Avionics software is safe-critical embedded software and its architecture is evolving from traditional federated architectures to Integrated Modular Avionics (IMA) to improve resource usability. ARINC653, as a standard widely employed in the avionics industry, supports partitioning concepts in accordance with the IMA philosophy. Monitoring the health of certain aerospace structures has been shown to be a key step in reducing the life cycle costs for structural maintenance and inspection. Since the health of the structures ultimately determines the health of a vehicle, health monitoring is also an important prerequisite for improved aviation safety. In this paper, we present the preliminary results from our ongoing project on designing and evaluating architectures for integrated structural health monitoring. To insure the development of the avionics software constructed on ARINC653 operating system with high reliability and efficiency, we propose a model-driven design methodology based on Architecture Analysis & Design Language (AADL) for HM module of ARINC653 system. This paper presents an approach for the modeling, verification and implementation of ARINC653 systems using AADL. It details a modeling approach exploiting the new features of AADL version 2 for the design of ARINC653 architectures. It also proposes modeling patterns to represent the safety mechanisms of the HM module of Integrated Modular Avionics. Thus, it assists system engineers to simulate and validate non functional requirements such as scheduling or resources dimensioning and then propose a method of testing the HM module of Integrated Modular Avionics using Fault Injection and Program Instrumentation Technology.


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    Title :

    Testing Method of Integrated Modular Avionics Health Monitoring


    Contributors:
    H. Zhang (author) / S. Wang (author) / B. Liu (author) / X. Diao (author)


    Publication date :

    2013




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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