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1. Rotor Fault Detection and Isolation in Aerial Vehicles with Dozens of Rotors

   https://doi.org/10.1109/LARS64411.2024.10786448  

   Gandhi, Neeraj; Xu, Jiawei; Saldaña, David; Phan, Linh_Thi Xuan (November 2024, IEEE)

   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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2. A Novel Quotient Space Approach to Model-Based Fault Detection and Isolation: Theory and Preliminary Simulation Evaluation

   https://doi.org/10.1109/IROS51168.2021.9636026  

   Mao, Annie M.; Whitcomb, Louis L. (September 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

   We report the development of novel fault detection and isolation (FDI) methods for model-based fault detection (MB-FD) and quotient-space fault isolation (QS-FI). This FDI approach performs MB-FD and QS-FI of single or multiple concurrent faults in plants and actuators simultaneously, without a priori knowledge of fault form, type, or dynamics. To detect faults, MB-FD characterizes deviation from nominal behavior using the plant velocity and plant and actuator parameters estimated by nullspace-based adaptive identification. To isolate (i.e. identify) faults, the QS-FI algorithm compares the estimated parameters to a nominal parameter class in progressively decreasing-dimensional quotient spaces of the parameter space. A preliminary simulation study of these proposed FDI methods applied to a three degree-of-freedom uninhabited underwater vehicle plant model shows their ability to detect as well as isolate faults for the cases of both single and multiple simultaneous faults and suggests the generalizability of the MB-FD and QS-FI approaches to any well-defined second-order plant and actuator model whose parameters enter linearly: a broad class of systems which includes aerial vehicles, marine vehicles, spacecraft, and robot arms. 

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3. Fault Detection and Isolation of Uncertain Nonlinear Parabolic PDE Systems

   https://doi.org/https://doi.org/10.48550/arXiv.2203.15850  

   Zhang, Jingting; Yuan, Chengzhi; Zeng, Wei; Wang, Cong. (March 2022, ArXivorg)

   This paper proposes a novel fault detection and isolation (FDI) scheme for distributed parameter systems modeled by a class of parabolic partial differential equations (PDEs) with nonlinear uncertain dynamics. A key feature of the proposed FDI scheme is its capability of dealing with the effects of system uncertainties for accurate FDI. Specifically, an approximate ordinary differential equation (ODE) system is first derived to capture the dominant dynamics of the original PDE system. An adaptive dynamics identification approach using radial basis function neural network is then proposed based on this ODE system, so as to achieve locally-accurate identification of the uncertain system dynamics under normal and faulty modes. A bank of FDI estimators with associated adaptive thresholds are finally designed for real-time FDI decision making. Rigorous analysis on the FDI performance in terms of fault detectability and isolatability is provided. Simulation study on a representative transport-reaction process is conducted to demonstrate the effectiveness and advantage of the proposed approach. 

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4. FLOWUnsteady: An Interactional Aerodynamics Solver for Multirotor Aircraft and Wind Energy

   https://doi.org/10.2514/6.2022-3218  

   Alvarez, Eduardo J.; Mehr, Judd; Ning, Andrew (June 2022, AIAA AVIATION 2022 Forum)

   View Video Presentation: https://doi.org/10.2514/6.2022-3218.vid The ability to accurately and rapidly assess unsteady interactional aerodynamics is a shortcoming and bottleneck in the design of various next-generation aerospace systems: from electric vertical takeoff and landing (eVTOL) aircraft to airborne wind energy (AWE) and wind farms. In this study, we present a meshless CFD framework based on the reformulated vortex particle method (rVPM) for the analysis of complex interactional aerodynamics. The rVPM is a large eddy simulation (LES) solving the Navier-Stokes equations in their vorticity form. It uses a meshless Lagrangian scheme, which not only avoids the hurdles of mesh generation, but it also conserves the vortical structure of wakes over long distances with minimal numerical dissipation, while being 100x faster than conventional mesh-based LES. Wings and rotating blades are introduced in the computational domain through actuator line and actuator surface models. Simulations are coupled with an aeroacoustics solver to predict tonal and broadband noise radiated by rotors. The framework, called FLOWUnsteady, is hereby released as an open-source code and extensively validated. Validation studies published in previous work by the authors are summarized, showcasing rotors across operating conditions with a rotor in hover, propellers, a wind turbine, and two side-by-side rotors in hover. Validation of rotor-wing interactions is presented simulating a tailplane with tip-mounted propellers and a blown wing with propellers mounted mid-span. The capabilities of the framework are showcased through the simulation of a tiltwing eVTOL vehicle and an AWE wind-harvesting aircraft, featuring rotors with variable RPM, variable pitch, tilting of wings and rotors, non-trivial flight paths, and complex aerodynamic interactions. 

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5. Wind Speed Statistics from a Small UAS and Its Sensitivity to Sensor Location

   https://doi.org/10.3390/atmos13030443  

   Wilson, Trevor C.; Brenner, James; Morrison, Zachary; Jacob, Jamey D.; Elbing, Brian R. (March 2022, Atmosphere)

   With the increase in the use of small uncrewed aircraft systems (UAS) there is a growing need for real-time weather forecasting to improve the safety of low-altitude aircraft operations. This will require integration of measurements with autonomous systems since current available sampling lack sufficient resolution within the atmospheric boundary layer (ABL). Thus, the current work aims to assess the ability to measure wind speeds from a quad-copter UAS and compare the performance with that of a fixed mast. Two laboratory tests were initially performed to assess the spatial variation in the vertically induced flow from the rotors. The horizontal distribution above the rotors was examined in a water tunnel at speeds and rotation rates to simulate nominally full throttle with a relative air speed of 0 or 8 m/s. These results showed that the sensor should be placed between rotor pairs. The vertical distribution was examined from a single rotor test in a large chamber, which suggested that at full throttle the sensor should be about 400 mm above the rotor plane. Field testing was then performed with the sensor positioned in between both pairs of rotors at 406, 508, and 610 mm above the rotor plane. The mean velocity over the given period was within 5.5% of the that measured from a fixed mast over the same period. The variation between the UAS and mast sensors were better correlated with the local mean shear than separation distance, which suggests height mismatch could be the source of error. The fluctuating velocity was quantified with the comparison of higher order statistics as well as the power spectral density, which the mast and UAS spectra were in good agreement regardless of the separation distance. This implies that for the current configuration a separation distance of 5.3 rotor diameters was sufficient to minimize the influence of the rotors. 

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