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Co-TS: Design and Implementation of a 2-UAV Cooperative Transportation System 2-UAV协同运输系统的设计与实现
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293231158443
Qianli Weng, Guanming Liu, Pei Zhou, Haoran Shi, Kai Wen Zhang
UAV application research has attracted more and more attention of researchers. However, in the field of UAV transportation, especially in the case of multi-UAV cooperation, there is little research or design on the overall system of multi-UAV cooperative transportation due to the complexity of the task and many factors need to be considered. In this paper, we first introduce a 2-UAV cooperative transportation task scenario and we call it Co-TS. Then according to the scenario, we design a task planning system, which describes the entire process of 2-UAV performing transportation tasks; in order to solve the design complexity of this UAV upper-layer software, we propose a model architecture of 2-UAV transportation application, design the functions of each module and analyze the relationship between modules in the model architecture; in addition, to realize the correct execution of the 2-UAV cooperative transportation task, the task execution is divided into four states which include preparation, rising, forwarding, and landing states, and the corresponding cooperative transportation control flow algorithm is designed for four states. Finally, we develop this system and conduct experiments. The quantitative and qualitative results demonstrate the effectiveness of our method.
无人机的应用研究越来越受到研究者的重视。然而,在无人机运输领域,特别是在多无人机协同运输的情况下,由于任务的复杂性和需要考虑的因素很多,对多无人机协同运输整体系统的研究和设计很少。本文首先介绍了一种2架无人机协同运输任务场景,我们称之为Co-TS。然后根据场景设计了任务规划系统,描述了2架无人机执行运输任务的全过程;为解决该无人机上层软件的设计复杂性,提出了2-无人机运输应用的模型体系结构,设计了各模块的功能,分析了模型体系结构中各模块之间的关系;此外,为了实现2-无人机协同运输任务的正确执行,将任务执行分为准备、上升、转发和降落四种状态,并针对四种状态设计了相应的协同运输控制流算法。最后,对系统进行了开发并进行了实验。定量和定性结果证明了该方法的有效性。
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引用次数: 2
Kinematic modeling and analysis of transmission mechanism with joint clearance for flapping wing micro aerial vehicle 扑翼微型飞行器带关节间隙传动机构运动学建模与分析
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293231179945
Xin Fang, Jianghao Wu, Feng Du
A theoretical model is built to reveal the effect of the joint clearance on the kinematic performance of the transmission mechanism of a flapping wing micro aerial vehicle (FWMAV). Massless link approach is used to model the joint clearance and the reciprocal screw is introduced to solve the kinematic model. Finite element method simulations are also performed to validate the model. The kinematic model reveals that the inertia force of the transmission mechanism contributes little to the flapping motion whereas the sign of the resultant moment of aerodynamic drag and wing inertia force plays decisive role. Besides, the joint clearance can either increase or decrease the flapping angle of the wing during a flapping period and it will significantly affect the flapping amplitude while involves little in the mean flapping angle. The effects of the positions of the joint with clearance and its magnitude on the flapping motion are also revealed.
