Method and device for evaluating uncertainty of three-dimensional ultrasonic anemometer with adjustable angle

Abstract

The application discloses a kind of uncertainty evaluation method and device of three-dimensional ultrasonic anemometer with adjustable angle, and it relates to the technical field of uncertainty evaluation, the method comprises: control anemometer transducer transceiver circuit, let each group transducer take turns to send and receive ultrasonic waves, solve the wind speed component in each direction using the headwind and tailwind time of flight of ultrasonic waves and transducer spacing.For the deviation caused by equipment wind shadow area and airflow disturbance, combine the actual wind speed model with the theoretical wind speed model;Then, for the error caused by transducer inclination adjustment and azimuth installation correction, rely on the actual wind direction model to build the wind direction theoretical model.Horizontal wind speed is calculated from multi-directional wind speed components, and the final wind speed and wind direction calculation model is obtained by substituting the two types of actual models.Finally, the uncertainty evaluation of the anemometer wind speed and wind direction measurement results is completed by using the established uncertainty evaluation algorithm.The uncertainty evaluation of the three-dimensional ultrasonic anemometer with adjustable angle is realized.

Description

Technical Field

[0001] This invention relates to the field of uncertainty assessment technology, and in particular to a method and apparatus for uncertainty assessment of a three-dimensional ultrasonic anemometer with adjustable included angle. Background Technology

[0002] A three-dimensional ultrasonic anemometer typically consists of three sets of piezoelectric transducers, a signal processing unit, and a protective housing. Currently, mainstream products can be divided into two categories: The three-dimensional orthogonal ultrasonic anemometer consists of three sets of transducers, each perpendicular to the others, forming a spatial rectangular coordinate system. Its advantages lie in its simple calculation logic: wind speed components directly correspond to the orthogonal coordinate axes, the mathematical model is concise, horizontal and vertical wind components are clearly distinguished, and the computational load is low, making development easier. Its disadvantages include the tendency for the support frame and transducer body to create a wind shadow zone, leading to airflow distortion and measurement deviation; the closer the wind direction is to the acoustic channel direction, the more significant the error.

[0003] To overcome the drawbacks of orthogonal structures, three-dimensional symmetrical non-orthogonal ultrasonic anemometers have emerged, employing a three-axis symmetrical non-orthogonal layout. This means the axes of the three transducers are not perpendicular, but rather form spatially symmetrical angles (typically 60°–120°). This type of structure disperses the transducers and supports, resulting in relatively smooth airflow and reducing the probe's own wind shadow area. However, it has the following drawbacks: 1) Poor structural versatility, making optimization for specific prevailing wind directions impossible. When a stable prevailing wind direction exists (such as valley winds, sea breezes, monsoons, or building-related winds), the "symmetric advantage" becomes "asymmetric loss"—the fixed support arm is constantly positioned in the windward vortex or leeward wind shadow area, leading to a persistently large measurement error in the prevailing wind direction; 2) The fixed tilt and horizontal angles of the three transducers cannot adapt to local wind fields, making it difficult to balance the measurement accuracy of both prevailing and secondary wind directions; 3) The symmetrical support structure is often centrally located, directly facing the incoming flow, actively disturbing the primary airflow and creating secondary wind shadow areas, making it impossible to optimize flow field interference at the installation level.

[0004] Furthermore, current research on the assessment of measurement uncertainty for three-dimensional ultrasonic anemometers mainly focuses on the aforementioned three-dimensional orthogonal ultrasonic anemometers and three-dimensional symmetrical non-orthogonal ultrasonic anemometers. For three-dimensional ultrasonic anemometers with adjustable included angles, research in this area remains significantly lacking. Therefore, there is an urgent need to propose a method for assessing the uncertainty of three-dimensional ultrasonic anemometers with adjustable included angles. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method and apparatus for evaluating the uncertainty of a three-dimensional ultrasonic anemometer with adjustable included angle, which aims to evaluate the uncertainty of the three-dimensional ultrasonic anemometer with adjustable included angle.

[0006] This invention proposes a method for evaluating the uncertainty of a three-dimensional ultrasonic anemometer with an adjustable included angle, the method comprising: The transducer transceiver circuit in the anemometer is controlled so that each pair of transducers in the anemometer transmits and receives ultrasonic waves in sequence. By measuring the flight time of the ultrasonic waves in the headwind and headwind and the distance between each pair of transducers, the wind speed components in different directions are obtained. Based on the wind shadow zone and airflow disturbance introduced by the anemometer, the actual wind speed measurement model is obtained by combining the horizontal wind speed theoretical model. Based on the errors introduced by the anemometer's transducer angle and azimuth adjustment and the error during installation azimuth correction, the actual wind direction measurement model is obtained by combining the horizontal wind direction theoretical model. Different horizontal wind speeds are determined based on the wind speed components in different directions. and Based on horizontal wind speed and The wind speed measurement model and the wind direction measurement model were calculated by comparing them with the actual wind speed measurement model and the actual wind direction measurement model, respectively. The uncertainty assessment results of the anemometer are obtained by using a preset uncertainty assessment algorithm based on the wind speed measurement model and the wind direction measurement model of the anemometer.

[0007] Furthermore, the uncertainty assessment method for the aforementioned three-dimensional ultrasonic anemometer with adjustable included angle, wherein the anemometer includes three pairs of transducers, namely transducers... and transducer 、 transducer and transducer and transducers and transducer The step of obtaining wind speed components in different directions by measuring the flight time of ultrasonic waves in headwinds and headwinds, as well as the distance between each pair of transducers, includes: By measuring the flight time of the ultrasonic waves in both headwind and tailwind conditions, as well as the spacing between each pair of transducers, the wind speed component along the line connecting each pair of transducers is obtained. v 1. v 2. v 3; in: ; ; ; In the formula, For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind; For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind; For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind.

