Abstract

For unmanned aerial systems (UAS) to be successfully deployed and integrated within the national airspace, it is imperative that they possess the capability to effectively complete their missions without compromising the safety of other aircraft, as well as persons and property on the ground. This necessity creates a natural requirement for UAS that can respondto uncertain environmental conditions and emergent failures in real-time, with robustness and resilience close enough to those of manned systems. We introduce a system that meets this requirement with the design of a real-time onboard system health management (SHM) capability to continuously monitor sensors, software, and hardware components. This system can detect and diagnose failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; and (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software. We call this approach rt-R2U2, a name derived from its requirements. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual flight data from theNASA Swift UAS.

Highlights

  • Modern unmanned aerial systems (UAS) are highly complex pieces of machinery, combining mechanical and electrical subsystems with complex software systems and controls, such as the autopilot and payload systems

  • Actual sensor and signal values are prefixed by “s,” e.g., s baroAlt comprises a stream of sensor readings of the barometric altitude

  • We have in this article presented a coordinated, extensible, three-pronged approach to sensor and software health management in real time, on-board a UAS

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Summary

Introduction

Modern unmanned aerial systems (UAS) are highly complex pieces of machinery, combining mechanical and electrical subsystems with complex software systems and controls, such as the autopilot and payload systems (e.g., cameras or scientific instruments). Even after thorough preflight certification, mission-time diagnostics and prognostics capabilities are required to react to unforeseeable events during operation. In case of problems and faults in components, sensors, or the flight software, the on-board system health capability must be able to detect and diagnose the failure(s) and respond in a timely manner, possibly by triggering mitigation actions. These corrective actions can range from a simple. INTERNATIONAL JOURNAL OF PROGNOSTICS AND HEALTH MANAGEMENT mode change to following a pre-programmed flight path to continue the mission (in case of minor problems, such as a lost communications link) to a “limp” home. In case of severe problems, a controlled emergency landing in a remote and safe area might be necessary

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