High-accuracy, high-resolution downwash flow field measurements of an unmanned helicopter for precision agriculture

Tang, Qing; Zhang, Ruirui; Chen, Liping; Xu, Gang; Deng, Wei; Ding, Chenchen; Xu, Min; Yi, Tongchuan; Wen, Yao; Li, Longlong

doi:10.1016/j.compag.2020.105390

Cited by 27 publications

(15 citation statements)

References 19 publications

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“…For crop protection UAS, the high spray height and the downwash airflow make the droplet transportation environment more complex than traditional ground machines. In recent years, scholars have used CFD simulations [10,24] or PIV measure technology [19,22] to analyze the transportation environment in the UAS spray. They found that the rotor tip vortex would make droplets curl up into a higher space and small droplets much easier to drift, and the high flight speed would enhance this phenomenon [11] .…”

Section: Discussionmentioning

confidence: 99%

“…Scholars applied wind tunnel tests and computational fluid dynamics (CFD) simulations to research the spray deposition or drift principles within the wind field of manned aircraft such as propeller wake flow [14] and wing tip vortex [15] . Similarly, particle image velocimetry (PIV) tests and CFD simulations were used in China to research the downwash airflow [16][17][18][19] and droplet transportation process [10,[20][21][22][23][24] of rotor UASs. Most of these studies showed that the downwash airflow of the UAS rotor was beneficial to deposition, but swirls and bounces of airflow increased the risk of drift.…”

Section: Introduction mentioning

confidence: 99%

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Influence of nozzle enabling strategy on spray deposition of crop protection unmanned aerial system

Gu¹,

Xue²,

Chen³

et al. 2021

International Journal of Agricultural and Biological Engineering

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Proper nozzles arrangement is significant to improve spray deposition of crop protection unmanned aerial system (UAS). Besides fuselage structure, the control strategy is another nozzle location changing method when there are multiple sets of nozzles. A four-rotor crop protection UAS equipped with four centrifugal nozzles was used to conduct a field experiment in the rupturing stage of rice. Two sets of nozzles in the front and rear of the fuselage were enabled independently to investigate spray deposition, including spray coverage and droplet density on the sampling cards. Various nozzle rotating speeds and flight speeds were employed in the experiment to study the influence of nozzle location on the deposition. With different nozzle rotating speeds, the droplet spectrum could be controlled. The results show that the average coverage and average cumulative droplet density are negatively correlated with flight speed. Average droplet density is also negatively correlated with the droplet size. Spray deposition of front nozzles is significantly reduced compared with that of the rear nozzles under the same spray parameters, especially when the droplet size is too large or the flight speed is too fast. The reduction is mainly concentrated in the center area of the spray swath. As a result, the average cumulative droplet density of the front nozzles decreases by 25.96% in total. The average droplet density decreases by 18.54% when the droplet size is smaller than 100 μm, decreases by 25.02% when between 100 μm and 200 μm, and decreases by more than half when larger than 200 μm. This research can provide guidance for the installation of UAS nozzles and spray control strategy design.

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Section: Discussionmentioning

confidence: 99%

Section: Introduction mentioning

confidence: 99%

Influence of nozzle enabling strategy on spray deposition of crop protection unmanned aerial system

Gu¹,

Xue²,

Chen³

et al. 2021

International Journal of Agricultural and Biological Engineering

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“…According to the current applied situation in China [11][12][13][14][15]33,34] , the payloads of most CPUASs are less than 50 kg, and the total weight of CPUAS is not more than 100 kg. In practical aerial pesticide spraying, the CPUAS flight altitude is from 1.5 m to 7.0 m above the crops.…”

Section: Main Technical Parametersmentioning

confidence: 99%

“…Guo et al [32] simulated and verified the spatial and temporal distributions of the downwash of a quad-rotor CPUAS in hover state, and the speed test experiment was designed to measure the wind field with an anemometer. Tang et al [33] developed an indoor measurement technique to investigate the downwash flow field of a 1:10 scaled unmanned agricultural helicopter, in which high-speed particle image velocimetry was employed to obtain the instantaneous and average speed field of the downwash.…”