[0008] Furthermore, in the uncertainty assessment method for the aforementioned three-dimensional ultrasonic anemometer with adjustable included angle, the expression for the actual wind speed measurement model is as follows: ; in, l The correction factor is used to address the errors introduced by the wind shadow zone and airflow disturbances generated by the anemometer. and For different horizontal wind speeds.

[0009] Furthermore, in the uncertainty assessment method for the aforementioned three-dimensional ultrasonic anemometer with adjustable included angle, the expression for the actual wind direction measurement model is as follows: ; in, The correction coefficients are used to address the errors introduced by the transducer angle and azimuth adjustment of the anemometer. For the installation azimuth correction amount, This refers to the correction factor corresponding to the error when correcting the installation azimuth angle. and For different horizontal wind speeds.

[0010] Furthermore, the uncertainty assessment method for the aforementioned three-dimensional ultrasonic anemometer with adjustable included angle involves determining different horizontal wind speeds based on the wind speed components in different directions. and The calculation process is as follows: ; ; in, v1. v 2. v 3 represents the wind speed component along the connection line of each pair of transducers; i 1. i 2. i 3 represents the elevation angle between the line connecting each pair of transducers and the horizontal plane; α , β Let be the angle between the projections of each pair of transducers onto the horizontal plane.

[0011] Furthermore, in the uncertainty assessment method for the aforementioned three-dimensional ultrasonic anemometer with adjustable included angle, the elevation angle between the line connecting each pair of transducers and the horizontal plane is... i 1. i 2. i 3 and the included angle between the projections of each pair of transducers onto the horizontal plane. α , β , c The determination steps include: Collect basic wind field data at the site where the anemometer is deployed. The basic wind field data includes the long-term dominant wind direction of the site environment, the wind rose diagram data corresponding to the annual wind direction frequency distribution, and the site turbulence characteristic parameters. Based on the basic wind field data, the expected wind vector field of the site is constructed. With the goal of achieving the best wind vector detection accuracy, the matching criteria between the three detection channels and the expected wind vector field are determined. Based on the matching criteria and considering the influence of site turbulence characteristic parameters on the wind measurement error of the sound channel, the elevation angle between the line connecting each pair of transducers and the horizontal plane is iteratively solved. i 1. i 2. i 3, and the angle between the projections of the lines connecting each pair of transducers onto the horizontal plane. α , β , c This ensures that the direction of each detection channel achieves optimal matching with the expected wind vector field.

[0012] Furthermore, the uncertainty assessment method for the aforementioned three-dimensional ultrasonic anemometer with adjustable included angle, wherein the steps of obtaining the uncertainty assessment result of the anemometer based on the wind speed measurement model and the wind direction measurement model of the anemometer using a preset uncertainty assessment algorithm include: Obtain the model inputs and corresponding probability distribution functions of the wind speed measurement model and the wind direction measurement model, respectively; Randomly select sample values ​​generated by the probability distribution function of the model input to extract the experimental sample size for each model input; Discrete values ​​of the corresponding output quantities were calculated based on the wind speed measurement model and the wind direction measurement model, respectively, for the experimental sample size. The discrete values ​​of the output are sorted in non-decreasing order to obtain the distribution function of the sorted output, and the evaluation result of the measurement uncertainty of the anemometer is determined based on the discrete representation of the distribution function of the output.

[0013] Another object of the present invention is to provide an uncertainty assessment device for a three-dimensional ultrasonic anemometer with adjustable included angle, the device comprising: The acquisition module is used to control the transceiver circuit of the anemometer, so that each pair of transceivers in the anemometer will transmit and receive ultrasonic waves in sequence. By measuring the flight time of the ultrasonic waves in the headwind and headwind and the distance between each pair of transceivers, the wind speed components in different directions are obtained. The correction module is used to obtain the actual wind speed measurement model by combining the horizontal wind speed theoretical model with the error introduced by the wind shadow area and airflow disturbance generated by the anemometer, and to obtain the actual wind direction measurement model by combining the error introduced by the transducer angle and azimuth adjustment of the anemometer and the error when correcting the installation azimuth angle with the horizontal wind direction theoretical model. The calculation module is used to determine different horizontal wind speeds based on the wind speed components in different directions. and Based on horizontal wind speed and The wind speed measurement model and the wind direction measurement model were calculated by comparing them with the actual wind speed measurement model and the actual wind direction measurement model, respectively. The measurement module is used to obtain the uncertainty assessment results of the anemometer based on the wind speed measurement model and the wind direction measurement model of the anemometer, respectively, using a preset uncertainty assessment algorithm.

[0014] Another object of the present invention is to provide a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0015] Another object of the present invention is to provide an electronic device including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the method described above.

[0016] This invention controls the transducer transceiver circuit of a three-dimensional ultrasonic anemometer with adjustable angle, causing each pair of transducers to alternately perform ultrasonic wave transmission and reception. It detects the flight time of the ultrasonic waves in the wind and the transducer spacing, and calculates multi-directional wind speed components. Combining the anemometer's wind shadow zone and error factors caused by airflow disturbances, it adapts a horizontal wind speed theoretical model to construct an actual wind speed measurement model. Simultaneously, it adapts a horizontal wind direction theoretical model to construct an actual wind direction measurement model, combining transducer angle and azimuth adjustment errors and installation azimuth correction errors. Based on the multi-directional wind speed components, the horizontal wind speed is calculated, and precise modeling and calculation are completed using the actual wind speed and wind direction measurement models. Finally, relying on a preset uncertainty assessment algorithm, it outputs the overall uncertainty assessment result of the anemometer based on the established wind speed and wind direction measurement models. Customized transducer angles and orientations were designed to address the specific wind environment characteristics of the site, concentrating asymmetric environmental losses and enabling precise correction of differential errors across multiple transducer sets. The adjustable structural characteristics and working mechanism of the angle-adjustable 3D ultrasonic anemometer were thoroughly explored. The system systematically identified and quantified various core error influencing factors, including wind shadow and airflow disturbances, adjustable angle installation deviations, and asymmetric wind field losses. A refined wind speed and direction measurement model tailored to complex field conditions was constructed, effectively solving the technical challenges of traditional fixed-deployment anemometers failing to adapt to site wind field characteristics, exhibiting differential transducer measurement error distribution, and deviating evaluation results from actual measurement accuracy. This resulted in accurate and comprehensive evaluation of the measurement uncertainty of the angle-adjustable 3D ultrasonic anemometer, significantly improving the authenticity, accuracy, and reliability of anemometer uncertainty evaluation in complex field scenarios, and meeting the requirements for high-precision and high-stability field wind field monitoring. Attached Figure Description

