摘要
将图像处理与模式识别技术用于铝合金TIG焊接过程信息提取过程 ,根据铝合金熔池图像随机噪声强的特点 ,采用加权中值滤波、统计灰度边缘检测、统计期望阈值法和投影方法对铝合金熔池图像进行了预处理。探索了将神经网络用于焊接熔池图像处理的方法 ,采用BP神经网络对二值化熔池图像进行边缘提取 ,取得了理想的效果。研究了大电流条件下铝合金熔池图像的对称性 ,通过单面图像 ,得到了完全的熔池边缘图像。
The image processing and pattern recognition was first used to obtain information of the TIG welding process of aluminum alloy.The image of welding pool of aluminum alloy was pretreated with a series of methods using weighted median filter,statistical gray enhancement,threshold by expectation and projection according to the strong noise in the image.A neural network method was used to process image of welding pool and the result of detecting the edge of binary image with BP neural network was excellent.The symmetry of welding pool of aluminum alloy was studied when the welding current is great.The whole welding pool edge of the image is obtained in the single side image and the accurate measuring method of the welding pool geometry parameter is provided.
出处
《焊接学报》
EI
CAS
CSCD
北大核心
2002年第5期73-76,共4页
Transactions of The China Welding Institution
关键词
熔池
铝合金
TIG焊
图像处理
模式识别
aluminum alloy
TIG welding
image processing
pattern recognition
