{"title":"利用四旋翼无人驾驶航空系统进行高分辨率风速测量:在带主动网格的风洞中进行校准和验证","authors":"Johannes Kistner, Lars Neuhaus, Norman Wildmann","doi":"10.5194/amt-17-4941-2024","DOIUrl":null,"url":null,"abstract":"Abstract. As a contribution to closing observational gaps in the atmospheric boundary layer (ABL), the Simultaneous Wind measurement with Uncrewed Flight Systems in 3D (SWUF-3D) fleet of uncrewed aerial systems (UASs) is utilized for in situ measurements of turbulence. To date, the coefficients for the transformation terms used in our algorithm for deriving wind speeds from avionic data have only been determined via calibration flights in the free field. Therefore, we present in this work calibration and verification under laboratory conditions. The UAS measurements are performed in a wind tunnel equipped with an active grid and constant temperature anemometers (CTAs) as a reference. Calibration is performed in x- and y-coordinate directions of the UAS body frame at wind speeds of 2 … 18 m s−1. For systematic verification of the measurement capabilities and identification of limitations, different measurement scenarios like gusts, velocity steps, and turbulence are generated with the active grid. Furthermore, the measurement accuracy under different angles of sideslip (AoSs) and wind speeds is investigated, and we examined whether the calibration coefficients can be ported to other UASs in the fleet. Our analyses show that the uncertainty in measuring the wind speed depends on the wind speed magnitude and increases with extreme velocity changes and with higher wind speeds, resulting in a root-mean-square error (RMSE) of less than 0.2 m s−1 for steady wind speeds. Applying the calibration coefficients from one UAS to others within the fleet results in comparable accuracies. Flights in gusts of different strengths yield an RMSE of up to 0.6 m s−1. The maximal RMSE occurs in the most extreme velocity steps (i.e., a lower speed of 5 m s−1 and an amplitude of 10 m s−1) and exceeds 1.3 m s−1. For variances below approx. 0.5 and 0.3 m2 s−2, the maximal resolvable frequencies of the turbulence are about 2 and 1 Hz, respectively. The results indicate successful calibration but with susceptibility to high AoSs in high wind speeds, no necessity for wind tunnel calibration for individual UASs, and the need for further research regarding turbulence analysis.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"36 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-resolution wind speed measurements with quadcopter uncrewed aerial systems: calibration and verification in a wind tunnel with an active grid\",\"authors\":\"Johannes Kistner, Lars Neuhaus, Norman Wildmann\",\"doi\":\"10.5194/amt-17-4941-2024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. As a contribution to closing observational gaps in the atmospheric boundary layer (ABL), the Simultaneous Wind measurement with Uncrewed Flight Systems in 3D (SWUF-3D) fleet of uncrewed aerial systems (UASs) is utilized for in situ measurements of turbulence. To date, the coefficients for the transformation terms used in our algorithm for deriving wind speeds from avionic data have only been determined via calibration flights in the free field. Therefore, we present in this work calibration and verification under laboratory conditions. The UAS measurements are performed in a wind tunnel equipped with an active grid and constant temperature anemometers (CTAs) as a reference. Calibration is performed in x- and y-coordinate directions of the UAS body frame at wind speeds of 2 … 18 m s−1. For systematic verification of the measurement capabilities and identification of limitations, different measurement scenarios like gusts, velocity steps, and turbulence are generated with the active grid. Furthermore, the measurement accuracy under different angles of sideslip (AoSs) and wind speeds is investigated, and we examined whether the calibration coefficients can be ported to other UASs in the fleet. Our analyses show that the uncertainty in measuring the wind speed depends on the wind speed magnitude and increases with extreme velocity changes and with higher wind speeds, resulting in a root-mean-square error (RMSE) of less than 0.2 m s−1 for steady wind speeds. Applying the calibration coefficients from one UAS to others within the fleet results in comparable accuracies. Flights in gusts of different strengths yield an RMSE of up to 0.6 m s−1. The maximal RMSE occurs in the most extreme velocity steps (i.e., a lower speed of 5 m s−1 and an amplitude of 10 m s−1) and exceeds 1.3 m s−1. For variances below approx. 