[0017] Figure 1 This is a flowchart of the uncertainty assessment method for the three-dimensional ultrasonic anemometer with adjustable included angle in the first embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the three-dimensional ultrasonic anemometer with adjustable included angle in the uncertainty evaluation method of the three-dimensional ultrasonic anemometer with adjustable included angle in one embodiment of the present invention. Figure 3 This is a schematic diagram showing the relationship between the horizontal plane projection and the horizontal orientation of the three-dimensional ultrasonic anemometer with adjustable angle in the uncertainty evaluation method of the three-dimensional ultrasonic anemometer with adjustable angle in one embodiment of the present invention. Figure 4 This is a three-dimensional spatial schematic diagram of the three-dimensional ultrasonic anemometer with adjustable included angle in the uncertainty evaluation method of the three-dimensional ultrasonic anemometer with adjustable included angle in one embodiment of the present invention. Figure 5 This is a schematic diagram of the horizontal plane projection of the three-dimensional ultrasonic anemometer with adjustable angle in the uncertainty evaluation method of the three-dimensional ultrasonic anemometer with adjustable angle in one embodiment of the present invention. Figure 6 This is a structural block diagram of the uncertainty assessment device for an adjustable three-dimensional ultrasonic anemometer according to the third embodiment of the present invention.

[0018] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0019] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0020] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0022] Example 1 Please see Figure 1 The figure shows the uncertainty evaluation method of the three-dimensional ultrasonic anemometer with adjustable included angle in the first embodiment of the present invention, the method including steps S10 to S13.

[0023] Step S10: Control the transducer transceiver circuit in the anemometer to make each pair of transducers in the anemometer transmit and receive ultrasonic waves in sequence. By measuring the flight time of the ultrasonic waves in the headwind and headwind and the distance between each pair of transducers, the wind speed components in different directions are obtained.

[0024] The transceiver circuit controls the transducer to transmit and receive ultrasonic waves sequentially. The speed of sound propagation is the superposition of the wind speed component along the sound wave direction: the speed increases with the wind and decreases with the wind. By measuring the flight time with and against the wind, and combining this with the known spacing between the transducers, the wind speed components in each direction can be calculated.

[0025] Specifically, such as Figure 2As shown, the anemometer includes three pairs of transducers, namely transducers... and transducer 、 transducer and transducer and transducers and transducer ; By measuring the flight time of the ultrasonic waves in both headwind and tailwind conditions, as well as the spacing between each pair of transducers, the wind speed component along the line connecting each pair of transducers is obtained. v 1. v 2. v 3; in: ; ; ; In the formula, For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind; For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind; For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind.

[0026] Step S11: Based on the wind shadow area generated by the anemometer and the error introduced by airflow disturbance, the actual wind speed measurement model is obtained by combining the horizontal wind speed theoretical model. Based on the error introduced by the anemometer's transducer angle and azimuth adjustment and the error during installation azimuth correction, the actual wind direction measurement model is obtained by combining the horizontal wind direction theoretical model.

[0027] In this process, the wind speed measurement model takes into full account the wind shadow zone formed by the structure of the anemometer itself, which causes disturbance to the surrounding airflow. This type of environmental interference can lead to measurement deviations in wind speed detection. Such errors are introduced into the calculation process as correction conditions. Then, the model is optimized and derived by combining the classic horizontal wind speed theoretical calculation formula to construct an actual wind speed measurement model that can offset airflow interference. At the same time, the system deviations caused by adjusting the transducer tilt angle and spatial orientation during the equipment commissioning process, as well as the additional correction errors generated during the subsequent correction of the installation azimuth angle, are also taken into account. These two types of error terms caused by installation and commissioning are included in the calculation, and then optimized and corrected based on the horizontal wind direction theoretical model. Finally, an actual wind direction measurement model that can compensate for installation deviations is established.

[0028] Specifically, meteorological wind speed and direction usually refer to horizontal winds; therefore, the theoretical model for horizontal wind speed is as follows: ; Considering the influence of wind shadow areas and airflow disturbances still present in the instrument, the actual wind speed measurement model is as follows: ; in, l The correction factor is used to address the errors introduced by the wind shadow zone and airflow disturbances generated by the anemometer. and For different horizontal wind speeds.

[0029] Assuming the angle between the ambient wind and the horizontal north direction is... The theoretical model for horizontal wind direction (azimuth) is as follows: ; Considering the potential errors introduced by the internal transducer angle and azimuth adjustment (such as loose fasteners), as well as the errors during azimuth correction, a correction coefficient is introduced. Therefore, the actual measurement model for the wind direction is: ; in, The correction coefficients are used to address the errors introduced by the transducer angle and azimuth adjustment of the anemometer. For installation azimuth correction (e.g.) Figure 3 (as shown) This refers to the correction factor corresponding to the error when correcting the installation azimuth angle. and For different horizontal wind speeds.

