摘要
激光超声检测金属材料晶粒尺寸的信号中包含了大量噪声,而无法实现平均晶粒尺寸相近时的快速检测。本文以冷轧低碳钢为研究对象,采用了奇异值分解降噪方法对激光超声检测晶粒尺寸的信号进行处理,实现了平均晶粒尺寸偏差在4μm范围内的精确识别,提高了激光超声检测金属材料平均晶粒尺寸的检测精度和分辨率。
The signal of the laser ultrasonic detection of the grain size of metallic materials contains a large amount of noise,while rapid detection cannot be achieved when the average grain size is similar.In this paper,cold rolled low carbon steel is used as the research object,and the singular value decomposition noise reduction method is used to process the signal of the laser ultrasonic detection of the grain size,which realizes the accurate identification of the average grain size deviation within 4μm,and improves the detection accuracy and resolution of the average grain size of metal materials using the laser ultrasonic.
作者
彭昊
朱振格
宋学勇
徐亚诚
殷安民
束学道
王英
左锦荣
谢重阳
谯自健
PENG Hao;ZHU Zhen-ge;SONG Xue-yong;XU Ya-cheng;YIN An-min;SHU Xue-dao;WANG Ying;ZUO Jin-rong;XIE Chong-yang;QIAO Zi-jian(School of Mechanical Engineering and Mechanics,Ningbo University,Ningbo 315211,China;Zhejiang Provincial Key Laboratory of Part Rolling Technology Research,Ningbo 315211,China;Ningbo Key Laboratory of Digital Manufacturing Technology,Ningbo 315211,China)
出处
《激光与红外》
CAS
CSCD
北大核心
2021年第12期1586-1593,共8页
Laser & Infrared
基金
国家自然科学基金项目(No.51805279)
浙江省自然科学基金项目(No.Y21E050021)
宁波市“科技创新2025”重大专项项目(No.2020Z110)资助。