Quantitative damage detection and sparse sensor array optimization of carbon fiber reinforced resin composite laminates for wind turbine blade structural health monitoring.
Quantitative damage detection and sparse sensor array optimization of carbon fiber reinforced resin composite laminates for wind turbine blade structural health monitoring.
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用于风力涡轮机叶片结构健康监测的碳纤维增强树脂复合材料层压板的定量损伤检测和稀疏传感器阵列优化
DOI：
10.3390/s140407312
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发表时间：
2014-04-23
期刊：
影响因子：
--
通讯作者：
Chen X
中科院分区：
文献类型：
--
作者：
Li X;Yang Z;Chen X
针对风力涡轮机叶片 (WTB) 复杂复合材料层合结构的主动结构健康监测 (SHM) 方法解决了重要且复杂的信号噪声问题。在阐述了风能行业的发展前景及其对健康管理的关键要求后，提出了一种基于邻近系数的改进的冗余第二代小波变换（IRSGWT）预处理算法，用于微弱信号去噪。该方法可以避免传统小波方法在变换中丢失信息的缺点以及冗余第二代小波(RSGWT)去噪可能导致误差传播的缺点。对于大规模WTB复合材料，如何在保证精度的同时最大限度地减少传感器数量也是一个关键问题。提出了一种用于 WTB 应用的复合材料稀疏传感器阵列优化，可以减少必须使用的传感器数量。与完整的 16 个换能器阵列相比，优化的 8 个换能器配置在识别具有各向异性特性的复合材料层压板上模拟损伤（负载质量）的正确位置方面表现出比非优化阵列更高的准确性。它有助于保证对更频繁遭受损坏的区域进行更灵活、更优质的监控。所提出的方法在碳纤维增强树脂复合材料层压板样品上进行了实验验证。
The active structural health monitoring (SHM) approach for the complex composite laminate structures of wind turbine blades (WTBs), addresses the important and complicated problem of signal noise. After illustrating the wind energy industry's development perspectives and its crucial requirement for SHM, an improved redundant second generation wavelet transform (IRSGWT) pre-processing algorithm based on neighboring coefficients is introduced for feeble signal denoising. The method can avoid the drawbacks of conventional wavelet methods that lose information in transforms and the shortcomings of redundant second generation wavelet (RSGWT) denoising that can lead to error propagation. For large scale WTB composites, how to minimize the number of sensors while ensuring accuracy is also a key issue. A sparse sensor array optimization of composites for WTB applications is proposed that can reduce the number of transducers that must be used. Compared to a full sixteen transducer array, the optimized eight transducer configuration displays better accuracy in identifying the correct position of simulated damage (mass of load) on composite laminates with anisotropic characteristics than a non-optimized array. It can help to guarantee more flexible and qualified monitoring of the areas that more frequently suffer damage. The proposed methods are verified experimentally on specimens of carbon fiber reinforced resin composite laminates.
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