scholarly journals Technique of Measuring Wind Speed and Direction by Using a Roll-rotating Three-Axis Ultrasonic Anemometer (II)

2018 ◽  
Vol 9 (4) ◽  
pp. 9-15
Author(s):  
CHANG BYEONG HEE ◽  
김양원 ◽  
이승훈
Keyword(s):  
Wind Speed ◽  
Ultrasonic Anemometer

scholarly journals Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 269 ◽  
Author(s):  
Wei Zhang ◽  
Zhipeng Li ◽  
Xuyang Gao ◽  
Yanjun Li ◽  
Yibing Shi
Keyword(s):  
Wavelet Transform ◽  
Wind Speed ◽  
Arrival Time ◽  
Time Window ◽  
Signal To Noise Ratio ◽  
Information Criteria ◽  
Echo Signal ◽  
Time Frequency ◽  
Ultrasonic Echo ◽  
Ultrasonic Anemometer

The time-difference method is a common one for measuring wind speed ultrasonically, and its core is the precise arrival-time determination of the ultrasonic echo signal. However, because of background noise and different types of ultrasonic sensors, it is difficult to measure the arrival time of the echo signal accurately in practice. In this paper, a method based on the wavelet transform (WT) and Bayesian information criteria (BIC) is proposed for determining the arrival time of the echo signal. First, the time-frequency distribution of the echo signal is obtained by using the determined WT and rough arrival time. After setting up a time window around the rough arrival time point, the BIC function is calculated in the time window, and the arrival time is determined by using the BIC function. The proposed method is tested in a wind tunnel with an ultrasonic anemometer. The experimental results show that, even in the low-signal-to-noise-ratio area, the deviation between mostly measured values and preset standard values is mostly within 5 μs, and the standard deviation of measured wind speed is within 0.2 m/s.

WindSonic – a new ultrasonic anemometer

Sensor Review ◽  
2002 ◽  
Vol 22 (3) ◽  
pp. 218-222 ◽  
Author(s):  
Chris Stock
Keyword(s):  
Wind Speed ◽  
Time Of Flight ◽  
Operating Principle ◽  
Air Velocity ◽  
Vector Measurement ◽  
Ultrasonic Technology ◽  
Ultrasonic Anemometer ◽  
Air Speed

Describes the developments of a small, robust ultrasonic wind speed and direction indicator. Gill’s patented ultrasonic technology is based on the time‐of‐flight operating principle, which provides vector measurement of air velocity, given the dimensions and geometry of pairs of transducers. In this case, two pairs of transducers are used such that the air velocity can be derived along orthogonal axes and hence the air speed and direction can be computed.

Estimation of Wind Vector Profile Using a Hexarotor Unmanned Aerial Vehicle and Its Application to Meteorological Observation up to 1000 m above Surface

2018 ◽  
Vol 35 (8) ◽  
pp. 1621-1631 ◽  
Author(s):  
Tomoya Shimura ◽  
Minoru Inoue ◽  
Hirofumi Tsujimoto ◽  
Kansuke Sasaki ◽  
Masato Iguchi
Keyword(s):  
Wind Speed ◽  
Profile Measurement ◽  
Wind Vector ◽  
Doppler Lidar ◽  
Wind Speeds ◽  
Wide Range ◽  
Lidar Measurements ◽  
Ultrasonic Anemometer ◽  
Aerial Vehicle ◽  
Meteorological Observations

