用于先进高温焊缝检测的爬行机器人

IF 4.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
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引用次数: 0

摘要

高温工业检测面临诸多挑战,尤其是通过移动机器人进行自主检测。本文介绍了用于工业超级双相不锈钢容器焊缝自主无损检测(NDT)的移动机器人 CRAS(Climbing Robot for Advanced inSpection)。它涵盖了设计过程、以前的工作、主要挑战和现场测试。机器人的主要目标是在运行时对加热的分离罐进行超声波检测。待检测结构的金属表面在运行时持续处于高温(80 °C-135 °C)下。CRAS 将磁轮作为一种粘附方法和一种能够识别和跟踪焊缝的感知系统。无损检测方法采用相控阵超声波技术。本文针对高温带来的三个挑战提出了解决方案:机器人丧失附着力、超声波信号变形以及损坏敏感设备(如传感器、摄像头和任何电子元件)的风险。文中详细介绍了 CRAS 所采用的解决方案,并探讨了 CRAS 未来的发展步骤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Climbing robot for advanced high-temperature weld bead inspection

High-temperature industrial inspection has several challenges, especially if it is an autonomous inspection through mobile robots. This paper introduces the mobile robot CRAS (Climbing Robot for Advanced inSpection) for autonomous non-destructive testing (NDT) of weld beads from industrial super-duplex stainless steel vessels. It covers the design process, previous works, main challenges, and field testing. The main objective of the robot is to perform ultrasonic inspection over a heated separator tank while it operates. The metallic surfaces of the structure to be inspected are under constant high temperatures (80 °C–135 °C) when in operation. CRAS presents magnetic wheels as an adhesion method and a perception system able to identify and follow weld beads. The NDT method uses the phased-array ultrasonic technique. This paper approaches and proposes a solution for three challenges due to the high temperature: the loss of robot adhesion, ultrasound signal deformation, and the risk of damaging sensitive equipment such as sensors, cameras, and any electronic component. The CRAS adopted solutions are detailed and future steps of CRAS development are also addressed.

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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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