Abstract Horizontal welding is important for heavy or huge welding structures. Keyhole mode variable polarity plasma arc welding of aluminum alloy plates with medium thickness was carried out in horizontal position. T...Abstract Horizontal welding is important for heavy or huge welding structures. Keyhole mode variable polarity plasma arc welding of aluminum alloy plates with medium thickness was carried out in horizontal position. The characteristic of welding defects was introduced. Preliminary experiments indicated that the undercut defect could not be eliminated easily. The relationship between welding parameters and the undercut defect showed that this deject could be lessened by using higher heat input. The fluid flow of weld pool was observed by a high speed camera. The fluid flow in weld pool was not symmetric and much of molten metal gathered in the lower part. The fluid flow velocity in the lower part was bigger than that in the upper part. To this end, the formative mechanism of the undercut defect was proposed. The flowability of the molten metal was an influential factor for the undercut defect. A preheating method was designed to verify the formative mechanism.展开更多
针对窄间隙熔化极气体保护焊(Gas Metal Arc Welding,GMAW)焊道侧壁处局部咬边缺陷检测困难的问题,提出了一种基于电弧声信号特征提取与处理的咬边缺陷在线检测方法。通过分析正常、临界咬边和咬边这3种焊接状态的电弧形态和电弧声信号...针对窄间隙熔化极气体保护焊(Gas Metal Arc Welding,GMAW)焊道侧壁处局部咬边缺陷检测困难的问题,提出了一种基于电弧声信号特征提取与处理的咬边缺陷在线检测方法。通过分析正常、临界咬边和咬边这3种焊接状态的电弧形态和电弧声信号特征,证实坡口侧壁引起的电弧形态变化是影响电弧声信号变化的重要因素。在此基础上采用小波包时频分析,同时引入特征类间标准差作为评价指标,确定了能有效识别3种焊接状态的敏感特征。采用Sigmoid支持向量机和五折交叉验证建立预测模型,实验结果表明该模型能较好地实现3种焊接状态的预测分类,识别准确率达到96.0%。展开更多
A method for automatic detection of burning through of short circuit CO 2 arc welding is presented. It is based on the extraction of arc signal features as well as classification of the obtained features using self ...A method for automatic detection of burning through of short circuit CO 2 arc welding is presented. It is based on the extraction of arc signal features as well as classification of the obtained features using self organize feature map(SOM) neural networks in order to get the weld quality information, for example, to determine if there is defect in the product. This is important for the on line monitoring of weld quality especially in robotic welding and lay the foundation for the further real time control of weld quality.展开更多
Employing the arc discharge method we prepared carbon nanotubes, CNTs, in open air deionized water. Their morphology was studied varying the annealing temperature and characterizing by Raman Spectroscopy, Transmission...Employing the arc discharge method we prepared carbon nanotubes, CNTs, in open air deionized water. Their morphology was studied varying the annealing temperature and characterizing by Raman Spectroscopy, Transmission Electron Microscopy (TEM), X-Ray Diffractogram (XRD) and Energy Dispersion X-Ray (EDX). According to the study, the CNTs are found self-assembled where the graphene sheets and/or defects are observed sort out themselves with enhancement of temperature.展开更多
基金This research is supported by the National Natural Science Foundation of China （Grant No. 51475105）.
文摘Abstract Horizontal welding is important for heavy or huge welding structures. Keyhole mode variable polarity plasma arc welding of aluminum alloy plates with medium thickness was carried out in horizontal position. The characteristic of welding defects was introduced. Preliminary experiments indicated that the undercut defect could not be eliminated easily. The relationship between welding parameters and the undercut defect showed that this deject could be lessened by using higher heat input. The fluid flow of weld pool was observed by a high speed camera. The fluid flow in weld pool was not symmetric and much of molten metal gathered in the lower part. The fluid flow velocity in the lower part was bigger than that in the upper part. To this end, the formative mechanism of the undercut defect was proposed. The flowability of the molten metal was an influential factor for the undercut defect. A preheating method was designed to verify the formative mechanism.
文摘针对窄间隙熔化极气体保护焊(Gas Metal Arc Welding,GMAW)焊道侧壁处局部咬边缺陷检测困难的问题,提出了一种基于电弧声信号特征提取与处理的咬边缺陷在线检测方法。通过分析正常、临界咬边和咬边这3种焊接状态的电弧形态和电弧声信号特征,证实坡口侧壁引起的电弧形态变化是影响电弧声信号变化的重要因素。在此基础上采用小波包时频分析,同时引入特征类间标准差作为评价指标,确定了能有效识别3种焊接状态的敏感特征。采用Sigmoid支持向量机和五折交叉验证建立预测模型,实验结果表明该模型能较好地实现3种焊接状态的预测分类,识别准确率达到96.0%。
基金ProvincialNaturalScience FoundationofGuangdong (No .990 5 5 0 )
文摘A method for automatic detection of burning through of short circuit CO 2 arc welding is presented. It is based on the extraction of arc signal features as well as classification of the obtained features using self organize feature map(SOM) neural networks in order to get the weld quality information, for example, to determine if there is defect in the product. This is important for the on line monitoring of weld quality especially in robotic welding and lay the foundation for the further real time control of weld quality.
文摘Employing the arc discharge method we prepared carbon nanotubes, CNTs, in open air deionized water. Their morphology was studied varying the annealing temperature and characterizing by Raman Spectroscopy, Transmission Electron Microscopy (TEM), X-Ray Diffractogram (XRD) and Energy Dispersion X-Ray (EDX). According to the study, the CNTs are found self-assembled where the graphene sheets and/or defects are observed sort out themselves with enhancement of temperature.