[0030] Step S12: Determine different horizontal wind speeds based on the wind speed components in different directions. and Based on horizontal wind speed and The wind speed measurement model and the wind direction measurement model were calculated by comparing them with the actual wind speed measurement model and the actual wind direction measurement model, respectively.

[0031] Specifically, such as Figure 4 to Figure 5 As shown, the anemometer includes three pairs of transducers, namely transducers... and transducer 、 transducer and transducer and transducers and transducer The wind speed component in the direction of the line connecting them is denoted as v 1. v 2. v 3; The angle of elevation between the line connecting each pair of transducers and the horizontal plane is... i 1. i 2. i 3; The included angle between the projections of each pair of transducers onto the horizontal plane is... α , β , c ,satisfy α + β + c =360°.

[0032] It should be noted that, α Defined as: v 1. Horizontal projection and v 2. The angle between the horizontal projections.

[0033] β Defined as: v 1. Horizontal projection and v 3. The angle between the horizontal projections. c It is a derived value because the sum of the three included angles must be 360°, so the third included angle... c (Right now v 3 and v The angle between 1 and 1 is a given. α and β The derived value of the decision.

[0034] Will v If the horizontal projection direction of 1 coincides with the prevailing wind direction at the installation site, then the horizontal wind speed can be established. v x and v y The calculation formula: ; ; in, v 1. v 2. v3 represents the wind speed component along the connection line of each pair of transducers; i 1. i 2. i 3 represents the angle between each connecting line and the horizontal plane; α , β , c The angle between the horizontal projections.

[0035] Specifically, v The horizontal projection direction of plane 1 coincides with the long-term prevailing wind direction (mainstream wind direction) of the installation site, and this is used as the horizontal plane. The reference direction of the axis, therefore v 1 in The contribution of wind speed in the axial direction is zero.

[0036] v 2. The horizontal projection direction relative to the prevailing wind direction ( v 1) It has been rotated by an angle α on the horizontal plane; therefore, its horizontal wind speed component is... Axis (downwind direction) and Corresponding projection contributions were generated along the axis (crosswind direction).

[0037] v 3. The horizontal projection direction relative to the prevailing wind direction ( v 1) Rotated on the horizontal plane β Angle (usually with) v 2. On the opposite side (to cover the entire wind direction), therefore its horizontal wind speed component is shaft and Corresponding projection contributions were generated on the axes respectively.

[0038] Will v 2. v Substituting the 3 values ​​into the actual wind speed measurement model v x expression, v 1. v 2. v 3. Substitute the actual wind direction measurement model v y The expression can be used to obtain the wind speed measurement model and the wind direction measurement model.

[0039] Step S13: Obtain the uncertainty assessment result of the anemometer using the preset uncertainty assessment algorithm based on the wind speed measurement model and wind direction measurement model of the anemometer.

[0040] Specifically, the wind speed measurement model and the wind direction measurement model apply a preset uncertainty assessment algorithm. For example, the Monte Carlo method (MCM) can be used to assess the uncertainty.

[0041] The present invention introduces novel structures such as adjustable angle, asymmetrical layout, and leeward installation, leading to the coupling of multiple errors, including transducer angle deviation, assembly error, and flow field disturbance, resulting in a measurement model exhibiting strong nonlinear characteristics. Without a scientific uncertainty assessment, it is impossible to quantify the impact range of various errors on wind speed and direction, determine the compliance of equipment data, and verify the actual disturbance reduction effect of the device structure.

[0042] Traditional error propagation methods (such as the GUM method) are only applicable to linear models, and may result in distortion or omissions when dealing with the nonlinear coupled calculation logic of this instrument. Based on the Monte Carlo method (MCM), which simulates the entire error propagation process according to the probability distribution of each input quantity, this method is adapted to nonlinear models and can comprehensively superimpose various errors such as transducer spacing, sound wave propagation time difference, assembly angle, on-site installation, and variable angle processing. It accurately quantifies the fluctuation range and confidence interval of wind measurement results and distinguishes between factory verification and field calibration scenarios, thus becoming the optimal choice for uncertainty assessment of this equipment.

[0043] In summary, the uncertainty assessment method for the angle-adjustable three-dimensional ultrasonic anemometer in the above embodiments of the present invention controls the transducer transceiver circuit of the angle-adjustable three-dimensional ultrasonic anemometer, causing each pair of transducers to alternately complete ultrasonic wave transmission and reception actions, detecting the ultrasonic wave flight time with and against the wind and the transducer spacing, and calculating the multi-directional wind speed components; combining the wind shadow area of ​​the anemometer and the error factors caused by airflow disturbance, an actual wind speed measurement model is constructed by adapting the horizontal wind speed theoretical model; simultaneously, combining the transducer angle and azimuth adjustment error and the installation azimuth angle correction error, an actual wind direction measurement model is constructed by adapting the horizontal wind direction theoretical model; the horizontal wind speed is calculated based on the multi-directional wind speed components, and accurate modeling calculation is completed by combining the actual wind speed and wind direction measurement models; finally, based on the established wind speed and wind direction measurement models, the overall uncertainty assessment result of the anemometer is output according to the preset uncertainty assessment algorithm. Customized transducer angles and orientations were designed to address the specific wind environment characteristics of the site, concentrating asymmetric environmental losses and enabling precise correction of differential errors across multiple transducer sets. The adjustable structural characteristics and working mechanism of the angle-adjustable 3D ultrasonic anemometer were thoroughly explored. The system systematically identified and quantified various core error influencing factors, including wind shadow and airflow disturbances, adjustable angle installation deviations, and asymmetric wind field losses. A refined wind speed and direction measurement model tailored to complex field conditions was constructed, effectively solving the technical challenges of traditional fixed-deployment anemometers failing to adapt to site wind field characteristics, exhibiting differential transducer measurement error distribution, and deviating evaluation results from actual measurement accuracy. This resulted in accurate and comprehensive evaluation of the measurement uncertainty of the angle-adjustable 3D ultrasonic anemometer, significantly improving the authenticity, accuracy, and reliability of anemometer uncertainty evaluation in complex field scenarios, and meeting the requirements for high-precision and high-stability field wind field monitoring.

