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An integrated framework for intelligent reliability design and prognostic health management of space robotic systems

机译:用于空间机器人系统的智能可靠性设计和预后健康管理的集成框架

摘要

Space robotics has received significant attention from both theoretic research and applications. The mission in future will be involving and be heavily supported by different robotic systems, such as planetary rovers and manipulators for orbital servicing, etc. The harsh environment in space can severely affect the operating safety of space robotic systems and therefore the lifecycle reliability problem and prognostic healthmanagement have paramount importance to make the space robotic systems more successful and safer in future space missions. Though there has a great deal of research on failure detection, fault diagnosis and condition monitoring for conventional space systems and other engineering applications such as nuclear power station, it has a lack of research on the general methodology for both the reliability design and health management of space robotic systems to improve the operating safety. This paper proposes an integrated framework (named as iRPHM) in which the higher reliability is designed for space robotic systems by taking advantage of reliability-based intelligent design optimization while considering the expected random loadings. The prognostic health management (PHM) is implemented in the proposed framework to decrease the failures arising from the unexpected events in harsh space environment.
机译:太空机器人技术已经从理论研究和应用中获得了极大的关注。未来的任务将涉及不同的机器人系统,并受到它们的大力支持,例如行星漫游者和用于轨道服务的操纵器等。太空中的恶劣环境会严重影响太空机器人系统的运行安全,从而严重影响生命周期的可靠性和可靠性。预后健康管理对于使太空机器人系统在未来的太空飞行中更成功,更安全至关重要。尽管对常规空间系统和其他工程应用(例如核电站)的故障检测,故障诊断和状态监视进行了大量研究,但对于可靠性设计和健康管理的通用方法却缺乏研究。太空机器人系统提高了操作安全性。本文提出了一个集成的框架(称为iRPHM),其中在考虑预期的随机载荷的同时,利用基于可靠性的智能设计优化技术,为太空机器人系统设计了更高的可靠性。在建议的框架中实施了预后健康管理(PHM),以减少在恶劣的空间环境中因意外事件引起的故障。

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