Sea state information estimation method

Abstract

To make it possible to estimate flow velocity without using a flow velocity measuring sensor.SOLUTION: A sea state information estimation method uses a marine phenomenon buoy that is moored to a fixed part, moves in accordance with a sea surface, includes an antenna and a GNSS receiver, and is configured to obtain position information using the GNSS receiver. The method calculates a direction from position information of an installation point P0 of the marine phenomenon buoy and position information of a position Pt of the marine phenomenon buoy, calculates a second-order difference value from a time series of the direction, calculates an extreme value of the second-order difference value, calculates a product of adjacent extreme values, and estimates a current speed from the product of extreme values and an approximation curve of the actual measurement current speed.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a method and device for estimating sea state information, particularly, tidal current speed. [Background technology]

[0002] Conventional devices for measuring the velocity of tidal currents have been known to have a dedicated sensor, such as an ultrasonic current meter, installed outside the buoy. In this configuration, a cable is pulled into the buoy, which requires time and cost for maintenance, such as water leakage, cable breakage, sensor deterioration due to attached organisms, and battery replacement.

[0003] The applicant of this application has proposed a wave height measuring device that measures wave height by mounting a receiver that receives radio waves from a GPS (Global Positioning System) satellite on a buoy and measuring the three-dimensional position of the buoy (see Patent Document 1). This wave height measuring device is equipped with a GPS antenna, a GPS receiver, a data recorder, a data processor, and a transmitter, and can measure the wave height at the site where the buoy is floating. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-165752 Summary of the Invention [Problem to be solved by the invention]

[0005] Patent Document 1 does not disclose measuring current speed using GPS data. Current speed information is important for fixed net fishermen and other fishery-related personnel, and is also necessary for ensuring the safety of boats docking at piers, and is also necessary from the perspective of disaster prevention.

[0006] Therefore, an object of the present invention is to provide a method and device for estimating ocean condition information that can measure the flow speed of tidal currents using position information obtained by a GNSS (Global Navigation Satellite System) receiver. [Means for solving the problem]

[0007] The present invention provides a method for estimating oceanographic information using a marine buoy that is moored to a fixed part, moves along with the sea surface, has an antenna and a GNSS receiver, and obtains position information by the GNSS receiver, The direction is calculated from the position information of the installation point P0 of the marine buoy and the position information of the marine buoy's position Pt. Calculate the second-order difference value of the time series of the orientation, Calculate the extreme value of the second difference value, Calculate the product of adjacent extreme values, Estimate the flow velocity from the product of the extreme values ​​and the approximate curve of the measured flow velocity This is a method for estimating ocean condition information. Effect of the Invention

[0008] According to the present invention, it is possible to estimate the flow velocity by only using the position information received by the GNSS receiver. Note that the effects described herein are not necessarily limited to those described herein, and may be any of the effects described herein. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a schematic diagram showing the configuration of a moored type current velocity and direction measurement device according to one embodiment of the present invention. [Diagram 2] FIG. 2 is a schematic diagram for explaining a position on an XY plane of three-dimensional position information measured by a GNSS receiver. [Diagram 3] FIG. 3 is a block diagram showing the system configuration of sea condition information according to one embodiment of the present invention. [Figure 4]FIG. 4 is a schematic diagram showing the flow of a process for estimating a current direction and a current speed from a change in the position of a marine phenomenon buoy. [Diagram 5] FIG. 5 is a graph showing the current velocity measured by an ultrasonic current meter and a graph showing the current direction measured from the direction of movement of the oceanographic buoy. [Figure 6] Figure 6 shows a graph of the second-order difference of the flow direction and the average flow velocity. [Figure 7] Figure 7 shows a scatter plot of the product of adjacent extremes (horizontal axis) versus flow velocity (vertical axis). [Figure 8] FIG. 8 is a graph showing the flow velocity estimated from the flow direction using an approximation curve and the actually measured flow velocity superimposed on each other. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, the embodiments of the present invention will be described. Note that the embodiments described below are preferred specific examples of the present invention, and various technically preferable limitations are attached, but the scope of the present invention is not limited to these embodiments unless otherwise specified in the following description to the effect that the present invention is limited.

[0011] Figure 1 shows the configuration of a moored current velocity and direction measurement device in one embodiment of the present invention. Reference numeral 1 denotes a current velocity and direction measurement buoy (hereinafter referred to as a marine phenomenon buoy). The marine phenomenon buoy 1 is designed to float on the sea surface SF, and has a dome-shaped equipment storage section that is not easily affected by wind, a ring-shaped life ring installed around the device storage section, and a solar cell attached to the life ring.