[0044] Example 2 This embodiment also proposes an uncertainty evaluation method for a three-dimensional ultrasonic anemometer with adjustable included angle. The difference between the uncertainty evaluation method for the three-dimensional ultrasonic anemometer with adjustable included angle in this embodiment and the uncertainty evaluation method for the three-dimensional ultrasonic anemometer with adjustable included angle in Embodiment 1 is as follows: Obtain the model inputs and corresponding probability distribution functions of the wind speed measurement model and the wind direction measurement model, respectively; Randomly select sample values ​​generated by the probability distribution function of the model input to extract the experimental sample size for each model input; Discrete values ​​of the corresponding output quantities were calculated based on the wind speed measurement model and the wind direction measurement model, respectively, for the experimental sample size. The discrete values ​​of the output are sorted in non-decreasing order to obtain the distribution function of the sorted output, and the evaluation result of the measurement uncertainty of the anemometer is determined based on the discrete representation of the distribution function of the output.

[0045] The process involves processing and calculating the inputs to the wind speed and wind direction measurement models to ultimately determine the measurement uncertainty. Specifically, the process begins by acquiring all the inputs to both models and identifying their respective probability distribution functions. These inputs are key factors influencing the measurement results, and their probability distribution functions reflect their value patterns. Next, random sampling is performed based on these probability distribution functions to extract experimental sample sizes for each input. These sample sizes form the basis for subsequent calculations and simulate the possible values ​​of the inputs in actual measurements. Then, the extracted test sample size is substituted into the corresponding wind speed measurement model and wind direction measurement model for calculation, thereby obtaining the discrete values ​​of the output. These discrete values ​​reflect the possible situations of the measurement results under different combinations of input samples. Then, the obtained discrete output values ​​are sorted in non-decreasing order to obtain the sorted output distribution function. The discrete representation of this distribution function can reflect the overall distribution characteristics of the output. Finally, based on the discrete representation of this output distribution function, the uncertainty assessment results of the angle-adjustable three-dimensional ultrasonic anemometer in wind speed and wind direction measurement can be determined, thereby evaluating the reliability and accuracy of the measurement results.

[0046] Additionally, in some optional embodiments of the present invention, the elevation angle between the line connecting each pair of transducers and the horizontal plane... i 1. i 2. i 3 and the included angle between the projections of each pair of transducers onto the horizontal plane. α ,β , c The determination steps include: Collect basic wind field data at the site where the anemometer is deployed. The basic wind field data includes the long-term dominant wind direction of the site environment, the wind rose diagram data corresponding to the annual wind direction frequency distribution, and the site turbulence characteristic parameters. Based on the basic wind field data, the expected wind vector field of the site is constructed. With the goal of achieving the best wind vector detection accuracy, the matching criteria between the three detection channels and the expected wind vector field are determined. Based on the matching criteria and considering the influence of site turbulence characteristic parameters on the wind measurement error of the sound channel, the elevation angle between the line connecting each pair of transducers and the horizontal plane is iteratively solved. i 1. i 2. i 3, and the angle between the projections of the lines connecting each pair of transducers onto the horizontal plane. α , β , c This ensures that the direction of each detection channel achieves optimal matching with the expected wind vector field.

[0047] Specifically, the first step is to collect basic wind field data at the anemometer deployment site. This data includes at least three core types of information: the long-term dominant wind direction, the wind rose diagram data corresponding to the annual wind direction frequency distribution, and site turbulence characteristic parameters. The long-term dominant wind direction is obtained by statistically analyzing meteorological observation data from the site over several consecutive years. The wind direction with the longest cumulative occurrence time and the highest corresponding average wind speed is selected as the long-term dominant wind direction, which serves as the azimuth reference for subsequent channel orientation deployment. The wind rose diagram data corresponding to the annual wind direction frequency distribution includes the frequency of occurrence of each wind direction in 16 or 32 azimuth directions and the weight of each wind speed interval. This data can be obtained from the historical observation dataset of the local official meteorological station over the past five years, or it can be generated by statistically analyzing raw data collected continuously for at least twelve months using anemometers at the deployment site. Site turbulence characteristic parameters include three core types: turbulence intensity, turbulence integral scale, and wind direction fluctuation standard deviation. These parameters can be obtained by continuously collecting second-level wind speed data for at least one quarter using high-frequency ultrasonic anemometers at the site, and then calculating them through time-domain statistical analysis. For sites with complex terrain, the corresponding parameters can also be extracted through computational fluid dynamics simulation by combining terrain elevation data. The three types of wind field data together constitute all the input conditions for the subsequent angle optimization calculation. Secondly, based on the aforementioned wind field data, a site-expected wind vector field is constructed. With the goal of achieving optimal wind vector detection accuracy, matching criteria are determined for the three detection channels and the expected wind vector field. When constructing the site-expected wind vector field, the frequencies of each wind direction in the wind rose diagram data are used as weights, superimposed with the average wind speed and turbulent fluctuation characteristics under the corresponding wind direction. Typical values ​​for the vertical wind component are also introduced to form a three-dimensional wind vector distribution model covering the entire wind direction and speed range. The weights of different wind conditions in the model are positively correlated with their annual occurrence frequency, with the weight under the prevailing wind direction being significantly higher than other wind directions. The matching criteria use the overall accuracy of wind vector calculation as the core evaluation index. Specifically, it is set that the measurement error of the wind speed component along the channel axis is minimized under the prevailing wind direction with the highest weight, while the variance of the three-dimensional wind vector calculation error is minimized across the entire wind direction range. Vertical wind speed measurement accuracy constraints or measurement stability constraints under extreme wind speeds can also be added according to the actual needs of the site. The matching criteria provide a clear evaluation standard for the subsequent optimization of angle parameters, ensuring that the final angle parameters can fully adapt to the actual wind field characteristics of the site.