建立了一个理论模型,揭示了关节间隙对扑翼微型飞行器(FWMAV)传动机构运动性能的影响。采用无质量连杆法对关节间隙进行建模,并引入倒螺杆求解运动学模型。通过有限元仿真对模型进行了验证。运动学模型表明,传动机构的惯性力对扑翼运动的影响较小,气动阻力和机翼惯性力的合力矩的符号对扑翼运动起决定性作用。此外,在扑动期间,关节间隙会增大或减小机翼的扑动角,对扑动幅度的影响较大,而对平均扑动角的影响较小。分析了带间隙关节的位置和间隙大小对扑动的影响。
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引用次数: 0
A data-driven predictive maintenance model to estimate RUL in a multi-rotor UAS 一种用于估计多旋翼无人机RUL的数据驱动预测维修模型
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293221150171
Erkan Caner Ozkat, O. Bektas, Michael Juul Nielsen, A. la Cour-Harbo
Unmanned Aircraft Systems (UAS) has become widespread over the last decade in various commercial or personal applications such as entertainment, transportation, search and rescue. However, this emerging growth has led to new challenges mainly associated with unintentional incidents or accidents that can cause serious damage to civilians or disrupt manned aerial activities. Machine failure makes up almost 50% of the cause of accidents, with almost 40% of the failures caused in the propulsion systems. To prevent accidents related to mechanical failure, it is important to accurately estimate the Remaining Useful Life (RUL) of a UAS. This paper proposes a new method to estimate RUL using vibration data collected from a multi-rotor UAS. A novel feature called mean peak frequency, which is the average of peak frequencies obtained at each time instance, is proposed to assess degradation. The Long Short-Term Memory (LSTM) is employed to forecast the subsequent 5 mean peak frequency values using the last 7 computed values as input. If one of the estimated values exceeds the predefined 50 Hz threshold, the time from the estimation until the threshold is exceeded is calculated as the RUL. The estimated mean peak frequency values are compared with the actual values to analyze the success of the estimation. For the 1st, 2nd, and 3rd replications, RUL results are 4 s, 10 s, and 10 s, and root mean square error (RMSE) values are 3.7142 Hz, 1.4831 Hz, and 1.3455 Hz, respectively.
无人驾驶飞机系统(UAS)在过去十年中已广泛应用于各种商业或个人应用,如娱乐,运输,搜索和救援。然而,这种新兴的增长带来了新的挑战,主要与意外事件或事故有关,这些事件或事故可能对平民造成严重损害或扰乱有人驾驶的空中活动。机器故障占事故原因的近50%,其中近40%的故障发生在推进系统。为了防止机械故障引起的事故,准确估计无人机的剩余使用寿命(RUL)是非常重要的。本文提出了一种利用多旋翼无人机的振动数据估计RUL的新方法。提出了一种称为平均峰值频率的新特征,它是在每个时间实例中获得的峰值频率的平均值,用于评估退化。使用长短期记忆(LSTM)以最后7个计算值作为输入,预测随后的5个平均峰值频率值。如果其中一个估计值超过了预定义的50hz阈值,则从估计值到超过阈值的时间作为RUL计算。将估计的平均峰值频率值与实际值进行比较,以分析估计的成功。对于第1次、第2次和第3次重复,RUL结果分别为4 s、10 s和10 s,均方根误差(RMSE)值分别为3.7142 Hz、1.4831 Hz和1.3455 Hz。
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引用次数: 1
Influence of fuselage arm cross-section on the aerodynamic and aeroacoustic performance of quadcopter unmanned aerial vehicles: A numerical investigation 机身臂横截面对四旋翼无人机气动和气动声学性能的影响:数值研究
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293231200281
Jizhou Liu, Li Ming, Kaimin Yang, Gao Lei
This paper investigates the influence of the fuselage arm cross-section shape on the aerodynamic and aeroacoustic performance of quadcopter Unmanned Aerial Vehicles in hover state by numerical simulation. The unsteady simulations of the flow field around one generic two-blade rotor and one fuselage arm are conducted by the Reynolds Averaged Navier-Stokes solver with the [Formula: see text] SST turbulence model. The total thrust forces and the sound pressure level spectra of five fuselage arm cross-section shapes with the same cross-section area are simulated and compared. Results show that the fuselage arm with a square cross-section has the highest aerodynamic performances for all the tested speeds of rotation. The fuselage arm with a circular cross-section ranks second in aerodynamic performance. However, it has the best aeroacoustic performance. The other three tested cross-section shapes show less thrust forces and higher sound pressure levels at the blade passing frequencies than the circular cross-section, which are not optimal neither aerodynamically nor aeroacoustically.
