Now showing items 1-8 of 8

    • Advanced data-driven prognostics and health management for complex dynamic systems 

      Bai, Guangxing (Wichita State University, 2016-05)
      Prognostics and health management (PHM) is an emerging engineering discipline that diagnoses and predicts how an engineered system will degrade its performance and when it will lose its partial or whole functionality. With ...
    • Battery prognostics using a self-cognizant dynamic system approach 

      Bai, Guangxing; Wang, Pingfeng (IEEE, 2015)
      This paper proposes a new self-cognizant dynamic system approach for Battery PHM, that incorporates an artificial neural network model into a dual extended Kalman filter (DEKF) algorithm. A feed-forward neural network ...
    • Failure prognosis based on adaptive state space models 

      Bai, Guangxing; Abdolsamadi, Amirmahyar; Wang, Pingfeng (ASME, 2016)
      This paper presents a generic data-driven failure prognosis method based on adaptive state space models for engineering systems, which integrates adaptive model recognition with a dynamic system model for remaining useful ...
    • A generic model-free approach for lithium-ion battery health management 

      Bai, Guangxing; Wang, Pingfeng; Hu, Chao; Pecht, Michael (Elsevier Ltd., 2014-12-15)
      Accurate estimation of the state-of-charge (SoC) and state-of-health (SoH) for an operating battery system, as a critical task for battery health management, greatly depends on the validity and generalizability of battery ...
    • An internal state variable mapping approach for Li-plating diagnosis 

      Bai, Guangxing; Wang, Pingfeng (Elsevier B.V., 2016-08-15)
      Li-ion battery failure becomes one of major challenges for reliable battery applications, as it could cause catastrophic consequences. Compared with capacity fading resulted from calendar effects, Li-plating induced battery ...
    • Prognostics using an adaptive self-cognizant dynamic system approach 

      Bai, Guangxing; Wang, Pingfeng (IEEE, 2016-09)
      Prognostics and health management is an emerging engineering technology that has been applied to a large variety of engineering systems to improve system's reliability. However, existing prognostics approaches have been ...
    • A self-cognizant dynamic system approach for prognostics and health management 

      Bai, Guangxing; Wang, Pingfeng; Hu, Chao (Elsevier B.V., 2015-03-15)
      Prognostics and health management (PHM) is an emerging engineering discipline that diagnoses and predicts how and when a system will degrade its performance and lose its partial or whole functionality. Due to the complexity ...
    • Time-variant reliability-based design optimization using sequential kriging modeling 

      Li, Mingyang; Bai, Guangxing; Wang, Zequn (Springer Berlin Heidelberg, 2018-03-21)
      This paper presents a sequential Kriging modeling approach (SKM) for time-variant reliability-based design optimization (tRBDO) involving stochastic processes. To handle the temporal uncertainty, time-variant limit state ...