Predicting laser penetration welding states of high-speed railway Al butt-lap joint based on EEMD-SVM

• DOI: 10.1016/j.jmrt.2022.09.102
• Publication Date: 2022-09-30T06:30:58Z
• Authors: Yuhang Liu; Biao Yang; Xiaohui Han; Caiwang Tan; Fuyun Liu; Zhi Zeng; Bo Chen; Xiaoguo Song
• Keywords: 0209 industrial biotechnology; Mining engineering. Metallurgy; Laser welding; TN1-997; Penetration state; Support vector machine (SVM); 02 engineering and technology; Ensemble experience mode decomposition (EEMD); Butt-lap joint

The Al butt-lap joints are widely applied in China Railway High-speed (CRH) trains body joints. However, the gaps caused by the thermal deformation in Al butt-lap joints lead to the lack penetration or over penetration. To predict the penetration state of laser welds in Al butt-lap joints with different gaps, this work investigated the correlation between the plasma plume morphology and penetration state monitored by high-speed imaging system and the vertical gap and horizontal gap were utilized as intermediary. The ensemble experience mode decomposition (EEMD) was used to obtain the frequency features of plasma plume morphology. A support vector machine (SVM) model combined with EEMD was then established to classify the different penetration state, which adopted the original signals at time-domain and the mode decomposition signals at frequency-domain as input. The EEMD-SVM accuracy of 97.98% was the highest among the EMD-SVM of 86.44% and the SVM of 58.15%. The EEMD-SVM obtained both high Accuracy and Recall when the quantity of positive and negative samples were utmost different. The classification of the EEMD-SVM model was the most superior among the EMD-SVM model and SVM model. This proposed method provided a novel and accurate approach to perform process monitoring and penetration defects detection during laser welding of butt-lap joints.