[0012] More specifically, the oceanographic buoy 1 is a small (approximately 80 cm) disc-shaped buoy that floats just above the sea surface and has an isotropic shape that makes it easy to follow movements on the sea surface. As a result, the buoy itself is much less affected by wind and currents than conventional cylindrical buoys such as spar buoys, and its behavior is almost synchronized with changes in the sea surface.

[0013] By combining this unique buoy structure with machine learning, it becomes possible to estimate the buoy's motion characteristics only from sea level fluctuations, in other words, from the fluctuation pattern of three-dimensional position information. That is, when generating an estimation model by machine learning, it becomes possible to learn sea level fluctuation characteristics specific to waves, and estimate wave height and current direction only from the fluctuation pattern of three-dimensional position information. Furthermore, one embodiment of the present invention is adapted to estimate current speed by processing three-dimensional position information of the marine phenomenon buoy 1. In the following explanation, the estimation of current direction and current speed will be mainly explained, but wave height can be measured by a method proposed by the applicant of the present application (for example, the method described in Patent Document 1 mentioned at the beginning).

[0014] A marine buoy 1 is connected to a mooring device via a rope. The mooring device has a single-point mooring configuration. A small, lightweight buoy 13 serving as a floating body is connected via ropes 12a, 12b, and 12c to a sandbag 11 serving as an anchor installed on the seabed. The ropes are connected to each other via return twists to prevent twisting. The marine buoy 1 is connected to the return twists for connecting the ropes 12b and 12c via the return twist and rope 14a, the return twist 15, and the rope 14b. In addition, a chain W1 and a sinker W2 serving as a sinker are connected to the buoy 13.

[0015] The total length of the ropes 12a to 12c is longer than the water depth at the installation location. Furthermore, the disc-shaped marine phenomenon buoy 1, which is less affected by ocean winds, is connected to the mooring device via ropes 14a and 14b, and a sinker W3 is connected to the rope 14a. Since the ropes are connected with multiple twists, the behavior of the marine phenomenon buoy 1 is synchronized with sea level fluctuations, and the current direction and speed can be measured accurately.

[0016] The oceanographic buoy 1 has an antenna and a GNSS (Global Navigation Satellite System) receiver that receives radio waves from satellites through the antenna. GNSS is a general term for satellite positioning systems such as GPS, GLONASS, Galileo, and the Quasi-Zenith Satellite System (QZSS). For example, the Quasi-Zenith Satellite System (Michibiki) has recently started operation, complementing GPS and enabling more accurate positioning.

[0017] The GNSS receiver also uses its antenna to receive error correction information obtained by receiving radio waves from satellites at electronic reference points whose positions are known in advance. The error correction information is received at a frequency of 5 Hz to 10 Hz. As a result, the positioning accuracy is high. The GNSS receiver obtains three-dimensional position information of the oceanographic buoy 1 (antenna). The three-dimensional position information is expressed as (X: longitude, Y: latitude, Z: altitude).

[0018] FIG. 2 is a schematic diagram for explaining the position on the XY plane of the three-dimensional position information measured by the GNSS receiver. The center point (reference point) P0 corresponds to the position of the buoy 13 of the mooring device, and its coordinates are known values ​​(X0, Y0). For example, the position of the buoy 13 when there is no current (slack tide) is taken as the center point. Pt corresponds to the position of the measured oceanographic buoy 1, and its coordinates are expressed as (Xt, Yt). The north, east, south, and west directions relative to the center point P0 are 0°, 90°, 180°, and 270°, respectively. In the example of FIG. 2, for example, the angle θ with respect to the north is measured as the tidal direction at that time. Note that the way of expressing the tidal direction is not limited to (0° to 360°), and (-180° to +180°) may also be used.

[0019] Furthermore, the oceanographic buoy 1 has a wireless communication unit for transmitting three-dimensional position information, in addition to the GNSS receiver, and a power supply unit. The wireless communication unit has an antenna and performs wireless communication with a website on the Internet or a center on the ground. For example, communication is performed using a mobile phone network. Communication may also be performed using a satellite telephone network. The power supply unit is composed of, for example, a secondary battery and a solar power generation device.

