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Using Telemetry for Maintenance of Special Military Vehicles

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Modelling and Simulation for Autonomous Systems (MESAS 2017)

Abstract

This article suggests using telemetry during the diagnostics of a technical state and the maintenance of combat and special vehicles including autonomous vehicles and UGV. The aim of this article is to show different possibilities of performing a predictive and later a proactive maintenance in the military environment. When performing an on-line diagnostics, combat and special vehicles have to be equipped with diagnostic and sensor networks. When it comes to harmonizing vehicle networks, it is important for the diagnostic protocols of military vehicles to comply with relevant standards. If the inner vehicle communication and relating diagnostics possibilities are perfectly in line with relevant standards, and a logistic personnel is equipped with a suitable off-line diagnostics, sufficient conditions will be created for implementing a predictive or a proactive maintenance. In this paper the authors describe the possibilities of on-board diagnostics followed by data processing and transferring to create a convenient maintenance system. This system is expected to provide a high level of dependability (availability) and reduce overall maintenance costs. When implementing higher preventive maintenance systems it is essential to train a technical personnel and apply relevant hardware and software equipment.

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References

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Acknowledgment

Presented work has been prepared with the support of the Ministry of Defence of the Czech Republic, Partial Project for Institutional Development, Department of Combat and Special Vehicles, University of Defence, Brno.

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Correspondence to Jan Furch .

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Furch, J., Turo, T., Krobot, Z., Stastny, J. (2018). Using Telemetry for Maintenance of Special Military Vehicles. In: Mazal, J. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2017. Lecture Notes in Computer Science(), vol 10756. Springer, Cham. https://doi.org/10.1007/978-3-319-76072-8_28

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  • DOI: https://doi.org/10.1007/978-3-319-76072-8_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76071-1

  • Online ISBN: 978-3-319-76072-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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