A remote control triggering method for collecting water samples in near-shore sea areas

Abstract

The application discloses a kind of offshore sea area water sample collection's remote control triggering method, it is related to marine environmental monitoring technical field, including: obtaining nearshore wind direction parameter;Based on nearshore wind direction parameter is distributed and is collected, and obtains multiple live parameter database;Obtain the triggering collection parameter of water sample collection equipment;Based on nearshore wind direction parameter, multiple live parameter database and triggering collection parameter, control water sample collection equipment executes collection operation;The application is used to solve the existing offshore sea area water sample collection's remote control triggering method in, in water sample collection point position matching aspect, lack of method based on time delay, equipment moving rate and water flow rate collaborative calculation target intersection point, to cause sampling position and original target water body deviate, lead to the problem that initial water sample to be collected cannot be accurately captured.

Description

Technical Field

[0001] This invention relates to the field of marine environmental monitoring technology, specifically a remote control triggering method for collecting water samples in nearshore waters. Background Technology

[0002] Nearshore water sampling is a core and fundamental step in marine environmental monitoring. It refers to the collection of representative seawater samples from nearshore sea areas according to standardized procedures for subsequent laboratory analysis and assessment of water quality and ecological conditions. Remote control triggering of nearshore water sampling refers to the technical mode in which operators send instructions to the sampling equipment via wireless signals to control the sampling action and complete the water sample collection.

[0003] Existing methods for remote-controlled water sampling in nearshore waters typically rely on the wireless remote control and positioning navigation capabilities of drones. The drone is controlled to fly to the sampling point in the nearshore waters and hover, then a remote command is issued to lower the sampling equipment to the designated water depth to complete the water sample acquisition. This achieves non-contact remote-controlled water sampling. While this improved method allows for unobstructed sampling of the target water body, it lacks a method for calculating the target intersection point based on time delay, equipment movement speed, and water flow velocity. This results in a deviation between the sampling location and the original target water body, and ineffective sampling when the water flow velocity is high. This leads to the inability to accurately capture the initial water sample, as illustrated in patent application CN107063755A. The patent application discloses a method for collecting water samples using unmanned aerial vehicles (UAVs). This method utilizes a UAV to fly directly to a target point and remotely control the collection of water samples, without being limited by geographical environment. It has the advantages of high efficiency and high accuracy in water sample collection. However, improvements to other remote control triggering methods for nearshore water sample collection usually focus on optimizing the collection device. In terms of water sample collection point matching, there is still a lack of a method for calculating the target intersection point based on time delay, equipment movement speed, and water flow velocity. This results in the sampling location deviating from the original target water body, and ineffective collection of the target water body when the water flow velocity is high, leading to the problem of inaccurate capture of the initial water sample to be collected. In view of this, it is necessary to improve the existing remote control triggering methods for nearshore water sample collection. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art by proposing a remote control triggering method for nearshore water sampling. This method addresses the lack of a method for calculating the target intersection point based on time delay, equipment movement speed, and water flow velocity in existing remote control triggering methods for nearshore water sampling. This results in a deviation between the sampling location and the original target water body, and ineffective sampling of the target water body when the water flow velocity is high, leading to the inability to accurately capture the initial water sample to be collected.

[0005] To achieve the above objectives, this application provides a remote control triggering method for nearshore water sample collection, comprising the following steps: The environment of the nearshore sea area is monitored, and nearshore wind direction parameters are obtained based on the monitoring results; the water bodies in the nearshore sea area are collected in a distributed manner based on the nearshore wind direction parameters, and a multi-real-time parameter database is obtained based on the distributed collection results; Remote triggering simulation was conducted on water sampling equipment in nearshore waters, and the triggering and acquisition parameters of the water sampling equipment were obtained based on the simulation results. The triggering and acquisition parameters include response start parameters and path acquisition parameters. When collecting water samples from nearshore waters, the water sampling equipment is controlled to perform the sampling operation based on real-time monitoring of nearshore wind direction parameters, a database of multiple real-time parameters, and triggering sampling parameters.

