Lebesgue-Time–Space-Model-Based Diagnosis and Prognosis for Multiple Mode Systems

Lebesgue-sampling-based fault diagnosis and prognosis (LS-FDP) is developed with advantages of light computation and small uncertainty accumulation. In previous research, the applications of LS-FDP are developed for single-model degradation processes, which do not consider degradation processes that involve multiple modes with switching models. To address this scenario, this article proposes a modified interacting multiple model filter in the Lebesgue-time-space-model-based FDP framework. The design, analysis, and particle filtering-based implementation of the proposed method are discussed in detail. A simulation example and a real experiment are presented to demonstrate the accuracy, effectiveness, robustness, and universality of the proposed method.