A method for modeling and analysis of fault propagation in hybrid systems using stochastic activity networks

Hybrid systems consist of both continuous and discrete parts. These systems include several different components. A fault in one of these components can be activated and propagate to other components. Due to the advancement of technology and intelligent systems such as driverless car, health control devices and automated factories, the occurrence of a fault in one component and its propagation to other components can lead to financial and human-life losses. It is necessary to design a fault propagation model before construction of a system. With such a model, we can observe the propagation of the effects of a fault in a component to other components, before the construction of the system. It is also possible to identify critical components of the system. In this paper, a method for modeling fault propagation based on stochastic activity networks is presented. Based on this model, it is possible to identify the critical points of the system, the effect of different components on each other and the component failure behavior. The proposed model has been applied in a case study (an aircraft fuel system), and its simulation and quantitative results are presented in this paper.