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An image-based feature tracking algorithm for real-time measurement of clad height

机译：基于图像的特征跟踪算法，用于包层高度的实时测量

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This paper presents a novel algorithm for real-time detection of clad height in laser cladding which is known as a layered manufacturing technique. A realtime measurement of clad geometry is based on the use of a developed trinocular optical detector composed of three CCD cameras and the associated interference filters and lenses. The images grabbed by the trinocular optical detector are fed into an algorithm which combines an image-based tracking protocol and a recurrent neural network to extract the clad height in real-time. The image feature tracking strategy is a synergy between a simple image selecting protocol, a fuzzy thresholding technique, a boundary tracing method, a perspective transformation and an extraction of elliptical features of the projected melt pool's images. The proposed algorithm and the trained network were utilized in the process resulting in excellent detection of the clad height at various working conditions in which SS303L was deposited on mild steel. It was concluded that the developed system can detect the clad height independent from clad paths with about 12% maximum error.
机译：本文提出了一种新颖的实时检测激光熔覆层熔覆高度的算法，称为分层制造技术。包覆层几何形状的实时测量是基于开发的三目光学探测器的使用，该探测器由三个CCD摄像机以及相关的干涉滤光镜和透镜组成。三目光学检测器捕获的图像被馈送到一种算法中，该算法结合了基于图像的跟踪协议和递归神经网络以实时提取包层高度。图像特征跟踪策略是简单的图像选择协议，模糊阈值技术，边界跟踪方法，透视变换和投影熔池图像的椭圆特征提取之间的协同作用。在该过程中利用了所提出的算法和训练有素的网络，可以很好地检测SS303L沉积在低碳钢上的各种工作条件下的包层高度。结论是，开发的系统可以独立于包层路径检测包层高度，最大误差约为12％。

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