KR102677913B1 - TM Coordinate Based Flow Rate Measurement Device and Method Using Drone - Google Patents

Abstract

The present invention provides TM (Transverse Meractor) coordinates, a plane rectangular coordinate system, to orthophotographs of the water surface using a drone when measuring river flow, enabling efficient surface flow measurement and flow calculation based on TM coordinates using a drone. It relates to a flow measurement device and method. A GCP survey information management unit that manages GCP survey information according to Ground Control Point (GCP) survey; a drone is hovered at a certain height and occupies the channel. An aerial photography control unit that controls orthophotography to maintain collinear conditions between the camera and the floating object on the water surface so that one GCP point is included; coordinates are given for the moving position of the floating object, and the coordinates are given through digitizing the point of the floating object. From the It includes a surface flow rate calculation unit that calculates the surface flow rate by dividing the total correction distance, which is the sum of the correction distances for each location, by the total travel time; a flow rate calculation unit that calculates the flow rate using the surface flow rate calculated in the surface flow rate calculation unit.

Description

TM Coordinate Based Flow Rate Measurement Device and Method Using Drone}

The present invention relates to river flow measurement technology, and specifically, to a drone that enables efficient surface flow measurement and flow rate calculation by assigning TM (Transverse Meractor) coordinates, a plane rectangular coordinate system, to water surface photos taken orthophoto using a drone. This relates to a flow measurement device and method based on TM coordinates.

Currently, drones are used in a wide range of fields, including agriculture, weather observation, communications, broadcasting, logistics transportation, and aerial surveying, and industries using drones are continuously expanding.

Drone aerial surveying has been dominated by techniques using expensive sensors such as LiDAR (Light detection and Ranging, or Light+Radar), infrared, multispectral, and hyperspectral, but due to frequent drone loss accidents, general optical sensors are used. It is being replaced by aerial photogrammetry techniques using (digital cameras).

The accuracy of aerial photogrammetry has been proven through many studies in various fields.

Meanwhile, research using drones is also actively underway in the water resources field, and the river surveying field is a representative example. A representative example of research on flow velocity measurement at home and abroad is the PIV (Particle Image Velocimetry) technique, which is a method of measuring surface velocity fields through video recording.

In particular, in overseas cases, a method was developed to stabilize images taken from the air with high accuracy, and the river surface distribution was measured using the stabilized images using the STIV (Space Time Image Velocimetry) technique.

This method was developed by combining algorithms such as SIFT (Scale Invariant Feature Transform) and RIPOC (Rotation Invariant Phase Only Correlation) in the image stabilization process and was applied to investigate flooding caused by snowmelt in the Uono River in 2014.

Another method is to perform flow measurement in a completely non-contact manner using a drone. The cross-section of the river was measured by correcting the refraction of the image taken by a drone, and the surface flow rate was estimated by applying the LSPIV (Large Scale Particle Image Velocimetry) method.

In Korea, Yu and Hwang (2017) applied surface image velocimetry through a four-step process of image capture, image correction, image analysis, and post-processing using a video camera mounted on a drone in an experimental waterway. Surface flow velocity was measured.

What these surface flow measurement methods have in common is the image processing process for digitization by shooting a video and dividing it into time intervals of still images, as well as the coordinate conversion process between the actual coordinates of floating objects flowing in the river and CRT (Cathode-ray tube coordinates) coordinates. Correction for image distortion must be performed through .

Flow measurement in the event of a flood in the conventional technology is carried out using advanced measuring equipment such as electromagnetic wave velocimeter, video velocimeter, radar velocimeter, ADCP, etc. There are difficulties in carrying out measurements at the point.

Therefore, there is a need for the development of new technology that can improve this problem and allow a minimum number of people to easily measure flow rate using a drone in a short period of time.

Republic of Korea Patent No. 10-1996992 Republic of Korea Patent No. 10-1978351 Republic of Korea Patent No. 10-2113791

The present invention is intended to solve the problems of the river flow measurement technology of the prior art, and provides efficient surface flow measurement and flow calculation by assigning TM (Transverse Meractor) coordinates, a plane rectangular coordinate system, to water surface photos taken orthophotographed using a drone. The purpose is to provide a flow measurement device and method based on TM coordinates using a drone.

