基于电弧传感的GMAW过程焊缝缺陷识别方法  

Identification of Weld Defects in GMAW Based on Arc Sensing

作　　者：李迪[1] 宋永伦[1] 叶峰[1] 江伟[1] 

机构地区：[1]华南理工大学,广州510640

出　　处：《焊接学报》2000年第1期30-33,共4页Transactions of The China Welding Institution

基　　金：广东省自然科学基金!(940 50 4;990 550 );国家自然科学基金!(597850 0 4 );教育部留学回国人员科研启动基金资助项目

摘　　要：CO2 气体保护焊广泛应用于自动焊及机器人焊接领域 ,其过程中焊接质量的自动监测是目前工业界亟待解决的问题。而基于电弧传感 (through the arcsensing)信息的监测研究 ,由于其特有的优势得到了越来越多的关注。本文提出一种在CO2 气体保护焊过程中对焊缝缺陷的自动监测方法。该方法基于对电弧传感信号特征的提取 ,通过采用自组织特征映射 (SOM)神经网络对信号分类 ,在焊接过程中在线识别焊缝缺陷。试验表明 ,该方法有效地实现了焊缝缺陷的识别 ,可用于焊接过程的在线监测 ,对机器人焊接生产的产品“零缺陷”质量控制具有重要应用价值。CO 2 gas shielded arc welding is widely used in automatic and robotic welding.The automatic monitoring of weld quality is a problem that needs urgently solved in industry.Through the arc sensing,due to its advantages in practical applications,gets more and more concerns in recent years.This paper presents a monitoring method of weld defects for CO 2 gas shielded arc welding process.It is based on the feature extraction for the arc signals by the classification of signals'histogram in the welding process using Self Organize feature Map (SOM) neural networks.Experiments show that this strategy realizes effectively the identification of weld defects and can be used in the on line monitoring of welding process.It is very improtant for the welding process in achieving the aim of “zero defect”products.

关 键 词：焊接 电弧传感 焊缝缺陷识别 GMAW焊 

分 类 号：TG444.7[金属学及工艺—焊接] TG409