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

Zhonglai Wang, Yi Chen, Erfu Yang

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Abstract

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.
Original languageEnglish
Pages1-5
Number of pages5
Publication statusPublished - 29 Oct 2015
EventSpace Robotics Symposium: Present and Future Robotics In Space Applications - Technology & Innovation Centre, University of Strathclyde, Glasgow, United Kingdom
Duration: 29 Oct 201530 Oct 2015
http://onlinelearning.dmem.strath.ac.uk/laulima/tiki-download_file.php?fileId=45799

Other

OtherSpace Robotics Symposium
CountryUnited Kingdom
CityGlasgow
Period29/10/1530/10/15
Internet address

Keywords

  • space robotics
  • reliability design
  • failure mechanism
  • fault diagnosis
  • fault drediction
  • condition monitoring
  • prognostic health management

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  • Cite this

    Wang, Z., Chen, Y., & Yang, E. (2015). An integrated framework for intelligent reliability design and prognostic health management of space robotic systems. 1-5. Paper presented at Space Robotics Symposium, Glasgow, United Kingdom.