Multiple Failure Prognosis for Hybrid Systems

Diagnosis and prognosis are two important aspects in condition-based maintenance. Diagnosis is posterior event analysis and prognosis is prior event analysis. Prognosis is much more efficient than diagnostics to achieve zero-downtime performance. This is very important when a fault or a failure is catastrophic in some situations (e.g., nuclear power plant and helicopter gearbox). This chapter aims to develop a model based prognosis method for hybrid systems with multiple incipient faults. Several prescribed dynamic models are used to describe the degradation behaviors of incipient faults and such degradation models will serve as a base for prognosis purpose. A concept of augmented global analytical redundancy relations (AGARRs) is developed to describe the fault under parametric and nonparametric nature. Experimental results are presented to illustrate the effectiveness. Additionally, a dynamic fault isolation scheme is proposed to facilitate the situation where multiple faults happen simultaneously at a mode where these faults have different detectabilities. The degradation behavior of each faulty component is mode-dependent and can be estimated by a hybrid differential evolution algorithm. Thereafter, the remaining useful life of faulty component which varies with different operating modes is calculated by using both the estimated degradation model and the user-selected failure threshold. Experiments are carried out to validate the key concepts of the developed methods and results suggest the effectiveness.