防灾工厂巡检智能机器人视觉系统

Saifuddin Mahmud, Justin Dannemiller, R. Sourave, Xiangxu Lin, Jong-Hoon Kim
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引用次数: 1

摘要

应急情景模拟和例行检查是确保电厂、炼油厂、铁厂和工业单位正常运行和安全的必要手段。此外,通过使用自主机器人,可以提高此类检查的可靠性和频率。除了位于危险区域的设施(如海上工厂)可能无法派遣响应小组之外,可以通过对设施(泵、储罐、锅炉等)的自动检查和诊断来防止人为错误造成的事故。机器人辅助检测操作的主要障碍之一是检测各种类型的仪表,读取它们,并采取适当的行动。本研究描述了一种独特的基于机器人视觉的工厂检查系统,可用于提高例行检查的频率,从而最大限度地减少由人为错误或自然退化引起的设备故障和事故(由气体泄漏引起的爆炸或火灾)。该建议系统可以通过检测和读取各种仪表来进行设施检查,并在检测到任何异常时发出报告。此外,该系统还能够应对不可预见的异常事件,这些事件可能对人类响应团队造成潜在危害,例如在气体泄漏时直接操纵阀门。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Robot Vision System for Plant Inspection for Disaster Prevention
Simulation of emergency response scenarios and routine inspections are imperative means in ensuring the proper functioning and safety of power plants, oil refineries, iron works, and industrial units. By utilizing autonomous robots, moreover, the reliability and frequency of such inspections can be improved. With the exception of facilities located in hazardous areas, such as off-shore factories, where dispatching response teams might be impossible, accidents caused by human mistakes can be prevented by autonomous inspections and diagnosis of facilities (pumps, tanks, boilers, and so on). One of the primary obstacles in robot-assisted inspection operations is detecting various types of gauges, reading them, and taking appropriate action. This study describes a unique robot vision-based plant inspection system that may be used to enhance the frequency of routine checks and, in turn, minimize equipment faults and accidents (explosions or fires caused by gas leaks) caused by human mistakes or natural degradation. This suggested system can conduct facility inspections by detecting and reading a variety of gauges and issuing reports upon the detection of any anomalies. Furthermore, this system is capable of responding to unforeseen anomalous events that pose potential harm to human response teams, such as the direct manipulation of valves in the presence of a gas leak.
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