The present invention measures the surface flow rate by assigning TM coordinates, a plane rectangular coordinate system, to a water surface photograph taken orthophoto using a drone, and applies the cross-sectional area to the water level from the measured cross-sectional data, enabling rapid and accurate flow measurement. The purpose is to provide a flow measurement device and method based on TM coordinates using a drone.

The present invention is a TM coordinate-based method using a drone that enables quick and easy measurement in flood stage flow measurement, protects measurement personnel from the risk of accidents, and contributes to improving data accuracy by assigning the necessary manpower to other tasks when measuring flood stage. The purpose is to provide a flow measurement device and method.

The present invention is a measurement using an aerial surveying technique. Compared to the PIV technique through video shooting, the present invention is a TM coordinate-based method using a drone that improves measurement convenience and accuracy by eliminating the need for multiple correction steps such as image and image coordinate correction. The purpose is to provide a flow measurement device and method.

Other objects of the present invention are not limited to the objects mentioned above, and other objects not mentioned will be clearly understood by those skilled in the art from the description below.

The TM coordinate-based flow measurement device using a drone according to the present invention to achieve the above purpose includes a GCP survey information management unit that manages GCP survey information according to Ground Control Point (GCP) survey; a drone is raised to a certain height; An aerial photography control unit that controls orthophotography to maintain collinear conditions between the camera and the floating object floating on the water surface so that the GCP point occupied within the river channel is included in the hovering state; about the moving position of the floating object Coordinates are given, and the flow angle is calculated in the direction perpendicular to the cross section of the upstream and downstream ends and the movement distance during the reference time according to the flow from the and a flow angle calculation unit; a surface flow rate calculation unit that calculates the surface flow rate by dividing the total correction distance, which is the sum of correction distances for each location from the upstream end to the downstream end, by the total travel time; using the surface flow rate calculated in the surface flow rate calculation unit. It is characterized by including a flow rate calculation unit that calculates the flow rate.

Here, the GCP surveying information management department conducts ground surveying through trilateration using VRS DGPS (Virtual Reference Station DGPS) surveying equipment to obtain a ground control point (GCP) and monitors the movement of floating objects in the river. For two-dimensional analysis, it is characterized by using only X and Y values, excluding the Z value, which is the height value in the aerial photogrammetry concept.

And it is characterized by further comprising an orthocorrection unit that corrects the image captured under the control of the aerial photography control unit using GCP coordinates.

And the aerial photography control unit controls the drone and camera to maintain the collinearity condition in which the target point on the ground, the image point of the target point captured in the photo, and the three exposure points are located on one straight line. It is characterized by filming.

And in the coordinate assignment and flow angle calculation unit, the It is characterized in that the coordinate system of the aerial photo orthophotographed by the drone is defined as the central Korean origin of the GRS80 TM coordinate system, which is a plane rectangular coordinate system.

In addition, the coordinate assignment and flow angle calculation unit sets the camera interval function at regular intervals and provides coordinates for the movement path of the floating object through point digitizing the position of the floating object in several aerial photos taken during the set time. It is characterized by:

And the flow rate calculation unit calculates the flow rate for each side line by multiplying the average cross-sectional area of each side line corresponding to the cross section of the upstream and downstream ends by the average flow rate of each side line shown in the flow velocity-distribution curve, and the sum of the flow rates for all side lines. It is characterized in that it is calculated as the total flow rate.

The TM coordinate-based flow measurement method using a drone according to the present invention to achieve another purpose includes a GCP survey information management step of managing GCP survey information according to Ground Control Point (GCP) survey; a drone at a certain height; Aerial photography control step to control orthophotography to maintain collinear conditions between the camera and floating objects on the water surface so that the GCP point occupied within the river channel is included in the hovering state; the captured image is converted to GCP coordinates Orthocorrection step of orthocorrection using; Coordinates are given for the moving position of the floating object, and from the Coordinate assignment and flow angle calculation steps to calculate the flow angle to the perpendicular direction of the cross section of the downstream end; Surface flow rate is calculated by dividing the total correction distance, which is the sum of the correction distances for each location flowing from the upstream end to the downstream end, by the total travel time. It is characterized in that it includes a surface flow rate calculation step; a flow rate calculation step of calculating the flow rate using the surface flow rate calculated in the surface flow rate calculation step.

