JP7797735B2 - Wave amplitude estimation method, amplitude estimation device, and program - Google Patents

Description

The present invention relates to a wave amplitude estimation method, an amplitude estimation device, and a program.

Wave height meters are used to monitor water level fluctuations in real time in the sea areas surrounding construction sites. There are various types of wave height meters, including seabed-mounted types, airborne emission types, and buoy types.

A seafloor-mounted wave height meter is a type of wave height meter that uses ultrasonic radiation devices and water pressure sensors from the seabed to detect water surface fluctuations. Because a diver is required to install a seafloor-mounted wave height meter, it is difficult to install at great depths. Furthermore, because the ultrasonic radiation devices and water pressure sensors are located on the seafloor, they must be connected by cable to transmit the observation data to a work vessel on the ocean.

Airborne wave height meters emit ultrasonic waves from the air toward the water surface and detect water surface fluctuations from the reflection. However, if a workboat is moving, that movement must be taken into consideration. Also, because the waves need to be emitted at a right angle toward the water surface, it is difficult to maintain a right-angle emission angle due to the movement of the vessel.

A buoy-type wave height meter is a type of wave height meter that uses a buoy (also called a float) floating on the water surface to detect water surface fluctuations. Buoy-type wave height meteres include those that use the Global Navigation Satellite System (GNSS) and those that use acceleration sensors.

Buoy-type wave height meters that use GNSS can obtain elevation information from GNSS, but depending on the required accuracy, the equipment can become large.

A buoy-type wave height meter that uses an acceleration sensor measures vertical acceleration using an acceleration sensor attached to the buoy, and estimates water level fluctuations by double-integrating this acceleration over time.

For example, Patent Document 1 describes a wave observation device that uses an acceleration sensor and is configured to obtain velocity components by integrating the output of an acceleration sensor, or to obtain displacement components by further integrating those velocity components.The wave observation device is characterized in that the extracted velocity or displacement components are passed through a high-pass filter with a required passband to remove trend components that are superimposed on those components.

Japanese Unexamined Patent Publication No. 61-212716

However, in order to estimate water level fluctuations using the method of double-integrating acceleration over time, a relatively high-precision acceleration sensor is required.

One of the purposes of the present invention is to estimate wave height, or wave amplitude, without integrating acceleration time series data that shows the time-dependent change in measured values of vertical acceleration experienced by floating objects on the water due to the up and down movement of the water surface.

The amplitude estimation method according to claim 1 of the present invention is a wave amplitude estimation method comprising: an acceleration acquisition step of acquiring acceleration time series data indicating changes over time in measured values of vertical acceleration that a floating object on the water experiences due to the up and down movement of the water surface; a period determination step of determining the period of the change over time in acceleration indicated by the acceleration time series data; and an amplitude estimation step of estimating the wave amplitude corresponding to the period determined in the period determination step, in accordance with the relationship between the wave amplitude and period.

The amplitude estimation method according to claim 2 of the present invention is an amplitude estimation method in the aspect of claim 1, wherein the period identification step includes a time interval calculation step of calculating the time interval at which the time-varying acceleration indicated by the acceleration time-series data changes from a negative value to a positive value, and a statistical value calculation step of calculating, as the period, the statistical value of a predetermined number of consecutive time intervals on the time axis calculated in the time interval calculation step.

The amplitude estimation method according to claim 3 of the present invention is an amplitude estimation method in the aspect of claim 1, wherein the period identification step includes a time interval calculation step of calculating the time interval at which the time-varying acceleration indicated by the acceleration time-series data changes from a positive value to a negative value, and a statistical value calculation step of calculating, as the period, the statistical value of a predetermined number of consecutive time intervals on the time axis calculated in the time interval calculation step.

The amplitude estimation method according to claim 4 of the present invention is an amplitude estimation method according to any one of claims 1 to 3, which uses the relationship that the wave amplitude is the value obtained by multiplying the amplitude of the acceleration by the square of the period of the acceleration and dividing the result by four times the square of pi.

The amplitude estimation method according to claim 5 of the present invention is an amplitude estimation method according to any one of claims 1 to 4, which includes a smoothing step of smoothing the change over time in acceleration indicated by the acceleration time series data over a predetermined period, and the period identification step of identifying the period from the change over time in acceleration smoothed in the smoothing step.

