A novel wavelet method for electric signals analysis in underwater arc welding

A novel wavelet method for electric signals analysis in underwater arc welding

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摘要 Electric signals are acquired and analyzed in order to monitor the underwater arc welding process. Voltage break point and magnitude are extracted by detecting arc voltage singularity through the modulus maximum wavelet （MMW） method. A novel threshold algorithm, which compromises the hard-threshold wavelet （HTW） and soft-threshold wavelet （STW） methods, is investigated to eliminate welding current noise. Finally, advantages over traditional wavelet methods are verified by both simulation and experimental results. Electric signals are acquired and analyzed in order to monitor the underwater arc welding process. Voltage break point and magnitude are extracted by detecting arc voltage singularity through the modulus maximum wavelet （MMW） method. A novel threshold algorithm, which compromises the hard-threshold wavelet （HTW） and soft-threshold wavelet （STW） methods, is investigated to eliminate welding current noise. Finally, advantages over traditional wavelet methods are verified by both simulation and experimental results.

作者张为民王国荣石永华钟碧良

机构地区 School of Mechanical and Automotive Engineering Department of Computer Technology

出处《China Welding》 EI CAS 2009年第2期12-16,共5页 中国焊接（英文版）

关键词 underwater arc welding electric signals wavelet method threshold algorithm underwater arc welding, electric signals, wavelet method, threshold algorithm

分类号 TN911.6 [电子电信—通信与信息系统] TM862 [电气工程—高电压与绝缘技术]

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2009年第2期

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A novel wavelet method for electric signals analysis in underwater arc welding

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