Arc initiation process characteristics and stability evalution method in P-GMAW
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摘要:
脉冲熔化极气体保护焊(pulsed gas metal arc welding,P-GMAW)起弧过程易产生不稳定现象,会严重影响电弧传感焊缝跟踪精度.针对这一问题,对摆动电弧窄间隙P-GMAW不稳定起弧过程的成因进行了研究,发现送丝速度对起弧过程稳定性具有重要影响. 通过对电弧图像与电信号特征进行对比分析,提取了表征电弧稳定性的电信号特征变量;为减小变量冗余性和过拟合,采用最大似然估计法筛选并提取了8个变量,并通过主成分分析法(principal component analysis, PCA)对变量进行融合,提取了方差贡献率最高的前两个主成分;根据因子载荷发现,相比熔滴过渡阶段和基值阶段,脉冲峰值阶段是电弧更易发生不稳定现象的阶段. 结合提取的主成分变量与二分类Logistic回归模型建立了起弧过程电弧稳定性判别模型. 通过受试者工作特征(receiver operating characteristic,ROC)曲线得到了模型的最佳阈值. 结果表明,该模型对脉冲稳定性判别准确率达到了80%以上,表明模型具有良好的判别性能.该模型对提高窄间隙高低跟踪精度、保证焊接质量具有一定应用价值.
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关键词:
- 窄间隙焊接 /
- 起弧过程稳定性 /
- 主成分分析 /
- 二分类Logistic回归
Abstract:The arc initiation process of P-GMAW is prone to instability, which can significantly affect the accuracy of arc sensing and weld seam tracking. In response to this issue, a study was conductedon on the causes of unstable arc initiation in oscillating arc narrow gap P-GMAW, revealing the significant impact of wire feed speed on the stability of the arc initiation process. By comparing and analyzing arc images and electrical signal characteristics, key signal features representing arc stability are extracted. To reduce redundancy and overfitting, a maximum likelihood estimation method is employed to select and extract 8 variables, which are then fused using principal component analysis to extract the top two components with the highest variance contribution. Based on the factor loading, it is found that the pulse peak stage is the phase where the arc is more prone to instability compared to the droplet transition stage and the baseline stage. By combining the extracted principal component variables with a binary logistic regression model, an arc stability discrimination model for the arc initiation process is established. The optimal threshold model was obtained through the ROC curve. Experimental validation shows that the model achieves an accuracy rate of over 80% in pulse stability discrimination, indicating good discriminatory performance. This model holds certain application value in improving the accuracy of narrow gap high-low tracking and ensuring welding quality.
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表 1 焊接工艺参数
Table 1 Welding parameters
摆动幅度
${S_{\text{w}}}$/mm摆动频率
$f$/Hz焊接速度
$v$/(mm·s−1)侧停时间
$t$/ms3 1.8 4 100 气体流量
$Q$/(L·min−1)送丝速度
${v_{\text{f}}}$/(m·min−1)焊丝伸出长度
$l$/mm焊丝直径
φ/mm15 6 12 1 表 2 单变量最大似然估计
Table 2 Univariate maximum likelihood estimation
变量 对数自然函数值 $\ln [L(\theta )]$ 自由度 ${d_{\text{f}}}$ 显著性 ${S_1}$ 峰值电流上升斜率 x1 − 189.10845 1 0 峰值动态电阻 x2 − 194.89861 1 0 峰值变异系数 x3 − 170.74018 1 0 熔滴过渡变异系数 x4 − 120.66539 1 0 基值变异系数 x5 − 194.85681 1 0 峰值极差 x6 − 162.22914 1 0 熔滴过渡极差 x7 − 115.91707 1 0 基值极差 x8 − 196.57049 1 0 脉冲周期 x9 − 206.13597 1 0 峰值能量 x10 − 215.57218 1 0 表 3 因子载荷和得分系数
Table 3 Factors load and scores coefficient
变量 因子载荷 得分系数 主成分F1 主成分F2 主成分F1 主成分F2 峰值电流上升斜率 ${x_1}$ − 0.7244 − 0.4751 − 0.20258 − 0.00784 峰值动态电阻 ${x_2}$ − 0.8915 − 0.1651 − 0.40750 0.23845 峰值变异系数 ${x_3}$ 0.9045 0.3233 0.35470 − 0.14980 熔滴过渡变异系数 ${x_4}$ 0.4609 0.7759 − 0.04961 0.28493 基值变异系数 ${x_5}$ 0.3403 0.8657 − 0.14702 0.38349 峰值极差 ${x_6}$ 0.8821 0.3600 0.32909 − 0.11968 熔滴过渡极差 ${x_7}$ 0.4649 0.6814 − 0.01186 0.22756 基值极差 ${x_8}$ 0.1723 0.8987 − 0.24798 0.46632 -
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