The amplitude estimation device according to claim 6 of the present invention is a wave amplitude estimation device comprising: acceleration acquisition means for acquiring acceleration time series data indicating changes over time in measured values of vertical acceleration that a floating object on the water experiences due to the up and down movement of the water surface; period determination means for determining the period of the change over time in acceleration indicated by the acceleration time series data; and amplitude estimation means for estimating the wave amplitude corresponding to the period determined by the period determination means, in accordance with the relationship between the wave amplitude and period.

The program according to claim 7 of the present invention causes a computer to execute the following processes: acquiring acceleration time series data indicating changes over time in measured values of vertical acceleration experienced by floating objects on the water due to the up and down movement of the water surface; identifying the period of the change over time in acceleration indicated by the acceleration time series data; and estimating the wave amplitude corresponding to the period identified in the period identification process, in accordance with the relationship between the wave amplitude and period.

According to the present invention, wave amplitude can be estimated without integrating acceleration time series data that indicates the time-dependent change in measured values of vertical acceleration experienced by floating objects on the water due to the up and down movement of the water surface.

FIG. 1 is a schematic diagram showing an example of the overall configuration of an amplitude estimation system 9. FIG. 1 is a diagram showing an example of the configuration of an amplitude estimation device 1. FIG. 2 is a diagram showing an example of the configuration of a terminal 2; FIG. 2 is a diagram showing an example of the functional configuration of the amplitude estimation device 1. FIG. 3 is a flowchart showing an example of the operation flow of the amplitude estimation device 1. 5A and 5B are diagrams showing examples of time-series data acquired or calculated by the amplitude estimation device.

<Overall configuration of the amplitude estimation system>
Fig. 1 is a schematic diagram showing an example of the overall configuration of an amplitude estimation system 9. The amplitude estimation system 9 includes an amplitude estimation device 1 and a terminal 2. The amplitude estimation system 9 shown in Fig. 1 also includes a communication line 3.

The water surface Lv is the surface of the ocean or lake, and moves up and down vertically due to the action of waves. Floating objects J are structures such as buoys that float on the water. Floating objects J move vertically in conjunction with the up and down movement of the water surface Lv.

Terminal 2 is attached to floating object J. Therefore, together with floating object J, terminal 2 is subjected to vertical forces due to the up and down movement of the water surface Lv. Terminal 2 has the function of measuring at least vertical acceleration, and generates acceleration time series data that shows changes in the measured acceleration values over time, and supplies this to amplitude estimation device 1.

The amplitude estimation device 1 is an information processing device, such as a computer, that estimates the amplitude of waves occurring on the water surface Lv. The amplitude estimation device 1 acquires the above-mentioned acceleration time series data from the terminal 2. The amplitude estimation device 1 then identifies the period of the change in acceleration over time indicated by the acquired acceleration time series data, and estimates the wave amplitude using the identified period in accordance with a predetermined relationship.

The communication line 3 is a line that wirelessly connects the amplitude estimation device 1 and the terminal 2 so that they can communicate with each other. The terminal 2 transmits the acceleration time series data that it generates to the amplitude estimation device 1 via this communication line 3. The communication line 3 may be, for example, a line that uses LPWA (Low Power Wide Area).

Examples of LPWA include "ELTRES (registered trademark)," "LoRa (registered trademark)," "LoRaWAN (registered trademark)," "RPMA (registered trademark)," "SIGFOX (registered trademark)," "EnOcean (registered trademark) Long Range," "NB-IoT," "NB-Fi Protocol," "GreenOFDM," "DASH7," "Wi-SUN," "Weightless-P," "LTE-MTC," "LTE Cat.0," and "LTE Cat.M1."

<Configuration of Amplitude Estimation Device>
2 is a diagram showing an example of the configuration of the amplitude estimation device 1. The amplitude estimation device 1 has a processor 11, a memory 12, and an interface 13. The processor 11 controls the amplitude estimation device 1 by executing a computer program (hereinafter simply referred to as a program) stored in the memory 12. The processor 11 is, for example, a CPU (Central Processing Unit).

The interface 13 is an interface through which the processor 11 exchanges information with the communication line 3 and other external devices.

The processor 11 connects to the communication line 3 via the interface 13 and acquires the acceleration time series data generated by the terminal 2 from the communication line 3.

