Fault diagnosis of hard rock tunnel boring machine cutterhead driving system based on adaptive observers

Rock cutting and excavation of TBM are mainly depend on the cutterhead driving system. This paper puts forward a cutterhead driving system dynamic model which can be used to fault diagnosis and model control. As some of the system parameters are time-varying, such as gear backlash which is one of the main factors causing deterioration in the dynamic and static performance of gear mesh process. This paper designs an adaptive observer with exponential forgetting factor to estimate the undetermined parameters. Compared to the adaptive observer without forgetting factor, the estimated parameter in proposed observer has a better performance in noise resisting ability and accuracy. The simulation results of cutterhead driving system show the estimated parameters can track the changing of the true values rapidly with an extremely small error.