Monitoring fatigue delamination growth in a wind turbine blade using passive thermography and acoustic emission

分层(地质) 热成像 声发射 材料科学 涡轮叶片 复合材料 巴黎法 弯曲 Spar平台 结构工程 涡轮机 红外线的 断裂力学 地质学 裂缝闭合 光学 工程类 地震学 航空航天工程 俯冲 物理 构造学
作者
Seyed Sina Samareh‐Mousavi,Xiao Chen,Malcolm McGugan,С. Г. Семенов,Peter Berring,Kim Branner,Niels Ludwig
出处
期刊:Structural Health Monitoring-an International Journal [SAGE Publishing]
卷期号:23 (5): 2906-2921 被引量:18
标识
DOI:10.1177/14759217231217179
摘要

Damage monitoring is an essential step to understand fatigue damage growth in composite wind turbine blades and for reliable lifetime prediction. The current study is an experimental investigation of fatigue delamination induced by an intentionally embedded defect in the spar cap of a 31 m wind turbine blade. A constant cyclic flap-wise bending was applied to the blade for 320,000 cycles. Delamination growth is identified and measured by visual inspection, acoustic emission (AE), and infrared thermography of the blade surface. It was observed that the area of delaminated regions grew faster during the early cycles, then their growth rates decreased, and the interlayer cracks reached stable growth. The experiment shows fatigue delamination develops gradually in the spar cap and allows monitoring of the damage before reaching a critical stage. The ability of AE and thermography methods to detect subsurface damage is demonstrated by the identification of steady delamination growth during cyclic load. Damage localization by both methods is in good agreement with the delamination location. Most acoustic activities are spotted in the boundaries of delaminated regions, and the position of a significant number of acoustic activities with the highest energy content correlates with the location of delamination crack fronts. It is shown that the surface temperature distribution contour indicates the shape of the largest delaminated region, and the growth of the hot region area correlates with damage propagation. However, multiple delaminations through the thickness cannot be discriminated from the thermal images.
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