Furthermore, the amplitude estimation device 1 is connected to, for example, an external display device via the interface 13, and displays the determined information to the user.

Memory 12 is a storage device such as RAM (Random Access Memory), ROM (Read Only Memory), a solid-state drive, or a hard disk drive, and stores the operating system, various programs, data, etc. that are loaded into processor 11.

<Device configuration>
3 is a diagram showing an example of the configuration of the terminal 2. The terminal 2 includes a processor 21, a memory 22, an interface 23, and an acceleration sensor 26.

The processor 21 controls the terminal 2 by executing programs stored in the memory 22. The processor 21 is, for example, a CPU.

The interface 23 is an interface through which the processor 21 exchanges information with the communication line 3 and other external devices.

The processor 21 connects to the communication line 3 via the interface 23 and transmits the acceleration time series data to the amplitude estimation device 1 via the communication line 3.

In addition, terminal 2 may be connected to an external storage device, such as a flash memory, via interface 23, and acceleration time series data, etc., may be stored in this storage device.

Memory 22 is a storage device such as RAM, ROM, a solid-state drive, or a hard disk drive, and stores the operating system, various programs, data, etc. that are loaded into processor 21.

The acceleration sensor 26 is a sensor that measures acceleration using, for example, a MEMS (Micro Electro Mechanical Systems) method. The acceleration sensor 26 measures at least the vertical acceleration that it receives and stores the measured acceleration in the memory 22 sequentially. As a result, acceleration time series data indicating changes in the measured vertical acceleration over time is generated in the memory 22. As described above, this generated acceleration time series data is transmitted to the amplitude estimation device 1. Note that since the terminal 2 is attached to the floating object J, the acceleration measured by the processor 21 is the acceleration that the terminal 2 receives as well as the acceleration that the floating object J receives.

<Functional Configuration of Amplitude Estimation Device>
4 is a diagram showing an example of the functional configuration of the amplitude estimation device 1. The processor 11 of the amplitude estimation device 1 executes the above-mentioned program to function as acceleration acquisition means 111, smoothing means 112, period identification means 113, amplitude estimation means 114, and reference position identification means 115.

The acceleration acquisition means 111 acquires the above-mentioned acceleration time series data from the terminal 2 via the interface 13. In other words, the processor 11 functioning as this acceleration acquisition means 111 is an example of acceleration acquisition means that acquires acceleration time series data that indicates the change over time in the measured value of the vertical acceleration that a floating object on the water experiences due to the up and down movement of the water surface.

4 calculates the average value of acceleration over a relatively long predetermined period (hereinafter referred to as the first period), such as a period equivalent to approximately the most recent 100 waves (which may be non-integer waves such as 100.3 waves or 97.8 waves), based on the position that changes over time based on the acceleration time-series data transmitted from the terminal 2 and acquired by the acceleration acquisition means 111, and identifies a reference position of the water surface in the vertical direction (referred to as the reference position) by using this average value. In other words, the processor 11 functioning as this reference position identification means 115 is an example of a processor that executes a reference position identification step that calculates the average value of the acceleration that changes over time indicated by the acceleration time-series data over a predetermined period, and identifies the reference position of the water surface in the vertical direction based on this average value.

The smoothing means 112 reads the acceleration time series data acquired by the acceleration acquisition means 111 and stored in memory 12, and smooths the change in acceleration over time over a predetermined period indicated by this acceleration time series data. This predetermined period is a relatively short period (hereinafter referred to as the second period), for example, two seconds. In this case, the smoothing means 112 smooths the acceleration data actually measured by the terminal 2 by calculating the moving average value of the acceleration over the two seconds. Note that although the second period described above is two seconds, the second period need only be equal to or shorter than the period Ta described below, and is not limited to two seconds.

The period determination means 113 uses the acceleration time series data to determine the period of time-varying vertical acceleration that a floating object J on the water experiences due to the up and down movement of the water surface. In other words, the processor 11 functioning as the period determination means 113 is an example of a period determination means that determines the period of time-varying acceleration indicated by the acceleration time series data. The period determination means 113 shown in Figure 4 determines the period of time-varying acceleration smoothed by the smoothing means 112.

Note that the period determination means 113 shown in FIG. 4 includes a time interval calculation means 113a and a statistical value calculation means 113b.

