论文标题
机器人操作系统（ROS）的预后和健康管理（PHM）工具
Prognostic and Health Management (PHM) tool for Robot Operating System (ROS)
论文作者
论文摘要
如今，预后感知系统越来越多地用于许多系统，对于维持自主权至关重要。所有工程系统，尤其是机器人都不是完美的。在一定时间内没有故障是完美的系统，实际上是不可能的。在所有工程工作中，我们必须尝试预测或最小化/防止系统中的故障。系统中的故障通常未知，因此预测系统的这些故障和可靠性是通过预测过程进行的。可靠性分析对于改善系统性能，扩展系统寿命等很重要。预后和健康管理（PHM）包括可靠性，安全性，预测性故障检测 /隔离，高级诊断 /预后，预后 /预后，组件跟踪，健康报告和信息管理和信息管理等。本研究提出了一种开放源机器人的预后和健康管理工具，使用了基于模型的方法，请使用rous nooksy n soft os os n os sonics。该工具是与与ROS兼容的任何类型的机器人（移动机器人，机器人，无人机等）一起使用的通用工具。 Some features of this tool are managing / monitoring robots' health, RUL, probability of task completion (PoTC) etc. User is able to enter the necessary equations and components information (hazard rates, robot configuration etc.) to the PHM tool and the other sensory data like temperature, humidity, pressure, load etc. In addition to these, a case study is conducted for the mobile robots (OTA) using this tool.
Nowadays, prognostics-aware systems are increasingly used in many systems and it is critical for sustaining autonomy. All engineering systems, especially robots, are not perfect. Absence of failures in a certain time is the perfect system and it is impossible practically. In all engineering works, we must try to predict or minimize/prevent failures in the system. Failures in the systems are generally unknown, so prediction of these failures and reliability of the system is made by prediction process. Reliability analysis is important for the improving the system performance, extending system lifetime, etc. Prognostic and Health Management (PHM) includes reliability, safety, predictive fault detection / isolation, advanced diagnostics / prognostics, component lifecycle tracking, health reporting and information management, etc. This study proposes an open source robot prognostic and health management tool using model-based methodology namely "Prognostics and Health Management tool for ROS". This tool is a generic tool for using with any kind of robot (mobile robot, robot arm, drone etc.) with compatible with ROS. Some features of this tool are managing / monitoring robots' health, RUL, probability of task completion (PoTC) etc. User is able to enter the necessary equations and components information (hazard rates, robot configuration etc.) to the PHM tool and the other sensory data like temperature, humidity, pressure, load etc. In addition to these, a case study is conducted for the mobile robots (OTA) using this tool.
