests were performed at an accredited wind turbine blade test facility for comparison to classical strange gauges, sensitivity and dynamic range validation. The POF sensor gauges were attached to the inside of the blade at about 1/3 from the root of the blade. The sensor output signal was captured for different blade loading scenarios. The test results confirm that the POF sensor technology performance variables matches the requirements needed for load management applications. Additional benefits are: 1) integration over a larger area of the blade, thus eliminating material micro-structural influences 2) inherent temperature compensation 3) ease of installation, and already previously presented benefits of using POF technology

The second stage of the measurement campaign (in an operational two bladed turbine) is in process.


Conclusion

Using the processed information from the sensor system; turbine companies can apply preventive maintenance, increase the blade and turbine lifetime, but also link controllers actively to the sensor system to improve performance (e.g. individual pitch control).

The use of POF Sensor technology using simple signal processing methods; provides cost and implementation advantages when used for blade load management.


Learning objectives
Application of POF based sensor technology for the measurement of strain in blades for active load monitoring and control applications.
Reduction of maximum loading on turbine and tower elements. Extension of lifetime. Reduction in manufacturing cost.