二分搜索和压缩感知在激光超声内部缺陷快速检测技术的应用

Application of binary search and compressive sensing for rapid detection of defects inside laser ultrasound

激光超声检测技术由于其非接触、高灵敏度和高空间分辨率特点,在无损检测领域具有广阔的应用前景。但其在高空间分辨率下进行大面积扫查需要花费较长的扫描时间,实用性受到制约。针对上述问题,文中提出使用二分搜索方法提高了检测速度,并使用压缩感知算法将所探测到的激光超声信号表示为小波基的线性加权组合,最终从二分搜索获得的较少实测激光超声信号中还原出整个待测范围内的信号。进一步,搭建了内部缺陷的激光超声扫描检测装置,使用脉冲激光实现超声的激光激发,多普勒测振仪实现超声的非接触探测,通过固定激发探测距离移动样品的方式实现了基于二分搜索和压缩感知的激光超声内部缺陷快速检测。文中提出的技术不但具有非接触、高灵敏度和高空间分辨率等激光超声的特点,还能提高检测效率。实验结果表明,在120 mm×30 mm×8 mm的铝板上确定缺陷位置需6 min,相比于逐点扫查需要14 min,缩短了体内缺陷定位所需要时间。

Laser ultrasonic inspection technology has a broad application prospect in the field of nondestructive testing due to its non-contact,high sensitivity and high spatial resolution characteristics.However,its practicality is limited by the long scanning time required for large area sweeping at high spatial resolution.To address the above problems,a binary search method was proposed to improve the detection speed,and a compressed sensing algorithm was used to represent the detected laser ultrasound signal as a linear weighted combination of wavelet bases,and finally the entire range to be measured was restored from the less real laser ultrasound signal obtained by binary search.Further,a laser ultrasonic scanning detection device for internal defects was built,the laser excitation of ultrasound was achieved by using a pulsed laser,the non-contact detection of ultrasound was achieved by Doppler vibrometer,and a fast detection of internal defects by laser ultrasound based on binary search and compression perception was achieved by moving the sample at a fixed excitation detection distance.The technique proposed in this paper not only has the characteristics of laser ultrasound such as non-contact,high sensitivity and high spatial resolution,but also can improve the detection efficiency.The experimental results show that it takes 6 min to determine the defect location on a 120 mm×30 mm×8 mm aluminum plate,compared with 14 min for point-by-point sweeping,which shortens the time required for in vivo defect localization .