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Automatic Patrol and Inspection Method for Machinery Diagnosis Robot—Sound Signal-Based Fuzzy Search Approach

机译:基于机械诊断机器人声音信号的模糊搜索方法自动巡逻和检测方法

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This paper developed the basic theories and techniques for a plant machinery diagnosis robot (MDR). The workplace of MDR is usually a large-scale plant or a place with a dangerous environment. It must autonomously carry out the condition monitoring of plant machinery with sensors in order to detect machinery faults for securing the safety of the plant. In this paper, the basic function, concept and structure of the MDR are discussed. The intelligent control method by rough set, fuzzy neural network (FNN) and self-location-azimuth correction for the MDR that patrols on the inspection route are proposed. Additionally, navigation and search method by fuzzy inference using extracted fault sound signals are also proposed, by which the MDR will be navigated to the near side of the faulty machine when the fault of a machine has been detected during inspection. Finally, examples of practical navigation and fault machine searching are also shown.
机译:本文开发了植物机械诊断机器人(MDR)的基本理论和技术。 MDR的工作场所通常是一个大型工厂或一个有危险环境的地方。它必须自主地使用传感器进行植物机械的状态监测,以便检测用于确保植物安全的机械故障。本文讨论了MDR的基本功能,概念和结构。提出了智能控制方法,提出了对检验路线巡逻的MDR的模糊神经网络(FNN)和自我定位 - 方位角校正。另外,还提出了使用提取的故障声音信号的模糊推断的导航和搜索方法,通过该信号在检查期间检测到机器的故障时,MDR将导航到故障机器的近侧。最后,还显示了实际导航和故障机器搜索的例子。

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