The time interval calculation means 113a shown in Figure 4 identifies the timings at which the acceleration smoothed by the smoothing means 112 undergoes a predetermined change, and calculates the time interval between those timings.

For example, the time interval calculation means 113a uses the zero point of acceleration (the average value of acceleration for the first period) corresponding to the reference position identified by the reference position identification means 115, and the so-called zero-down crossing points where the acceleration changes from positive to negative, to calculate the time interval for each wave sandwiched between two adjacent zero-down crossing points. In other words, the processor 11 functioning as the time interval calculation means 113a is an example of a processor that executes a time interval calculation step that calculates the time interval between the timing at which the acceleration that changes over time, indicated by the acceleration time series data, changes from a positive value to a negative value.

The statistical value calculation means 113b shown in FIG. 4 calculates statistical values for a predetermined number of consecutive time intervals on the time axis calculated by the time interval calculation means 113a as the period of change in acceleration over time. This statistical value calculation means 113b, for example, calculates the average value of the most recent three time intervals calculated in the past as the period of change in acceleration over time.

The amplitude estimation means 114 estimates the wave amplitude corresponding to the period identified by the period identification means 113, in accordance with the relationship between the wave amplitude and the period of the change in acceleration over time. For example, the relationship between the wave amplitude and the period of the change in acceleration over time can be expressed as follows: the wave amplitude is the value obtained by multiplying the acceleration amplitude by the square of the period of this acceleration, and dividing the result by four times the square of pi.

The amplitude estimation means 114 transmits the estimated wave amplitude information via the interface 13 to, for example, an external display device, and displays it.

<Operation of Amplitude Estimation Device>
5 is a flow diagram showing an example of the operation flow of the amplitude estimation device 1. The processor 11 of the amplitude estimation device 1 acquires acceleration time-series data (step S101) and smooths the change over time of the acceleration indicated by the acquired acceleration time-series data over a second period (e.g., 2 seconds). This smoothing is performed, for example, by calculating the arithmetic mean value of the acceleration measured over the second period (step S102).

Note that the above-mentioned step S101 is an example of an acceleration acquisition process that acquires acceleration time series data that indicates the change over time in the measured value of the vertical acceleration that a floating object on the water experiences due to the up and down movement of the water surface.

Furthermore, step S102 described above is an example of a smoothing process that smooths the change in acceleration over a predetermined period of time indicated by the acceleration time series data.

6A and 6B are diagrams showing examples of time-series data acquired or calculated by the amplitude estimation device. The measured acceleration _a0 shown in Fig. 6A is a curve showing the change over time in acceleration measured by the acceleration sensor 26 of the terminal 2. The horizontal axis of the graph shown in Fig. 6A represents time, and the vertical axis represents the acceleration value. Note that this measured acceleration _a0 is obtained by multiplying the measured acceleration by -1, with the sign reversed.

The smoothed acceleration a _ave shown in Fig. 6(a) is the arithmetic mean of the above-mentioned values of _a0 for two seconds, which is a so-called moving average. That is, the smoothed acceleration a _ave shown in Fig. 6(a) is obtained by smoothing the actually measured acceleration _a0 for a predetermined period.

Meanwhile, in parallel with the execution of the process of step S102, processor 11 executes the processes of the following steps S103 and S104 to determine the period for estimating the wave amplitude. That is, processor 11 calculates the average value of the acceleration indicated by the acceleration time series data acquired in step S101 over a first period (e.g., the most recent 100 waves) (step S103), and uses this average value to identify the reference position of the water surface indicated by the position time series data (step S104).

Next, as shown in FIG. 5, the processor 11 calculates the time interval at which the smoothed acceleration undergoes a predetermined change (step S105). An example of the predetermined change is the timing of the zero-down crossing point described above.

Processor 11 calculates (identifies) the statistical values of a predetermined number of consecutive time intervals from the calculated time intervals as the period of the change in acceleration over time (step S106). This step S106 is an example of a period identification process that identifies the period of the change in acceleration over time indicated by the acceleration time series data.

For example, since the graph shown in FIG. 6A has reversed positive and negative values, times t0, t1, t2, t3, and t4 are all times when the value of the smoothed acceleration a _ave described above changes from positive to negative.

