Surface roughness degrades the performance of ultrasonic methods when detecting sub-wavelength flaws. In this work, a roughness-modified doubly-scattered response (DSR) model is developed to enhance the flaw detection method for two-phase Ti-6Al-4V with rough surfaces. Extreme value statistics are used to calculate the confidence bounds of grain noise, then the bounds are treated as a time-dependent threshold for segmenting flaws in C-scan images of two-phase Ti-6Al-4V with rough surfaces. Three Ti-6Al-4V samples with different surface roughness are designed and manufactured for validating the present method; ultrasonic C-scan results show that it can distinguish sub-wavelength flaws (about 1/3 wavelength) in two-phase Ti-6Al-4V with rough surfaces, which can be extended to industry applications.

中文翻译：

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检测粗糙表面的两相 Ti-6Al-4V 中的小缺陷

在检测亚波长缺陷时，表面粗糙度会降低超声波方法的性能。在这项工作中，开发了一种粗糙度修正双散射响应 (DSR) 模型，以增强具有粗糙表面的两相 Ti-6Al-4V 的探伤方法。使用极值统计计算晶粒噪声的置信界限，然后将该界限作为时间相关阈值，用于在粗糙表面的两相Ti-6Al-4V的C扫描图像中分割缺陷。设计并制造了三个不同表面粗糙度的 Ti-6Al-4V 样品以验证本方法；超声C扫描结果表明，它可以区分表面粗糙的两相Ti-6Al-4V中的亚波长缺陷（约1/3波长），可扩展到工业应用。