摘要
窄间隙激光焊作为核电领域大型厚壁构件的先进连接工艺,具有热输入小、焊接效率高、接头质量高等优点。然而,受现场复杂施焊环境影响,焊缝内部易因污染物清理不尽而产生气孔缺陷。传统的焊后无损检测费时耗力,且检测结果受零部件尺寸结构制约及检测人员主观判断影响,因此亟待发展气孔缺陷在线检测技术。本文设计研制了基于发射光谱的窄间隙激光焊质量检测系统,探究工艺参数及水、油等污染物对气孔缺陷的影响规律,分析水对激光致等离子体电子温度、光谱强度的作用机制,开发因污染物导致的气孔缺陷在线预警软件系统。结果表明,窄间隙激光焊时由于受工件侧壁拘束使得等离子体密度高,对激光反射、散射作用强,测得光谱强度值较弱。窄间隙填丝焊时由于激光能量存在损耗、不能完全被母材和丝材吸收,其测得的光谱强度小于窄间隙自熔焊。采用Boltzmann作图法求得窄间隙激光填丝焊光致等离子体电子温度为7201.1 K,电子密度为5.2797×10^(15)cm^(-3),均小于窄间隙激光自熔焊时的热力学状态参数。在本文的6组自熔焊工艺参数范围内,X射线探伤未检测到密集气孔缺陷。当母材表面有水时,焊缝表面有气孔产生,通过X射线探伤观察到焊缝中有大量密集气孔存在。与正常工艺下获得的光谱数据相比,光谱仪全波段上的相对光强均降低,电子温度也下降至6900~7200 K范围内动态波动,但电子密度会增大。采用神经网络模型对主成分分析降维后的光谱数据进行训练,可对窄间隙激光填丝焊时因水、油等污染物导致的气孔缺陷进行高准确率的预测。开发的气孔检测系统可对因污染物导致的气孔缺陷进行有效识别,准确率达90%,响应时间在0.1 s内。
As an advanced joining process for large thick components in nuclear power fields,narrow gap laser welding has the advantages of low heat input,high welding efficiency,and high joint quality.However,attributing to the complex welding environment on site,porosity defects are prone to be generated due to inadequate cleaning of pollutants.The traditional post-welding nondestructive testing is time and labor-consuming,and the part size and the subjective judgment of the testers restrict the test results.Therefore,developing an online detection technology for porosity defects is urgent.In this study,a narrow gap laser welding detection system based on the emission spectrum was designed and developed.The effect of process parameters and pollutants such as water and oil on welding quality was investigated.The action mechanism of water on the electron temperature and spectral intensity of laser-induced plasma was analyzed.An online warning software system for porosity defects caused by pollutants was developed.The results showed that the spectrum intensity of narrow gap laser welding was weak due to the strong reflection and scattering of high plasma density caused by the side wall constraint of the workpiece.Due to the loss of laser energy,the measured spectral intensity during wire-filling welding was less than that of self-fusion welding.The electron temperature and electron density of plasma induced by narrow gap laser filling wire welding were 7201.1 K and 5.2797×10^(15) cm^(-3),respectively,which were both lower than the thermodynamic parameters of self-fusion welding.Dense porosity defects were not detected by X-ray inspection in the self-fusion welding.When water was on the base material surface,pores on the weld surface were observed,and many dense pores were detected by X-ray inspection.The relative light intensity in all bands was reduced compared with the spectral data obtained under the normal process.The electron temperature also reduced from 6900 to 7200 K,but the electron density increased.Using a neural network model to train the spectral data after dimensionality reduction of principal component analysis,the porosity defects caused by water and oil in narrow gap laser wire filling welding can be predicted with high accuracy.The developed detection system can effectively identify porosity defects caused by pollutants with an accuracy of 90% and a response time of 0.1 s.
作者
佘昆
李冬辉
杨凯淞
杨立军
刘金平
黄一鸣
SHE Kun;LI Dong-hui;YANG Kai-song;YANG Li-jun;LIU Jin-ping;HUANG Yi-ming(School of Electrical and Information Engineering,Tianjin University,Tianjin 300350,China;Guangdong Institute of Special Equipment Inspection and Research,Guangzhou 510655,China;Tianjin Key Laboratory of Advanced Joining Technology,School of Materials Science and Engineering,Tianjin University,Tianjin 300350,China;China Nuclear Industry 23 Construction Co.,LTD.,Industry Research and Engineering Co.,LTD.,China National Nuclear Corporation Key Laboratory of High Efficiency Welding,Beijing 101300,China)
出处
《光谱学与光谱分析》
北大核心
2025年第2期507-514,共8页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(52201048)
中国博士后科学基金项目(2020M670651)资助。
关键词
窄间隙激光焊
光谱诊断
光致等离子体
气孔缺陷
在线检测
Narrow gap laser welding
Spectral diagnosis
Laser-induced plasma
Porosity defect
On-line detection
