传感技术学报2024，Vol.37Issue(4)：612-619,8.DOI:10.3969/j.issn.1004-1699.2024.04.008
基于电流多特征融合的窄间隙P-GMAW摆动电弧传感焊缝跟踪方法
Seam Tracking with an Arc Sensor in the Narrow Gap P-GMAW Process Based on the Current Multi-Feature Fusion Method
刘文吉 1朱鹏飞 1于镇洋 1杨嘉昇 1肖宇1
作者信息
- 1. 天津工业大学机械工程学院,天津 300387
- 折叠
摘要
Abstract
Arc sensing is one of the important methods to track the seam in narrow gap welding.In response to the problems of poor stabil-ity and low reliability,fusing multiple statistical features of current information in the swing cycle is proposed to overcome the problem that a single data feature is easily affected by the stability of the arc.Firstly,multiple time-domain features of the current signal are extracted,and the feature matrix is calculated to correlate with the deviation vector.Then,the features with high correlation rate are fused by using the method of principal component analysis,and the first two principal components are adopted as the observation observed data.Finally,a support vector machine model based on multiple classifications is used for the classification test.The test results show that the maximum error is 0.2 mm,and the error within 0.1 mm accounts for 93.75%of the total erro.The method has improved accuracy compared with the traditional method,and the training samples used are less and the training process is simpler compared with the neural network method.关键词
数据处理/焊缝跟踪/特征融合/电弧传感Key words
data processing/weld seam tracking/feature fusion/arc sensing分类
矿业与冶金引用本文复制引用
刘文吉,朱鹏飞,于镇洋,杨嘉昇,肖宇..基于电流多特征融合的窄间隙P-GMAW摆动电弧传感焊缝跟踪方法[J].传感技术学报,2024,37(4):612-619,8.
