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Vertical take-off and landing (VTOL) vehicles are becoming increasingly popular for real-world transport; but, as with any vehicle, guaranteeing safety is both extremely critical and highly challenging due to issues like rotor faults. Existing fault detection and isolation (FDI) techniques usually focus on multirotor systems or fixed wing systems, rather than the hybrid VTOLs. Since VTOLs have both rotors and ailerons, a fault in a rotor may be masked by the (correctly working) ailerons, making it much more difficult to detect faults. However, this masking only works when ailersons are used (e.g., during cruising), leaving the takeoff and landing vulnerable to crashes. This paper presents an online rotor fault detection and isolation (FDI) method for VTOLs. The approach uses pose analysis and aileron command data to quickly and accurately identify the faulty rotor and to compute the severity of the fault. Our method works for hard-to-detect fault scenarios, such as small-severity faults that are masked during cruise flight but not during vertical motion. We evaluated our technique in a SITL PX4 simulation of a modified Deltaquad QuadPlane. The results show that our FDI technique can quickly detect and isolate faults in real time (within 1s-2.5s) and achieve high isolation success rate (91.67%) across six rotors, and that it can estimate the severity of faults to within 2%. When applying a simple recovery process post-isolation, the system consistently achieved safe landing.
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This content will become publicly available on November 11, 2025
Rotor Fault Detection and Isolation in Aerial Vehicles with Dozens of Rotors
Aerial vehicles with dozens of rotors are becoming increasingly common in important applications such as transportation and construction. One challenge with building such a system is to ensure that the system is robust against faults: as the number of rotors increases, the likelihood of a rotor failing during operation also increases; despite the spare thrust capacity provided by the redundant rotors, a rotor fault can significantly impact the motion and safety of the system. This paper presents an efficient fault detection and isolation (FDI) method for aerial vehicles with a large number of rotors. Our approach relies on two key insights: First, the effect of a faulty rotor directly affects the tracking error in roll and in pitch. This property can be used to order our faulty rotor search space. Second, the error in either roll or pitch is related to both the distance from the (relevant) axis and the severity of a fault. With these observations, we can use probe faults to isolate faulty rotors. Evaluation results show that our technique can efficiently detect and isolate faults in multi-rotor aerial vehicles with up to 64 rotors (8 more rotors than in existing FDI work), and that it can help improve robustness. To the best of our knowledge, our FDI method is the first that scales to several dozens of rotors.
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- Award ID(s):
- 1955670
- PAR ID:
- 10609864
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3315-0880-7
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Location:
- Arequipa, Peru
- Sponsoring Org:
- National Science Foundation
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