[0048] Based on the aforementioned matching criteria and considering the influence of site turbulence characteristic parameters on the sound channel wind measurement error, the elevation angles corresponding to the three sets of transducers are iteratively solved. i 1. i 2. i 3, and the included angles between each pair of projections of the lines connecting the three transducers onto the horizontal plane. α , β , c This ensures that the direction of each detection channel achieves optimal matching with the expected wind vector field.

[0049] For example, the solution process first establishes a channel wind measurement error analysis model, introducing site turbulence characteristic parameters into the model to quantitatively calculate the ultrasonic propagation time fluctuations caused by turbulence and the corresponding systematic and random errors in wind speed measurement under different channel orientations and elevation angle combinations. Then, using the accuracy index corresponding to the matching criterion as the optimization objective function, the three elevation angle parameters and the three horizontal projection angle parameters are set as independent variables to be optimized. Simultaneously, physical constraints on the angles are set: the elevation angle can be set from 10 degrees to 60 degrees, the sum of the three horizontal projection angles is 360 degrees, and the value of any single angle is not less than 60 degrees to avoid singularities in wind vector calculation caused by excessively close channel proximity. The optimization solution can be implemented using a genetic algorithm, particle swarm optimization algorithm, or gradient descent iterative algorithm. Through multiple iterations, the values ​​of the six angle parameters are continuously adjusted, and the objective function value corresponding to each set of parameters is calculated synchronously until the objective function converges to the global optimum. Finally, the elevation angle that meets the accuracy requirements is output. i 1. i 2. i 3 Angle with horizontal projection α , β , cThe obtained angle parameters can ensure the highest wind measurement resolution and accuracy under the prevailing wind direction, while also taking into account the measurement stability across the entire wind direction range. In a specific implementation of this invention, after solving for the elevation angle... i 1. i 2. i 3 Angle with horizontal projection α , β , c Three sets of transducers can be oriented accordingly, precisely aligning the long-term prevailing wind direction with a specific detection channel among the three sets of transducers. Before deployment, transducer mounting brackets are custom-made based on the calculated angle parameters, with the brackets pre-reserved for the corresponding elevation angle installation positioning surface and horizontal azimuth adjustment structure. During on-site deployment, the actual azimuth of the long-term prevailing wind direction is first determined using a compass or satellite positioning equipment. Using this azimuth as a reference, the horizontal installation positions of the three sets of transducers are marked sequentially according to the calculated horizontal projection angle. Then, the vertical installation tilt angle of each set of transducers is adjusted according to the corresponding elevation angle. During deployment, the detection channel with the highest overlap with the long-term prevailing wind direction is selected as the specific detection channel. The horizontal projection direction of this channel is calibrated to ensure complete overlap with the azimuth of the long-term prevailing wind direction, achieving precise alignment of the long-term prevailing wind direction with the specific detection channel. Adjust the placement and orientation of the remaining two transducers and their supporting brackets to ensure they are all positioned on the leeward side of the prevailing wind direction, thus completing the customized layout of the spatial angles and orientations of the three transducers. After fixing the orientation of the specific detection channel, using the direction of the prevailing wind as a reference, place the remaining two transducers and their supporting brackets in the leeward area of ​​the specific detection channel. Simultaneously adjust the installation orientation and height of the two transducers to ensure that the channel direction strictly matches the calculated elevation and horizontal projection angle parameters. At the same time, ensure that the main structure and support brackets of both transducers are within the wake shielding range of the prevailing wind direction, avoiding direct impact from the high-speed flow. After completing the positioning calibration and mechanical fixing of all transducers, the customized layout process for the spatial angles and orientations of all three transducers is complete. Through the customized layout of the aforementioned angles and orientations, the high-speed incoming flow from the prevailing wind direction directly acts only on the transducer assembly corresponding to the specific detection channel aligned with the wind direction. Asymmetric losses such as particle erosion, structural vibration fatigue, and diurnal temperature variation deformation carried by the wind field are concentrated on this single assembly. This assembly can be designed as a modular, replaceable structure for easy and rapid replacement during later maintenance. The other two sets of detection channels on the leeward side experience significantly reduced incoming wind speed and turbulence intensity acting on the transducer surface due to the shielding effect of the components in front. This results in a substantial decrease in the erosion rate of the transducer surface, a marked slowdown in the accumulation of structural fatigue, and a corresponding reduction in the amplitude of temperature variation deformation. Therefore, it can maintain high-precision detection performance and stable structural operation over a long period, effectively extending the overall high-precision service life of the system and reducing the comprehensive cost of long-term maintenance.

[0050] For example, we take the basic wind field data of a coastal monsoon region as an example (the prevailing wind direction is northeast, the annual occurrence frequency is >60%, and the turbulence intensity is about 0.1) and perform iterative optimization to solve the problem.

[0051] Among them, with the goal of minimizing the measurement error of the prevailing wind direction and the comprehensive calculation error of the entire wind direction, under the physical constraints of an elevation angle of 10°~60° and a horizontal angle of 360° with each angle ≥60°, the following optimal angle parameters are obtained after iterative convergence by the particle swarm algorithm.

