CAJ | 학술논문

利用小波分析方法，对所采集的CO2焊接电流、电弧电压和电弧声波进行了信号降噪处理和奇异点分析，提取不同频率范围的声波能量作为表征焊接过程状态变化的特征向量。采用统计学方法研究了特征值集合与焊接飞溅的相关性，完成了特征集合的评价与降维，为实现焊接过程的在线诊断奠定了基础。
이용소파분석방법，대소채집적CO2한접전류、전호전압화전호성파진행료신호강조처리화기이점분석，제취불동빈솔범위적성파능량작위표정한접과정상태변화적특정향량。채용통계학방법연구료특정치집합여한접비천적상관성，완성료특정집합적평개여강유，위실현한접과정적재선진단전정료기출。
Wavelet analysis is utilized on eliminating noises and interpreting zero crossings of welding current,arc voltage and arc sound in CO2 arc welding process,which are collected by experiment system.Extracted energy of arc sound in different frequency ranges is as characteristic vectors that can indicate changes in the welding processing,The correlation between characteristic class and welding sprays is studied by statistic test to evaluate and reduce dimensions of characteristic class.The base to fulfill on-line diagnose of welding process has been advanced in this paper.