上海交通大学学报(自然版) ›› 2013, Vol. 47 ›› Issue (11): 1655-1660.

• 金属学与金属工艺 •    下一篇

Al-Mg合金钨极气体保护焊接电弧的光谱特征提取方法

余焕伟,叶震,张志芬,陈华斌,陈善本
  

  1. (上海交通大学 材料科学与工程学院, 上海 200240)
     
  • 收稿日期:2013-01-09 出版日期:2013-11-28 发布日期:2013-11-28
  • 基金资助:

    国家自然科学基金资助项目(51075268)

Arc Spectral Characteristics Extraction Method in Pulsed Gas Tungsten Arc Welding for Al-Mg Alloy
 

YU Huanwei,YE Zhen,ZHANG Zhifen,CHEN Huabin,CHEN Shanben   

  1. (School of Materials Science and Engineering, Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2013-01-09 Online:2013-11-28 Published:2013-11-28

摘要:

摘要: 
以Al-Mg合金的脉冲交流钨极气体保护焊接为背景,运用主成分分析方法对电弧光谱进行冗余信息去除和特征信号提取,分别使用信号脉冲周期内平均和小波重构的方法对特征信号进行去脉冲干扰,并对特征信号和不同类型焊接缺陷间的关系进行研究.结果表明,第1、2主成分包含了电弧光谱中的主要信息,分别对应Ar I谱线和金属谱线,反映了焊接过程的不同方面,第1主成分特征信号与电弧的热量输入关系较大,而第2主成分特征信号与熔池的稳定性密切相关.

 
 

关键词: 钨极气体保护焊, 电弧光谱, 主成分分析, 特征提取, 焊接缺陷

Abstract:

In this paper, aimed at the problems in arc spectral information in AlMg Alloy pulsed alternating current (AC) GTAW, principal component analysis (PCA) was utilized for redundancy removal and spectral characteristic signals extraction. The spectral wavelengths were classified as the first and the second principal components, associated with Ar I lines and metal lines respectively; pulse interference caused by welding current was eliminated by using mean value during signal’s pulse period (MSP) and wavelet reconstruction. The relations between these extracted signals and different defects were discussed. The results show that the first principal component is closely related to the arc heat input while the second principal component is closely related to the weld pool stability.
 

Key words: gas tungsten arc welding (GTAW), arc spectra, principal component analysis, characteristics extraction, welding defect

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