[0006] Furthermore, the environment of the nearshore waters is monitored, and nearshore wind direction parameters are obtained based on the monitoring results, including: Obtain the area corresponding to the nearshore sea area on the map and denote it as the nearshore area; place the outline of the nearshore area in a Cartesian coordinate system with coordinate axes in meters; obtain the smallest circumcircle of the nearshore area in the Cartesian coordinate system and denote the midpoint of the smallest circumcircle as the nearshore midpoint; A wind speed and direction sensor is placed at the midpoint of the nearshore area, and the wind speed and direction sensor is used to monitor for a duration of T. The data of wind speed monitoring during the monitoring process is recorded as wind speed data, and the data of wind direction monitoring is recorded as wind direction data. The closed interval formed by the minimum and maximum wind speed values ​​in the wind speed data is denoted as the nearshore wind speed interval; the set of all different wind directions in the wind direction data is denoted as the nearshore wind direction set; and the nearshore wind speed interval and the nearshore wind direction set are denoted as the nearshore wind direction parameter.

[0007] Furthermore, distributed data collection was conducted on nearshore waters based on nearshore wind direction parameters, and a multi-real-time parameter database was obtained based on the distributed collection results, including: k points are uniformly acquired in the nearshore area and denoted as distributed sampling point FC1 to distributed sampling point FC2, respectively. kFor any distributed sampling point: a current velocity and direction meter is fixedly placed at the location of the distributed sampling point in the nearshore sea area, and is denoted as the parameter acquisition instrument of the distributed sampling point; Based on the parameter acquisition instrument with all distributed sampling points, the nearshore sea area is sampled t times using the multi-real-time acquisition method. A multi-real-time parameter database is constructed, which stores the point flow direction and point flow velocity corresponding to all distributed sampling points, the simulated wind speed, and the simulated wind direction after each distributed acquisition.

[0008] Furthermore, distributed acquisition includes: A wind speed and wind direction are randomly selected from the nearshore wind speed range and the nearshore wind direction set, and are respectively recorded as the collected simulated wind speed and collected simulated wind direction; a mobile marine wind simulation vehicle integrating variable frequency wind turbine, wind vane and meteorological sensor is used to conduct a wind field simulation in the nearshore area for a duration of T1, and the wind speed and wind direction during the simulation are respectively the collected simulated wind speed and collected simulated wind direction. When the mobile ocean wind simulator is used to simulate a wind field, the parameter acquisition instrument at the distributed sampling point is used to collect the water flow velocity and direction at the distributed sampling point, and the collected data are recorded as the flow velocity data and flow direction data of the distributed sampling point, respectively.

[0009] Furthermore, distributed acquisition also includes: For any distributed sampling point: the water flow direction that is recorded most frequently in the flow direction data of the distributed sampling point after the wind field simulation is recorded as the point flow direction corresponding to the collected simulated wind speed and collected simulated wind direction; the average flow velocity of all flow velocities recorded in the flow velocity data of the distributed sampling point after the wind field simulation is recorded as the point flow velocity corresponding to the collected simulated wind speed and collected simulated wind direction. Acquire all distributed sampling points and the simulated wind speed, as well as the point flow direction and point flow velocity corresponding to the simulated wind direction.

[0010] Furthermore, the remote control trigger simulation includes: For any distributed acquisition where the simulated wind speed and simulated wind direction are α and β respectively: For distributed sampling points FC1 to distributed sampling points FC k Any distributed sampling point FC in j When the water sampling device is in its initial position, at any time t1 during the distributed sampling process, a sampling command is sent to the water sampling device, and the sampling target point is the distributed sampling point FC. j , where j is a positive integer less than or equal to k and greater than or equal to 1, and the initial position is the location where the water sampling equipment is deployed in the nearshore waters; The moment when the water sampling device starts up at rated power after the acquisition command is sent is recorded as t2, and the moment when the water sampling device arrives at the distributed sampling point FC is recorded as t2. j The time is denoted as t3; Let the value of t2 minus t1 be denoted as the distributed sampling point FC. j The corresponding device response time; the average speed of the water sample collection device between t2 and t3 is denoted as the distributed sampling point FC. j The corresponding acquisition path speed.

[0011] Furthermore, the remote-controlled trigger simulation also includes: The average response time of all devices corresponding to all distributed sampling points is recorded as the average response parameter; the acquisition path speed corresponding to all distributed sampling points is recorded as the average acquisition speed. The average value of all average response parameters obtained from all distributed acquisitions is recorded as the response start parameter; the average acquisition speed corresponding to all distributed acquisitions is recorded as the path acquisition parameter.

