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针对风力机叶片疲劳损伤过程难以定量评价的问题,提出一种基于裂纹扩展AE信号分形特征的疲劳损伤模糊评价方法。首先用修正系数μ改进关联维数的计算式,确定32组试样所适合的修正系数和最佳嵌入维数,然后在裂纹扩展试验中将AE信号的关联维数与加载条件、裂纹结构参数等共同组成评价疲劳损伤的影响因素集合,从试样数据中在集合近似的条件下求得权重集合,最后对某风场1.5 MW的风力机叶片进行评价,为探索风力机叶片疲劳损伤状态和裂纹扩展之间的内在规律提供了一条新思路。
Aiming at the problem that the fatigue damage of wind turbine blades is difficult to quantitatively evaluate, a fuzzy evaluation method of fatigue damage based on fractal characteristics of crack propagation AE is proposed. Firstly, the correction coefficient μ is used to improve the calculation formula of the correlation dimension, and the correction coefficient and the optimal embedding dimension suitable for the 32 groups of samples are determined. Then, the correlation dimension between the AE signal and the loading condition, crack structure parameter And so on together constitute a set of influencing factors for evaluating fatigue damage. From the sample data, the set of weights is obtained under a set approximation. Finally, the wind turbine blade of 1.5 MW in a wind farm is evaluated. In order to explore the fatigue damage state of the wind turbine blade and The inherent law between crack propagation provides a new idea.