Group velocity and characteristic wave curves of Lamb waves in composites: Modeling and experiments

Wang, Lei; Fang, Yuan

doi:10.1016/j.compscitech.2006.09.023

Cited by 271 publications

(173 citation statements)

References 26 publications

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“…In guided wave analysis of composites, the hypothesis of considering each layer isotropic across the thickness is commonly adopted; each ply is a homogeneous orthotropic layer. This assumption is based on the fact that the wavelengths of the propagating guided waves are substantially longer than the characteristic size of the cross section of the fibres (Tauchert and Guzelsu 1972;Wang and Yuan 2007). In Tauchert and Guzelsu (1972), it is shown that the scattering produced by the fibres of each layer occurs when the wavelength is of the same order of the diameter of the fibres for longitudinal modes, and 40 times the order of the diameter for flexural modes.…”

Section: Simulationmentioning

confidence: 99%

“…This distinction expands the previous definition of the phase velocity for anisotropic materials in order to involve in the equation the direction of the wave vector, which can be expressed as Eq. (3.6) (Wang and Yuan 2007):…”

Section: Guided Waves In Compositesmentioning

confidence: 99%

“…Hereafter called symmetric S i , antisymmetric A i and shear horizontal SH i modes for simplicity reasons. The attenuation is another factor to have in mind for guided wave propagation in composites, since it gets significant at higher frequencies, due to the viscoelastic behaviour of the resin which damps the wave energy and also because of the scattering caused by the fibres (Wang and Yuan 2007).…”

Section: Guided Waves In Compositesmentioning

confidence: 99%

“…(3.4b) presented before, the group velocity can be defined as Eq. (3.8) (Wang and Yuan 2007;Karmazin et al 2013):…”

Section: Guided Waves In Compositesmentioning

confidence: 99%

“…So the skew angle will be zero and the wave vector and group velocity will have the same direction. Group velocity wave front (Wang and Yuan 2007) Geometrically, the wave vector can be related to the group velocity, see Fig. 3.13.…”

Section: Guided Waves In Compositesmentioning

confidence: 99%

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Damage Sensing in Blades

Crespo

2016

Mare-Wint

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This chapter is divided into three parts; the problem, possible solutions and the chosen option to address the problem, which is my PhD topic within the project MAREWINT. So firstly, the chapter presents an overview of the typical damages that a wind turbine blade can suffer during its life operation. Then, a review of different Structural Health Monitoring (SHM) techniques which are currently being investigated for wind turbine blades is presented. Finally, the chapter provides the state-of-the-art of Guided Wave Technology in composite materials; where different aspects of this SHM technique are explained in more detail. IntroductionWind energy is an important renewable energy source which has gained high relevance during the last decades. Different countries have released plans to invest in wind energy in the future years; such as the USA that will generate 20 % of the country's electricity from wind power by 2030 or Denmark that have set the targets of producing 50 % of the power from the wind by 2020 and also of making Denmark completely free of dependence on fossil fuels by 2050. So, the use of wind power is not expected to decrease within the next decade (Márquez et al. 2012). The trend is to manufacture bigger wind turbines and deploy them offshore. These new wind turbines have around 6 MW power output, 120-metre height tower and 80-metre long blades. They are designed to be operating in rough conditions in difficult-to-reach areas. Therefore, the deployment of Structural Health Monitoring (SHM) techniques becomes essential in order to assess remotely the integrity of the structure. The advantages of using these techniques are many (Schulz and Sundaresan 2006), such as reducing expensive costs for periodic inspections of turbines which are hard to reach, prevention of unnecessary replacement of components based on time of use, or minimizing down time and frequency of sudden breakdowns.

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Section: Simulationmentioning

confidence: 99%

Section: Guided Waves In Compositesmentioning

confidence: 99%

Section: Guided Waves In Compositesmentioning

confidence: 99%

“…(3.4b) presented before, the group velocity can be defined as Eq. (3.8) (Wang and Yuan 2007;Karmazin et al 2013):…”

Section: Guided Waves In Compositesmentioning

confidence: 99%

Section: Guided Waves In Compositesmentioning

confidence: 99%

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Damage Sensing in Blades

Crespo

2016

Mare-Wint

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Development of Material‐Integrated Actuator‐Sensor‐Arrays for Obstacle Sensing

et al. 2018

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The specific manufacturing processes of fiber‐reinforced plastics (FRP) enable a seamless integration of sensors and actuators, allowing realization of tasks that are additional to the main load bearing functionality, for example, obstacle distance sensing. Through the integration of several distributed piezoelectric actuators into a FRP component and their time‐shifted actuation, a directional plate wave can be generated. The interaction of the plate wave with the surrounding medium induces a sound wave, which − reflected from an obstacle − returns toward the component and forms a plate wave, that is, detected by another integrated transducer array. Since the time between the generation of the initial wave and the reflected wave appearance is a linear function of the distance to the obstacle, an appropriate evaluation enables the realization of the obstacle distance sensing functionality. Presented experimental investigations are conducted to confirm the feasibility of the above described operational principle. It is shown that a directional generation of plate waves and their radiation in surrounding medium can be achieved using a suitable actuator‐sensor arrangement. The operating principle is successfully demonstrated for exemplary textile‐reinforced composite plate with integrated piezoceramic actuator‐sensor transducer arrays.

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Acoustic emission source location in unidirectional carbon‐fiber‐reinforced plastic plates with virtually trained artificial neural networks

Caprino

Lopresto

Leone

et al. 2011

J of Applied Polymer Sci

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Acoustic emission (AE) source location in a unidirectional carbon-fiber-reinforced plastic plate was attempted with artificial neural network (ANN) technology. The AE events were produced by a lead break, and the response wave was received by piezoelectric sensors. The time of arrival, determined through the conventional threshold-crossing technique, was used to measure the dependence of the wave velocity on the fiber orientation. A simple empirical formula, relying on classical lamination and suggested by wave-propagation theory, was able to accurately model the experimental trend. On the basis of the formula, virtual training and testing data sets were generated for the case of a plate monitored by three transducers and were adopted to select two potentially effective ANN architectures. For final validation, experimental tests were carried out, with the source positioned at predetermined points evenly distributed within the plate area. A very satisfactory correlation was found between the actual source locations and those predicted by the virtually trained ANNs.

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Group velocity and characteristic wave curves of Lamb waves in composites: Modeling and experiments

Cited by 271 publications

References 26 publications

Damage Sensing in Blades

Damage Sensing in Blades

Development of Material‐Integrated Actuator‐Sensor‐Arrays for Obstacle Sensing

Acoustic emission source location in unidirectional carbon‐fiber‐reinforced plastic plates with virtually trained artificial neural networks

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