KR102665538B1 - Floating wind condition measuring device, control method thereof, computer-readable storage medium, computer program and monitoring system using the same - Google Patents

Abstract

The present invention is provided on one side of a sea buoy to generate wind data, measure the movement of the sea buoy to generate motion data, correct the wind data using the motion data, and filter out mismeasurement data from the corrected wind data to determine the wind condition. Provides a floating wind measurement device that purifies data.

Description

Floating wind condition measuring device, its control method, computer-readable recording medium, computer program, and monitoring system using the same

The present invention relates to a floating wind measurement device, a control method thereof, a computer-readable recording medium, a computer program, and a monitoring system using the same. More specifically, a floating wind measurement device in which a sea buoy is provided to measure wind conditions at sea. It relates to a device, a control method thereof, a computer-readable recording medium, a computer program, and a monitoring system using the same.

In general, a buoy is a device that floats on the sea to indicate navigation within the port's controlled waters or to indicate dangerous areas. In this way, the buoy is formed to have a specific color or shape to enable identification during the day, and is formed by adding lighting to enable identification at night.

In addition, in response to the need for efficient use of buoys, buoys with various functions, in addition to the above-described navigational route indication and danger zone display functions, have been recently developed and operated. In particular, the Korea Meteorological Administration and the Ministry of Oceans and Fisheries operate marine observation buoys to observe marine weather and collect environmental information. These marine observation buoys are constructed with expensive equipment such as wind direction and speed sensors, and superstructures.

However, conventional marine observation buoys may be shaken by weather phenomena such as wind or waves, causing errors in the observed information. The errors generated in this way have a negative impact on the purpose for which marine observation buoys are installed, and accordingly, a method to correct the shaking of the buoy due to meteorological phenomena is required.

Domestic registered patent No. 10-1633812 (2016.06.21.)

The technical problem to be solved by the present invention is to provide a floating wind measurement device that detects the movement of a sea buoy and corrects the wind condition measured through LiDAR, a control method thereof, a computer-readable recording medium, a computer program, and a monitoring system using the same. It is provided.

One aspect of the present invention is a LiDAR module provided on one side of an offshore buoy to generate wind data; A motion detection module that generates motion data by measuring movement of the sea buoy; and a control module that corrects the wind condition data using the motion data and refines the wind condition data by filtering erroneous data from the corrected wind condition data.

In addition, the LiDAR module is a first LiDAR that emits one wavelength and generates first wind condition data based on the wavelength reflected by particles in the atmosphere; And a second LIDAR that emits a plurality of different wavelengths and generates second wind condition data based on the wavelengths reflected by particles in the atmosphere.

In addition, the control module determines a correlation between the first wind condition data and the second wind condition data, and determines the mismeasurement data among the first wind condition data and the second wind condition data based on the correlation, The determined erroneous data can be removed from the first wind data and the second wind data, and the refined wind data can be generated based on the first wind data and the second wind data from which the incorrect data has been removed. .

Additionally, the control module may calculate a change in inclination of the sea buoy from the motion data and compensate for the wind data based on the calculated change in inclination.

Additionally, the motion detection module may include a gyro sensor that generates motion data by measuring the rotation of the sea buoy.

In addition, the LIDAR module can measure a point cloud at preset time periods and generate the wind data so that at least one of wind speed and wind direction appears based on changes in a plurality of point clouds measured at different time points. there is.

In addition, a position measurement module that measures the position of the sea buoy; An image recording module that generates image data by monitoring objects existing around the sea buoy; and a communication module that transmits at least one of the motion data, the refined wind data, the location data, and the image data to a preset control server.

Another aspect of the present invention includes the steps of providing a LiDAR module on one side of an offshore buoy to generate wind condition data; Generating motion data by measuring movement of the sea buoy; correcting the wind condition data using the motion data; and refining the wind condition data by filtering mismeasured data from the corrected wind condition data.

In addition, the LiDAR module is a first LiDAR that emits one wavelength and generates first wind condition data based on the wavelength reflected by particles in the atmosphere; And a second LIDAR that emits a plurality of different wavelengths and generates second wind condition data based on the wavelengths reflected by particles in the atmosphere.

In addition, the step of refining the wind condition data includes determining a correlation between the first wind condition data and the second wind condition data; determining the incorrect data from the first wind data and the second wind data based on the correlation, and removing the determined incorrect data from the first wind data and the second wind data; and generating the refined wind condition data based on the first wind condition data and the second wind condition data from which the erroneous data has been removed.

