University of Brasilia, Faculty of Technology, Department of Mechanical, Mechatronic Engineering, Campus Universitario Darcy Ribeiro, Brasilia/DF, Brazil.
Sensors (Basel). 2012;12(6):6953-66. doi: 10.3390/s120606953. Epub 2012 May 25.
The present study shows the relationship between welding quality and optical-acoustic emissions from electric arcs, during welding runs, in the GMAW-S process. Bead on plate welding tests was carried out with pre-set parameters chosen from manufacturing standards. During the welding runs interferences were induced on the welding path using paint, grease or gas faults. In each welding run arc voltage, welding current, infrared and acoustic emission values were acquired and parameters such as arc power, acoustic peaks rate and infrared radiation rate computed. Data fusion algorithms were developed by assessing known welding quality parameters from arc emissions. These algorithms have showed better responses when they are based on more than just one sensor. Finally, it was concluded that there is a close relation between arc emissions and quality in welding and it can be measured from arc emissions sensing and data fusion algorithms.
本研究展示了 GMAW-S 过程中，焊接过程中的电弧光学-声学发射与焊接质量之间的关系。采用制造标准中选择的预设参数进行了板对板焊接试验。在焊接过程中，通过油漆、油脂或气体故障在焊接路径上产生干扰。在每个焊接过程中，采集电弧电压、焊接电流、红外和声学发射值，并计算电弧功率、声学峰值率和红外辐射率等参数。通过评估来自电弧发射的已知焊接质量参数，开发了数据融合算法。这些算法在基于不止一个传感器时表现出更好的响应。最后得出结论，电弧发射与焊接质量之间存在密切关系，可以通过电弧发射感应和数据融合算法来测量。