通过数值模拟研究了机身臂截面形状对悬停状态四旋翼无人机气动性能和气动声学性能的影响。采用[公式:见文]SST湍流模型,采用Reynolds平均Navier-Stokes解算器对某型双桨转子和机身臂周围的流场进行了非定常模拟。对具有相同横截面面积的5种机身臂横截面形状的总推力和声压级谱进行了仿真比较。结果表明,在不同转速下,方形截面的机身臂具有最佳的气动性能。圆形横截面的机身臂在气动性能上排名第二。然而,它具有最好的气动声学性能。与圆形截面相比,其他三种截面在叶片通过频率下的推力较小,声压级较高,这在气动和气动声学上都不是最优的。
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引用次数: 0
Seeing with sound; surface detection and avoidance by sensing self-generated noise 用声音看;通过感应自生噪声进行表面探测和规避
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293221148377
S. Wilshin, Stephen M. Amos, R. Bomphrey
Here, we demonstrate obstacle and secondary drone avoidance capability by quadcopter drones that can perceive and react to modulation of their self-generated acoustic environment when in proximity to surfaces. A ground truth for the interpretation of self-noise was established by measuring the intrinsic, three-dimensional, acoustic signature of a drone in an anechoic chamber. This was used to design sensor arrangements and machine learning algorithms to estimate the position of external features, obstacles or another drone, within the environment. Our machine learning approach took short segments of recorded sound and their Fourier transforms, fed these into a convolutional neural network, and output the location of an obstacle or secondary drone in the environment. The convolutional layers were constructed with a suitable topology that matched the physical arrangement of the sensors. Our surface detection and avoidance algorithms were refined during tethered flight within an anechoic chamber, followed by an exercise in free flight without obstacle avoidance, and finally free flight obstacle detection and avoidance. Our acoustic sense-and-avoid capability extends to vertical and horizontal planar surfaces and tethered secondary drones.
在这里,我们展示了四旋翼无人机的避障和二次无人机能力,当它们靠近表面时,可以感知并对其自身产生的声学环境的调制做出反应。通过测量无人机在消声室内的固有三维声学特征,建立了解释自噪声的基本事实。这被用于设计传感器布置和机器学习算法,以估计外部特征、障碍物或其他无人机在环境中的位置。我们的机器学习方法采用记录声音的短片段及其傅立叶变换,将其输入卷积神经网络,并输出环境中障碍物或次要无人机的位置。卷积层是用合适的拓扑结构构建的,该拓扑结构与传感器的物理布置相匹配。我们的表面检测和规避算法在消声室内的系留飞行过程中进行了改进,然后进行了无障碍自由飞行练习,最后进行了自由飞行障碍检测和规避。我们的声学感知和躲避能力扩展到垂直和水平平面以及系留的辅助无人机。
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引用次数: 0
AD-YOLOv5s based UAV detection for low altitude security ad - yolov5型无人机低空安全探测
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293231190017
Yuanfeng Shang, Chang Liu, Dawei Qiu, Zixuan Zhao, Ruikang Wu, Shuyuan Tang
UAV (Unmanned Aerial Vehicle) black flight at low altitude could cause serious safety risks. Consequently, it is crucial to detect and manage low altitude small UAVs. The existing methods of low altitude small UAV detection suffer from problems such as high false alarm rate, and poor real-time performance. In order to solve the above problems, we present a novel approach, named AD-YOLOv5s, to achieve low altitude small UAV detection with high precision and high real-time performance. Firstly, the feature enhancement method is used to expand the dataset. We optimize the model feature fusion, the prediction head structure, and the loss function. Based on the CBAM (Convolutional Block Attention Module) attention mechanism, feature enhancement is performed to improve the detection accuracy. Secondly, the ghost module and depthwise separable convolution are used to reduce the number of parameters of the model, and we propose the method of lightweight design of model to improve the detection speed. Compared with the YOLOv5s model, the experiment result shows that our proposed AD-YOLOv5s model improves the value of mAP by 2.2% and the value of Recall by 1.8%, reduces the value of GFLOPs by 29.9% and parameters by 38.8%, and achieves 27.6 FPS when the proposed model deploy on a low-cost edge computing device (jetson nano).