[0012] Furthermore, when collecting water samples from nearshore waters, the water sampling equipment is controlled to perform sampling operations based on real-time monitored nearshore wind direction parameters, a multi-real-time parameter database, and trigger sampling parameters, including: When collecting water samples from nearshore waters, wind speed and direction are acquired in real time based on wind speed and direction sensors at the midpoint of the nearshore area, and recorded as real-time wind speed and real-time wind direction, respectively. Obtain the angle between all the simulated wind directions and the real-time wind directions recorded in the multi-real-time parameter database, and sort all the simulated wind directions from smallest to largest based on the angle; obtain the absolute value of the difference between all the simulated wind speeds and the real-time wind speeds recorded in the multi-real-time parameter database, and sort all the simulated wind speeds from smallest to largest based on the absolute value. For any distributed acquisition corresponding to the acquisition simulation wind speed and acquisition simulation wind direction, the sum of the number of digits of the acquisition simulation wind speed in the sorting and the number of digits of the acquisition simulation wind direction in the sorting is recorded as the real-world similarity number of the distributed acquisition. Obtain the real-world similarity number of all distributed acquisitions, and denote the distributed acquisition corresponding to the smallest real-world similarity number as the real-world similar acquisition; denote the acquired simulated wind speed and acquired simulated wind direction in the real-world similar acquisition as α1 and β1, respectively.

[0013] Furthermore, when collecting water samples from nearshore waters, the control of the water sampling equipment to perform sampling operations, based on real-time monitored nearshore wind direction parameters, a multi-real-time parameter database, and triggering sampling parameters, also includes: The average acquisition speed corresponding to the real-world similar acquisition in the path acquisition parameters is recorded as the real-world device speed. In the nearshore area, the points where water samples need to be collected are marked and recorded as the sampling points; the distributed sampling points that are closest to the sampling points in a straight line are recorded as the feature sampling points, and the point flow direction and point flow velocity corresponding to the feature sampling points and α1 and β1 in the multi-real-time parameter database are recorded as the real-time flow direction and real-time flow velocity of the feature sampling points, respectively.

[0014] Furthermore, when collecting water samples from nearshore waters, the control of the water sampling equipment to perform sampling operations, based on real-time monitored nearshore wind direction parameters, a multi-real-time parameter database, and triggering sampling parameters, also includes: When collecting data from the point to be collected, a point γ is obtained in the area where the nearshore area is located, such that γ satisfies both conditions 1 and 2. The Bluetooth module is used to send a collection command to the water sample collection device to collect data from the target point γ. When there are multiple γ points, the γ point closest to the point to be collected is set as the target collection point. Condition 1 is: when the point to be collected is taken as the starting point, the real-time flow direction is taken as the direction, and the real-time flow velocity is taken as the speed, the point to be collected can reach γ after time t4. Condition 2 is: when the initial position of the water sampling device is taken as the starting point, the position of γ is taken as the direction, and the actual speed of the device is taken as the speed, the water sampling device can reach γ after time t5 from its initial position, where t5 is t4 minus the response start parameter.