[0052] Specifically, the prevailing wind direction is stable (annual frequency >60%), and is northeasterly (wind direction angle π / 8). The optimization objective is to minimize the measurement error of the prevailing wind direction and the variance of the overall wind direction measurement. The quantified objective function is as follows:

[0053] In the formula: j The objective function is to optimize the whole; w1 and w2 are weighting coefficients, with w1=0.7 and w2=0.3, to prioritize the accuracy of the prevailing wind direction measurement. e main The system error in measuring the wind speed component of the lower channel under the prevailing wind. s all The variance of the three-dimensional wind vector solution for the entire wind direction range; constraints: the sum of the angles of the three sets of horizontal projections is 360°, and physical boundaries are set for the elevation angle and horizontal angle of each set to avoid geometric singularities of the sound channel.

[0054] Basic wind field data for this site were collected: the long-term prevailing wind direction is northeast (wind angle π / 8), the annual frequency of northeast wind is 62%, the site turbulence intensity is 0.12, and the turbulence integral scale is 12 m. These wind field parameters and the objective function were substituted into a particle swarm optimization algorithm. After multiple iterations and convergence, the optimal geometric angle parameters were output. The angle between the lines connecting the three transducer sets and the horizontal plane is... i1= i 2= i 3 = 60°; the angle between any two points in the horizontal projection: α =135° β =135° c =90°, which satisfies the condition. α + β + c =360° constraint.

[0055] In summary, the uncertainty assessment method for the angle-adjustable three-dimensional ultrasonic anemometer in the above embodiments of the present invention controls the transducer transceiver circuit of the angle-adjustable three-dimensional ultrasonic anemometer, causing each pair of transducers to alternately complete ultrasonic wave transmission and reception actions, detecting the ultrasonic wave flight time with and against the wind and the transducer spacing, and calculating the multi-directional wind speed components; combining the wind shadow area of ​​the anemometer and the error factors caused by airflow disturbance, an actual wind speed measurement model is constructed by adapting the horizontal wind speed theoretical model; simultaneously, combining the transducer angle and azimuth adjustment error and the installation azimuth angle correction error, an actual wind direction measurement model is constructed by adapting the horizontal wind direction theoretical model; the horizontal wind speed is calculated based on the multi-directional wind speed components, and accurate modeling calculation is completed by combining the actual wind speed and wind direction measurement models; finally, based on the established wind speed and wind direction measurement models, the overall uncertainty assessment result of the anemometer is output according to the preset uncertainty assessment algorithm. Customized transducer angles and orientations were designed to address the specific wind environment characteristics of the site, concentrating asymmetric environmental losses and enabling precise correction of differential errors across multiple transducer sets. The adjustable structural characteristics and working mechanism of the angle-adjustable 3D ultrasonic anemometer were thoroughly explored. The system systematically identified and quantified various core error influencing factors, including wind shadow and airflow disturbances, adjustable angle installation deviations, and asymmetric wind field losses. A refined wind speed and direction measurement model tailored to complex field conditions was constructed, effectively solving the technical challenges of traditional fixed-deployment anemometers failing to adapt to site wind field characteristics, exhibiting differential transducer measurement error distribution, and deviating evaluation results from actual measurement accuracy. This resulted in accurate and comprehensive evaluation of the measurement uncertainty of the angle-adjustable 3D ultrasonic anemometer, significantly improving the authenticity, accuracy, and reliability of anemometer uncertainty evaluation in complex field scenarios, and meeting the requirements for high-precision and high-stability field wind field monitoring.

[0056] Example 3 Please see Figure 6 The figure shows an uncertainty assessment device for a three-dimensional ultrasonic anemometer with adjustable included angle proposed in the third embodiment of the present invention. The device includes: The acquisition module 100 is used to control the transceiver circuit of the anemometer, so that each pair of transceivers in the anemometer will transmit and receive ultrasonic waves in sequence. By measuring the flight time of the ultrasonic waves in the headwind and headwind and the distance between each pair of transceivers, the wind speed components in different directions are obtained. The correction module 200 is used to obtain the actual wind speed measurement model by combining the horizontal wind speed theoretical model with the error introduced by the wind shadow area and airflow disturbance generated by the anemometer, and to obtain the actual wind direction measurement model by combining the error introduced by the transducer angle and azimuth adjustment of the anemometer and the error when correcting the installation azimuth angle with the horizontal wind direction theoretical model. Calculation module 300 is used to determine different horizontal wind speeds based on wind speed components in different directions. and Based on horizontal wind speed and The wind speed measurement model and the wind direction measurement model were calculated by comparing them with the actual wind speed measurement model and the actual wind direction measurement model, respectively. The measurement module 400 is used to obtain the uncertainty assessment results of the anemometer based on the wind speed measurement model and the wind direction measurement model of the anemometer using a preset uncertainty assessment algorithm.

[0057] The functions or operation steps implemented by the above modules are largely the same as those in the above method embodiments, and will not be repeated here.

[0058] Example 4 In another aspect, the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the method described in any one of Embodiments 1 to 2 above.

[0059] Example 5 In another aspect, the present invention provides an electronic device, the electronic device including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of any one of the methods described in Embodiments 1 to 2 above.

[0060] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0061] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable storage medium" can mean any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0062] More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable storage media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0063] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0064] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0065] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method for evaluating the uncertainty of a three-dimensional ultrasonic anemometer with adjustable included angle, characterized in that, The method includes: The transducer transceiver circuit in the anemometer is controlled so that each pair of transducers in the anemometer transmits and receives ultrasonic waves in sequence. By measuring the flight time of the ultrasonic waves in the headwind and headwind and the distance between each pair of transducers, the wind speed components in different directions are obtained. Based on the wind shadow zone and airflow disturbance introduced by the anemometer, the actual wind speed measurement model is obtained by combining the horizontal wind speed theoretical model. Based on the errors introduced by the anemometer's transducer angle and azimuth adjustment and the error during installation azimuth correction, the actual wind direction measurement model is obtained by combining the horizontal wind direction theoretical model. Different horizontal wind speeds are determined according to wind speed components in different directions With , based on the horizontal wind speed With The wind speed measurement model and the wind direction measurement model are calculated respectively with the wind speed actual measurement model and the wind direction actual measurement model. The uncertainty assessment results of the anemometer are obtained by using a preset uncertainty assessment algorithm based on the wind speed measurement model and the wind direction measurement model of the anemometer.