无人机(UAV)在低空黑色飞行会造成严重的安全隐患。因此,对低空小型无人机的探测和管理至关重要。现有的低空小型无人机检测方法存在虚警率高、实时性差等问题。为了解决上述问题,我们提出了一种新的方法,命名为AD-YOLOv5s,以实现高精度和高实时性的低空小型无人机检测。首先,采用特征增强方法对数据集进行扩展。对模型特征融合、预测头结构和损失函数进行了优化。在CBAM (Convolutional Block Attention Module)注意机制的基础上,进行特征增强,提高检测精度。其次,利用幽灵模块和深度可分卷积来减少模型的参数数量,并提出模型轻量化设计的方法来提高检测速度;实验结果表明,与YOLOv5s模型相比,我们提出的AD-YOLOv5s模型在低成本边缘计算设备(jetson nano)上部署时,mAP值提高了2.2%,Recall值提高了1.8%,GFLOPs值降低了29.9%,参数值降低了38.8%,FPS达到27.6。
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引用次数: 0
Evaluation of drag coefficient for a quadrotor model 四旋翼模型的阻力系数评估
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293221148378
G. Hattenberger, M. Bronz, Jean-Philippe Condomines
This paper focuses on the quadrotor drag coefficient model and its estimation from flight tests. Precise assessment of such a model permits the use of a quadrotor as a sensor for wind estimation purposes without the need for additional onboard sensors. Firstly, the drag coefficient has been estimated in a controlled environment via wind generator and motion capture system. Later, the evolution of the coefficient is observed for various mass and fuselage shapes. Finally, an estimation method is proposed, based on the least-squares optimization, that evaluates the drag of the quadrotor directly from outdoor flight data. The latter leads the methodology towards easier adoption in other researchers’ systems without the need for complex and expensive flight testing facilities. The accuracy of the proposed method is presented both in simulation, based on a realistic flight dynamics model, and also for real outdoor flights.
本文重点研究了四旋翼飞行器的阻力系数模型及其在飞行试验中的估计。这种模型的精确评估允许使用四旋翼作为风估计目的的传感器,而不需要额外的机载传感器。首先,通过风力发电机和运动捕捉系统估算了受控环境下的阻力系数。随后,观察了不同质量和机身形状下系数的演变。最后,提出了一种基于最小二乘优化的四旋翼飞行器阻力估计方法,该方法直接从室外飞行数据中评估四旋翼飞行器的阻力。后者使方法论更容易在其他研究人员的系统中采用,而不需要复杂和昂贵的飞行测试设施。在基于真实飞行动力学模型的仿真中,以及在真实的室外飞行中,都证明了该方法的准确性。
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引用次数: 4
An investigation on the structural vibrations of multi-rotor passenger drones 多旋翼无人机结构振动研究
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293231199097
Kejing Chen, Wei Meng, Jinhan Wang, Kun Liu, Zhenbo Lu
In order to solve the structural damage problem of the first generation of large multi-rotor manned drones, the present work has designed to study the structural vibration problems of multi-rotor drones. On a small multi-rotor drone, the laser vibration meter verified the reliability of acceleration sensor measurement of vibration and found that circular shape carbon fiber arms have strong damping abilities, with the strongest vibration in the Z-axis direction. To improve the design of the second generation of large multi-rotor manned drones, elliptical shape carbon fiber arms were employed instead of circular arms. Experiments showed that the main vibrations of the large multi-rotor manned drone’s arm are low-frequency vibrations below 200Hz, producing mainly torsional and bending modes, and the elliptical carbon fiber arms significantly reduce vibrations in the Z-axis direction. This study provides experimental data support for multi-rotor manned drones and further presents an improvement strategy for suppressing the vibrations of the multi-rotor manned drones.
