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中文摘要：
针对钢板背后多层橡胶粘接结构，选择较佳实验频率值作为电磁声换能器的激励源频率。提取了检测回波的瞬时振幅、瞬时相位和瞬时频率三种瞬时参数，将瞬时参数构成三维瞬时图谱定性识别不同粘接状态。将敏感时间窗内的平均瞬时参数组成特征向量，利用BP神经网络进行识别，对训练集与测试集的识别结果表明，该方法可以实现电磁超声界面回波的自动识别与分类，识别正确率不低于95％。
英文摘要：
The proper frequency is experimentally chosen to be the actuator frequency of the electromagnetic acoustic transducer. The instantaneous amplitude, phase and frequency of the detected ultrasonic echoes from a multilayer adhesive sample of steel and rubber materials are calculated and composed to form three-dimensional instantaneous spectrum which is successful to distinguish the testing signals from different adhesive states qualitatively. Then, average instantaneous parameters in sensitive time window are picked up and used as the input eigenvectors for the BP artificial neural network. Identified results in both training and testing volumes demonstrate that the detected electromagnetic ultrasonic interfacial echoes can be identified and classified automatically with the correctness ratio larger than 95%.
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