In deep penetration laser welding,the generation of the laser-induced plasma exhibits significant randomness and temporal variability.A novel passive triple-probe electrical signal acquisition device was utilized to collect the plasma electrical signals with high temporal resolution,thereby obtaining the large sample of thermodynamic information,including plasma temperature.K-means clustering,an unsupervised learning method,was used to conduct the clustering analysis of the complex dynamic behaviors of the plasma.The results indicated that under the experimental conditions of present work,the frequency of the plasma eruption mainly fell within the range of 1240-2200 Hz,and the temperature change rate was primarily distributed between 5000-30000 K/ms.Additionally,the sway frequency of the plasma was mainly observed in the range of 1050-1410 Hz,and the temperature change rate concentrated between 200-2000 K/ms.Consequently,there was a significant difference in the temperature change rates between plasma eruption and sway.
关键词
激光深熔焊/电信号/等离子体动态行为/K-均值聚类
Key words
deep penetration laser welding/electrical signal/plasma dynamic behavior/clustering analysis
维普
万方数据