[0015] The beneficial effects of this invention are as follows: This application first monitors the environment of the nearshore sea area and obtains nearshore wind direction parameters based on the monitoring results; it then conducts distributed data collection on the water body in the nearshore sea area based on the nearshore wind direction parameters, and obtains a multi-real-time parameter database based on the distributed data collection results. The advantage of this is that by monitoring the marine environment and obtaining nearshore wind direction parameters, and then building a real-time parameter database through distributed data collection, it can provide real and reliable basic data for the collaborative calculation of equipment response delay, movement speed, and water flow velocity, thereby accurately predicting the water body migration trajectory and intersection point, effectively reducing the point calculation deviation, and ensuring the accuracy of subsequent target water sample collection. This application also conducts remote-controlled triggering simulations of water sampling equipment in nearshore waters and obtains the triggering parameters of the water sampling equipment based on the simulation results. Finally, when collecting water samples in nearshore waters, the water sampling equipment is controlled to perform sampling operations based on real-time monitored nearshore wind direction parameters, a multi-real-time parameter database, and triggering parameters. The advantage of this is that by remotely triggering simulations and determining the triggering parameters, the response and movement characteristics of the sampling equipment can be verified in advance by combining real-time wind direction and wind speed. This allows the parameters calculated subsequently to dynamically adapt to changes in water flow, accurately matching the actual moving speed of the equipment with the timing and location of water movement, thereby improving the accuracy of water sample capture and ensuring that the sampling equipment can directly and accurately sample the moved water. In addition, compared to other sampling schemes where the sampling equipment chases the moving water, directly moving the sampling equipment to the predicted water location can effectively improve sampling efficiency and avoid the problem of inaccurate sampling points when the sampling equipment chases the water. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the steps of the method of the present invention; Figure 2 This is a schematic diagram of the distributed acquisition process of the present invention; Figure 3 This is a schematic diagram showing the position of point γ in this invention; Figure 4 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 As shown, this application provides a remote control triggering method for nearshore water sample collection, comprising the following steps: Step S1: Monitor the environment of the nearshore sea area and obtain nearshore wind direction parameters based on the monitoring results; collect water bodies in the nearshore sea area in a distributed manner based on the nearshore wind direction parameters, and obtain a multi-real-time parameter database based on the distributed collection results. Step S1 includes: Step S101, obtaining the area corresponding to the nearshore sea area on the map and recording it as the nearshore area; placing the outline of the nearshore area in a Cartesian coordinate system with coordinate axes in m units, obtaining the smallest circumcircle of the nearshore area in the Cartesian coordinate system, and recording the midpoint of the smallest circumcircle as the nearshore midpoint. In the specific implementation process, if the shape of the nearshore area is relatively regular, the midpoint of the nearshore area can be directly obtained and recorded as the nearshore midpoint; the purpose of obtaining the smallest circumscribed circle is to obtain a relatively regular area that can effectively cover the nearshore area, so that the center of the smallest circumscribed circle can be used as the data collection point for the entire nearshore area. Step S102: Place a wind speed and wind direction sensor at the midpoint of the nearshore area and use the wind direction and wind speed sensor to monitor for a duration of T. Record the wind speed data and the wind direction data during the monitoring process as wind speed data. In the specific implementation process, the value of T can be determined according to the fluctuation of wind speed and wind direction in the nearshore area. If the fluctuation of wind speed and wind direction in the nearshore area is large, the value of T can be increased to obtain wind direction and wind speed data that are more in line with the actual situation in the nearshore area. In this embodiment, the value of T is set to 24h. Step S103: The closed interval formed by the minimum and maximum wind speed values ​​in the wind speed data is denoted as the nearshore wind speed interval; the set of all different wind directions in the wind direction data is denoted as the nearshore wind direction set; the nearshore wind speed interval and the nearshore wind direction set are denoted as the nearshore wind direction parameter.

[0019] Step S1 further includes: Step S103, uniformly acquiring k points in the nearshore area, and denoting them as distributed sampling point FC1 to distributed sampling point FC. k For any distributed sampling point: a current velocity and direction meter is fixedly placed at the location of the distributed sampling point in the nearshore sea area, and is denoted as the parameter acquisition instrument of the distributed sampling point; In the specific implementation process, the value of k can be determined according to the area of ​​the nearshore region and the actual data analysis capability. If the area of ​​the nearshore region is large and the actual data analysis capability is strong during the actual data collection, the value of k can be increased, so that the nearshore region can be collected in more detailed distributed data collection in subsequent analysis. In this embodiment, the value of k is set to 8. Step S104: Based on the parameter acquisition instrument of all distributed sampling points, use the multi-real-time acquisition method to perform t distributed acquisitions on the nearshore sea area; construct a multi-real-time parameter database, and store all distributed sampling points, the simulated wind speed, and the point flow direction and point flow velocity corresponding to the simulated wind direction after each distributed acquisition into the multi-real-time parameter database. In the specific implementation process, the value of t can be determined according to the size of the nearshore wind speed range and the nearshore wind direction set. If the amount of data in the nearshore wind speed range and the nearshore wind direction set is large, the value of t should be increased to ensure that all data in the nearshore wind speed range and the nearshore wind direction set are effectively analyzed. In the data analysis of this embodiment, after one data acquisition, the nearshore wind speed range is [4m / s, 10m / s], and the number of different wind directions in the nearshore wind direction set is 10. Therefore, the value of t can be set to 10 to ensure that all different wind directions in the nearshore wind direction set are collected once.

[0020] For step S105, please refer to... Figure 2 As shown, the distributed acquisition includes: step S1051, randomly acquiring a wind speed and wind direction from the nearshore wind speed range and the nearshore wind direction set, and recording them as the acquired simulated wind speed and the acquired simulated wind direction, respectively; based on a mobile marine wind simulation vehicle integrating a variable frequency wind turbine, a wind vane, and meteorological sensors, performing a wind field simulation for a duration of T1 in the nearshore area, and the wind speed and wind direction during the simulation are the acquired simulated wind speed and the acquired simulated wind direction, respectively; In the specific implementation process, the value of T1 can be determined according to the output power of the mobile ocean wind simulator. If the output power of the mobile ocean wind simulator is large, the wind field to be simulated can be quickly constructed in the nearshore area, so the value of T1 can be reduced, and the simulation can be stopped after the parameter acquisition instrument obtains valid data. If the output power of the mobile ocean wind simulator is small, the speed of constructing the wind field in the nearshore area is slow, so the value of T1 should be increased to ensure that the parameter acquisition instrument can effectively obtain the water flow velocity and direction at the distributed sampling points in the simulated wind field. In the analysis of this embodiment, the value of T1 is set to 30 min. Step S1052: When the mobile ocean wind simulator is simulating the wind field, the parameter acquisition instrument of the distributed sampling point is used to collect the water flow velocity and water flow direction at the distributed sampling point, and the collected data are recorded as the flow velocity data and flow direction data of the distributed sampling point, respectively.