[0020] Fig. 3 shows the system configuration for ocean condition information according to one embodiment of the present invention, and Fig. 4 shows the process flow for estimating current direction and current speed from the change in position of the ocean condition buoy 1. As described above, the ocean condition buoy 1 is connected to the mooring device via rope 14a, reel 15, and rope 14b. In Figs. 3 and 4, the reel and sinker of the mooring device are not shown.

[0021] The three-dimensional position information obtained by the marine buoy 1 is transmitted to a position information receiving server 21 of the cloud server 2 via, for example, mobile communication or satellite communication. For example, the three-dimensional position information is transmitted at intervals of 0.1 seconds. The position information receiving server 21 decodes the satellite positioning data, and the decoded three-dimensional position information and time information are registered in a database server 22.

[0022] Information (date, time, longitude, latitude, altitude) is registered in the database server 22. A pre-processing server 23 is connected to the database server 22, and an analysis server 24 is connected to the database server 22 and the pre-processing server 23.

[0023] The pre-processing server 23 extracts continuous data for a predetermined time period, for example 5 to 20 minutes, from the database server 22, cuts out noise specific to the satellite, smoothes the position information, and calculates the average value (Xt, Yt, Zt) of the three-dimensional position information.

[0024] The data preprocessed by the preprocessing server 23 is provided to the analysis server 24. The analysis server 24 performs the following processing to generate an approximation curve for estimating the flow velocity, and estimates the flow velocity using the approximation curve.

[0025] The direction and distance traveled are calculated from the coordinates (X0, Y0) of the installation point P0 of the oceanographic buoy 1 of the mooring device, the coordinates (Xt, Yt, Zt) of the position Pt of the oceanographic buoy 1, and the time information T. · Noise is eliminated by smoothing the time series direction (flow direction). Calculate the time difference value of the smoothed direction. Calculate the second-order difference value and extract the extreme value of the second-order difference value. The flow velocity is estimated from the product of adjacent extreme values ​​and an approximation curve of the measured flow velocity that is created separately.

[0026] The second-order differential values ​​are output (calculated) as a time series of discrete values ​​at regular intervals (for example, every 10 minutes). If these discrete values ​​are graphed, it will look like the graph in Figure 6. The peaks and valleys in this graph are called extreme values, but they are merely peak values ​​calculated from the relationship of the values ​​before and after them. In that sense, they can also be called nodes.

[0027] Find coefficients A, B, C, and D of polynomial approximation using the least squares method Y=A x (X cubed) + B x (X squared) + C x X + D

[0028] The current speed estimation value obtained by the analysis server 24 is made highly accurate by the AI ​​(artificial intelligence) correction server 25. In other words, the current speed estimation accuracy is increased by a current speed estimation learning model (current speed estimation and correction using a neural network) that includes tide level changes in the vertical direction (Z).

[0029] The estimated current speed corrected by the AI ​​correction server 25 is supplied to the analysis database 26. The analysis database 26 stores ocean condition data (date, time, current direction, current speed).

[0030] A content server 27 is connected to the analysis database 26, and a Web server 28 is connected to the content server 27, so that the data in the analysis database 26 can be accessed from outside. The data in the analysis database 26 can be accessed from outside via a smartphone 31, a personal computer 32, a cable television 33, etc.

[0031] The inventors of the present application have confirmed that the flow velocity can be estimated by the above-mentioned processing of the analysis server 24 as follows. Estimation of the flow velocity will be described with reference to Figs. 5, 6, 7, and 8. In order to generate an approximation curve for estimating the flow velocity, an ultrasonic flow meter is attached to, for example, one of the ropes 12a to 12c of the mooring device, and the flow velocity is measured. After the approximation curve is generated, the ultrasonic flow meter may be removed. In other words, the measurement value (teacher data) of the model ultrasonic flow meter is used when creating the approximation formula. Therefore, in reality, the ultrasonic flow meter is not attached to the buoy except for verification.

[0032] 5 shows a graph 40 showing the current velocity [cm / sec] measured by an ultrasonic current meter, and a graph 41 showing the current direction [0° to 360°] measured from the direction of movement of the oceanographic buoy 1. The horizontal axis shows the date and time, and values ​​are plotted at 10-minute intervals, for example. The vertical axis shows the current velocity and current direction.

[0033] Figure 6 shows a graph 42 of the second-order difference of the flow direction and a graph 43 of the average flow velocity. However, the horizontal axes of Figures 5 and 6 do not correspond to each other. In Figure 6, white dots represent extreme values ​​extracted from the second-order difference values.

