Study on Weld Seam Deviation Method of GMAW Arc Sound Signal in V-groove of Medium Thickness Plate
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摘要: 针对中厚板V型坡口GMAW(熔化极气体保护焊)焊缝偏差识别问题,提出一种新型基于电弧声信号的中厚板GMAW摆动焊焊缝偏差识别方法。在V型坡口摆动焊接中,发现当摆动中心与焊缝中心出现偏差,电弧声信号呈现明显非对称性。为此,针对电弧声信号的时域和频域特征开展了进一步研究,明确了与焊缝偏差信号存在密切关联的电弧声摆动极限位置能量差、标准差、小波包第7频带和第8频带能量等特征参量。构建基于上述4类参量的GS-SVR非线性回归方程,通过电弧声特征信号检测,可实现焊接过程中焊接偏差信息的在线识别,通过左右偏差试验表明该模型具有良好精度,可满足工程实际生产需要。Abstract: For the welding seam deviation recognition in GMAW welding of medium thickness plates, a weld seam deviation recognition method in GMAW swing welding of medium thickness plates based on arc sound signal is proposed. In V-groove swing welding, it is found that when the swing center deviates from the weld center, the arc sound signal presents obvious asymmetry. Therefore, the characteristics of arc sound signal in time domain and frequency domain were further studied, and the characteristic parameters, in which the energy difference of arc sound swing limit position, standard deviation, energy in the seventh and eighth band of wavelet packet were closely related to the weld seam deviation signal, were identified. The GS-SVR nonlinear regression equation based on the above four parameters was established. Through the detection of arc sound signal, the welding deviation information in the welding could be recognized online. The left and right deviation tests show that the model has good accuracy and can meet the requirement of production.
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Key words:
- weld seam deviation /
- GMAW /
- arc sound signal /
- deviation recognition
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表 1 焊接工艺参数
Table 1. Welding process parameters
试验参数 参数值 送丝速度 /(m·min–1) 6.4 摆动幅度 / mm 6 摆动频率 / Hz 1.5 焊丝直径 / mm 1 焊接速度 /(mm·s–1) 3 保护气 82%Ar + 18%CO2 -
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