PROJECT TITLE :
Dynamic Reliability Assessment for Multi-State Systems Utilizing System-Level Inspection Data
Ancient time-based mostly reliability assessment ways evaluate the reliability of a multi-state system (MSS) from a population or a statistical perspective that the reliability of a system is computed purely based upon historical time-to-failure knowledge collected from a massive population of identical elements or systems. These ways, but, fail to characterize the stochastic behaviors of a specific individual system. During this paper, by utilizing system-level observation history, a dynamic reliability assessment method for MSSs is put forth. The proposed recursive Bayesian formula is able to dynamically update the reliability operate of a selected MSS over time by incorporating system-level inspection knowledge. The dynamic reliability perform, state probabilities, and remaining useful life distribution of an MSS in residual lifetime are derived for two common cases: the degradation of components follows a homogeneous continuous time Markov method, and a non-homogeneous continuous time Markov process. The effectiveness and accuracy of the proposed technique are demonstrated via two numerical examples.
Did you like this research project?
To get this research project Guidelines, Training and Code... Click Here