Here, period T1 is the time interval from time t0 to time t1, and period T2 is the time interval from time t1 to time t2. Furthermore, period T3 is the time interval from time t2 to time t3, and period T4 is the time interval from time t3 to time t4. The processor 11 calculates periods T1, T2, T3, and T4 at times t1, t2, t3, and t4, respectively.

That is, step S106 is an example of a period determination step that includes a time interval calculation step of calculating the time interval at which the acceleration that changes over time and is indicated by the acceleration time-series data changes from a positive value to a negative value.

Next, during period T4, before time t4, processor 11 calculates period Ta, which is the period of the change in acceleration over time corresponding to periods T1 to T3. Processor 11 then uses this period Ta to predict in real time the waves that will occur during period T4. Similarly, for the period after time t4, processor 11 calculates the arithmetic mean value of the last three periods and predicts the amplitude of the waves that will occur during the period until the next zero-down crossing point.

Note that the arithmetic mean value in the time interval process was calculated over the most recent three periods, but this is not a limitation and it can be calculated over one or more recent periods.

The period Ta is calculated as the arithmetic mean value of periods T1, T2, and T3 using the following equation (1): In other words, step S106 is an example of a period determination process that includes a statistical value calculation process that calculates statistical values for a predetermined number of consecutive time intervals on the time axis calculated in the time interval calculation process as the period of the change in acceleration over time.

[Equation 1]
Ta = (T1+T2+T3)/3...(1)

The processor 11 then estimates the amplitude of the wave according to the calculated period Ta (step S107). The estimated displacement z _est shown in FIG. 6B is a value obtained by estimating the actual displacement z from the smoothed acceleration a _ave . For example, the estimated displacement z _est is calculated by multiplying the smoothed acceleration a _ave by the square of the acceleration period Ta and dividing the result by four times the square of pi π. In this case, the estimated displacement z _est is calculated according to the following equation (2) using the smoothed acceleration a _ave , the period Ta, and pi π. Note that, as described above, the actual measured acceleration a ₀ is calculated in advance by reversing the sign of the measured value, so there is no negative sign in equation (2).

[Equation 2]
z _est = (Ta ² /4π ² )×a _ave …(2)

This step S107 is an example of an amplitude estimation process that estimates the amplitude of the wave according to the period identified in the period identification process.

By executing the processes from step S101 to step S107 described above, the processor 11 estimates the amplitude of waves occurring on the water surface that changes over time. In other words, the amplitude estimation device 1 is a device that performs a wave amplitude estimation method that includes the processes from step S101 to step S107 described above.

Through the above operations, the amplitude estimation device 1 calculates the period of the changes in the most recent three accelerations over time from the acceleration time series data, and can estimate the changes in the water surface displacement over time from the changes in acceleration over time. High waves that threaten the safety of marine work are known to strike in succession to a certain extent. By taking into account the characteristics of the most recent waves, the amplitude estimation device 1 described above makes it possible to estimate the wave amplitude that contributes to work safety.

<Modification>
The above is a description of the embodiment, but the contents of this embodiment can be modified as follows: In addition, the following modifications may be combined.

<1>
In the above-described embodiment, when functioning as the time interval calculation means 113a, the processor 11 identifies so-called zero-down crossing points where the acceleration changes from positive to negative, and calculates the time interval for each wave sandwiched between two adjacent zero-down crossing points, but it may also identify the timing of other changes and calculate the time interval.

For example, when functioning as the time interval calculation means 113a, the processor 11 may identify so-called zero-up crossing points where acceleration changes from negative to positive. In this case, the processor 11 may calculate the time interval for each wave sandwiched between two adjacent zero-up crossing points. In this case, the processor 11 is an example of a processor that executes a time interval calculation step that calculates the time interval at which the acceleration that changes over time, indicated by the acceleration time series data, changes from a negative value to a positive value.

<2>
In the above-described embodiment, when functioning as the smoothing means 112, the processor 11 smoothes the acceleration data actually measured by the terminal 2 by calculating a moving average value of the acceleration measured over a predetermined period, such as two seconds. However, smoothing may not be performed. In this case, the period determination means 113 may simply determine the period of the change over time in the acceleration measured by the terminal 2.

<3>
In the above-described embodiment, the terminal 2 has the acceleration sensor 26, but as long as the acceleration in the direction of change of the water surface Lv can be measured along the time axis, it does not have to have the acceleration sensor 26. Furthermore, the terminal 2 is attached to a floating object J, but the terminal 2 itself may be configured to float on the water.

