摘要
为了提高激光超声检测铝板缺陷的最大振幅超声波C扫描图像的质量并精确识别缺陷大小,在算法上,提出滤波和差分相结合的数据处理方法;在实验上分别用不同频率不同角度的超声换能器对铝板缺陷扫描激励检测确定最优检测参数。实验结果表明:超声换能器与铝板之间90°倾角耦合时虽然可以有效识别表面缺陷,但45°倾角耦合时,超声换能器对铝板内部缺陷检测效果更佳,经过滤波和差分处理后的图像质量显著提高;利用处理后的图像计算得到的缺陷尺寸与实际缺陷进行对比,误差在10%以内,进一步说明该方法在金属板材缺陷检测方面的广阔应用前景。
In order to improve the quality of maximum amplitude C-scan image of aluminum plate defect detected by laser ultrasound and identify the defect size accurately,a data processing method combining filtering and difference was proposed.Ultrasonic transducers with different frequencies and coupling angles were applied to scan excitation detection of aluminum plate defects,and the optimal detection parameters were verified by experiments.The experimental results show that although surface defects can be identified effectively when ultrasonic transducer is coupled with aluminum plate at 90°inclination angle,the detection effect of ultrasonic transducer is better when ultrasonic transducer is coupled with aluminum plate at 45°inclination angle.After filtering and differential processing,the defect image quality of aluminum plate is improved significantly.The defect size calculated by the processed image is compared with the actual detected aluminum plate defect,and the error is less than 10%,which further demonstrates the broad application prospect of this method in metal plate defect detection.
作者
董晓虎
程绳
范杨
辛巍
范炜亮
夏慧
DONG Xiao-hu;CHENG Sheng;FAN Yang;XIN Wei;FAN Wei-liang;XIA Hui(State Grid Hubei Electric Power Co., Ltd., Maintenance Company,Wuhan 430050, China;College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China;Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China;School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100190, China)
出处
《科学技术与工程》
北大核心
2022年第6期2170-2176,共7页
Science Technology and Engineering
基金
国家自然科学基金(61771448,51937010)
北京市自然科学基金(7212210)
国家电网科技项目(52152020001A)。
关键词
激光超声
可视化检测
图像处理
定量化检测
laser ultrasound
visual detection
image processing
quantitative testing