Here, in the aerial photography control stage, the drone and camera can be controlled to maintain the collinearity condition in which the three points of the target point on the ground, the image point of the target point captured in the photo, and the exposure point are located on one straight line. It is characterized by orthophotography.

And in the step of assigning coordinates and calculating the flow angle, the It is characterized by using coordinates and defining the coordinate system of the aerial photo orthophotographed by a drone as the central Korean origin of the GRS80 TM coordinate system, which is a plane rectangular coordinate system.

In addition, in the coordinate assignment and flow angle calculation stage, the camera interval function is set at regular intervals, and the coordinates of the movement path of the floating object are obtained through point digitizing the position of the floating object in several aerial photos taken during the set time. It is characterized by giving.

And in the surface flow calculation stage, the movement distance for each location is divided into the distance perpendicular to the cross-sectional area through the flow angle. Compensated moving distance ( ) is calculated, where: The distance the float moves in 3 seconds, is characterized in that it is the flow angle with respect to the direction perpendicular to the cross-sectional area for each location.

And the sum of the correction distances for each position from the upstream end to the downstream end is Calculate the total correction distance ( ) is the total travel time ( ) divided by surface flow rate ( ) is characterized by calculating.

And in the flow rate calculation stage, the average cross-sectional area of each side line corresponding to the cross section of the upstream and downstream ends is multiplied by the average flow rate of each side line shown in the flow velocity-distribution curve to calculate the flow rate for each side line, and the flow rate for all side lines is calculated. It is characterized by calculating the sum as the total flow rate.

As described above, the TM coordinate-based flow measurement device and method using a drone according to the present invention has the following effects.

First, TM (Transverse Meractor) coordinates, a plane rectangular coordinate system, are given to orthophotographs of the water surface using a drone, enabling efficient surface flow velocity measurement and flow rate calculation.

Second, surface flow velocity is measured by assigning TM coordinates, a plane rectangular coordinate system, to orthophotographs of the water surface using a drone, and the cross-sectional area for the water level is applied from the measured cross-sectional data to enable rapid and accurate flow measurement. do.

Third, it enables quick and easy measurement in measuring flood flow, protecting measurement personnel from the risk of accidents, and contributing to improving data accuracy by allocating the necessary manpower to other tasks when measuring flood season.

Fourth, compared to the PIV technique through video shooting, measurement using aerial surveying techniques eliminates the need for multiple correction processes such as image and image coordinate correction, thereby improving measurement convenience and accuracy.

1 is a configuration diagram showing an example of a drone for measuring flow rate according to the present invention.
Figures 2a to 2d are diagrams showing an example of ground control point (GCP) occupancy.
Figure 3 is a block diagram of a TM coordinate-based flow measurement device using a drone according to the present invention.
Figure 4 is a flow chart showing a flow rate measurement method based on TM coordinates using a drone according to the present invention.
5A and 5B are configuration diagrams showing an example of orthophotography according to the present invention.
Figures 6a and 6b are diagrams showing an example of target point selection for flow rate calculation
Figures 7a and 7b are diagrams showing another example of target point selection for flow rate calculation.
Figures 8a and 8b are diagrams showing an example of floating object coordinate settings
Figures 9a to 9c show an example of a TM coordinate table for each position of a floating object given through a point digitizing operation from a taken aerial photograph, and an example of flow angle calculation for the perpendicular direction of the cross section of the upstream and downstream ends of the cross-sectional area. Configuration diagram shown
Figures 10a and 10b are diagrams showing an example of a flow rate calculation method by measuring the flow rate.
Figures 11a and 11b are graphs showing comparative analysis results regarding the accuracy of flow rate measured with a drone

Hereinafter, a preferred embodiment of the TM coordinate-based flow measurement device and method using a drone according to the present invention will be described in detail as follows.

The features and advantages of the TM coordinate-based flow measurement device and method using a drone according to the present invention will become apparent through the detailed description of each embodiment below.