Section: Introduction mentioning

confidence: 99%

Design and experiment of a hydraulic lifting wind field test platform for crop protection UAS

Zhang

Qiu

Xue

et al. 2021

International Journal of Agricultural and Biological Engineering

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As a new type of crop protection machine, the crop protection unmanned aerial system (CPUAS) is developing rapidly in China. The wind field generated by the rotor has a great influence on the deposition and penetration of spraying droplets. The purpose of this study was to develop a reliable and stable test platform that could be used for wind field test of CPUAS, and to carry out the downwash experiments on the platform to obtain the downwash distribution law of a CPUAS Z-3N (100 kg level, Nanjing Research Institute on Simulation Technique, Nanjing, China). The tests showed that the performances of the developed platform could meet the expected design requirements. The platform operated stably and reliably during the downwash experiments of Z-3N, which indicated it could be applied for CPUASs of 100 kg level and below. The vibration characteristics of the platform with different heights (2.0 m, 3.0 m, 5.0 m, 7.0 m, 10.0 m) were obtained through modal analysis, which could effectively guide avoiding the resonance for stable and reliable operation during the experiments with the tested CPUAS Z-3N. A ring-radial method was designed combined with the platform for the downwash measurement. The experimental results showed that the downwash distribution of Z-3N was not symmetrical; the downwash wind speed decreased with the increase of the radial distance while the changing trend was not consistent as the height increased. Moreover, the area with high wind speed was mainly within 3.0 m of the radial distance, and the maximum value was 11.37 m/s. The study provided a new way for wind field test of CPUASs and would provide some references for better utilization of wind field during the CPUAS spraying.

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“…Compared with aerial systems, the UAVs fly at lower altitudes and are not subject to air traffic control [ 15 ], and they have more advantages in practical applications because of their lower cost and higher operational flexibility, which is fundamental for precise agriculture monitoring [ 16 ]. UAV-based multispectral imaging is mostly applied to classification and mapping [ 17 ], but it fails to meet the needs of quantitative soil estimation due to the limitation of spectral resolution [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Soil Nutrient Estimation and Mapping in Farmland Based on UAV Imaging Spectrometry

Yang

Bao

et al. 2021

Sensors

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Soil nutrient is one of the most important properties for improving farmland quality and product. Imaging spectrometry has the potential for rapid acquisition and real-time monitoring of soil characteristics. This study aims to explore the preprocessing and modeling methods of hyperspectral images obtained from an unmanned aerial vehicle (UAV) platform for estimating the soil organic matter (SOM) and soil total nitrogen (STN) in farmland. The results showed that: (1) Multiplicative Scattering Correction (MSC) performed better in reducing image scattering noise than Standard Normal Variate (SNV) transformation or spectral derivatives, and it yielded a result with higher correlation and lower signal-to-noise ratio; (2) The proposed feature selection method combining Successive Projections Algorithm (SPA) and Competitive Adaptive Reweighted Sampling algorithm (CARS), could provide selective preference for hyperspectral bands. Exploiting this method, 24 and 22 feature bands were selected for SOM and STN estimation, respectively; (3) The particle swarm optimization (PSO) algorithm was employed to obtain optimized input weights and bias values of the extreme learning machine (ELM) model for more accurate prediction of SOM and STN. The improved PSO-ELM model based on the selected preference bands achieved higher prediction accuracy (R2 of 0.73 and RPD of 1.91 for SOM, R2 of 0.63, and RPD of 1.53 for STN) than support vector machine (SVM), partial least squares regression (PLSR), and the ELM model. This study provides an important guideline for monitoring soil nutrient for precision agriculture with imaging spectrometry.

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High-accuracy, high-resolution downwash flow field measurements of an unmanned helicopter for precision agriculture

Cited by 27 publications

References 19 publications

Influence of nozzle enabling strategy on spray deposition of crop protection unmanned aerial system

Influence of nozzle enabling strategy on spray deposition of crop protection unmanned aerial system

Design and experiment of a hydraulic lifting wind field test platform for crop protection UAS

Soil Nutrient Estimation and Mapping in Farmland Based on UAV Imaging Spectrometry

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