Distributed Fault Diagnosis and Prognosis of Nonlinear Mechatronic System Using Adaptive Biogeography-based Optimization

This paper proposes a distributed fault diagnosis and prognosis scheme for nonlinear mechatronic system, where multiple compound faults are considered. Firstly, the bond graph (BG) model of the nonlinear mechatronic system is established, and the BG based model structural decomposition is used to build minimal submodels from the global model. Secondly, distributed fault detection and isolation (FDI) framework is constructed based on minimal submodels, which mainly consists of distributed analytical redundancy relations and distributed fault signature matrix. Then, on the basis of the isolated possible faults obtained from distributed FDI framework, corresponding local estimator of each submodel is designed, where adaptive biogeography-based optimization algorithm is introduced for distributed fault estimation. The local estimator aims to identify the amplitude of abrupt fault, the appearing instants and the degradation model of incipient fault respectively. After that, for incipient fault, the distributed remaining useful life prediction is carried out based on the degradation model obtained from distributed fault estimation. Finally, simulation results show the effectiveness of the proposed distributed fault diagnosis and prognosis method.