Figure 1 is a configuration diagram showing an example of a drone for measuring flow rate according to the present invention, and Figures 2A to 2D are configuration diagrams showing an example of ground control point (GCP) occupancy.

The flow measurement device and method using a drone according to the present invention enables efficient surface flow measurement and flow rate calculation by assigning TM (Transverse Meractor) coordinates, a plane rectangular coordinate system, to water surface photos taken orthophotographed using a drone.

To this end, the present invention provides a configuration for aerial photography using a drone to calculate flow velocity and flow rate, a configuration for using an aerial surveying technique using a plane rectangular coordinate system (TM) rather than a PIV using an image coordinate system, and a configuration for calculating surface flow velocity. It may include a configuration for calculating the flow rate.

An example of a drone used to measure flow rate according to the present invention is shown in FIG. 1.

Drones are largely divided into fixed wing and rotary wing. In the present invention, it is preferable to use a rotary wing drone to quickly and accurately measure the surface flow velocity of a river, but is not limited thereto.

The drone's performance is required to have a stationary flight accuracy range of about 0.5m vertically and 1.5m horizontally, a wind resistance of up to 10 m/s, and a maximum flight time of about 30 minutes, but is not limited to this.

In one embodiment of the present invention, the camera mounted on the drone is equipped with a 1-inch 20-megapixel sensor and performs continuous shooting at a shutter speed ranging from 8 seconds to 1/8000 second and a constant time interval ranging from 2 seconds to 60 seconds. Those with possible interval functions are used, but are not limited to this.

As shown in Figure 1, it is desirable for the camera to be attached to a 3-axis (pitch, roll, yaw) holder (Gimbal) to enable stable shooting against vibration.

In the present invention, a ground reference point preoccupation step is performed to measure flow rate using a drone.

Ground Control Point (GCP) refers to the acquisition of reference coordinates through precise on-site surveying of points identified on aerial photographs in order to accurately determine the external expression elements of aerial photographs during the aerial photogrammetry post-processing process.

Ground reference point surveying is a series of surveying processes to calculate the ground coordinates of GCP in the shooting area, and refers to ground surveying conducted in the field through trilateration using the VRS DGPS (Virtual Reference Station DGPS) surveying equipment shown in Figure 2a.

For GCP surveying, an anti-aircraft beacon is installed in the target area before flight, as shown in Figure 2b, and is used as an absolute position reference point for photos taken. The appropriate number of GCPs can be adjusted depending on the area and characteristics of the shooting area.

In one embodiment of the present invention, VRS DGPS is secured by securing a total of 4 GCPs, 2 on the left and right sides of the river at each point, at the Uijeongbu City (Shingok Bridge) point, which is the target point in Figure 2c, and the Yeongdong-gun (Yeongdong 2nd Bridge) point in Figure 2d. A coordinate survey was performed using

The measured GCP values are as shown in Table 1 and are used for more precise correction of orthoimages taken under collinear conditions.

Since the present invention requires a two-dimensional analysis of the movement of floating objects in the river, only the X and Y values are used, excluding the Z value, which is the height value in the aerial photogrammetry concept.

The configuration of the flow measurement device using a drone according to the present invention will be described in detail as follows.

Figure 3 is a block diagram of a TM coordinate-based flow measurement device using a drone according to the present invention.

Specifically, as shown in FIG. 3, the flow measurement device based on TM coordinates using a drone according to the present invention includes a GCP survey information management unit 31 that manages GCP survey information by conducting a GCP survey for use as an absolute position reference point for photos; , Aerial photography control unit that controls orthophotography of the camera and floating objects on the surface of the water to maintain collinear conditions so that the drone is hovering at a certain height and includes four GCP points located within the river channel. (32) and an orthocorrection unit 33 that more precisely orthocorrects the image captured under the control of the aerial photography control unit 32 using GCP coordinates, and provides coordinates for the moving position of the floating object, From the (34) and the surface flow rate calculation unit (35), which calculates the surface flow rate by dividing the total correction distance, which is the sum of the correction distances for each location from the upstream end to the downstream end, by the total travel time, and the cross section of the upstream end and the downstream end. The average cross-sectional area of each lateral line is multiplied by the average flow rate of each lateral line shown in the flow velocity-distribution curve to calculate the flow rate for each lateral line, and the flow rate calculation unit 36 calculates the sum of the flow rates for all lateral lines as the total flow rate. Includes.