[0021] Distributed acquisition also includes: step S1053, for any distributed sampling point: the water flow direction that is recorded most frequently in the flow direction data of the distributed sampling point after the wind field simulation is completed is recorded as the point flow direction corresponding to the distributed sampling point and the collected simulated wind speed and the collected simulated wind direction; the average flow velocity of all flow velocities recorded in the flow velocity data of the distributed sampling point after the wind field simulation is recorded as the point flow velocity corresponding to the distributed sampling point and the collected simulated wind speed and the collected simulated wind direction. In the data analysis of this embodiment, for example, in a distributed sampling of simulated wind speed and simulated wind direction of 4 m / s and due north, the point flow direction and point flow velocity of distributed sampling point FC5 are obtained as 10° east of north and 3.3 m / s, respectively. Then, the point flow direction and point flow velocity corresponding to the simulated wind speed "4 m / s" and simulated wind direction "due north" can be recorded as 10° east of north and 3.3 m / s in the multi-real-time parameter database. Step S1054: Obtain all distributed sampling points and the corresponding point flow direction and point flow velocity for the simulated wind speed and simulated wind direction.

[0022] Step S2: Perform remote triggering simulation of the water sampling equipment in the nearshore sea area, and obtain the triggering acquisition parameters of the water sampling equipment based on the simulation results. The triggering acquisition parameters include response start parameters and path acquisition parameters. Remote-triggered simulation includes: Step S201, for any distributed acquisition of simulated wind speed and simulated wind direction as α and β respectively: Step S202, for distributed sampling points FC1 to distributed sampling points FC k Any distributed sampling point FC in j When the water sampling device is in its initial position, at any time t1 during the distributed sampling process, a sampling command is sent to the water sampling device, and the sampling target point is the distributed sampling point FC. j , where j is a positive integer less than or equal to k and greater than or equal to 1, and the initial position is the location where the water sampling equipment is deployed in the nearshore waters; Step S203: Record the moment when the water sampling device starts up at rated power after the acquisition command is sent as t2, and record the arrival time of the water sampling device at the distributed sampling point FC. j The time is denoted as t3; Step S204: Subtract t1 from t2 and denote the value as the distributed sampling point FC. j The corresponding device response time; the average speed of the water sample collection device between t2 and t3 is denoted as the distributed sampling point FC. j The corresponding acquisition path speed; In the data analysis of this embodiment, for example, during a single data analysis, the distributed acquisition for remote-triggered simulation analysis involves: acquiring simulated wind speed and simulated wind direction at 4 m / s and due north, respectively. Analysis of distributed sampling point FC5 reveals that a acquisition command is sent to the water sampling device at 12:00:00, with the target point being distributed sampling point FC5; the water sampling device starts at rated power at 12:00:00:15; and the water sampling device arrives at distributed sampling point FC5. jThe time is 12:00:10.15; in addition, the distance between the initial position of the water sampling device and the distributed sampling point FC5 is 18m. Therefore, through data analysis, the device response time is 0.15s and the path sampling speed is 1.8m / s.

[0023] The remote control triggering simulation also includes: step S205, recording the average response time of the devices corresponding to all distributed sampling points as the average response parameter; and recording the acquisition path speed corresponding to all distributed sampling points as the average acquisition speed; Step S206: Obtain the average value of all average response parameters obtained from all distributed acquisitions and record it as the response start parameter; record the corresponding average acquisition speed of all distributed acquisitions as the path acquisition parameter; In the data analysis of this embodiment, for example, after one data analysis, the obtained response start parameter is 0.15s, and for distributed acquisition of simulated wind speed and simulated wind direction of 4m / s and due north, the obtained average acquisition speed is 2m / s.

