基于激光超声技术的3D打印材料表面缺陷检测研究  

Research on surface defect detection of 3D printing materials based on laser ultrasonic technology

作　　者：毛毛[1] MAO Mao(Nanjing Tech University,Nanjing 211800,China)

机构地区：[1]南京工业大学,南京211800

出　　处：《激光杂志》2022年第12期31-35,共5页Laser Journal

基　　金：国家教育部产学合作协同育人项目(No.201901043020)。

摘　　要：3D打印材料表面缺陷在检测过程中存在人为干扰因素,使其检测结果不佳。针对该问题,研究了基于激光超声技术的3D打印材料表面缺陷检测方法。首先对3D表面材料缺陷检测超声波实施去噪处理;通过核主成分分析法提取超声波能量特征,将特征作为支持向量机的输入进行学习,实现3D打印材料表面缺陷检测和类识别。实验结果表明:该方法可去除3D金属材料激光超声波回波信号噪声,可有效检测存在0.02 mmh和0.05 mm微小缺陷的3D打印材料,具备较强应用性。The surface defects of 3D printing materials have human interference factors in the detection process,which makes the detection results poor.To solve this problem,the surface defect detection method of 3D printing materials based on laser ultrasonic technology is studied.Firstly,the 3D surface material defect detection ultrasonic is denoised;The ultrasonic energy feature is extracted by kernel principal component analysis,and the feature is used as the input of support vector machine for learning to realize the surface defect detection and class recognition of 3D printing materials.The experimental results show that this method can remove the laser ultrasonic echo signal noise of 3D metal materials,and can effectively detect 3D printing materials with 0.02 mmh and 0.05 mm small defects,which has strong applicability.

关 键 词：激光超声 3D打印材料 表面缺陷检测 超声波能量 特征提取 

分 类 号：TN247[电子电信—物理电子学]