The flow measurement method of the TM coordinate-based flow measurement device using a drone according to the present invention having such a configuration will be described in detail as follows.

Figure 4 is a flow chart showing a flow rate measurement method based on TM coordinates using a drone according to the present invention.

As shown in FIG. 4, the flow measurement method based on TM coordinates using a drone according to the present invention first performs a GCP survey to use as an absolute position reference point of the photo to measure flow rate using a drone (S401).

Next, with the drone hovering at a certain height, orthophotography is performed to ensure that the camera and the floating object floating on the water surface maintain collinear conditions so that the four GCP points occupied within the channel are included. (S402 )

Then, more precise orthocorrection is performed using GCP coordinates (S403).

Next, coordinates are given for the moving position of the floating object, and from the Calculate the flow angle for (S404)

Then, the surface flow rate is calculated by dividing the total correction distance, which is the sum of the correction distances for each location from the upstream end to the downstream end, by the total travel time (S405).

Next, the average cross-sectional area of each lateral line corresponding to the cross section of the upstream and downstream ends is multiplied by the average flow rate of each lateral line shown in the flow velocity-distribution curve to calculate the flow rate for each lateral line, and the sum of the flow rates for all lateral lines is calculated as the total flow rate. Calculated as (S406)

The TM coordinate-based flow measurement method using a drone according to the present invention having this configuration will be described in detail in each step as follows.

Figures 5a and 5b are configuration diagrams showing an example of orthophotography according to the present invention.

For aerial photography, as shown in Figure 5a, the drone is hovering at a certain height, and the camera and the floating object on the water surface can maintain collinear conditions so that four GCP points are occupied within the river channel. Take full-length photos so that you can

The collinearity condition refers to the condition that three points - the target point on the ground, the image point of the target point captured in the photo, and the exposure point (camera lens or CCD) - are located on one straight line, as shown in Figure 4b.

Most of the coordinates of digital maps and digital orthoimages in Korea are based on the Transversal Mercator projection (TM) projection using a plane rectangular coordinate system, and the ellipsoid is converted using the Global Geodetic System GRS80 (Geodetic Reference System, 1980) ellipsoid. .

For TM coordinates, the

In Korea, the four origins of the Western Coordinate System, Central Coordinate System, Eastern Coordinate System, and East Sea Coordinate System are used as coordinate reference points in the TM coordinate or plane rectangular coordinate system.

Therefore, in one embodiment of the present invention, the coordinate system of an aerial photo orthophotographed by a drone is defined as the central Korean origin of the GRS80 TM coordinate system, which is a plane rectangular coordinate system.

Additionally, orthocorrection is performed more precisely using GCP coordinates.

A detailed explanation of the selection of target points for flow calculation is as follows.

FIGS. 6A and 6B are diagrams showing an example of selecting a target point for flow rate calculation, and FIGS. 7A and 7B are diagrams showing another example of selecting a target point for flow rate calculation.

In an embodiment for flow measurement using the TM coordinate-based flow measurement device and method using a drone according to the present invention, the target points are Uijeongbu City (Singok Bridge) located upstream of Jungnangcheon Stream, a tributary of the Han River, and upstream of Yeongdongcheon Stream, a tributary of the Geumgang River. The Yeongdong-gun (Yeongdong 2nd Bridge) branch located in was selected.

For measurement at the Uijeongbu City (Shingok Bridge) point, the upstream and downstream cross sections were selected at a location approximately 500 m downstream of Singok Bridge, with a flow distance of approximately 50 m, as shown in Figures 6a and 6b.

At the time of measurement, the flow width according to the water level was approximately 45 m.

For measurement at the Yeongdong-gun (Yeongdong 2nd Bridge) point, the upstream and downstream cross sections were selected in the downstream direction of Yeongdong 2nd Bridge, as shown in Figures 7a and 7b, with a flow distance of about 20 m.

At the time of measurement, the river width according to the water level was approximately 30 m.

An example of floating object coordinate settings for surface flow velocity measurement is described as follows.

