HUANG Cong, LI Jiyu, LAN Yubin, YE Weixin, LI Sijia, XING Hang. Design and experiment of a wind speed detection equipment with wind pressure conversion near ground[J]. Journal of South China Agricultural University, 2018, 39(1): 105-111. DOI: 10.7671/j.issn.1001-411X.2018.01.017
    Citation: HUANG Cong, LI Jiyu, LAN Yubin, YE Weixin, LI Sijia, XING Hang. Design and experiment of a wind speed detection equipment with wind pressure conversion near ground[J]. Journal of South China Agricultural University, 2018, 39(1): 105-111. DOI: 10.7671/j.issn.1001-411X.2018.01.017

    Design and experiment of a wind speed detection equipment with wind pressure conversion near ground

    • Objective  The current wind speed detection equipment is influenced by wind speed interference in the wind field. To solve this problem, this paper presented a new kind of wind speed detection equipment using pitot tube speed sensors based on wind pressure signal to obtain better unmanned aerial vehicle(UAV) wind parameters near ground.
      Method  We first used axial fan to test the interference of induction position of pitot tube wind speed sensor as well as vane anemometer, and then used hot wire anemometer to detect the changes of wind speeds before and after interference. In the end, we used axial fan to test and record wind speeds of all pitot sensors at the same wind speed, and obtained the consistency of the system. The measured wind speed of the standard hot wire anemometer was compared with that of the sensor in the system at the same wind speed to find out the range of wind speed in which the accuracy of pitot tube wind speed sensor was low. Matlab software was used to fit the wind pressure signal and wind speed value.
      Result  At the wind speed of 10–15 m·s–1, the reduction of wind speed interfered by pitot tube did not exceed 1%, while reached more than 20% for the vane anemometer. The maximum absolute discrepancy of all 30 sensors of this equipment was 0.96 m·s–1when the wind speed was 15.00 m·s–1, the maximum relative discrepancy was 6.40%, and the coefficient of variation was about 1%. Fitting with three-time formula, the sum of squares for error was 0.099 6, the goodness of fit (R2) was more than 0.96.
      Conclusion  Comparing to the current methodology, the proposed system can effectively detect the rotor wind speed data of UAV and has the significant advantage of reducing interference. This system can effectively help research the field work of UAV.
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