基于红外温度场的电弧增材制造缺陷在线检测方法

Online detection of defects in arc additive manufacturing based on infrared temperature field

  • 摘要: 根据增材制造逐层累积的特殊性,分层实施的在线检测思想能避免加工完成后出现不可修复的废品。采用基于实时采集分析熔积层红外温度场的无损检测方法,将多帧温度场数据堆叠获取熔积层红外轮廓,根据提取的红外轮廓特征对当前熔积层成形质量进行判断,利用残差网络ResNet18对红外轮廓图像进行分类识别。通过在线验证,检测分类的准确率可达97.16%,单张红外轮廓图像检测分类时间仅1.35 ms。该方法能在增材制造过程中在线检测成形质量,便于后续铣削、补焊及工艺参数的优化处理,具有实际工程意义。

     

    Abstract: According to the particularity of layer by layer accumulation in additive manufacturing,the idea of online layer detection could avoid irreparable wastes after finishing processing. A nondestructive detection method was adopted based on real-time acquisition and analysis of the infrared temperature field of the fusion layer. The infrared contour of the fusion layer by stacking multiple frames of temperature field data was obtained,and the forming quality of the current fusion layer was judged according to the extracted infrared contour characteristics. Finally,the infrared contour image was classified and identified through the residual network ResNet18. Through online verification,the accuracy of detection classification could reach 97. 16%,and the detection and classification time of the single infrared contour image was only 1. 35 ms. This method could be used to detect the forming quality in the process of additive manufacturing,which was convenient for subsequent milling,repair welding and optimization of process parameters. It had practical engineering significance.

     

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