Figures 8a and 8b are configuration diagrams showing an example of floating object coordinate settings.

Setting the coordinates of a floating object for surface flow velocity measurement is done as follows.

To measure surface flow velocity using a drone, aerial photos are taken in stationary flight at about 50m above the ground to include four GCP points on the left and right sides of the flow section within the river channel.

When taking aerial photos, you can take about 20 aerial photos in about 1 minute by setting the camera interval function at 3-second intervals.

GSD (Ground Sample Distance), which is related to the precision of photogrammetry, refers to the resolution of the photo and is the ground distance acquired per pixel of the camera video image, which is proportional to the flight altitude.

In one embodiment of the present invention, the positions of 20 floating objects are given coordinates for the movement path of the floating objects through a point digitizing method.

For example, at the Uijeongbu City (Shingok Bridge) branch, rainfall stopped on August 30, 2018, and one result was filmed at the lower part of the heavy rain event. The moving positions of the floating objects according to the flow under the condition of a water level of 1.58 m are as shown in Figure 8a, and the coordinates of the moving positions of the six floating objects were given.

The Yeongdong-gun (Yeongdong 2nd Bridge) branch recorded three water levels of 2.06m, 2.09m, and 1.98m near the peak of the heavy rain event during a lull in rainfall on July 21, 2019.

The moving positions of floating objects according to the flow under the condition of a water level of 1.98 m are as shown in Figure 8b, and the coordinates of the moving positions of 10 floating objects were given. The TM coordinates for each position of the floating object assigned through point digitizing from the captured aerial photograph are representatively presented for the Uijeongbu City (Shingok Bridge) point in Figure 9a.

Figures 9a to 9c show an example of a TM coordinate table for each position of a floating object given through a point digitizing operation from a taken aerial photograph, and an example of flow angle calculation for the perpendicular direction of the cross section of the upstream and downstream ends of the cross-sectional area. This is the configuration diagram shown.

The surface flow rate is calculated as follows.

From the Calculate as in Lesson 2).

Therefore, the movement distance for each location is the distance in the direction perpendicular to the cross-sectional area with respect to the flow angle, and the movement distance corrected as in Equation 1 ( ) is calculated.

here, The distance the float moves in 3 seconds, is the flow angle with respect to the direction perpendicular to the cross-sectional area for each location.

In addition, the sum of the correction distances for each position from the upstream end to the downstream end is as shown in Equation 2.

The total correction distance in Equation 2 ( ) is the total travel time ( ) divided by the surface flow rate ( ) is calculated.

And the flow rate calculation according to the surface flow velocity calculation is done as follows.

Figures 10a and 10b are diagrams illustrating an example of a flow rate calculation method using float measurement.

Flow rate calculation according to surface flow rate calculation is calculated as shown in Figures 10a and 10b, which is the flow rate calculation method by floating measurement.

At the midpoint between the two upper and lower cross section lines, another line MN can be drawn parallel to the cross section line. The water surface points that separate the various lateral lines of the two cross sections are connected by dotted lines, and the start and end points of each side are drawn and connected by fixed lines.

Where the fixed line crosses the MN line, the corresponding average flow rate (surface flow rate * correction coefficient) is plotted perpendicular to MN, and the end points of these flow vectors are connected to form a flow velocity-distribution curve.

When the average cross-sectional area of each lateral line corresponding to the cross section of the upstream and downstream ends is multiplied by the average flow rate of each lateral line shown in the flow velocity-distribution curve, the flow rate for each lateral line is calculated, and the sum of the flow rates for all lateral lines is calculated as the total flow rate. It is calculated as in Equation 4.

The average flow velocity at a line is determined by measuring the area under the velocity-distribution curve for that line using a quadrature, or an approximation equal to the measured flow velocity midway through the section is adopted.

here, is the surface flow rate for each side line, is the cross-sectional area of each upstream side line, is the cross-sectional area of each downstream side line.

In one embodiment of the present invention, the correction coefficient for calculating the average flow rate was calculated by multiplying the calculated surface flow rate by the generally applied 0.85, and the average cross-sectional area of each side line corresponding to the cross-section at the upstream and downstream ends was calculated as Calculate the average cross-sectional area for each line considering the location where the floating material passed.

