School of Automation Engineering, University of Electronic Science and Technology of China, China.
School of Automation Engineering, University of Electronic Science and Technology of China, China.
Ultrasonics. 2020 Jul;105:106115. doi: 10.1016/j.ultras.2020.106115. Epub 2020 Mar 10.
The ultrasonic testing method is a well-known non-destructive testing technique which has been applied to the tube inspection for guarantying the quality of the production. However, there exist several challenges to detect the defects of tubes with small diameter and thin-wall due to the complex of multiple reflections and waveform conversion. Parameters selection of the transducer takes key role to enhance the detection sensitivity such as frequency, size, refraction angle, distance offset, and focal point distance. This selection is generally dependent on human experience as it is highly time-consuming and subjective. In this paper, a novel parameter selection method based on physical perspective linked forward-inverse intelligence strategy has been proposed for ultrasonic immersed testing method. The optimized parameters can be calculated automatically while both testing and calibration repeated experiments can be avoided. The proposed method is computationally affordable and yields a high accuracy objective performance. Both simulation and experiments have been conducted to verify the efficacy of the proposed method.
超声检测方法是一种众所周知的无损检测技术，已应用于管材检测，以保证生产质量。然而，由于多次反射和波形转换的复杂性，对于直径小、壁厚薄的管材缺陷检测存在一些挑战。换能器参数的选择对于提高检测灵敏度起着关键作用，如频率、尺寸、折射角、距离偏移和焦点距离。这种选择通常依赖于人的经验，因为它非常耗时且主观。在本文中，提出了一种基于物理视角的正向-反向智能策略的新型参数选择方法，用于超声浸液检测方法。可以自动计算优化参数，同时避免测试和校准重复实验。该方法计算成本低，具有高精度的客观性能。已经进行了模拟和实验来验证所提出方法的有效性。
