A fault propagation modeling method based on a finite state machine

With the development of technology and the expansion of application in different areas, the function and structure of engineering systems becomes more and more complex, which brings increasingly strict requirements for system reliability and safety. System failure is one of the primary reasons for accidents, thus it is of primary importance to investigate the fault propagation process and to establish the fault propagation model, which provides a basis for reducing accident risk. However, there are complex interactive relationships existing among the components as well as between the external environment and the system, so it is difficult to get a satisfactory result through a traditional safety analysis method. The model based safety analysis (MBSA) is able to solve the problem of poor expression ability and the low description precision of traditional analysis methods, so as to improve the efficiency and objectivity of safety analysis. The existing MBSA method, however, still has deficiencies in fault and/or failure modeling, lacking an abundant fault model library. Based on the study of fault propagation process and the research of traditional modeling methods, this paper decomposes the system into subsystems through the analysis of local fault effects based on Failure Modes and Effects Analysis (FMEA), proposing fault propagation modes according to the interaction between components. Subsequently, combined with Finite State Machine (FSM) theory, this paper describes the interactive behaviors between the components, constructing the transition process of fault propagation through the extraction of the state, input, output and state function of the component, abstracting out the system interactive model. This aims at enriching the MBSA fault model library while describing the fault propagation process within the entire system in a more detailed way. Finally, a case study is provided using Stateflow, software based on FSM theory, to verify the effectiveness and feasibility of this approach.