Detection of defects in wind turbine composite blades using statistically enhanced Lock-In Thermography

被引:20
作者
Manohar, Arun [1 ]
di Scalea, Francesco Lanza [1 ]
机构
[1] Univ Calif San Diego, Dept Struct Engn, NDE & SHM Lab, La Jolla, CA 92093 USA
来源
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL | 2013年 / 12卷 / 5-6期
基金
美国国家科学基金会;
关键词
Lock-In Thermography; multivariate outlier analysis; composite structures; defect detection; NONDESTRUCTIVE EVALUATION;
D O I
10.1177/1475921713498531
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Delaminations are a common type of defect that occurs in composite structures such as wind turbine blades. In this study, a nondestructive testing technique based on Lock-In Thermography is proposed to detect skin-skin delaminations and skin-core delaminations present in a 9-m CX-100 wind turbine blade. A set of image processing algorithms and multivariate outlier analysis were used in conjunction with the classical Lock-In Thermography technique to counter the blind frequency effects and to improve the defect contrast. Receiver operating characteristic curves were used to quantify the gains obtained by using multivariate outlier analysis. Experiments were performed on a set of 16 defects of various sizes that were incorporated during the construction of the CX-100 wind turbine blade at different locations and depths.
引用
收藏
页码:566 / 574
页数:9
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