Ultrasonic Recognition of Component Crack Defect
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摘要: 将小波包多分辨率分析与能量谱相结合，提出了两种金属材料缺陷特征提取的方法，即能量-裂纹法和小波包-功率谱法。能量-裂纹法选取最能反映缺陷特征的能量特征向量作为特征参数，进行缺陷的识别。小波包-功率谱法需要找到小波包分解中对裂纹缺陷最敏感的结点，然后对其进行功率谱分析，从而可以很明显地区分出有无裂纹的信号以及裂纹类型。以航天发射塔架钢连接构件疲劳裂纹超声信号为例，对这两种方法进行验证，表明是行之有效的特征提取方法，为金属材料缺陷检测与识别开拓了新的思路。Abstract: Two methods of extraction of defect features of metal matrix composite by combining multi-resolution signal decomposition of the wavelet packet with energy spectrum were suggested. In the first method, the energy characteristic vector, which is the best parameter that reflects the defect features, is chosen as characteristic parameter for defect recognition. In the other method, it is need to find the most sensitive node for crack defects and analyze its energy spectrum so that one can distinct apparently the signals of crack and non-crack and which one in crack's signals. As an example, the defect signals of steel connected components are processed with two methods It is shown that two methods are effective for extraction and recognition. They develop a new direction for extraction and recognition of the defect of composite material.
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