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Autonomous Non-Destructive Remote Robotic Inspection of Offshore Assets

机译:自主无损远程机器人检查海上资产

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Offshore assets suffer from material degradation over their lifetimes. Regular inspections are necessary to prevent failures and to reduce the cost of maintenance. These often require downtime of the asset and can involve risk to human workers who have to be sent to the offshore location. In this work, we present a non-destructive (NDE) system in conjunction with a robotic platform, which can perform inspections of the thickness of a component, for example from the outside of a tank or a pressure vessel. The NDE system consists of a digital acquisition system and an electromagnetic acoustic transducer (EMAT). The EMAT generates an acoustic wave, which reflects from the internal features of the component. The wave is received by the same device. The received signal is then processed by the acquisition system to determine the thickness of the component. The NDE system is integrated with a robotic platform that can autonomously or semi-autonomously perform scans of the asset. The robot platform presented in this work uses sensor fusion, machine vision and state of the art motion planning techniques to build a map of the material quality in 3D. This is achieved by exploiting the precise movement of the robot end-effector along the surface of the asset and then integrating the position of the NDE sensor. The collected data is then presented to the remote operator in a user-friendly way, which allows them to evaluate the state of the asset. We validate this system using material samples with known defects. We performed experiments in a controlled environment, and we demonstrate the system in a case study at a testing facility operated by our industrial partners.
机译:离岸资产遭受其寿命的物质退化。预防故障并降低维护成本是必要的经常检查。这些往往需要资产的停机,并且可能涉及必须送到离岸地点的人工的风险。在这项工作中,我们介绍了一种非破坏性(NDE)系统,与机器人平台一起,可以执行组件的厚度的检查,例如从罐或压力容器的外部进行。 NDE系统包括数字采集系统和电磁声换能器(EMAT)。 EMAT产生声波,其从组件的内部特征中反映。波是由同一设备接收的。然后通过采集系统处理接收信号以确定组件的厚度。 NDE系统与机器人平台集成,可以自主或半自动执行资产的扫描。本作工作中提供的机器人平台使用传感器融合,机器视觉和最先进的运动规划技术,以构建3D中材料质量的地图。这是通过利用机器人末端执行器的精确运动沿着资产的表面,然后集成NDE传感器的位置来实现的。然后,收集的数据以用户友好的方式向远程运营商呈现给远程运营商,其允许它们评估资产的状态。我们使用具有已知缺陷的材料样本验证该系统。我们在受控环境中进行了实验,我们在由我们的工业伙伴运营的测试设施进行了案例研究中展示了该系统。

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