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An inspection robot using infrared thermography for belt conveyor

机译:一种使用红外热成像的检查机器人,用于带式输送机

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The key mechanical components of belt conveyor is lack of effective monitoring at present. The traditional monitoring methods such as visual inspection, temperature measurement have shortcoming, the huge workload, blind spots and other issues are difficult to solve. This paper proposes an inspection robot program with infrared thermometer for belt conveyor. Along the inspection track, the motor drive the infrared thermometer moves which mounted on robot. Infrared thermal image of motor, pulleys, rollers and other key transmission components are captured. With image signal processing and pattern recognition technology, the infrared images are processed. After infrared image segmentation, feature extraction and classification, the automatic identification of the typical elements are realized. Finally, make use of the component type that has identified, the warning temperature values and contract the library rules of failure database, this paper achieves a Failure Prognostic System (FRS) on drive system of belt conveyor. Experimental results show that the method can achieve automatic identification and fault warning abnormal temperature rise of motor, pulley and roller and the other mechanical components.
机译:皮带输送机的关键机械部件目前缺乏有效的监测。传统的监测方法如目视检查,温度测量缺点,巨大的工作量,盲点等问题都难以解决。本文提出了一种带有红外温度计的检查机器人程序,用于带式输送机。沿着检查轨道,电机驱动安装在机器人上的红外温度计移动。捕获电动机,滑轮,滚筒和其他关键传动部件的红外线热图像。利用图像信号处理和模式识别技术,处理红外图像。在红外图像分割后,特征提取和分类,实现了典型元件的自动识别。最后,利用已识别的组件类型,警告温度值和合同的故障数据库库规则,在皮带输送机驱动系统上实现了失败的预后系统(FRS)。实验结果表明,该方法可以实现自动识别和故障警告电动机,滑轮和滚筒和其他机械部件的异常温度升高。

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