[0034] FIG. 7 shows a scatter plot of the product of adjacent extreme values ​​(horizontal axis) and the average flow velocity (vertical axis). An approximation curve 44 can be generated from this scatter plot. The generated approximation curve 44 is stored in a storage device, for example, the storage device of the analysis server 24. By storing the approximation curve 44, the flow velocity can be estimated from the product of the extreme values. The flow velocity at other times that do not correspond to an extreme value can be obtained by extrapolating from the multiple extreme values ​​obtained up to the immediately preceding time.

[0035] FIG. 8 is a graph showing the flow velocity estimated from the flow direction using the approximation curve 44 and the flow velocity actually measured using an ultrasonic flow meter or the like, superimposed on each other. The thick line graph 45 is the flow velocity estimated using the approximation curve 44, and the thin line graph 46 is the actually measured flow velocity. As can be seen from FIG. 8, the difference between the estimated flow velocity and the actually measured flow velocity is small, and the estimated flow velocity is close to the actually measured value. Note that the above-mentioned data example is an example that has not been corrected by the AI ​​server 25, and the accuracy can be improved by performing correction.

[0036] According to the embodiment described above, by generating an approximation curve, it is possible to estimate the flow direction and flow speed from the position information from the marine buoy 1. Therefore, unlike the case of measuring the flow speed using a sensor such as an ultrasonic current meter, maintenance (battery replacement, cleaning, etc.) is not required. Furthermore, although an ultrasonic current meter is required to generate the approximation curve, the ultrasonic current meter is not required after the approximation curve is generated, which allows for cost reduction.

[0037] Although the embodiment of the present invention has been specifically described above, the present invention is not limited to the above-mentioned embodiment, and various modifications based on the technical concept of the present invention are possible. For example, the place where the marine buoy 1 is moored is not limited to the seabed, but may be a fixed part such as a pier at a port. In addition, the marine buoy 1 may have some functions of a cloud server, such as a pre-processing server function. The configurations, methods, steps, shapes, materials, and values ​​given in the above-mentioned embodiment are merely examples, and different configurations, methods, steps, shapes, materials, and values ​​may be used as necessary. [Explanation of symbols]

[0038] 1···Marine buoy, 2···Cloud server, 11···Sandbag, 12a, 12b, 12c, 14a, 14b···Rope, 13···Buoy, 21···Location information receiving server, 22···Database server, 24···Analysis server, 25···AI correction server, 26···Analysis database

Claims

1. A method for estimating oceanographic information using a marine buoy that is moored to a fixed part, moves in accordance with the sea surface, has an antenna and a GNSS receiver, and is configured to obtain position information by the GNSS receiver, comprising: Calculating a direction from the position information of the installation point P0 of the marine weather buoy and the position information of the position Pt of the marine weather buoy; Calculating a second-order difference value of the time series of the orientation; Calculating the extreme value of the second difference value; Calculating the product of adjacent extreme values; The flow velocity is estimated from the product of the extreme values ​​and the approximate curve of the measured flow velocity. Sea state information estimation method.

2. The method for estimating oceanographic information according to claim 1 , wherein the measured current speed is measured separately at a location where the oceanographic buoy is installed.

3. 3. The method for measuring oceanographic information according to claim 1 or 2, wherein the coordinates of the positions of the oceanographic buoys have been subjected to noise removal processing.

4. 3. The method for measuring oceanographic information according to claim 1, further comprising the step of correcting the estimated current velocity.

5. A sea state information estimation device using a sea state buoy that is moored to a fixed part, moves along with the sea surface, has an antenna and a GNSS receiver, and is configured to obtain position information by the GNSS receiver, Calculating a direction from the position information of the installation point P0 of the marine weather buoy and the position information of the position Pt of the marine weather buoy; Calculating a second-order difference value of the time series of the orientation; Calculating the extreme value of the second difference value; Calculating the product of adjacent extreme values; The flow velocity is estimated from the product of the extreme values ​​and the approximate curve of the measured flow velocity. Ocean condition information estimation device.

6. The oceanographic information estimation device according to claim 5 , wherein the measured current speed is measured separately at the installation point of the oceanographic buoy.

7. 7. The oceanographic information measuring device according to claim 5 or 6, wherein the coordinates of the positions of the oceanographic buoys have been subjected to noise removal processing.

8. 7. The oceanographic information measuring device according to claim 5, wherein the estimated current velocity is corrected.

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