基于电弧信息时频特征的多层多道焊缝熔宽预测研究

基于电弧信息时频特征的多层多道焊缝熔宽预测研究 Prediction of melt width of multi-layer and multi-pass welding based on the time-frequency characteristics of arc information 袁飞 YUAN Fei 1 first-author 岳晨凯 YUE Kaichen 2 黄勇 HUANG Yong 2 3 李晓鹏 LI Xiaopeng 2 3 王克鸿 WANG Kehong 2 3 江南造船(集团)有限责任公司江南研究院焊接制造实验室 江南造船(集团)有限责任公司江南研究院焊接制造实验室 College of Material Science and Engineering, Nanjing University of Science and Technology College of Material Science and Engineering, Nanjing University of Science and Technology 南京理工大学材料科学与工程学院 南京理工大学材料科学与工程学院 Jiangsu Jingning Intelligent Manufacturing Co., Ltd Jiangsu Jingning Intelligent Manufacturing Co., Ltd 江苏靖宁智能制造有限公司  江苏靖宁智能制造有限公司  Jiangnan Research Institute Welding Manufacturing Laboratory, Jiangnan Shipyard(Group)Co., Ltd. Jiangnan Research Institute Welding Manufacturing Laboratory, Jiangnan Shipyard(Group)Co., Ltd. 以多层多道的熔化极气体保护电弧焊接过程为研究对象,以识别熔宽为目标,设置了不同的工艺实验,获得了不同熔宽下对应的电弧信号。对不同工艺条件下的电信号进行了时频特征分析,并利用变分模态分解(VMD)方法提取其时频特征值,结合支持向量机(SVM)模式识别算法对熔宽进行多分类,构建了不同工艺参数与熔宽的预测模型。经验证,预测精度达到98.611 1%。为焊接过程信息化和智能化发展奠定了较好的技术基础。 The study of the electrical signal characteristics under different process parameters and the establishment of the relationship between electrical signal characteristics and forming characteristics are of great significance for the realisation of highly accurate and sensitive closed-loop control of welding quality. To identify the weld width, different process experiments were set up to obtain the corresponding arc signals under different melt widths. The time-frequency characteristics of electrical signals under different processing conditions were analyzed. The time-frequency characteristic values were extracted by the Variational Mode Decomposition（VMD） method,and the fusion width was classified by the Support Vector Machine（SVM） pattern recognition algorithm. The prediction models of different processing parameters and fusion width were constructed. It is proved that the prediction accuracy is 98.6111%, which lays a great technical foundation for the development of information and intelligence in the welding process. 电弧 电信号 时频特征 熔宽 预测 arc electric signal time-frequency characteristics melt width prediction TG444 2022-03-08 12 51