In addition, the step of correcting the wind condition data may include calculating a change in inclination of the sea buoy from the motion data and compensating for the wind condition data based on the calculated change in inclination.

Additionally, in the step of generating the motion data, a gyro sensor may generate motion data by measuring the rotation of the sea buoy.

In addition, the step of generating the wind situation data includes measuring a point cloud at preset time periods, and generating the wind situation data so that at least one of wind speed and wind direction appears based on changes in a plurality of point clouds measured at different time points. can be created.

Additionally, measuring position data of the sea buoy; Generating image data by monitoring objects existing around the sea buoy; and transmitting at least one of the motion data, the refined wind data, the location data, and the image data to a preset control server.

Another aspect of the present invention is a computer-readable recording medium storing a computer program, which, when executed by a processor, includes the following steps: a LiDAR module is provided on one side of a sea buoy to generate wind condition data; Generating motion data by measuring movement of the sea buoy; correcting the wind condition data using the motion data; and filtering erroneous data from the corrected wind condition data to purify the wind condition data. The method may include instructions for causing the processor to perform the method including.

Another aspect of the present invention is a computer program stored in a computer-readable recording medium, which, when executed by a processor, includes the following steps: a LiDAR module is provided on one side of a sea buoy to generate wind condition data; Generating motion data by measuring movement of the sea buoy; correcting the wind condition data using the motion data; and filtering erroneous data from the corrected wind condition data to purify the wind condition data. The method may include instructions for causing the processor to perform the method including.

Another aspect of the present invention is that a LiDAR module is provided on one side of a sea buoy to generate wind data, measure the movement of the sea buoy to generate motion data, and correct the wind data using the motion data. and a floating wind measurement device that purifies the wind condition data by filtering mismeasurement data from the corrected wind condition data; and a control server that receives the refined wind data and generates monitoring data.

According to one aspect of the present invention described above, by providing a floating wind measurement device, a control method thereof, a computer-readable recording medium, a computer program, and a monitoring system using the same, the movement of a sea buoy is detected and measured through lidar. Wind conditions can be corrected.

Figure 1 shows a monitoring system according to an embodiment of the present invention.
Figure 2 is a block diagram of a floating wind measurement device according to an embodiment of the present invention.
Figure 3 is a block diagram showing the process by which the control module of Figure 2 corrects wind data generated from multiple LIDARs.
Figure 4 is a detailed block diagram of the floating wind measurement device of Figure 2.
Figure 5 is a flowchart of a control method of a floating wind measurement device according to an embodiment of the present invention.

The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. The present embodiments are merely provided to ensure that the disclosure of the present invention is complete and to be understood by those skilled in the art in the technical field to which the present invention pertains. It is provided to fully inform those who have the scope of the invention, and the present invention is only defined by the scope of the claims.

In describing embodiments of the present invention, if a detailed description of a known function or configuration is judged to unnecessarily obscure the gist of the present invention, the detailed description will be omitted. The terms described below are defined in consideration of functions in the embodiments of the present invention, and may vary depending on the intention or custom of the user or operator. Therefore, the definition should be made based on the contents throughout this specification.

Figure 1 shows a monitoring system according to an embodiment of the present invention.

Referring to FIG. 1, the monitoring system 1 may include a floating wind measurement device 10, a control server 20, and a display device 30.

The floating wind measurement device 10 may be provided on one side of the sea buoy 19 to generate wind condition data. At this time, the floating wind measurement device 10 may be installed at any point on the sea. Through this, the floating wind condition measuring device 10 can generate wind condition data at the point where the floating wind measuring device 10 is installed. That is, the floating wind measurement device 10 may generate wind data in a predetermined direction or generate wind data for a point adjacent to the point where the floating wind measurement device 10 is installed.

The control server 20 may receive wind condition data generated by the floating wind condition measurement device 10. Accordingly, the control server 20 may store the delivered wind condition data and generate monitoring data based on the stored wind condition data.

Accordingly, the display device 30 can output monitoring data delivered from the control server 20.

Meanwhile, Figure 2 is a block diagram of a floating wind measurement device according to an embodiment of the present invention.

Referring to FIG. 2, the floating wind measurement device 10 may include a LiDAR module 11, a motion detection module 12, and a control module 13.

The LiDAR module 11 is provided on one side of the sea buoy 19 and can generate wind condition data. Here, wind data may include at least one of wind speed and wind direction.

