Feature Extraction of AC Square Wave SAW Arc Characteristics Based on Wavelet Packet Denoising and LMD

China Mechanical Engineering ›› 2013, Vol. 24 ›› Issue (16): 2141-2146.

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Feature Extraction of AC Square Wave SAW Arc Characteristics Based on Wavelet Packet Denoising and LMD

He Kuanfang;Xiao Siwen;Wu Jigang

Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment,Hunan University of Science and Technology,Xiangtan,Hunan,411201

Online:2013-08-25 Published:2013-08-23
Supported by:

National Natural Science Foundation of China（No. 51005073）;

Hunan Provincial Natural Science Foundation of China（No. 11JJ2027）;
Hunan Provincial Science and Technology program ( No. 2012TT2044, 2011GK3052)

基于小波消噪与LMD的埋弧焊交流方波电弧信息提取

何宽芳;肖思文;伍济钢

湖南科技大学机械设备健康维护湖南省重点实验室,湘潭,411201

基金资助:
国家自然科学基金资助项目(51005073);湖南省自然科学基金资助项目(11JJ2027);湖南省科技计划资助项目（2012TT2044, 2011GK3052);湖南省高校科技创新团队支持计划资助项目
National Natural Science Foundation of China（No. 51005073）;

Hunan Provincial Natural Science Foundation of China（No. 11JJ2027）;
Hunan Provincial Science and Technology program ( No. 2012TT2044, 2011GK3052)

Abstract

Abstract:

In order to extract the arc feature information associated with welding quality in alternating current square wave submerged arc welding(AC square wave SAW),a LMD method combining with the wavelet packet transform was put forward.After performing wavelet packet denoising,the LMD was used to decompose the collected current signals into a number of product functions(PFs),and then the PFs were selected for the Hilbert transform and energy entropy calculation.Application of wavelet denoising and LMD can
get the vaild waveform distortion of different frequency components effectively and the amplitude variation characteristics in the time scale.On the basis of that,the Hilbert transform and energy entropy calculation can be used to extracte arc characteristics effectively.Experimental results show the effectiveness of this approach to extract the arc physical information related to welding quality. 

Key words: alternating current(AC) square wave submerged arc welding(SAW), wavelet packet denoising, local mean decomposition(LMD), arc information

摘要：

埋弧焊交流方波电弧电信号存在畸变,影响焊接过程电弧稳定性和焊缝成形质量,针对于此,在对采集的埋弧焊交流方波电弧电流信号进行小波包降噪后,利用局部均值分解(local mean decomposition,LMD)对电弧电流信号进行自适应分解,获得若干个具有真实物理意义的PF(product function)分量,并对PF分量集进行Hilbert变换及能量熵计算。结果表明,利用小波消噪与LMD能有效得到埋弧焊交流方波电流波形畸变的不同频率成分及其幅值在时间特征尺度上的变化特征,在此基础上通过Hilbert变换及能量熵计算可以有效提取反映焊接过程电弧稳定性和焊缝成形质量的电弧特征信息。

关键词: 交流方波埋弧焊, 小波消噪；局部均值分解；电弧信息

CLC Number:

TG434

HE Kuan-Fang, XIAO Sai-Wen, WU Ji-Gang. Feature Extraction of AC Square Wave SAW Arc Characteristics Based on Wavelet Packet Denoising and LMD[J]. China Mechanical Engineering, 2013, 24(16): 2141-2146.

何宽芳, 肖思文, 伍济钢. 基于小波消噪与LMD的埋弧焊交流方波电弧信息提取[J]. 中国机械工程, 2013, 24(16): 2141-2146.

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Feature Extraction of AC Square Wave SAW Arc Characteristics Based on Wavelet Packet Denoising and LMD

基于小波消噪与LMD的埋弧焊交流方波电弧信息提取

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