Characteristics and processing method of ultrasound testing signal of titanium alloys
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摘要: 钛合金材料广泛应用于船舶、航空等领域，通常采用超声检测技术对其原材料与焊接质量进行评估，但在大规格构件与微小缺陷检测时，存在晶粒噪声导致缺陷信号难以识别的问题。基于水浸超声技术测试了典型钛合金组织的声学性能，结果表明其声速与衰减系数呈现各向异性，大厚度结构检测时影响灵敏度的关键因素为散射杂波的干扰。采用小波包能量熵作为特征参数，分析杂波信号与缺陷信号的特征，通过支持向量机与神经网络模型分类，缺陷信号的识别准确率达到90%以上。Abstract: Titanium alloy materials are widely used in ships, aviation and other fields, and the quality of raw materials and welding is usually evaluated by ultrasonic testing. However, grain noise makes it difficult to recognize signals when detecting large size components and small defects. In this paper, the acoustic properties of typical titanium alloy microstructures were tested by water immersion ultrasound technology. The results showed that the sound velocity and attenuation coefficient of titanium alloy were anisotropic and the key factor affecting the sensitivity of large thickness structures was scattering clutter interference. The wavelet packet energy spectrum was used as the characteristic parameter to study the characteristics of clutter signal and defect signal, and the recognition accuracy of defect signal could reach more than 90% by training and classifying the defect signal with the neural network algorithm.
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Keywords:
- titanium alloy /
- scattering clutter /
- wavelet packet energy spectrum /
- neural network
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