To this end, the LiDAR module 11 can emit a laser beam and observe a beam reflected or scattered from particles in the atmosphere, or observe light scattered by fine particles in the atmosphere.

Through this, the LIDAR module 11 can generate a point cloud by analyzing the observed beam or light waveform. Here, the point cloud includes multiple points, and each point may include information such as distance, height, and direction for particles in the air.

To this end, the LIDAR module 11 may generate points based on the time interval from the time of emitting the beam to the time of receiving the reflected beam, the frequency or phase difference between the emitted beam and the reflected beam, etc.

At this time, the LIDAR module 11 can measure the point cloud at every preset time period and record the time when the point cloud was measured.

Accordingly, the LIDAR module 11 collects wind data using the change in position of points appearing from the point cloud observed at one point in time and the point cloud observed at another point in time, the changed angle, the time interval at which the point cloud was observed, etc. can be created.

Meanwhile, the LiDAR module 11 may include multiple LiDARs. In this case, the LiDAR module 11 can control each LiDAR to generate wind condition data.

In this regard, FIG. 3 is a block diagram showing a process in which the control module of FIG. 2 corrects wind data generated from multiple LIDARs.

Referring to FIG. 3, the LiDAR module 11 may include a first LiDAR 11a and a second LiDAR 11b.

At this time, the first LIDAR 11a and the second LIDAR 11b may generate wind data in the same way or generate wind data in different ways.

In one embodiment, the first LIDAR (11a) generates first wind data by the Homodyne method, and the second LIDAR (11b) generates the second wind data by the Heterodyne method. You can.

Specifically, the first LIDAR 11a may emit one wavelength and generate first wind condition data based on the wavelength reflected by particles in the atmosphere. Additionally, the second LIDAR 11b can emit a plurality of different wavelengths and generate second wind condition data based on the wavelengths reflected by particles in the atmosphere.

At this time, the first LIDAR 11a and the second LIDAR 11b may generate wind data for the same point or generate wind data for points adjacent to each other. Accordingly, the first wind condition data and the second wind condition data may be measurements of the same wind condition using different measurement methods.

Meanwhile, the motion detection module 12 can generate motion data by measuring the movement of the sea buoy 19. Here, the movement of the sea buoy 19 may mean at least one of rotation and movement of the sea buoy 19.

In one embodiment, motion detection module 12 may include a gyro sensor. In this case, the gyro sensor can measure the rotation of the marine buoy 19 to generate motion data.

At this time, the gyro sensor can measure rotation about three axes. Accordingly, the motion data may represent the rotation angle and direction of the marine buoy 19 according to a preset time period.

In this regard, the motion detection module 12 may further include an acceleration sensor. At this time, an acceleration sensor may be installed to measure the rotational speed of the marine buoy 19. Accordingly, the motion detection module 12 can correct the rotation angle measured by the gyro sensor using the rotation speed measured by the acceleration sensor.

Through this, the motion detection module 12 can accurately measure the movement of the sea buoy 19.

The control module 13 can correct wind condition data using motion data. To this end, the control module 13 may calculate the change in inclination of the sea buoy 19 from the motion data and compensate for the wind condition data based on the calculated change in inclination.

Here, the tilt change may mean at least one of the rotation angle and rotation direction during a preset time period. Accordingly, the control module 13 may extract at least one of the rotation angle and rotation direction during a preset time period from the motion data to calculate the change in inclination of the sea buoy 19.

At this time, the time period for the slope change may be set to be the same as the time period for generating wind data in the LiDAR module 11.

In other words, the control module 13 may calculate a slope change during the same time interval for wind data according to the point cloud observed at two different viewpoints, and compensate for the wind data using the calculated slope change.

In one embodiment, the control module 13 may represent wind data as a vector according to wind direction and wind speed, and may represent the change in slope as a vector according to rotation direction and rotation angle. Accordingly, the control module 13 can generate corrected wind data by adding or subtracting vectors according to the rotation direction and rotation angle from vectors according to the wind direction and wind speed.

At this time, the control module 13 may perform corrections for the first wind condition data and the second wind condition data, respectively.

The control module 13 may purify the wind condition data by filtering mismeasured data from the corrected wind condition data. That is, the control module 13 can generate refined wind condition data by removing erroneous data from the corrected wind condition data. To this end, the control module 13 may determine the correlation between the first wind condition data and the second wind condition data.

