Dynamic reconstruction modeling method of avionics system based on altarica

Abstract

The invention relates to an avionics system dynamic reconfiguration modeling method based on AltaRica, which is used for avionics system task reliability modeling. On the basis of analyzing the characteristics of the avionics system, the invention proposes that the task reliability of the system is modeled based on the AltaRica model with the finite state machine as the theoretical basis. This method can realize the integrated modeling of system function and fault logic. Through the extended definitions of fault state and trigger event, it can describe the jump and influence relationship of each component working state under the condition of fault occurrence and fault-tolerant design, and truly reflect the design characteristics of avionics system. The invention models the complex dynamicreconstruction process, facilitates the analysis of the task reliability of the dynamic reconstruction process, combines the AltaRica model with the dynamic reconstruction process of the avionics system, and creates a new process modeling method.

Description

technical field [0001] The invention belongs to the technical field of aviation system mission reliability modeling, and in particular relates to an AltaRica-based dynamic reconstruction modeling method of an avionics system. Background technique [0002] With the development of the new generation of aviation equipment in the direction of integration, modularization and intelligence, a large number of new technologies represented by dynamic reconfigurable technology, fault tolerance technology, testability technology and content management system (CMS) technology have been popularized in the equipment and apply. Dynamic reconfiguration is an important feature of the avionics system. The most prominent advantage of the reconfiguration system is that when a failure occurs, the dynamic reconfiguration method of the system function is preset. When a module in a configuration set fails , the system will search for the next available configuration set according to the design blue...

AI Technical Summary

Problems solved by technology

[0004] In terms of reliability dynamic modeling technology, scholars at home and abroad have done a lot of research and explored a series of reliability modeling methods, such as Markov, dynamic fault tree, Petri net method, finite state machine, etc., but these methods There are still some deficiencies in the comprehensive promotion and technology application in the project

The Markov model is widely used as a technique for reliability analysis of complex fault-tolerant systems. However, as the complexity of the system continues to increase, the number of its state sets will increase exponentially, which will lead to the explosion of the model state space and the failure of the model. solve

The dynamic fault tree model extends the traditional fault tree analysis to dynamic system performance, and has the characteristics of sequence correlation, resource sharing, repairability, cold and hot backup, etc., but because the final analysis process is transformed into the corresponding Markov model, it is further solved , so it also faces the problem that the model cannot be solved due to the space explosion

Both Petri nets and finite state machine models are used to describe the relationship between existing conditions and events, and are important dynamic system modeling tools. However, as the complexity of the system increases, it is necessary to manually sort out the dynamic interaction and influence relationship at each level of the system. It becomes very difficult, and the model construction results cannot effectively represent the system architecture characteristics, which is not conducive to the inspection and reuse of the model, resulting in low availability of its engineering

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