Applications of Passive Vibration Control and Damage Detection in Composite Wind Turbine Blades PDF Download

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Applications of Passive Vibration Control and Damage Detection in Composite Wind Turbine Blades

Applications of Passive Vibration Control and Damage Detection in Composite Wind Turbine Blades PDF Author: Jeffery Dwayne Tippmann
Publisher:
ISBN: 9781321452037
Category :
Languages : en
Pages : 106

Book Description
The aim of this dissertation was to develop passive techniques for vibration control and structural health monitoring applications in structures operating in conditions of significant ambient noise. These goals were accomplished through the use of an experimental wind turbine blade that represents the materials and design of a full scale wind turbine with the inclusion of devices simulating the presence of known manufacturing defects. The vibration control aim was accomplished using a shunted array of piezoelectric elements tuned to the vibration properties of the blade skin. The macro-fiber composite (MFC) composite piezoelectric transducer was bonded to the wind turbine blade skin and connected to the tuned shunt circuit. The damage detection techniques were developed using both an aluminum plate and the experimental wind turbine blade. Two approaches using a reconstructed impulse response function are presented. The first examines the break in reciprocity of impulse response functions. A single similarity damage index was proposed and then extended into a multi-feature analysis. The second method applied linear and nonlinear beamforming techniques using an experimentally generated replica field and cross-spectral signal processing techniques. The passive reconstruction of the impulse response function between two sensors is an important topic in NDE and SHM. Previously studied methods using active pitch-catch approaches between any two sensors is well suited for structures such as wind turbine blades that experience significant amounts of noise during operation. The study of these approaches advances the understanding of passive damage detection using reconstructed impulse response functions.