Here, determining the correlation can be understood as setting a normal range for the first wind condition data and the second wind condition data based on the correlation between the first wind condition data and the second wind condition data.

In one embodiment, the control module 13 may calculate the average value of a plurality of first wind condition data and second wind condition data generated during a preset period, and set a normal range according to a preset ratio from the calculated average value. there is.

At this time, the preset period may be set based on the season, date, etc. when wind conditions change. For example, the preset period may be set at three-month intervals so that a different normal range appears for each season.

In another embodiment, the control module 13 may perform regression analysis using a plurality of first wind condition data and second wind condition data generated during a preset period.

Here, regression analysis may be a mathematical technique that determines the relationship between the independent variable and the dependent variable so that the dependent variable changes according to the change in the independent variable.

Accordingly, the control module 13 may set one of the first wind condition data and the second wind condition data as a dependent variable and set the other one as an independent variable. Accordingly, the control module 13 can calculate a relational expression by performing regression analysis on the dependent variable and the independent variable.

Through this, the control module 13 can set the normal range according to a preset ratio from the calculated relational expression.

The control module 13 may determine erroneous data from the first wind condition data and the second wind condition data based on the correlation, and remove the erroneous data determined from the first wind condition data and the second wind condition data.

At this time, the control module 13 may determine a value outside the normal range among the first wind condition data and the second wind condition data as mismeasurement data. Accordingly, the control module 13 may remove the value determined as erroneous data among the first wind condition data and the second wind condition data.

Accordingly, the first wind condition data and the second wind condition data from which erroneous data have been removed may include only values within the normal range.

The control module 13 may generate refined wind condition data based on the first wind condition data and the second wind condition data from which erroneous data has been removed.

In one embodiment, the control module 13 may generate refined wind condition data by extracting the value closest to the center value of the normal range from the first wind condition data and the second wind condition data measured within a preset time range.

In other words, the control module 13 may remove a value that has a larger difference from the center value of the normal range among the first wind condition data and the second wind condition data measured within a preset time range.

Here, the preset time range may be a time period for the refined wind data. Accordingly, the control module 13 may set the other value as the refined wind condition data when one of the first wind condition data and the second wind condition data is empty within a preset time range.

In another embodiment, the control module 13 extracts the other value when one of the first wind condition data and the second wind condition data is empty within a preset time range, and extracts the other value within the preset time range. When both the first wind condition data and the second wind condition data exist, a preset type of value from the first wind condition data and the second wind condition data can be extracted to generate refined wind condition data.

Meanwhile, Figure 4 is a detailed block diagram of the floating wind condition measuring device of Figure 2.

Referring to FIG. 4, the floating wind measurement device 10 may further include a power module 14, a position measurement module 15, an image recording module 16, a storage module 17, and a communication module 18. You can.

The power module 14 produces and stores power, and includes a lidar module 11, a motion detection module 12, a control module 13, a position measurement module 15, an image recording module 16, and a storage module ( Power may be supplied to at least one of the 17) and communication module 18.

To this end, the power module 14 may produce power through at least one of wind power generation and solar power generation. Accordingly, the power module 14 may include a battery to store the produced power.

The position measurement module 15 can measure the position of the sea buoy. For this purpose, the position measurement module 15 may use a global positioning system (GPS) that receives position data from at least one satellite or at least one satellite and a ground observatory.

The image recording module 16 can generate image data by monitoring objects existing around the sea buoy. To this end, the video recording module 16 may include a camera that captures a video or image.

The storage module 17 may store at least one of wind condition data, motion data, correlation calculated by the control module 13, refined wind condition data, location data, and image data.

The communication module 18 sends at least one of the wind condition data stored in the storage module 17, motion data, correlation calculated from the control module 13, refined wind condition data, location data, and image data to the control server 20. It can be delivered.

Referring again to FIG. 1, the control server 20 receives at least one of wind condition data, motion data, correlation calculated by the control module 13, refined wind condition data, location data, and image data from the communication module 18. It can be delivered.

Accordingly, the control server 20 may store at least one of the transmitted wind condition data, motion data, correlation calculated by the control module 13, refined wind condition data, location data, and image data.

In addition, the control server 20 monitors data based on at least one of wind data, motion data, correlation calculated by the control module 13, refined wind data, location data, and image data stored in the control server 20. may be generated, and the generated monitoring data may be transmitted to the display device 30.

Accordingly, the display device 30 can output monitoring data delivered from the control server 20.

