Reliability Assessment of a Drone Communication System using Truncated Markov Analysis
Reliability analysis of the drone communication system is proposed in this paper using the truncated markov analysis technique. Markov analysis is a dynamic risk analysis technique that is widely used to do reliability analysis as it explores all the states in detail but exploring all the system...
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Published in | 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) pp. 1 - 6 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
06.07.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Reliability analysis of the drone communication system is proposed in this paper using the truncated markov analysis technique. Markov analysis is a dynamic risk analysis technique that is widely used to do reliability analysis as it explores all the states in detail but exploring all the system's states for a larger and more complex system may reach to state-space exploration problem. To overcome this challenge, truncated markov analysis is proposed considering only the communication system of the drone system. Failure analysis of the communication system is performed using fault tree analysis prior to implementing the truncated markov analysis, and it is later transformed into a reliability block diagram for further study. Truncated markov analysis is used to gain a grasp of the number of working states and the probability of being in each state to ensure the drone system's safety and reliability. In this paper, the generation of the differential equations from the truncated state transition diagram is studied by applying Laplace's transformation. Through reliability analysis, failure analysis can be established. To do the reliability analysis, only failure data of the components from the NPRD-2016 dataset are considered. The study aims to focus on the reliability of the drone communication system considering the truncated states. |
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ISSN: | 2473-7674 |
DOI: | 10.1109/ICCCNT56998.2023.10306467 |