Hybrid prognostic method applied to mechatronic systems

Fault detection and isolation, or fault diagnostic, of mechatronic systems has been the subject of several interesting works. Detecting and isolating faults may be convenient for some applications where the fault does not have severe consequences on humans as well as on the environment. However, in some situations, diagnosing faults may not be sufficient and one needs to anticipate the fault. This is what is done by fault prognostics. This latter activity aims at estimating the remaining useful life of systems by using three main approaches: data-driven prognostics, model-based prognostics, and hybrid prognostics. In this paper, a hybrid prognostic method is proposed and applied on a mechatronic system. The method relies on two phases: an offline phase to build the behavior and degradation models and an online phase to assess the health state of the system and predict its remaining useful life.