为了解决异种材料扩散焊质量超声波检测时,从回波幅度无法判断界面是否存在微小缺陷的问题,采用支持向量机技术构建了扩散焊界面缺陷识别模型.以TiAl和40Cr扩散焊接头为研究对象,采用超声波水浸聚焦法采集扩散焊界面信号,从信号中提取4个特征值,优化样本数量和核参数后,训练扩散焊界面缺陷识别模型.扩散焊试样界面信号经模型识别后,根据C扫描图像的位置重构识别图像.结果表明,该模型有效地识别出未焊合、弱接合和微孔缺陷,3种缺陷的正确识别率分别为93%、90.5%和91.5%,识别图像直观地显示了界面的缺陷.TiAl/40Cr扩散焊界面缺陷识别模型实现了扩散焊试样界面缺陷的智能识别.
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