Existing icing detection technologies face challenges when applied to small and medium-sized aircraft,especially electric vertical take-off and landing(eVTOL)aircraft that meet the needs of low-altitude economic devel...Existing icing detection technologies face challenges when applied to small and medium-sized aircraft,especially electric vertical take-off and landing(eVTOL)aircraft that meet the needs of low-altitude economic development.This study proposes a data-driven icing detection method based on rotor performance evolution.Through dry-air baseline tests and dynamic icing comparative experiments(wind speed 0—30 m/s,rotational speed 0—3000 r/min,collective pitch 0°—8°)of a 0.6 m rotor in the FL-61 icing wind tunnel,a multi-source heterogeneous dataset containing motion parameters,aerodynamic parameters,and icing state identifiers is constructed.An innovative signal processing architecture combining adaptive Kalman filtering and moving average cascading is adopted.And a comparative study is conducted on the performance of support vector machine(SVM),multilayer perceptron(MLP),and random forest(RF)algorithms,achieving real-time identification of icing states in rotating components.Experimental results demonstrate that the method exhibits a minimum detection latency of 6.9 s and 96%overall accuracy in reserved test cases,featuring low-latency and low false-alarm,providing a sensor-free lightweight solution for light/vertical takeoff and landing aircraft.展开更多
Icing detection is critically important for preventing safety accidents and economic losses,especially concerning ice formation from invalidated anti-icing fluids(water and ethylene glycol)under extreme conditions.Tra...Icing detection is critically important for preventing safety accidents and economic losses,especially concerning ice formation from invalidated anti-icing fluids(water and ethylene glycol)under extreme conditions.Traditional technologies like ultrasonics and capacitor-antenna face challenges with limited detection areas,lower accuracy,and susceptibility to electromagnetic interference.Here,we introduce a novel viscosity-ultrasensitive fluorescent probe 40,4‴-(2,2-diphenyle-thene-1,1-diyl)bis-(3,5-dicarboxylate)(TPE-2B4C)based on AIEgens for moni-toring ice formation of anti-icing fluids in low-temperature environments.TPE-2B4C,consisting of four sodium carboxylate groups and multiple freely rotating benzene rings,demonstrates outstanding solubility in anti-icing fluids and exhibits no fluorescent background signal even at low temperatures(<−20°C).Upon freezing,TPE-2B4C relocates from the water phase to higher viscosity ethylene glycol,causing restriction of benzene rings and a significantly increased green fluorescence signal.TPE-2B4C can successfully determine whether the anti-icing fluids are icing from−5 to−20°C with a high contrast ratio.Due to its simple setup,fast operation,and broad applicability,our new method is anticipated to be employed for rapid,real-time,and large-scale icing detection.展开更多
A series of numerical methods,which are suitable to design the shape and configuration of the icing prober for the horizontal axis wind turbine,are presented.The methods are composed of a multiple reference frame(MRF)...A series of numerical methods,which are suitable to design the shape and configuration of the icing prober for the horizontal axis wind turbine,are presented.The methods are composed of a multiple reference frame(MRF)method for calculating flow field of air,a Lagrangian method for computing droplet trajectories,an Eulerian method for calculating droplet collection efficiency,and an arithmetic for fast computing ice accretion.All the numerical methods are based on the computational fluid dynamics(CFD)technology.After proposing the basic steps and ideas for the design of the icing detection system,the shape and configuration of the icing prober for a 1.5 MW horizontal axis wind turbine are then obtained with the methods.The results show that the numerical methods are efficient and the CFD technology plays an important role in the design process.展开更多
基金supported in part by the National Key R&D Program of China(No.2022YFE0203700)the Aeronautical Science Foundation of China(No.2023Z010027001)。
文摘Existing icing detection technologies face challenges when applied to small and medium-sized aircraft,especially electric vertical take-off and landing(eVTOL)aircraft that meet the needs of low-altitude economic development.This study proposes a data-driven icing detection method based on rotor performance evolution.Through dry-air baseline tests and dynamic icing comparative experiments(wind speed 0—30 m/s,rotational speed 0—3000 r/min,collective pitch 0°—8°)of a 0.6 m rotor in the FL-61 icing wind tunnel,a multi-source heterogeneous dataset containing motion parameters,aerodynamic parameters,and icing state identifiers is constructed.An innovative signal processing architecture combining adaptive Kalman filtering and moving average cascading is adopted.And a comparative study is conducted on the performance of support vector machine(SVM),multilayer perceptron(MLP),and random forest(RF)algorithms,achieving real-time identification of icing states in rotating components.Experimental results demonstrate that the method exhibits a minimum detection latency of 6.9 s and 96%overall accuracy in reserved test cases,featuring low-latency and low false-alarm,providing a sensor-free lightweight solution for light/vertical takeoff and landing aircraft.
基金support from the National Natural Science Foundation of China(9235630033,22105069)Shanghai Pujiang Program(20PJ1402900)+2 种基金Shanghai Natural Science Foundation(21ZR1418400)Innovation Program of Shanghai Municipal Education Commission(2023FGS01)Natural Science Foundation of Jiangsu Province(BK20231225).
文摘Icing detection is critically important for preventing safety accidents and economic losses,especially concerning ice formation from invalidated anti-icing fluids(water and ethylene glycol)under extreme conditions.Traditional technologies like ultrasonics and capacitor-antenna face challenges with limited detection areas,lower accuracy,and susceptibility to electromagnetic interference.Here,we introduce a novel viscosity-ultrasensitive fluorescent probe 40,4‴-(2,2-diphenyle-thene-1,1-diyl)bis-(3,5-dicarboxylate)(TPE-2B4C)based on AIEgens for moni-toring ice formation of anti-icing fluids in low-temperature environments.TPE-2B4C,consisting of four sodium carboxylate groups and multiple freely rotating benzene rings,demonstrates outstanding solubility in anti-icing fluids and exhibits no fluorescent background signal even at low temperatures(<−20°C).Upon freezing,TPE-2B4C relocates from the water phase to higher viscosity ethylene glycol,causing restriction of benzene rings and a significantly increased green fluorescence signal.TPE-2B4C can successfully determine whether the anti-icing fluids are icing from−5 to−20°C with a high contrast ratio.Due to its simple setup,fast operation,and broad applicability,our new method is anticipated to be employed for rapid,real-time,and large-scale icing detection.
文摘A series of numerical methods,which are suitable to design the shape and configuration of the icing prober for the horizontal axis wind turbine,are presented.The methods are composed of a multiple reference frame(MRF)method for calculating flow field of air,a Lagrangian method for computing droplet trajectories,an Eulerian method for calculating droplet collection efficiency,and an arithmetic for fast computing ice accretion.All the numerical methods are based on the computational fluid dynamics(CFD)technology.After proposing the basic steps and ideas for the design of the icing detection system,the shape and configuration of the icing prober for a 1.5 MW horizontal axis wind turbine are then obtained with the methods.The results show that the numerical methods are efficient and the CFD technology plays an important role in the design process.