AbstractSmall unmanned aerial vehicles (UAVs), also known as drones, have recently become promising tools in various fields. We investigated the feasibility of wind vector profile measurement using an ultrasonic anemometer installed on a 1-m-wide hexarotor UAV. Wind vectors measured by the UAV were compared to observations by a 55-m-high meteorological tower, over a wide range of wind speed conditions up to 11 m s−1, which is a higher wind speed range than those used in previous studies. The wind speeds and directions measured by the UAV and the tower were in good agreement, with a root-mean-square error of 0.6 m s−1 and 12° for wind speed and direction, respectively. The developed method was applied to field meteorological observations near a volcano, and the wind vector profiles, along with temperature and humidity, were measured by the UAV for up to an altitude of 1000 m, which is a higher altitude range than those used in previous studies. The wind vector profile measured by the UAV was compared with Doppler lidar measurements (collected several kilometers away from the UAV measurements) and was found to be qualitatively similar to that captured by the Doppler lidar, and it adequately represented the features of the atmospheric boundary layer. The feasibility of wind profile measurement up to 1000 m by a small rotor-based UAV was clarified over a wide range of wind speed conditions.

scholarly journals Technique for Measuring Wind Speed and Direction Using a Roll-rotating Three-Axis Ultrasonic Anemometer

2018 ◽  
Vol 9 (3) ◽  
pp. 5-12
Author(s):  
CHANG BYEONG HEE ◽  
조태환 ◽  
김양원 ◽  
이승훈
Keyword(s):  
Wind Speed ◽  
Ultrasonic Anemometer

scholarly journals Towards accurate and practical drone-based wind measurements with an ultrasonic anemometer

2021 ◽  
Vol 14 (2) ◽  
pp. 1303-1318
Author(s):  
William Thielicke ◽  
Waldemar Hübert ◽  
Ulrich Müller ◽  
Michael Eggert ◽  
Paul Wilhelm
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Sonic Anemometer ◽  
Substantial Reduction ◽  
Three Dimensional ◽  
Cost Effective ◽  
Single Location ◽  
Ultrasonic Anemometer ◽  
Induced Flow ◽  
Air Speed

Abstract. Wind data collection in the atmospheric boundary layer benefits from short-term wind speed measurements using unmanned aerial vehicles. Fixed-wing and rotary-wing devices with diverse anemometer technology have been used in the past to provide such data, but the accuracy still has the potential to be increased. A lightweight drone for carrying an industry-standard precision sonic anemometer was developed. Accuracy tests have been performed with the isolated anemometer at high tilt angles in a calibration wind tunnel, with the drone flying in a large wind tunnel and with the full system flying at different heights next to a bistatic lidar reference. The propeller-induced flow deflects the air to some extent, but this effect is compensated effectively. The data fusion shows a substantial reduction of crosstalk (factor of 13) between ground speed and wind speed. When compared with the bistatic lidar in very turbulent conditions, with a 10 s averaging interval and with the unmanned aerial vehicle (UAV) constantly circling around the measurement volume of the lidar reference, wind speed measurements have a bias between −2.0 % and 4.2 % (root-mean-square error (RMSE) of 4.3 % to 15.5 %), vertical wind speed bias is between −0.05 and 0.07 m s−1 (RMSE of 0.15 to 0.4 m s−1), elevation bias is between −1 and 0.7∘ (RMSE of 1.2 to 6.3∘), and azimuth bias is between −2.6 and 7.2∘ (RMSE of 2.6 to 8.0∘). Key requirements for good accuracy under challenging and dynamic conditions are the use of a full-size sonic anemometer, a large distance between anemometer and propellers, and a suitable algorithm for reducing the effect of propeller-induced flow. The system was finally flown in the wake of a wind turbine, successfully measuring the spatial velocity deficit and downwash distribution during forward flight, yielding results that are in very close agreement to lidar measurements and the theoretical distribution. We believe that the results presented in this paper can provide important information for designing flying systems for precise air speed measurements either for short duration at multiple locations (battery powered) or for long duration at a single location (power supplied via cable). UAVs that are able to accurately measure three-dimensional wind might be used as a cost-effective and flexible addition to measurement masts and lidar scans.

scholarly journals Method for airborne measurement of the spatial wind speed distribution above complex terrain