0.5 and 0.3 m2 s−2, the maximal resolvable frequencies of the turbulence are about 2 and 1 Hz, respectively. The results indicate successful calibration but with susceptibility to high AoSs in high wind speeds, no necessity for wind tunnel calibration for individual UASs, and the need for further research regarding turbulence analysis.\",\"PeriodicalId\":8619,\"journal\":{\"name\":\"Atmospheric Measurement Techniques\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Measurement Techniques\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/amt-17-4941-2024\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Measurement Techniques","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/amt-17-4941-2024","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
摘要为了填补大气边界层(ABL)观测方面的空白,利用无人驾驶航空系统(UAS)的三维风速同步测量(SWUF-3D)机群对湍流进行了现场测量。迄今为止,我们从航空数据推导风速的算法中使用的转换项系数只能通过自由场校准飞行来确定。因此,我们在这项工作中提出在实验室条件下进行校准和验证。无人机系统的测量是在风洞中进行的,风洞配备了主动网格和恒温风速计(CTA)作为参考。校准在风速为 2 ... 18 m s-1 的情况下在无人机机身框架的 x 坐标和 y 坐标方向上进行。为了系统地验证测量能力和识别限制,使用主动网格生成了不同的测量场景,如阵风、速度阶跃和湍流。此外,我们还研究了不同侧倾角(AoSs)和风速下的测量精度,并考察了校准系数是否可以移植到机队中的其他无人机上。我们的分析表明,风速测量的不确定性取决于风速大小,随着速度的剧烈变化和风速的增加而增加,导致稳定风速下的均方根误差(RMSE)小于 0.2 m s-1。将一个无人机系统的校准系数应用于机队中的其他系统,可获得相当的精度。在不同强度的阵风中飞行,均方根误差可达 0.6 m s-1。最大均方根误差出现在最极端的速度级(即低速 5 m s-1 和振幅 10 m s-1),超过 1.3 m s-1。当方差低于约 0.5 和 0.3 m2 s-2 时,湍流的最大可分辨频率分别约为 2 和 1 Hz。结果表明校准成功,但在高风速下易受高 AoSs 影响,无需对单个无人机系统进行风洞校准,并且需要对湍流分析进行进一步研究。
High-resolution wind speed measurements with quadcopter uncrewed aerial systems: calibration and verification in a wind tunnel with an active grid
Abstract. As a contribution to closing observational gaps in the atmospheric boundary layer (ABL), the Simultaneous Wind measurement with Uncrewed Flight Systems in 3D (SWUF-3D) fleet of uncrewed aerial systems (UASs) is utilized for in situ measurements of turbulence. To date, the coefficients for the transformation terms used in our algorithm for deriving wind speeds from avionic data have only been determined via calibration flights in the free field. Therefore, we present in this work calibration and verification under laboratory conditions. The UAS measurements are performed in a wind tunnel equipped with an active grid and constant temperature anemometers (CTAs) as a reference. Calibration is performed in x- and y-coordinate directions of the UAS body frame at wind speeds of 2 … 18 m s−1. For systematic verification of the measurement capabilities and identification of limitations, different measurement scenarios like gusts, velocity steps, and turbulence are generated with the active grid. Furthermore, the measurement accuracy under different angles of sideslip (AoSs) and wind speeds is investigated, and we examined whether the calibration coefficients can be ported to other UASs in the fleet. Our analyses show that the uncertainty in measuring the wind speed depends on the wind speed magnitude and increases with extreme velocity changes and with higher wind speeds, resulting in a root-mean-square error (RMSE) of less than 0.2 m s−1 for steady wind speeds. Applying the calibration coefficients from one UAS to others within the fleet results in comparable accuracies. Flights in gusts of different strengths yield an RMSE of up to 0.6 m s−1. The maximal RMSE occurs in the most extreme velocity steps (i.e., a lower speed of 5 m s−1 and an amplitude of 10 m s−1) and exceeds 1.3 m s−1. For variances below approx. 0.5 and 0.3 m2 s−2, the maximal resolvable frequencies of the turbulence are about 2 and 1 Hz, respectively. The results indicate successful calibration but with susceptibility to high AoSs in high wind speeds, no necessity for wind tunnel calibration for individual UASs, and the need for further research regarding turbulence analysis.
期刊介绍:
Atmospheric Measurement Techniques (AMT) is an international scientific journal dedicated to the publication and discussion of advances in remote sensing, in-situ and laboratory measurement techniques for the constituents and properties of the Earth’s atmosphere.
The main subject areas comprise the development, intercomparison and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.