Aeroacoustic Analysis of an Unmanned Aerial Vehicle

Author(s):  
Peter D. Lysak ◽  
James J. Dreyer ◽  
John B. Fahnline ◽  
Dean E. Capone ◽  
John E. Poremba

An acoustic analysis of a ducted fan unmanned aerial vehicle (UAV) was conducted to identify the primary aeroacoustic sources and to determine the potential for reducing the radiated noise levels. Computational fluid dynamics was used to determine the three-dimensional flow field through the ducted fan in hover and maneuvering configurations. The flow solutions provided information about the blade relative velocities, spatially non-uniform inflow, inflow turbulence, boundary layer turbulence, and blade wake velocity deficits for use in acoustical models of broadband and blade passing frequency noise. The computational results were in good agreement with experimentally measured noise levels, and showed that the tonal noise was produced primarily by unsteady forces resulting from the non-uniform inflow, while the broadband noise resulted from the inflow turbulence. Based on these findings, design modifications were recommended which offer the potential to reduce the noise by more than 10 dB.

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 54
Author(s):  
Minh-Thien Tran ◽  
Dong-Hun Lee ◽  
Soumayya Chakir ◽  
Young-Bok Kim

This article proposes a novel adaptive super-twisting sliding mode control scheme with a time-delay estimation technique (ASTSMC-TDE) to control the yaw angle of a single ducted-fan unmanned aerial vehicle system. Such systems are highly nonlinear; hence, the proposed control scheme is a combination of several control schemes; super-twisting sliding mode, TDE technique to estimate the nonlinear factors of the system, and an adaptive sliding mode. The tracking error of the ASTSMC-TDE is guaranteed to be uniformly ultimately bounded using Lyapunov stability theory. Moreover, to enhance the versatility and the practical feasibility of the proposed control scheme, a comparison study between the proposed controller and a proportional-integral-derivative controller (PID) is conducted. The comparison is achieved through two different scenarios: a normal mode and an abnormal mode. Simulation and experimental tests are carried out to provide an in-depth investigation of the performance of the proposed ASTSMC-TDE control system.


Author(s):  
A. Finn ◽  
K. Rogers ◽  
J. Meade ◽  
J. Skinner ◽  
A. Zargarian

<p><strong>Abstract.</strong> An acoustic signature generated by an unmanned aerial vehicle is used in conjunction with tomography to remotely sense temperature and wind profiles within a volume of atmosphere up to an altitude of 120&amp;thinsp;m and over an area of 300&amp;thinsp;m&amp;thinsp;&amp;times;&amp;thinsp;300&amp;thinsp;m. Sound fields recorded onboard the aircraft and by an array of microphones on the ground are compared and converted to sound speed estimates for the ray paths intersecting the intervening medium. Tomographic inversion is then used to transform these sound speed values into three-dimensional profiles of virtual temperature and wind velocity, which enables the atmosphere to be visualised and monitored over time. The wind and temperature estimates obtained using this method are compared to independent measurements taken by a co-located mid-range ZephIR LIDAR and sensors onboard the aircraft. These comparisons show correspondences to better than 0.5&amp;thinsp;&amp;deg;C and 0.3&amp;thinsp;m/s for temperature and wind velocity, respectively.</p>


Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.


2019 ◽  
Vol 35 (3) ◽  
pp. 367-376 ◽  
Author(s):  
Qiang Shi ◽  
Hanping Mao ◽  
Xianping Guan

Abstract. To analyze the droplet deposition under the influence of the flow field of an unmanned aerial vehicle (UAV), a hand-held three-dimensional (3D) laser scanner was used to scan 3D images of the UAV. Fluent software was used to simulate the motion characteristics of droplets and flow fields under the conditions of a flight speed of 3 m/s and an altitude of 1.5 m. The results indicated that the ground deposition concentration in the nonrotor flow field was high, the spray field width was 2.6 m, and the droplet deposition concentration was 50 to 200 ug/cm2. Under the influence of the rotor flow field, the widest deposition range of droplets reached 12.8 m. Notably, the droplet deposition uniformity worsened, and the concentration range of the droplet deposition was 0 to 500 ug/cm2. With the downward development of the downwash flow field, the overall velocity of the flow field gradually decreased, and the influence interval of the flow field gradually expanded. In this article, the droplet concentration was verified under simulated working conditions by a field experiment, thereby demonstrating the reliability of the numerical simulation results. This research could provide a basis for determining optimal UAV operating parameters, reducing the drift of droplets and increasing the utilization rate of pesticides. Keywords: Unmanned aerial vehicle (UAV), Aerial application, Downwash flow field, Droplet deposition, Simulation analysis.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yongqiang Qi ◽  
Shuai Li ◽  
Yi Ke

In this paper, a three-dimensional path planning problem of an unmanned aerial vehicle under constant thrust is studied based on the artificial fluid method. The effect of obstacles on the original fluid field is quantified by the perturbation matrix, the streamlines can be regarded as the planned path for the unmanned aerial vehicle, and the tangential vector and the disturbance matrix of the artificial fluid method are improved. In particular, this paper addresses a novel algorithm of constant thrust fitting which is proposed through the impulse compensation, and then the constant thrust switching control scheme based on the isochronous interpolation method is given. It is proved that the planned path can avoid all obstacles smoothly and swiftly and reach the destination eventually. Simulation results demonstrate the effectiveness of this method.


2019 ◽  
Vol 7 (3) ◽  
pp. 120-132
Author(s):  
Kashish Gupta ◽  
Bara Jamal Emran ◽  
Homayoun Najjaran

Purpose The purpose of this paper is to facilitate autonomous landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving/tilting platform using a robust vision-based approach. Design/methodology/approach Autonomous landing of a multi-rotor UAV on a moving or tilting platform of unknown orientation in a GPS-denied and vision-compromised environment presents a challenge to common autopilot systems. The paper proposes a robust visual data processing system based on targets’ Oriented FAST and Rotated BRIEF features to estimate the UAV’s three-dimensional pose in real time. Findings The system is able to visually locate and identify the unique landing platform based on a cooperative marker with an error rate of 1° or less for all roll, pitch and yaw angles. Practical implications The proposed vision-based system aims at on-board use and increased reliability without a significant change to the computational load of the UAV. Originality/value The simplicity of the training procedure gives the process the flexibility needed to use a marker of any unknown/irregular shape or dimension. The process can be easily tweaked to respond to different cooperative markers. The on-board computationally inexpensive process can be added to off-the-shelf autopilots.


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