Meanwhile, the control server 20 may receive a control command from the user and generate monitoring data based on the input control command.

At this time, the control command is a command to select at least one of wind condition data, motion data, correlation calculated in the control module 13, refined wind condition data, location data, and image data, wind condition data, motion data, and control module 13 ) may include a command for selecting the time or period at which at least one of the correlation calculated from, refined wind data, location data, and image data was recorded, a command for determining how the monitoring data is output, etc.

Figure 5 is a flowchart of a control method of a floating wind measurement device according to an embodiment of the present invention.

Referring to FIGS. 1, 2, and 5, the LiDAR module 11 is provided on one side of an offshore buoy to generate wind data (S100).

The motion detection module 12 may generate motion data by measuring the rotation of the sea buoy (S200).

The control module 13 may correct the wind data using motion data (S300).

The control module 13 may purify the wind condition data by filtering the erroneous data (S400).

Various embodiments of the present document are software (e.g., instructions stored in a machine-readable storage media (e.g., memory (built-in memory or external memory)) that can be read by a machine (e.g., a computer). : program). The device is a device capable of calling instructions stored in a storage medium and operating according to the called instructions, and may include an electronic device (eg, device) according to the disclosed embodiments. When the instruction is executed by a processor (eg, a processor), the processor may perform the function corresponding to the instruction directly or using other components under the control of the processor. Instructions may contain code generated or executed by a compiler or interpreter. A storage medium that can be read by a device may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' only means that the storage medium does not contain signals and is tangible, and does not distinguish whether the data is stored semi-permanently or temporarily in the storage medium.

According to one embodiment, methods according to various embodiments disclosed in this document may be provided and included in a computer program product.

The above description is merely an illustrative explanation of the technical idea of the present invention, and those skilled in the art will be able to make various modifications and variations without departing from the essential quality of the present invention. Accordingly, the embodiments disclosed in the present invention are not intended to limit the technical idea of the present invention, but are for illustrative purposes, and the scope of the technical idea of the present invention is not limited by these embodiments. The scope of protection of the present invention shall be interpreted in accordance with the claims below, and all technical ideas within the scope equivalent thereto shall be construed as being included in the scope of rights of the present invention.

1: Monitoring system
10: Floating wind measurement device
19: Marine buoy
20: Control server
30: display device

Claims (17)