为了解决第一代大型多旋翼载人无人机的结构损伤问题,本工作旨在研究多旋翼无人机的结构性振动问题。在一架小型多旋翼无人机上,激光测振仪验证了加速度传感器测量振动的可靠性,发现圆形碳纤维臂具有较强的阻尼能力,Z轴方向振动最强。为了改进第二代大型多旋翼载人无人机的设计,采用了椭圆形碳纤维臂代替了圆形臂。实验表明,大型多旋翼载人无人机手臂的主要振动是200Hz以下的低频振动,主要产生扭转和弯曲模式,椭圆碳纤维手臂显著降低了Z轴方向的振动。该研究为多旋翼载人无人机的振动抑制提供了实验数据支持,并提出了一种改进策略。
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引用次数: 0
Flight dynamics model identification of a meso-scale twin-cyclocopter in hover 中尺度双旋翼直升机悬停飞行动力学模型辨识
4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2023-01-01 DOI: 10.1177/17568293231206943
Carl Runco, Moble Benedict
In this paper the flight dynamics of a 33-gram twin-cyclocopter is analyzed via deriving a Linear Time Invariant (LTI) dynamics model from flight test data. The twin-cyclocopter is a novel micro air vehicle that uses two co-rotating cycloidal rotors to generate thrust and a coaxial nose rotor to counteract the reaction torque and provide additional thrust. During flight tests, perturbation maneuvers were performed about the hovering state to excite different modes and a 3D motion capture system collected attitude and position data. The data was used to extract a bare airframe LTI model linearized about the hovering state using time-domain system identification techniques. The model demonstrated that the roll and yaw modes are gyroscopically coupled with stable high-frequency and low-frequency modes. Comparing the two different yaw control methods: thrust vectoring of the cycloidal rotors and differential torque of the coaxial nose rotor, the former was more effective.
本文根据飞行试验数据,建立了一架33克双环直升机的线性时不变(LTI)动力学模型,对其飞行动力学进行了分析。双环直升机是一种新型微型飞行器,使用两个同向旋转摆线转子产生推力和同轴机头转子抵消反作用力并提供额外推力。在飞行试验中,对悬停状态进行摄动机动以激发不同模式,三维运动捕捉系统采集姿态和位置数据。利用这些数据,利用时域系统辨识技术提取悬停状态线性化的裸机体LTI模型。该模型表明,横摇和偏航模式与稳定的高频和低频模式是陀螺耦合的。对比摆线转子推力矢量和同轴机头转子差转矩两种不同的偏航控制方法,前者更有效。
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引用次数: 0
An experimental study of the unsteady vortex structures of a clapping-wing micro air vehicle 拍板翼微型飞行器非定常涡结构的实验研究
IF 1.4 4区 工程技术 Q2 ENGINEERING, AEROSPACE Pub Date : 2022-01-01 DOI: 10.1177/17568293221125846
Yanwei Zhang, Zhonglai Wang
It is a challenge to explore the unsteady vortex structures of flexible flapping wings of X-shaped flapping-wing micro air vehicles (also known as clapping-wing micro air vehicles (CWMAVs)). The objective of this paper is to obtain the influence of wind speed, flapping frequency, and angle of attack (AoA) on the instantaneous and average force coefficients of CWMAVs, investigate flow visualization of the leading-edge vortex (LEV), trailing-edge vortex (TEV) and wake vortex (WV) structures and identify some novel flow mechanisms of flapping propulsion. This paper proposes a mechanics and particle image velocimetry (PIV) measuring platform in a low-speed tunnel. In addition, cross-correlation peak analysis and kriging image reconstruction are applied for postprocessing to enhance PIV image recognition. Combining the time evolution of the forces, the force coefficients, and the flow visualization, we find the evolution and effects of LEV, TEV and WV structures.
探索X型扑翼微型飞行器(也称为拍板翼微型飞行器)柔性扑翼的非定常涡结构是一项挑战。本文的目的是获得风速、扑动频率和攻角(AoA)对CWMAV瞬时和平均力系数的影响,研究前缘涡(LEV)、后缘涡(TEV)和尾流涡(WV)结构的流动可视化,并确定一些新型的扑动推进流动机制。本文提出了一种用于低速隧道的力学和粒子图像测速(PIV)测量平台。此外,应用互相关峰值分析和克里格图像重建进行后处理,以增强PIV图像的识别能力。结合力的时间演化、力系数和流动可视化,我们发现了LEV、TEV和WV结构的演化和影响。
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引用次数: 1
期刊
International Journal of Micro Air Vehicles
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