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Prognostics for Nonlinear Degrading Systems with Three-Source Variability

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

Thanks to the rapid development of information and sensing technologies, the degradation signals of a system can be obtained relatively easily using CM techniques, and the past decade has witnessed an increasingly growing research interest on the RUL estimate of systems based on the sensed degradation signals [1, 2].

Suggested Citation

  • Xiao-Sheng Si & Zheng-Xin Zhang & Chang-Hua Hu, 2017. "Prognostics for Nonlinear Degrading Systems with Three-Source Variability," Springer Series in Reliability Engineering, in: Data-Driven Remaining Useful Life Prognosis Techniques, chapter 0, pages 313-336, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-662-54030-5_11
    DOI: 10.1007/978-3-662-54030-5_11
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    Cited by:

    1. Mikhail, Mina & Ouali, Mohamed-Salah & Yacout, Soumaya, 2024. "A data-driven methodology with a nonparametric reliability method for optimal condition-based maintenance strategies," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

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