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Acoustic Emission Signal Analysis and Damage Mode Identification of Composite Wind Turbine Blades covers both the underlying theory and various techniques for effective structural monitoring of composite wind turbine blades via acoustic emission signal analysis, helping readers solve critical problems such as noise elimination, defect detection, damage mode identification, and more. Author Pengfei Liu introduces techniques for identifying and analyzing progressive failure under tension, delamination, damage localization, adhesive composite joint failure, and other degradation phenomena, outlining methods such as time-difference, wavelet, machine learning, and more including combined methods. The disadvantages and advantages of using each method are covered as are techniques for different blade-lengths and various blade substructures. Piezoelectric sensors are discussed as is experimental analysis of damage source localization. The book also takes great lengths to let readers know when techniques and concepts discussed can be applied to composite materials and structures beyond just wind turbine blades. Features fundamental acoustic emission theories and techniques for monitoring the structural integrity of wind turbine blades Covers sensor arrangements, noise elimination, defect detection, and dominating damage mode identification using acoustic emission techniques Outlines the wavelet method, the time-difference defect detection method, and damage mode identification techniques using machine learning Discusses how the techniques covered can be extended and adapted for use in other composite structures under complex loads and in different environments
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.
This book concerns the development of novel finite elements for the structural analysis of composite beams and blades. The introduction of material damping is also an important aspect of composite structures and it is presented here in terms of their static and dynamic behavior. The book thoroughly presents a new shear beam finite element, which entails new blade section mechanics, capable of predicting structural blade coupling due to composite coupling and/or internal section geometry. Theoretical background is further expanded towards the inclusion of nonlinear structural blade models and damping mechanics for composite structures. The models effectively include geometrically nonlinear terms due to large displacements and rotations, improve the modeling accuracy of very large flexible blades, and enable the modeling of rotational stiffening and buckling, as well as, nonlinear structural coupling. Validation simulations on specimen level study the geometric nonlinearities effect on the modal frequencies and damping values of composite strips of various angle-ply laminations under either tensile or buckling loading. A series of correlation cases between numerical predictions and experimental measurements give credence to the developed nonlinear beam finite element models and underline the essential role of new nonlinear damping and stiffness terms.
In the wind industry, the current trend is towards building larger and larger turbines. This presents additional structural challenges and requires blade materials that are both lighter and stiffer than the ones presently used. This study is aimed to aid the work of designing new wind turbine blades by providing a comparative study of different composite materials. A coupled Finite-Element-Method (FEM) - Blade Element Momentum (BEM) code was used to simulate the aerodynamic forces subjected on the blade. For this study, the finite element study was conducted on the Static Structural Workbench of ANSYS, as for the geometry of the blade it was imported from a previous study prepared by Cornell University. Confirmation of the performance analysis of the chosen wind turbine blade is presented and discussed including the generated power, tip deflection, thrust and tangential force for a steady flow of 8m/s. A homogenization method was applied to derive the mechanical properties and ultimate strengths of the composites. The Tsai-Hill and Hoffman failure criterions were both conducted to the resulting stresses and shears for each blade composite material structure to determine the presence of static rupture. A progressive fatigue damage model was conducted to simulate the fatigue behavior of laminated composite materials, an algorithm developed by Shokrieh.
This paper gives a brief overview of a new project at LANL in structural damage identification for wind turbines. This project makes use of modeling capabilities and sensing technology to understand realistic blade loading on large turbine blades, with the goal of developing the technology needed to automatically detect early damage. Several structural health monitoring (SHM) techniques using piezoelectric active materials are being investigated for the development of wireless, low power sensors that interrogate sections of the wind turbine blade using Lamb wave propagation data, frequency response functions (FRFs), and time-series analysis methods. The modeling and sensor research will be compared with extensive experimental testing, including wind tunnel experiments, load and fatigue tests, and ultrasonic scans - on small- to mid-scale turbine blades. Furthermore, this study will investigate the effect of local damage on the global response of the blade by monitoring low-frequency response changes.
The objective of the program was to demonstrate and verify Certification-by-Analysis (CBA) capability for wind turbine blades made from advanced lightweight composite materials. The approach integrated durability and damage tolerance analysis with robust design and virtual testing capabilities to deliver superior, durable, low weight, low cost, long life, and reliable wind blade design. The GENOA durability and life prediction software suite was be used as the primary simulation tool. First, a micromechanics-based computational approach was used to assess the durability of composite laminates with ply drop features commonly used in wind turbine applications. Ply drops occur in composite joints and closures of wind turbine blades to reduce skin thicknesses along the blade span. They increase localized stress concentration, which may cause premature delamination failure in composite and reduced fatigue service life. Durability and damage tolerance (D & DT) were evaluated utilizing a multi-scale micro-macro progressive failure analysis (PFA) technique. PFA is finite element based and is capable of detecting all stages of material damage including initiation and propagation of delamination. It assesses multiple failure criteria and includes the effects of manufacturing anomalies (i.e., void, fiber waviness). Two different approaches have been used within PFA. The first approach is Virtual Crack Closure Technique (VCCT) PFA while the second one is strength-based. Constituent stiffness and strength properties for glass and carbon based material systems were reverse engineered for use in D & DT evaluation of coupons with ply drops under static loading. Lamina and laminate properties calculated using manufacturing and composite architecture details matched closely published test data. Similarly, resin properties were determined for fatigue life calculation. The simulation not only reproduced static strength and fatigue life as observed in the test, it also showed composite damage and fracture modes that resemble those reported in the tests. The results show that computational simulation can be relied on to enhance the design of tapered composite structures such as the ones used in turbine wind blades. A computational simulation for durability, damage tolerance (D & DT) and reliability of composite wind turbine blade structures in presence of uncertainties in material properties was performed. A composite turbine blade was first assessed with finite element based multi-scale progressive failure analysis to determine failure modes and locations as well as the fracture load. D & DT analyses were then validated with static test performed at Sandia National Laboratories. The work was followed by detailed weight analysis to identify contribution of various materials to the overall weight of the blade. The methodology ensured that certain types of failure modes, such as delamination progression, are contained to reduce risk to the structure. Probabilistic analysis indicated that composite shear strength has a great influence on the blade ultimate load under static loading. Weight was reduced by 12% with robust design without loss in reliability or D & DT. Structural benefits obtained with the use of enhanced matrix properties through nanoparticles infusion were also assessed. Thin unidirectional fiberglass layers enriched with silica nanoparticles were applied to the outer surfaces of a wind blade to improve its overall structural performance and durability. The wind blade was a 9-meter prototype structure manufactured and tested subject to three saddle static loading at Sandia National Laboratory (SNL). The blade manufacturing did not include the use of any nano-material. With silica nanoparticles in glass composite applied to the exterior surfaces of the blade, the durability and damage tolerance (D & DT) results from multi-scale PFA showed an increase in ultimate load of the blade by 9.2% as compared to baseline structural performance (without nan ...