Room:
Prandtl Hall
Topic:
F. Measurement, monitoring and experimental techniques
Form of presentation:
Oral
Duration:
120 Minutes
Chaired by: M. Kühn, J. Mann
10:30
Comparison of different modelling approaches of drive train temperature for the purposes of wind turbine failure detection
Jannis Tautz-Weinert | Loughborough University | United Kingdom
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Authors:
Jannis Tautz-Weinert | Loughborough University | United Kingdom
Simon Watson | United Kingdom
Effective condition monitoring techniques for wind turbines are needed to improve maintenance processes and reduce operational costs. Normal behaviour modelling of temperatures with information from other sensors can help to detect wear processes in drive trains. In a case study, modelling of bearing and generator temperatures is investigated with operational data from the SCADA systems of more than 100 turbines. The focus is here on automated training and testing on a farm level to enable an on-line system, which will detect failures without human interpretation. Modelling based on linear combinations, artificial neural networks, adaptive neuro-fuzzy inference systems, support vector machines and Gaussian process regression is compared. The selection of suitable modelling inputs is discussed with cross-correlation analyses and a sensitivity study, which reveals that the investigated modelling techniques react in different ways to an increased number of inputs.
10:50
Feasibility of large-scale calorimetric efficiency measurement for wind turbine generator drivetrains
Michael Pagitsch | RWTH Aachen University | Germany
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Authors:
Michael Pagitsch | RWTH Aachen University | Germany
Ralf Schelenz | Germany
Christian Liewen | Germany
Sebastian Reisch | Germany
Dennis Bosse | Germany
Georg Jacobs | Germany
Matthias Deicke | Germany
In the course of the global energy turnaround, the importance of wind energy is increasing continuously. For making wind energy more competitive with fossil energy, reducing the costs is an important measure. One way to reach this goal is to improve the efficiency. As the major potentials have already been exploited, improvements in the efficiency are made in small steps. One of the main preconditions for enabling these development activities is the sufficiently accurate measurement of the efficiency. This paper presents a method for measuring the efficiency of geared wind turbine generator drivetrains with errors below 0.5 % by directly quantifying the power losses. The presented method is novel for wind turbines in the multi-MW-class.
11:10
Investigations for Improvement of Energy Yield of Rotor-blades from the 1.5 MW Class
Torben Reichstein | Germany
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Authors:
Dr. Alois Peter Schaffarczyk | Kiel University of Applied Sciences | Germany
Nicolas Balaresque | Germany
Sven Bicker | Germany
Christoph Dollinger | Germany
A Fandrich | Germany
Michael Hoelling | Germany
Kai Irschick | Germany
Torben Reichstein | Germany
Cornelia von Zengen | Germany
In a combined approach of extensive measurement and accompanying simulation a wind turbine blade used in the 1.5 MW class was investigated for improvement of aerodynamic properties and especially the energy yield. One blade was dismantled and its geometry was locally measured by a specially designed laser scanning-system. From this geometry data set five 2D wind tunnel models were manufactured and measured in the wind tunnel of Deutsche Wind Guard Engineering GmbH at Bremerhaven, Germany. In addition, extensive CFD investigations were performed to investigate the usefulness of so-called aerodynamic devices like vortex generators, Gurney flaps and others for improving energy yield. As a result it could be shown that the aerodynamic efficiency of the manufactured blades - if measured in terms of lift-to-drag ratio - is at a high level but still can be further improved. 3D CFD investigations were able to show the influence of Gurney flaps and boundary layer fences and their interactions.
11:30
In-blade wind turbine blade angle of attack measurements and comparison with yaw models
Prof. David Johnson | University of Waterloo | Canada
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Authors:
Prof. David Johnson | University of Waterloo | Canada
Tyler Gallant | Canada
The torque generated by a wind turbine blade is dependent on several parameters, one of which is the angle of attack. Several models for predicting the angle of attack in yawed conditions have been proposed but there is a lack of experimental validation data. Experiments were conducted at the University of Waterloo Wind Generation Facility using a 3.4 m diameter test turbine. A five-hole pressure probe in a modular 3D printed blade was used to measure the angle of attack as a function of wind speed, radial position, yaw and azimuthal position. Experimental results were compared to angle of attack calculated using a model proposed by Morote. Modelled values were found to be in close agreement with the experimental results. The angle of attack was shown to vary cyclically in the yawed case. The quality of results indicates the potential of the developed instrument for wind turbine measurements.
11:50
Detection of rotor imbalance, including root cause, severity and location
Dr. Stefano Cacciola | POLITECNICO DI MILANO | Italy
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Authors:
Dr. Stefano Cacciola | POLITECNICO DI MILANO | Italy
Carlo Luigi Bottasso | Italy
Irene Munduate Agud | Italy
This paper presents a new way of detecting imbalances on wind turbine rotors, by using a harmonic analysis of the rotor response in the fixed frame. Rotor imbalances, irrespective of the causes, e.g. pitch misalignment, blade damage, ice accretion, etc., affect turbine fatigue and result, if protracted in time, in a reduced life. As operation and maintenance costs account for a significant portion of the cost of energy, methods capable of early detection of faults may be used for moving from a classical corrective maintenance approach to a predictive one. In this work, four different questions are considered: Is there a rotor imbalance? Which is the affected blade? What is the severity of the problem? What is causing it? The paper tries to address these needs by developing a novel detection technique based on neural networks. The performance of the algorithm is illustrated with the help of different fault scenarios, within a high-fidelity simulation environment.
12:10
Thermographic Stall Detection
Christoph Dollinger | University of Bremen | Germany
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Authors:
Christoph Dollinger | University of Bremen | Germany
Nicholas Balaresque | Germany
Alois Peter Schaffarczyk | Germany
Andreas Fischer | Germany
Thermographic wind tunnel measurements, both on a cylinder as well as on a 2D airfoil, were performed at various Reynolds numbers in order to evaluate the possibility of detecting and visualizing separated flow areas. A new approach by acquiring a series of thermographic images and applying a spatial-temporal statistical analysis allows improving both the resolution and the information content of the thermographic images. Separated flow regions become visible and laminar/turbulent transitions can be detected more accurately. The knowledge about possibly present stall cells can be used to confirm two-dimensional flow conditions and support the development of more effective and silent rotorblades.