2. The uncertainty evaluation method for the three-dimensional ultrasonic anemometer with adjustable included angle according to claim 1, characterized in that, The anemometer includes three pairs of transducers, namely transducers... and transducer 、 transducer and transducer and transducers and transducer The step of obtaining wind speed components in different directions by measuring the flight time of ultrasonic waves in headwinds and headwinds, as well as the distance between each pair of transducers, includes: By measuring the flight time of the ultrasonic waves in both headwind and tailwind conditions, as well as the spacing between each pair of transducers, the wind speed component along the line connecting each pair of transducers is obtained. v 1. v 2. v 3; in: ； ； ； In the formula, For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind; For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind; For transducers to transducer distance, For transducers and transducer Tailwind flight time, For transducers and transducer The time spent flying against the wind.

3. The uncertainty evaluation method for the three-dimensional ultrasonic anemometer with adjustable included angle according to claim 2, characterized in that, The expression for the actual wind speed measurement model is: ; in, λ The correction factor is used to address the errors introduced by the wind shadow zone and airflow disturbances generated by the anemometer. and For different horizontal wind speeds.

4. The uncertainty evaluation method for the three-dimensional ultrasonic anemometer with adjustable included angle according to claim 3, characterized in that, The expression for the actual wind direction measurement model is: ; in, The correction coefficients are used to address the errors introduced by the transducer angle and azimuth adjustment of the anemometer. For the installation azimuth correction amount, This refers to the correction factor corresponding to the error when correcting the installation azimuth angle. and For different horizontal wind speeds.

5. The uncertainty evaluation method for the three-dimensional ultrasonic anemometer with adjustable included angle according to claim 4, characterized in that, Different horizontal wind speeds are determined based on the wind speed components in different directions. and The calculation process is as follows: ； ； in, v 1. v 2. v 3 represents the wind speed component along the connection line of each pair of transducers; θ 1. θ 2. θ 3 represents the elevation angle between the line connecting each pair of transducers and the horizontal plane; α , β It is the angle between the projections of two pairs of transducers onto the horizontal plane.

6. The uncertainty evaluation method for the three-dimensional ultrasonic anemometer with adjustable included angle according to claim 5, characterized in that, The angle of elevation between the line connecting each pair of transducers and the horizontal plane θ 1. θ 2. θ 3 and the included angle between the projections of each pair of transducers onto the horizontal plane. α , β , γ The determination steps include: Collect basic wind field data at the site where the anemometer is deployed. The basic wind field data includes the long-term dominant wind direction of the site environment, the wind rose diagram data corresponding to the annual wind direction frequency distribution, and the site turbulence characteristic parameters. Based on the basic wind field data, the expected wind vector field of the site is constructed. With the goal of achieving the best wind vector detection accuracy, the matching criteria between the three detection channels and the expected wind vector field are determined. Based on the matching criteria and considering the influence of site turbulence characteristic parameters on the wind measurement error of the sound channel, the elevation angle between the line connecting each pair of transducers and the horizontal plane is iteratively solved. θ 1. θ 2. θ 3, and the angle between the projections of the lines connecting each pair of transducers onto the horizontal plane. α , β , γ This ensures that the direction of each detection channel achieves optimal matching with the expected wind vector field.

7. The uncertainty evaluation method for the three-dimensional ultrasonic anemometer with adjustable included angle according to claim 1, characterized in that, The steps of obtaining the uncertainty assessment results of the anemometer based on the wind speed measurement model and the wind direction measurement model of the anemometer using a preset uncertainty assessment algorithm include: Obtain the model inputs and corresponding probability distribution functions of the wind speed measurement model and the wind direction measurement model, respectively; Randomly select sample values ​​generated by the probability distribution function of the model input to extract the experimental sample size for each model input; Discrete values ​​of the corresponding output quantities were calculated based on the wind speed measurement model and the wind direction measurement model, respectively, for the experimental sample size. The discrete values ​​of the output are sorted in non-decreasing order to obtain the distribution function of the sorted output, and the evaluation result of the measurement uncertainty of the anemometer is determined based on the discrete representation of the distribution function of the output.

8. An uncertainty assessment device for a three-dimensional ultrasonic anemometer with adjustable included angle, characterized in that, The device includes: The acquisition module is used to control the transceiver circuit of the anemometer, so that each pair of transceivers in the anemometer will transmit and receive ultrasonic waves in sequence. By measuring the flight time of the ultrasonic waves in the headwind and headwind and the distance between each pair of transceivers, the wind speed components in different directions are obtained. The correction module is used to obtain the actual wind speed measurement model by combining the horizontal wind speed theoretical model with the error introduced by the wind shadow area and airflow disturbance generated by the anemometer, and to obtain the actual wind direction measurement model by combining the error introduced by the transducer angle and azimuth adjustment of the anemometer and the error when correcting the installation azimuth angle with the horizontal wind direction theoretical model. The calculation module is used to determine different horizontal wind speeds based on the wind speed components in different directions. and Based on horizontal wind speed and The wind speed measurement model and the wind direction measurement model were calculated by comparing them with the actual wind speed measurement model and the actual wind direction measurement model, respectively. The measurement module is used to obtain the uncertainty assessment results of the anemometer based on the wind speed measurement model and the wind direction measurement model of the anemometer, respectively, using a preset uncertainty assessment algorithm.

9. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor, when executing the program, implements the steps of the method as described in any one of claims 1 to 7.

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