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A robotic welding system using image processing techniques and a CAD model to provide information to a multi-intelligent decision module

机译:一种机器人焊接系统,使用图像处理技术和CaD模型为多智能决策模块提供信息

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摘要

Design/methodology/approach – A pattern recognition system recognizes shipbuilding parts using shape contour information. Fourier-descriptors provide information and neural networks make decisions about shapes. Findings – The system has distinguished between various parts and programs have been generated so that the methods have proved to be valid approaches. Practical implications – The new system used a rudimentary curvature metric that measured Euclidean distance between two points in a window but the improved accuracy and ease of implementation can benefit other applications concerning curve approximation, node tracing, and image processing, but especially in identifying images of manufactured parts with distinct corners. Originality /value – A new proposed system has been presented that uses image processing techniques in combination with a computer-aided design model to provide information to a multi-intelligent decision module. This module will use different criteria to determine a best weld path. Once the weld path has been determined then the program generator and post-processor can be used to send a compatible program to the robot controller. The progress so far is described.
机译:设计/方法/方法-模式识别系统使用形状轮廓信息识别造船零件。傅立叶描述符提供信息,神经网络做出有关形状的决策。结果–系统区分了各个部分,并生成了程序,因此该方法被证明是有效的方法。实际意义–新系统使用了基本的曲率度量标准,可以测量窗口中两点之间的欧几里得距离,但是改进的精度和易于实现的功能可以使曲线近似,节点跟踪和图像处理等其他应用受益,特别是在识别图像中具有明显角的制造零件。独创性/价值–提出了一个新的提议系统,该系统结合使用图像处理技术和计算机辅助设计模型来向多智能决策模块提供信息。该模块将使用不同的标准来确定最佳焊接路径。一旦确定了焊接路径,就可以使用程序生成器和后处理器将兼容程序发送到机器人控制器。描述了到目前为止的进展。

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