The results of the comparative analysis on the accuracy of the flow rate measured by the drone are as follows.

Figures 11a and 11b are graphs showing comparative analysis results regarding the accuracy of flow rate measured by a drone.

A comparative analysis was conducted on the accuracy of the flow rate measured by the drone by comparing the flow rate calculated through analysis of aerial photos taken with a drone and the flow rate calculated from the water level-flow relationship curve equation for the year at each point.

Uijeongbu City (Shingok Bridge) branch (ME, 2019) used Flow Tracker, ADCP, and Buja 44 times in 2018, and Yeongdong-gun (Yeongdong 2nd Bridge) branch (ME, 2020) used Flow Tracker, ADCP, etc. in 2019. A water level-flow relationship curve was developed through 37 measurements.

As a result of reviewing the standard error and uncertainty to evaluate the developed curve equation, as shown in Table 2, it can be seen that the standard error at Uijeongbu City (Shingok Bridge) point is 6.94% and the curve uncertainty is very precise, ranging from a minimum of 2.31% to a maximum of 4.03%. .

In addition, in the case of the Yeongdong-gun (Yeongdong 2nd Bridge) branch, it can be seen that the standard error is 7.37% and the curve uncertainty is similarly precise, with a minimum of 2.46% and a maximum of 6.49%.

Therefore, when the flow rate calculated through aerial photo analysis was included in the water level-flow relationship curve for each point in Figures 11a and 11b, it was confirmed that it showed a very close trend.

Table 3 shows the converted flow rate calculated from the water level-flow relationship curve equation and the flow rate measured with a drone, considering the flow rate without correcting the movement path of the floating object and the flow angle in the direction perpendicular to the cross-sectional area, and the average cross-sectional area for each location where the floating object passed. The flow rate that was taken into account and corrected was reviewed.

The overall corrected flow rate is approximately 3.88%, calculated to be within 5%, and

It can be seen that the applicability of the flow measurement method using aerial photography has been verified.

The TM coordinate-based flow measurement device and method using a drone according to the present invention described above provides efficient surface flow rate measurement and flow rate by assigning TM (Transverse Meractor) coordinates, a plane rectangular coordinate system, to water surface photos taken orthophotographed using a drone. This makes calculation possible.

Through this, the present invention enables quick and easy measurement in flood stage flow measurement, protects measurement personnel from the risk of accidents, contributes to improving data accuracy by allocating necessary manpower to other tasks when measuring flood stage, and can contribute to improving data accuracy by applying aerial surveying techniques. Compared to the PIV technique through video recording as a measurement, multiple steps of correction processes such as image and image coordinate correction are unnecessary, thereby improving measurement convenience and accuracy.

As described above, it will be understood that the present invention is implemented in a modified form without departing from the essential characteristics of the present invention.

Therefore, the specified embodiments should be considered from an illustrative rather than a limiting point of view, the scope of the present invention is indicated in the claims rather than the foregoing description, and all differences within the equivalent scope are intended to be included in the present invention. It will have to be interpreted.

31. GCP survey information management department 32. Aerial photography control department
33. Orthographic correction unit 34. Coordinate assignment and flow angle calculation unit
35. Surface flow calculation unit 36. Flow calculation unit

Claims (14)

