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RSL Prediction Approach for Systems with Operation State Switches

In: Data-Driven Remaining Useful Life Prognosis Techniques

Author

Listed:
  • Xiao-Sheng Si

    (Xi’an Institute of High-Technology)

  • Zheng-Xin Zhang

    (Xi’an Institute of High-Technology)

  • Chang-Hua Hu

    (Xi’an Institute of High-Technology)

Abstract

Predicting the residual life is of significant importance in proactive maintenance, and prognostics and health management of systems (Pecht, Prognostics and health management of electronics, 2008, [1], Ye et al., Eur J Oper Res 221(2):360–367, 2012, [2], Lall et al., IEEE Trans Ind Electron 59(11):4301–4314, 2012, [3]). Many highly critical systems in military and aerospace fields, like missiles, rockets, and their associated systems, are required of long-term storage before used (Mclain and Warren, Automated reliability life data analysis of missiles in storage and flight, (1990), [4], Zhao et al., Qual Reliab Eng Int 11(1):123–127, 1995, [5], Luo et al., Research on storage life prediction method for strap-down inertial navigation system, 2012, [6]). For such systems, storage is an essential part of their lifecycles and the operating time of such systems is usually very short compared with the time in storage. Therefore, the investigation of the residual storage life (RSL) prediction is of significant importance in that it can help to plan efficient monitoring policy to extend the system’s life.

Suggested Citation

  • Xiao-Sheng Si & Zheng-Xin Zhang & Chang-Hua Hu, 2017. "RSL Prediction Approach for Systems with Operation State Switches," Springer Series in Reliability Engineering, in: Data-Driven Remaining Useful Life Prognosis Techniques, chapter 0, pages 337-360, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-662-54030-5_12
    DOI: 10.1007/978-3-662-54030-5_12
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