Abstract
The successful operation of safety critical systems, such as aircraft, spacecraft, underwater systems, chemical plants and nuclear plants, is largely dependent on the validation of sensor data, which provide information for control and performance. The sensor data validation is an essential step to improve data reliability. Model-Based Programming (MBP) provides appropriate algorithms to validate the sensor data. MBP provides graphical modeling, automated code generation from design models, executable specification for continuous model-based verification and validation (V&V) for early identifying design errors. In this paper we discuss the signal data validation using model-based approach to provide the analysis of validation algorithm at the design stage rather than the code stage. Analog inputs of Stall Warning System SWS/AIC computer is used as a case study to discuss the results of the model-based algorithm analysis. The analog validation algorithm of SWS/AIC system is analyzed for its completeness, time dependency, and correctness as per the requirement specification and design description. The functional and the nonfunctional requirements are analyzed. Various scenarios are analyzed to check the robustness of the algorithm. The results are plotted for further analysis. The approach can be validated complex algorithm as it provides better understanding of the algorithm.
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Acknowledgements
The authors thank the Director, CSIR-NAL for his support and encouragement to carry out this research work.
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Krishnaprasad, R., Nanda, M., Jayanthi, J., Dhage, S.S. (2018). Model Based Algorithm Validation Approach for Safety Critical Applications. In: Shetty, N., Patnaik, L., Prasad, N., Nalini, N. (eds) Emerging Research in Computing, Information, Communication and Applications. ERCICA 2016. Springer, Singapore. https://doi.org/10.1007/978-981-10-4741-1_38
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DOI: https://doi.org/10.1007/978-981-10-4741-1_38
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