＜4＞
In the above-described embodiment, the amplitude estimation device 1 and the terminal 2 are connected to each other via the communication line 3 and exchange information, but they may exchange information without using the communication line 3. For example, the interface 13 of the amplitude estimation device 1 and the interface 23 of the terminal 2 both have a short-range wireless communication function, and the amplitude estimation device 1 and the terminal 2 may exchange information via this short-range wireless communication.

Furthermore, the amplitude estimation device 1 does not have to acquire acceleration time series data from the terminal 2 in real time. For example, the amplitude estimation device 1 may acquire the acceleration time series data stored in the memory 22 of the terminal 2 via the interface 23 and a wired cable connecting the interface 13. Furthermore, the terminal 2 may copy the acceleration time series data stored in the memory 22 to an external flash memory or the like via the interface 23. In this case, the amplitude estimation device 1 simply acquires a copy of the acceleration time series data described above from the flash memory or the like.

<5>
The program executed by the processor 11 described above may be provided in a state stored in a computer-readable recording medium, such as a magnetic recording medium such as a magnetic tape or a magnetic disk, an optical recording medium such as an optical disk, a magneto-optical recording medium, or a semiconductor memory. Alternatively, the program may be downloaded via a communication line such as the Internet. That is, the program causes a computer to execute the following processes: acquiring acceleration time-series data indicating changes over time in measured values of vertical acceleration experienced by floating objects on the water due to the up and down movement of the water surface; identifying the period of the acceleration change over time indicated by the acceleration time-series data; and estimating the wave amplitude corresponding to the period identified in the period identification process, based on the relationship between the wave amplitude and the period. Note that various devices other than a CPU may be used as the control means exemplified by the amplitude estimation device described above; for example, a dedicated processor may be used.

1...amplitude estimation device, 11...processor, 111...acceleration acquisition means, 112...smoothing means, 113...period determination means, 113a...time interval calculation means, 113b...statistical value calculation means, 114...amplitude estimation means, 115...reference position determination means, 12...memory, 13...interface, 2...terminal, 21...processor, 22...memory, 23...interface, 26...acceleration sensor, 3...communication line, 9...amplitude estimation system, Lv...water surface, J...floating matter, T1-T4...period, t0-t4...time.

Claims (6)

Acquire acceleration time series data that shows the time-dependent change in measured values of vertical acceleration that floating objects receive from waves,
smoothing the change in acceleration over time indicated by the acceleration time series data;
Identifying a period of the smoothed acceleration change over time;
a method for calculating an estimated value of displacement of the floating object from a reference position at a predetermined time in accordance with a predetermined calculation formula using the acceleration at a predetermined time among the smoothed time-varying acceleration and the period. The method according to claim 1, wherein the predetermined calculation formula indicates a relationship in which, when the period is Ta, the acceleration at the predetermined time is _aave , and the estimated value of the displacement is _z , _z is a value obtained by multiplying a by the _square of Ta and dividing the result by four times the square of pi. The method according to claim 1 , wherein the period is a time length of a period corresponding to one of the most recent waves at the predetermined time indicated by the change over time of the smoothed acceleration. The method according to claim 1 , wherein the period is a statistical value of the duration of each of a plurality of most recent consecutive waves at the predetermined time indicated by the change over time of the smoothed acceleration. Acquire acceleration time series data that shows the time-dependent change in measured values of vertical acceleration that floating objects receive from waves,
smoothing the change in acceleration over time indicated by the acceleration time series data;
Identifying a period of the smoothed acceleration change over time;
an estimation device that calculates an estimated value of displacement of the floating object from a reference position at a predetermined time according to a predetermined calculation formula using the acceleration at a predetermined time among the smoothed time-varying acceleration and the period. On the computer,
A process of acquiring acceleration time series data showing changes over time in measured values of vertical acceleration that floating objects receive due to waves;
A process of smoothing the change over time in acceleration indicated by the acceleration time series data;
identifying a period of the smoothed acceleration change over time;
a process of calculating an estimated value of displacement of the floating object from a reference position at a predetermined time in accordance with a predetermined calculation formula using the acceleration at a predetermined time among the accelerations that change over time and the period;
A program to execute.