Synchronous three-dimensional detection method for multiple parameters of wind fields based on vector principle

In the area of air-assisted spray, conventional detection of speed and direction of the wind fields for spray are separately conducted, and multiple kinds of sensors have to be laid on each coordinate axis during multidimensional detection. It limits the optimization of operation effect of sprayers based on wind-field distribution characteristics. This paper proposes a novel detection method to achieve synchronous measurement of wind speed and direction in three dimensions. Wind flow was considered as vectors and the sensing structure with a regular triangular pyramid shape supported by cantilever pieces was established. Strain gauges were utilized to detect the deformation in each direction by the wind thrust onto a ball before and after wind flow. Moreover, the calculation models of wind speed and direction were developed respectively based on the relationship of ‘strains-force-wind pressure-wind velocity’ and the principle of space operation of vectors, so multiple parameters of wind fields could be obtained simultaneously. Calibration was conducted based on a wind tunnel and the Testo 405i anemometers. The results showed that: the minimum relative error of wind-speed values was about 0.06%, while the maximum was about 10%. The average relative error of all the directions was less than 5%. Furthermore, the measurement of the wind among artificial tree canopies demonstrated that the proposed method could effectively measure both speed value and direction of the wind among canopies, and it also helped to find the wind distribution characteristics of the fan, SFG4-2R. The results highlighted both the reliability and the practical meaning of the proposed method, which could be a technical solution for measuring and evaluating wind-field characteristics of sprayers..

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:13

Enthalten in:

Frontiers in Plant Science - 13(2022)

Sprache:

Englisch

Beteiligte Personen:

Shenghui Yang [VerfasserIn]
Shenghui Yang [VerfasserIn]
Wenwei Li [VerfasserIn]
Wenwei Li [VerfasserIn]
Xingxing Liu [VerfasserIn]
Xingxing Liu [VerfasserIn]
Zimeng Wang [VerfasserIn]
Zimeng Wang [VerfasserIn]
Yongjun Zheng [VerfasserIn]
Yongjun Zheng [VerfasserIn]
Yu Tan [VerfasserIn]
Yu Tan [VerfasserIn]
Han Feng [VerfasserIn]
Han Feng [VerfasserIn]

Links:

doi.org [kostenfrei]
doaj.org [kostenfrei]
www.frontiersin.org [kostenfrei]
Journal toc [kostenfrei]

Themen:

Detection
Flow fields
Multidimensional systems
Plant culture
Sensors
Vector
Wind

doi:

10.3389/fpls.2022.1003659

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

DOAJ029366658