A LiDAR module installed on one side of an offshore buoy to generate wind data;
A motion detection module that generates motion data by measuring movement of the sea buoy; and
A control module that corrects the wind condition data using the motion data and filters mismeasurement data from the corrected wind condition data to purify the wind condition data,
The lidar module is,
A first LIDAR that emits one wavelength and generates first wind condition data based on the wavelength reflected by particles in the atmosphere; and
A second LIDAR that emits a plurality of different wavelengths and generates second wind condition data based on the wavelengths reflected by particles in the atmosphere,
The control module is,
Determine the degree of correlation between the first wind state data and the second wind state data, determine the mismeasurement data among the first wind state data and the second wind state data based on the correlation, and determine the first wind state data and the second wind state data. A floating wind measurement device that removes the determined erroneous data from the second wind condition data and generates the refined wind condition data based on the first wind condition data and the second wind condition data from which the erroneous data was removed.
delete delete The method of claim 1, wherein the control module:
A floating wind measurement device that calculates a change in inclination of the sea buoy from the motion data and compensates for the wind condition data based on the calculated change in inclination.
The method of claim 1, wherein the motion detection module:
A floating wind measurement device comprising a gyro sensor that measures rotation of the sea buoy and generates motion data.
The method of claim 1, wherein the lidar module,
A floating wind measurement device that measures a point cloud at preset time periods and generates wind data to indicate at least one of wind speed and wind direction based on changes in a plurality of point clouds measured at different time points.
According to claim 1,
A position measurement module that measures position data of the sea buoy;
An image recording module that generates image data by monitoring objects existing around the sea buoy; and
A communication module configured to transmit at least one of the motion data, the refined wind data, the location data, and the image data to a preset control server. Floating wind measuring device further comprising a.
A LiDAR module is provided on one side of a sea buoy to generate wind data;
Generating motion data by measuring movement of the sea buoy;
correcting the wind condition data using the motion data; and
Comprising: filtering out erroneous data from the corrected wind condition data to purify the wind condition data,
The lidar module is,
A first LIDAR that emits one wavelength and generates first wind condition data based on the wavelength reflected by particles in the atmosphere; and
A second LIDAR that emits a plurality of different wavelengths and generates second wind condition data based on the wavelengths reflected by particles in the atmosphere,
The step of refining the wind data is,
determining a correlation between the first wind condition data and the second wind condition data;
determining the incorrect data from the first wind data and the second wind data based on the correlation, and removing the determined incorrect data from the first wind data and the second wind data; and
Generating the refined wind condition data based on the first wind condition data and the second wind condition data from which the erroneous data has been removed; A control method of a floating wind condition measuring device comprising a.
delete delete The method of claim 8, wherein the step of correcting the wind data is,
A control method for a floating wind measurement device, calculating a change in inclination of the sea buoy from the motion data and compensating for the wind condition data based on the calculated change in inclination.
The method of claim 8, wherein generating the motion data comprises:
A control method for a floating wind measurement device in which a gyro sensor measures the rotation of the sea buoy and generates motion data.
The method of claim 8, wherein the step of generating wind data is:
A control method of a floating wind measurement device, measuring a point cloud at preset time periods and generating the wind data to indicate at least one of wind speed and wind direction based on changes in a plurality of point clouds measured at different time points. .
According to claim 8,
measuring position data of the marine buoy;
Generating image data by monitoring objects existing around the sea buoy; and
Transmitting at least one of the motion data, the refined wind data, the location data, and the image data to a preset control server; further comprising a method of controlling a floating wind data measuring device.
A computer-readable recording medium storing a computer program,
When the computer program is executed by a processor,
A LiDAR module is provided on one side of a sea buoy to generate wind data;
Generating motion data by measuring movement of the sea buoy;
correcting the wind condition data using the motion data; and
Comprising: filtering out erroneous data from the corrected wind condition data to purify the wind condition data,
The lidar module is,
A first LIDAR that emits one wavelength and generates first wind condition data based on the wavelength reflected by particles in the atmosphere; and
A second LIDAR that emits a plurality of different wavelengths and generates second wind condition data based on the wavelengths reflected by particles in the atmosphere,
The step of refining the wind data is,
determining a correlation between the first wind condition data and the second wind condition data;
determining the incorrect data from the first wind data and the second wind data based on the correlation, and removing the determined incorrect data from the first wind data and the second wind data; and
Generating the refined wind condition data based on the first wind condition data and the second wind condition data from which the erroneous data has been removed; a computer readout comprising instructions for causing the processor to perform the method including; Possible recording media.
A computer program stored on a computer-readable recording medium,
When the computer program is executed by a processor,
A LiDAR module is provided on one side of a sea buoy to generate wind data;
Generating motion data by measuring movement of the sea buoy;
correcting the wind condition data using the motion data; and
Comprising: filtering out erroneous data from the corrected wind condition data to purify the wind condition data,
The lidar module is,
A first LIDAR that emits one wavelength and generates first wind condition data based on the wavelength reflected by particles in the atmosphere; and
A second LIDAR that emits a plurality of different wavelengths and generates second wind condition data based on the wavelengths reflected by particles in the atmosphere,
The step of refining the wind data is,
determining a correlation between the first wind condition data and the second wind condition data;
determining the incorrect data from the first wind data and the second wind data based on the correlation, and removing the determined incorrect data from the first wind data and the second wind data; and
Generating the refined wind condition data based on the first wind condition data and the second wind condition data from which the erroneous data has been removed; a computer program comprising instructions for causing the processor to perform the method including; .
A LiDAR module is provided on one side of the sea buoy to generate wind data, measure the movement of the sea buoy to generate motion data, correct the wind data using the motion data, and make erroneous measurements from the corrected wind data. A floating wind measurement device that purifies the wind condition data by filtering the data; and
It includes a control server that receives the refined wind data and generates monitoring data,
The LiDAR module is a first LiDAR that emits one wavelength and generates first wind condition data based on the wavelength reflected by particles in the atmosphere; And a second LIDAR that emits a plurality of different wavelengths and generates second wind condition data based on the wavelengths reflected by particles in the atmosphere,
The wind condition measurement device determines a correlation between the first wind condition data and the second wind condition data, and determines the mismeasurement data among the first wind condition data and the second wind condition data based on the correlation, and A monitoring system that removes the determined incorrect data from the first wind data and the second wind data, and generates the refined wind data based on the first wind data and the second wind data from which the incorrect data was removed. .

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