Feature Extraction and Dimensionality Reduction of Arc Sound under Typical Penetration Status in Metal Inert Gas Welding

作     者：LIU Lijun LAN Hu ZHENG Hongyan JIAN Xiaoxia 

作者机构：Ningbo Institute of TechnologyZhejiang UniversityNingbo 315100China School of Material Science ＆ EngineeringHarbin University of Science and TechnologyHarbin 150080China Rongcheng CollegeHarbin University of Science and TechnologyRongcheng 264300China 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2012年第25卷第2期

页      面：293-298页

核心收录：

学科分类：080503[工学-材料加工工程] 0817[工学-化学工程与技术] 08[工学] 0807[工学-动力工程及工程热物理] 080203[工学-机械设计及理论] 0805[工学-材料科学与工程（可授工学、理学学位）] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 080201[工学-机械制造及其自动化] 

基　　金：supported by Harbin Academic Pacesetter Foundation of China (Grant No. RC2012XK006002) Zhegjiang Provincial Natural Science Foundation of China (Grant No. Y1110262) Ningbo Municipal Natural Science Foundation of China (Grant No. 2011A610148) Ningbo Municipal Major Industrial Support Project of China (Grant No.2011B1007) Heilongjiang Provincial Natural Science Foundation of China (Grant No. E2007-01) 

主　　题：metal inert gas welding penetration arc sound feature extraction dimensionality reduction 

摘      要：Arc sound is well known as the potential and available resource for monitoring and controlling of the weld penetration status,which is very important to the welding process quality control,so any attentions have been paid to the relationships between the arc sound and welding *** non-linear mapping models correlating the arc sound to welding parameters have been established with the help of neural ***,the research of utilizing arc sound to monitor and diagnose welding process is still in its infancy.A self-made real-time sensing system is applied to make a study of arc sound under typical penetration status,including partial penetration,unstable penetration,full penetration and excessive penetration,in metal inert-gas（MIG） flat tailored welding with spray *** sound is pretreated by using wavelet de-noising and short-time windowing technologies,and its characteristics,characterizing weld penetration status,of time-domain,frequency-domain,cepstrum-domain and geometric-domain are ***,high-dimensional eigenvector is constructed and feature-level parameters are successfully fused utilizing the concept of primary principal component analysis（PCA）.Ultimately,60-demensional eigenvector is replaced by the synthesis of 8-demensional vector,which achieves compression for feature space and provides technical supports for pattern classification of typical penetration status with the help of arc sound in MIG welding in the future.