GCP Survey Information Management Department, which manages GCP survey information according to Ground Control Point (GCP) survey;
An aerial photography control unit that controls the drone to take orthophotographs in a hovering state at a certain height so that the GCP points occupied within the river can be included so that the camera and floating objects floating on the water surface can maintain collinear conditions;
Coordinates are given for the moving position of the floating object, and from the Coordinate assignment and flow angle calculation unit for calculating the angle;
A surface flow rate calculation unit that calculates the surface flow rate by dividing the total correction distance, which is the sum of the correction distances for each location from the upstream end to the downstream end, by the total travel time;
It includes a flow rate calculation unit that calculates the flow rate using the surface flow rate calculated in the surface flow rate calculation unit,
The aerial photography control unit controls the drone and camera to maintain the collinearity condition in which the target point on the ground, the image point of the target point captured in the photo, and the three exposure points are located on one straight line. TM coordinate-based flow measurement device using a drone, which is characterized by taking pictures. The method of claim 1, wherein the GCP survey information management unit,
To obtain a ground control point (GCP), a ground survey is conducted through trilateration using VRS DGPS (Virtual Reference Station DGPS) survey equipment.
A flow measurement device based on TM coordinates using a drone, which uses only the The flow measurement device based on TM coordinates using a drone according to claim 1, further comprising an orthocorrection unit that corrects the image captured under the control of the aerial photography control unit using GCP coordinates. delete The method of claim 1, wherein the coordinate assignment and flow angle calculation unit,
The
A flow measurement device based on TM coordinates using a drone, characterized in that the coordinate system of an aerial photo taken orthophoto by a drone is defined as the central Korean origin of the GRS80 TM coordinate system, which is a plane rectangular coordinate system. The method of claim 1, wherein the coordinate assignment and flow angle calculation unit,
TM using a drone, which is characterized by setting the camera interval function at regular intervals and giving coordinates for the movement path of the floating object through point digitizing the position of the floating object in several aerial photos taken during the set time. Coordinate-based flow measurement device. The method of claim 1, wherein the flow rate calculation unit,
Calculate the flow rate for each lateral line by multiplying the average cross-sectional area of each lateral line corresponding to the cross section of the upstream and downstream ends by the average flow rate of each lateral line shown in the flow velocity-distribution curve,
A flow measurement device based on TM coordinates using a drone, which calculates the sum of the flow rates for all survey lines as the total flow rate. A GCP survey information management step of managing GCP survey information according to Ground Control Point (GCP) survey;
An aerial photography control step of controlling the drone to take orthophotographs so that the camera and floating objects floating on the surface of the water can maintain collinear conditions so that the GCP points occupied within the riverway are included in a hovering state at a certain height;
An orthocorrection step of orthocorrecting the captured image using GCP coordinates;
Coordinates are given for the moving position of the floating object, and from the Coordinate assignment and flow angle calculation steps for calculating the angle;
A surface flow velocity calculation step of calculating the surface velocity by dividing the total correction distance, which is the sum of correction distances for each location flowing from the upstream end to the downstream end, by the total travel time;
It includes a flow rate calculation step of calculating the flow rate using the surface flow rate calculated in the surface flow rate calculation step,
In the aerial photography control step, the drone and camera are controlled to maintain the collinearity condition in which the three points of the target point on the ground, the image point of the target point captured in the photo, and the exposure point are located on one straight line. TM coordinate-based flow measurement method using a drone characterized by orthophotography. delete The method of claim 8, wherein in the coordinate assignment and flow angle calculation steps,
The
A flow measurement method based on TM coordinates using a drone, characterized in that the coordinate system of the aerial photo orthophotographed by the drone is defined as the central Korean origin of the GRS80 TM coordinate system, which is a plane rectangular coordinate system. The method of claim 8, wherein in the coordinate assignment and flow angle calculation steps,
TM using a drone, which is characterized by setting the camera interval function at regular intervals and giving coordinates for the movement path of the floating object through point digitizing the position of the floating object in several aerial photos taken during the set time. Coordinate-based flow measurement method. The method of claim 8, wherein in the surface flow rate calculation step,
The moving distance for each location is calculated as the distance perpendicular to the cross-sectional area through the flow angle.
Compensated moving distance ( ) is calculated,
here, The distance the float moves in 3 seconds, TM coordinate-based flow measurement method using a drone, characterized in that is the flow angle to the direction perpendicular to the cross-sectional area for each location. According to claim 12, the sum of correction distances for each position from the upstream end to the downstream end is Find it with
Total correction distance ( ) is the total travel time ( ) divided by surface flow rate ( ) TM coordinate-based flow measurement method using a drone, characterized by calculating ). The method of claim 8, wherein in the flow rate calculation step,
Calculate the flow rate for each lateral line by multiplying the average cross-sectional area of each lateral line corresponding to the cross section of the upstream and downstream ends by the average flow rate of each lateral line shown in the flow velocity-distribution curve,
TM coordinate-based flow measurement method using a drone, characterized in that the sum of the flow rates for all survey lines is calculated as the total flow rate.

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