Monitoring of Electric Scooter With Intermittent Faults and Imperfect Maintenance: A Dynamic Observation Window Approach

摘要

In this article, a dynamic observation window (DOW)-based prognosis method is proposed for the electric scooter in the presence of intermittent faults and imperfect maintenance. First, analytical redundancy relations (ARRs) derived from the nonlinear bond graph (BG) model and fault signature matrix (FSM) are employed for fault detection and isolation (FDI), and an adaptive fruit fly optimization algorithm (AFOA) is developed to estimate the magnitude, appearing, and disappearing instants of intermittent faults. Second, the degradation characteristics of the intermittent fault are extracted using the concept of DOW. After that, a joint degradation model is established, where three impact factors are introduced to quantify the impacts of imperfect maintenance on intermittently faulty component. Based on this model, the remaining useful life (RUL) of the component subjected to intermittent fault and imperfect maintenance can be predicted. Finally, the effectiveness of the proposed method is experimentally verified.

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