Detection of rotor imbalance, including root cause, severity and location

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. The method is capable of distinguishing among different root causes of the imbalance. In addition, the imbalance severity and location, i.e. the affected blade, can be identified. The automatic classification of the imbalance problem is obtained by using a neural network. The performance of the method is illustrated with the help of different fault scenarios, within a high-fidelity simulation environment

Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project

Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF)method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of aCAD(Computer AidedDetection) solution and for the assessment of its added value, in order to be applied along with an Immunologist as a second Reader in detection of autoantibodies. This CAD system is able to identify on IIF images the fluorescence intensity and the fluorescence pattern. Preliminary results show that CAD, used as second Reader, appeared to perform better than Junior Immunologists and hence may significantly improve their efficacy; compared with two Junior Immunologists, the CAD system showed higher Intensity Accuracy (85,5% versus 66,0% and 66,0%), higher Patterns Accuracy (79,3% versus 48,0% and 66,2%), and higher Mean Class Accuracy (79,4% versus 56,7% and 64.2%)

Predicting the Influence of Surface Protuberance on the Aerodynamic Characteristics of a NACA 63 3

Leading Edge Roughness (LER) has become a critical challenge for wind turbine operators, often reducing the energy production of their turbines. LER has not yet been systematically categorized, and the transfer function between height/extent of roughness and the aerodynamic performance has not been established. A common method for emulating LER is to use zigzag tape or distributed sand grain roughness in a wind tunnel. This paper contains 2D and 3D CFD simulations and wind tunnel tests with zigzag tape on a NACA 633-418 airfoil, to evaluate the changes in aerodynamic characteristics. Because 3D CFD requires a vast amount of computing power, it is investigated if 2D simulation gives a sufficient level of accuracy