2021 ◽  
Vol 6 (2) ◽  
pp. 427-440
Author(s):  
Christian Ingenhorst ◽  
Georg Jacobs ◽  
Laura Stößel ◽  
Ralf Schelenz ◽  
Björn Juretzki
Keyword(s):  
Wind Speed ◽  
Complex Terrain ◽  
Wind Farm ◽  
Three Dimensional ◽  
High Sensitivity ◽  
Spatial And Temporal Variability ◽  
Speed Increase ◽  
Airborne Measurement ◽  
Ultrasonic Anemometer ◽  
Mean Wind Speed

Abstract. Wind farm sites in complex terrain are subject to local wind phenomena, which have a relevant impact on a wind turbine's annual energy production. To reduce investment risk, an extensive site evaluation is therefore mandatory. Stationary long-term measurements are supplemented by computational fluid dynamics (CFD) simulations, which are a commonly used tool to analyse and understand the three-dimensional wind flow above complex terrain. Though under intensive research, such simulations still show a high sensitivity to various input parameters like terrain, atmosphere and numerical setup. In this paper, a different approach aims to measure instead of simulate wind speed deviations above complex terrain by using a flexible, airborne measurement system. An unmanned aerial vehicle is equipped with a standard ultrasonic anemometer. The uncertainty in the system is evaluated against stationary anemometer data at different heights and shows very good agreement, especially in mean wind speed (< 0.12 m s−1) and mean direction (< 2.4∘) estimation. A test measurement was conducted above a forested and hilly site to analyse the spatial and temporal variability in the wind situation. A position-dependent difference in wind speed increase of up to 30 % compared to a stationary anemometer is detected.

scholarly journals Wind speed deviations in complex terrain

2020 ◽  
Author(s):  
Christian Ingenhorst ◽  
Georg Jacobs ◽  
Laura Stößel ◽  
Ralf Schelenz ◽  
Björn Juretzki
Keyword(s):  
Wind Speed ◽  
Complex Terrain ◽  
Wind Farm ◽  
Three Dimensional ◽  
Airborne Measurement ◽  
Ultrasonic Anemometer ◽  
Mean Wind Speed ◽  
Huge Impact ◽  
Aerial Vehicle ◽  
Site Evaluation

Abstract. Wind farm sites within complex terrain are subject to local wind phenomena, which have a huge impact on a wind turbine's annual energy production. To reduce investment risk, an extensive site evaluation is therefore mandatory. Stationary long-term measurements are supplemented by CFD simulations, which are a commonly used tool to analyse and understand the three-dimensional wind flows above complex terrain. Though being under heavy research, such simulations still show a huge sensitivity for various input parameters like terrain, atmosphere and numerical setup. Within this paper, a different approach aims to measure instead of simulate wind speed deviations above complex terrain by using a flexible, airborne measurement system. An unmanned aerial vehicle is equipped with a standard ultrasonic anemometer. The uncertainty of the system is evaluated against stationary anemometer at different heights and shows very good agreement, especially in mean wind speed (

scholarly journals Measuring Wind Speed Using the Internal Stabilization System of a Quadrotor Drone

Drones ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 23 ◽  
Author(s):  
Magdalena Simma ◽  
Håvard Mjøen ◽  
Tobias Boström
Keyword(s):  
Wind Speed ◽  
Test Site ◽  
Horizontal Wind ◽  
Mean Square ◽  
Flight Tests ◽  
Wind Speeds ◽  
Internal Stabilization ◽  
Ultrasonic Anemometer ◽  
Wind Measurements ◽  
The Cost

This article proposes a method of measuring wind speed using the data logged by the autopilot of a quadrotor drone. Theoretical equations from works on quadrotor control are utilized and supplemented to form the theoretical framework. Static thrust tests provide the necessary parameters for calculating wind estimates. Flight tests were conducted at a test site with laminar wind conditions with the quadrotor hovering next to a static 2D ultrasonic anemometer with wind speeds between 0–5 m/s. Horizontal wind estimates achieve exceptionally good results with root mean square error (RMSE) values between 0.26–0.29 m/s for wind speed, as well as between 4.1–4.9 for wind direction. The flexibility of this new method simplifies the process, decreases the cost, and adds new application areas for wind measurements.

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