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用Nd…YAG脉冲激光器对0.5mm厚TC4钛合金薄板进行了焊接实验。设计了与光路同轴的机器视觉系统,并利用高速电荷耦合器件(CCD)实时获取焊斑图像。通过采用辅助照明光源有效提高了焊斑成像质量。采用基于细胞神经网络的算法进行焊斑边缘提取。通过对焊斑图像的分析可以获得薄板穿孔或熔深不足的信息,以此作为反馈控制信号对脉冲激光功率进行实时调整。实验证明,该方法可有效减少薄板穿孔和熔深不足缺陷的发生,提高TC4钛合金薄板激光焊接的质量。
The welding experiment of 0.5 mm thick TC4 titanium alloy plate was carried out with Nd ... YAG pulsed laser. The machine vision system is designed to be coaxial with the optical path, and the spot image is acquired in real time by using the CCD (High Speed Charge Coupled Device). Through the use of auxiliary lighting source effectively improve the welding spot imaging quality. The algorithm based on cellular neural network is used to extract the edge of the welding spot. Through analyzing the welding spot image, we can get the information of sheet perforation or insufficient penetration, which can be used as the feedback control signal to adjust the pulse laser power in real time. Experiments show that the method can effectively reduce the perforation and penetration defects defects, improve the quality of laser welding TC4 titanium alloy sheet.