Malcolm McGugan

Damage tolerance and structural monitoring for wind turbine blades.

The paper proposes a methodology for reliable design and maintenance of wind turbine rotor blades using a condition monitoring approach and a damage tolerance index coupling the material and structure. By improving the understanding of material properties that control damage propagation it will be possible to combine damage tolerant structural design, monitoring systems, inspection techniques and modelling to manage the life cycle of the structures. This will allow an efficient operation of the wind turbine in terms of load alleviation, limited maintenance and repair leading to a more effective exploitation of offshore wind.

Multivariate data-driven modelling and pattern recognition for damage detection and identification for acoustic emission and acousto-ultrasonics

Different methods are commonly used for non-destructive testing in structures; among others, acoustic emission and ultrasonic inspections are widely used to assess structures. The research presented in this paper is motivated by the need to improve the inspection capabilities and reliability of structural health monitoring (SHM) systems based on ultrasonic guided waves with focus on the acoustic emission and acousto-ultrasonics techniques. The use of a guided wave based approach is driven by the fact that these waves are able to propagate over relatively long distances, and interact sensitively and uniquely with different types of defect. Special attention is paid here to the development of efficient SHM methodologies. This requires robust signal processing techniques for the correct interpretation of the complex ultrasonic waves. Therefore, a variety of existing algorithms for signal processing and pattern recognition are evaluated and integrated into the different proposed methodologies. As a contribution to solve the problem, this paper presents results in damage detection and classification using a methodology based on hierarchical nonlinear principal component analysis, square prediction measurements and self-organizing maps, which are applied to data from acoustic emission tests and acousto-ultrasonic inspections. At the end, the efficiency of these methodologies is experimentally evaluated in diverse anisotropic composite structures.

Materials for Wind Turbine Blades: An Overview

A short overview of composite materials for wind turbine applications is presented here. Requirements toward the wind turbine materials, loads, as well as available materials are reviewed. Apart from the traditional composites for wind turbine blades (glass fibers/epoxy matrix composites), natural composites, hybrid and nanoengineered composites are discussed. Manufacturing technologies for wind turbine composites, as well their testing and modelling approaches are reviewed.

Crack Detection in Fibre Reinforced Plastic Structures Using Embedded Fibre Bragg Grating Sensors: Theory, Model Development and Experimental Validation

In a fibre-reinforced polymer (FRP) structure designed using the emerging damage tolerance and structural health monitoring philosophy, sensors and models that describe crack propagation will enable a structure to operate despite the presence of damage by fully exploiting the material’s mechanical properties. When applying this concept to different structures, sensor systems and damage types, a combination of damage mechanics, monitoring technology, and modelling is required. The primary objective of this article is to demonstrate such a combination. This article is divided in three main topics: the damage mechanism (delamination of FRP), the structural health monitoring technology (fibre Bragg gratings to detect delamination), and the finite element method model of the structure that incorporates these concepts into a final and integrated damage-monitoring concept. A novel method for assessing a crack growth/damage event in fibre-reinforced polymer or structural adhesive-bonded structures using embedded fibre Bragg grating (FBG) sensors is presented by combining conventional measured parameters, such as wavelength shift, with parameters associated with measurement errors, typically ignored by the end-user. Conjointly, a novel model for sensor output prediction (virtual sensor) was developed using this FBG sensor crack monitoring concept and implemented in a finite element method code. The monitoring method was demonstrated and validated using glass fibre double cantilever beam specimens instrumented with an array of FBG sensors embedded in the material and tested using an experimental fracture procedure. The digital image correlation technique was used to validate the model prediction by correlating the specific sensor response caused by the crack with the developed model.

Embedded Fibre Bragg Grating Sensor Response Model: Crack Growing Detection in Fibre Reinforced Plastic Materials

This article presents a novel method to simulate the sensor output response of a Fibre Bragg Grating (FBG) sensor when embedded in a host material (Composite material or adhesive), during a crack growing/damage event. A finite element model of the crack growth mechanisms was developed, and different fracture modes were addressed. Then an output algorithm was developed to predict the sensor spectrum change during the different stages of the crack growing. Thus, it is possible to identify specific phenomenon that will only happen within the proximity of a crack, as compression field ahead the crack or non-uniform strain, and then identify the presence of such damage in the structure. Experimental tests were conducted in order to validate this concept and support the model. The FBG sensor response model was applied in a delamination of a Wind Turbine trailing edge, to demonstrate the applicability of this technique to more complicated structures, and to be used as a structural health monitoring design tool.

Non-Destructive Analysis of Wind Turbine Blade Structural Integrity

The hollow profile of a wind turbine blade is subject to high levels of deformation when under the crushing pressure that is induced by flapwise loading. The load bearing box girder will ovalize under the pressure like forces and the shear sandwich webs and monolithic composite flanges are critical components whose failure may cause overall blade failure. This paper addresses the underlying causes of failure for these two parts by performing individual representative mechanical testing on them, and using digital image correlation (DIC) and acoustic emissions (AE) monitoring. Results show that the strength of the flange is primarily determined by the tensile strength of a relatively thin biaxial layer in this complex design. The buckling tests performed on sandwich material show that DIC is useful in determining the causes of failure, whilst AE monitoring has potential for in-situ monitoring of these structures, and is able to provide important data about the damage inside a blade.© 2009 ASME

Design of Wind Turbine Blades

In this section the research program framework for European PhD network MARE-WINT is presented, particularly the technology development work focussing on reliability/maintenance and the models describing multi-body fluid structure interaction for the Rotor Blade structure. In order to give a context for the effort undertaken by the individual researchers this section gives a general background for Wind Turbine blades identifying the trends and issues of importance for these structures as well as concepts for “smarter” blades that address these issues.

Fibre Bragg Grating Sensor Signal Post-processing Algorithm: Crack Growth Monitoring in Fibre Reinforced Plastic Structures

A novel method to assess a crack growing/damage event in fibre reinforced plastic, using conventional single mode Fibre Bragg Grating sensors embedded in the host material is presented in this article. Three different damage mechanisms that can change the sensor output, longitudinal strain \( \varepsilon_{xx} \), transversal stress \( \sigma_{yy,zz} \), and non-uniform strain \( \varepsilon_{xx} (xx) \), were identified. These damage mechanisms were identified during the experimental testing and linked with the sensor output using a digital image correlation technique. A dedicated algorithm to extract information from the reflected spectrum that enables crack detection was developed. Double Cantilever Beams specimens made with glass fibre and bonded with structural adhesive, were instrumented with a Fibre Bragg Grating array embedded in the host material, and tested using an experimental fracture procedure. This method was successfully validated in three different loading conditions, where were obtained very promising results that enable crack growth monitoring.

Crack growth monitoring by embedded optical Fibre Bragg Grating sensors: Fibre reinforced plastic crack growing detection

This article presents a novel method to assess a crack growing/damage event in fibre reinforced plastic, or adhesive using Fibre Bragg Grating (FBG) sensors embedded in a host material. Different features of the crack mechanism that induce a change in the FBG response were identified. Double Cantilever Beams specimens made with glass fibre glued with structural adhesive, were instrumented with an array of FBG sensors embedded in the material and tested using an experimental fracture procedure. A digital image correlation technique was used to determine the presence of the specific phenomena caused by the crack, and to correlate with the FBG sensor. A Material-Sensor model was developed in order to predict the sensor output response under a crack/delamination situation, which can be used as an analysis tool for future application of this measurement technology in more complex structures.