Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.635540
Title: Structural health monitoring of wind turbine blades using guided wave NDT technique
Author: Burnham, Kenneth C.
ISNI:       0000 0004 5357 1309
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2014
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Abstract:
Wind energy is an increasingly important contributor of power within the renewable energy sector. In the year to 2012, wind generation within the United Kingdom (UK) increased 40% meeting 6% of the UK's national electricity demand. The UK is committed to providing 15% of its energy from renewable resources by 2020. Currently, the UK has approximately 40% of Europe's entire wind resource with significant potential for development of both on and offshore wind. In recent years, the number of reports on defective blades contributing towards turbine failure has grown. Blade manufacturers have privately reported a recurring problem with the spar cap - a critical strengthening component - which when weakened by damage, hastens the onset of operational failure. The contents of this thesis consider composite materials used within the blade and the detection techniques appropriate for in-field implementation. Application of Guided Waves, in particular Lamb waves, suits the typical dimensions of the blade composite structure. Experiments were conducted to understand the characteristics of Lamb wave modes within glass fibre reinforced plastic (GFRP) to assess attenuation levels; modal propagation; and dispersion with respect to fibre orientation. Finite Element Analysis (FEA) was used to observe material characteristics and discern possible modes of wave propagation. To exploit the directional qualities of GFRP, directional Macro Fibre Composite (MFC) sensors were applied to a wind turbine blade providing low-profile, light-weight, durability and conformability with sufficient sensitivity to detect elastic disturbance over large areas. Parametric monitoring of GFRP samples under loading identified tensile stress from defect onset. Cross correlation and sliding-window correlation signal processing techniques on recorded data from the applied sparse array identified the onset of fibre damage using Guided wave modes. This technique was able to identify modal changes to specific defects providing the prospect for in-situ blade monitoring.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.635540  DOI: Not available
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