[0024] Step S3: When collecting water samples from nearshore waters, the water sample collection equipment is controlled to perform the collection operation based on the nearshore wind direction parameters obtained from real-time monitoring, the multi-real-time parameter database, and the trigger collection parameters. Step S3 includes: Step S301, when collecting water samples in the nearshore sea area, wind speed and wind direction are acquired in real time based on the wind speed and wind direction sensor at the midpoint of the nearshore area, and recorded as real-time collected wind speed and real-time collected wind direction respectively. Step S302: Obtain the angle between all the collected simulated wind directions and the real-time collected wind directions recorded in the multi-real-time parameter database, and sort all the collected simulated wind directions from smallest to largest based on the angle; obtain the absolute value corresponding to the difference between all the collected simulated wind speeds and the real-time collected wind speeds recorded in the multi-real-time parameter database, and sort all the collected simulated wind speeds from smallest to largest based on the absolute value. In the data analysis of this embodiment, for example, during actual data acquisition, the real-time wind speed and direction are 4.1 m / s and due north, respectively. Then, by sorting all simulated wind directions and simulated wind speeds in the multi-real-time parameter database and obtaining the real-time similarity number of all distributed acquisitions, the distributed acquisition corresponding to the smallest real-time similarity number is: the distributed acquisition with simulated wind speed and simulated wind direction of 4 m / s and due north, respectively. In addition, by analyzing the location of the acquisition point, the characteristic sampling point obtained is the distributed sampling point FC5. Step S303: For any distributed acquisition corresponding to the acquisition simulation wind speed and acquisition simulation wind direction, the sum of the number of digits of the acquisition simulation wind speed in the sorting and the number of digits of the acquisition simulation wind direction in the sorting is recorded as the real-world similarity number of the distributed acquisition. Step S304: Obtain the real-world similarity number of all distributed acquisitions, and record the distributed acquisition corresponding to the smallest real-world similarity number as the real-world similar acquisition; record the acquisition simulated wind speed and acquisition simulated wind direction in the real-world similar acquisition as α1 and β1, respectively.

[0025] Step S3 also includes: Step S305, recording the average acquisition speed corresponding to the real-world similar acquisition in the path acquisition parameters as the real-world device speed; In the nearshore area, the points where water samples need to be collected are marked and recorded as the sampling points; the distributed sampling points that are closest to the sampling points in a straight line are recorded as the feature sampling points, and the point flow direction and point flow velocity corresponding to the feature sampling points and α1 and β1 in the multi-real-time parameter database are recorded as the real-time flow direction and real-time flow velocity of the feature sampling points, respectively.

[0026] In the data analysis of this embodiment, as summarized above, α1 and β1 can be denoted as 4 m / s and due north, respectively, and the actual equipment speed can be denoted as 2 m / s. The real-time flow direction and velocity of the characteristic sampling point can be denoted as 10° east of north and 3.3 m / s. Therefore, when collecting data from the sampling point, if there is a point γ in the nearshore area, satisfying condition 1: when starting from the sampling point, moving at 10° east of north, and with a speed of 3.3 m / s, the sampling point arrives at γ after 10 seconds; and simultaneously satisfying condition 2: when starting from the initial position of the water sampling device, moving at the position of γ, and with a speed of 2 m / s, the sampling device arrives at γ after 9.85 seconds; then it indicates that after setting γ as the target point for the water sampling device, when the water sampling device receives the instruction and arrives at γ, it can directly collect data from the water body originally located at the sampling point. Step S3 also includes: Step S306, please refer to Figure 3 As shown, when collecting data from the point to be collected, a point γ is obtained in the area where the nearshore area is located, so that γ satisfies both conditions 1 and 2. The Bluetooth module is used to send a collection command to the water sample collection device to collect data from the target point γ. When there are multiple γ, the γ closest to the point to be collected is set as the target collection point. In the specific implementation process, when there are multiple points γ, only the one closest to the point to be sampled should be set as the target sampling point to avoid the water body at point γ being too far away from the point to be sampled, which would result in a large difference between the water body at point γ and the water body at the original point to be sampled. After obtaining a point γ in the nearshore area that meets both conditions 1 and 2, the staff or the control tower can send a sampling command with point γ as the sampling target point to the water sampling equipment based on the Bluetooth module integrated in the water sampling equipment, thereby reducing the response time of the water sampling equipment and improving the sampling efficiency. Condition 1 is: when the point to be collected is taken as the starting point, the real-time flow direction is taken as the direction, and the real-time flow velocity is taken as the speed, the point to be collected can reach γ after time t4. Condition 2 is: when the initial position of the water sampling device is taken as the starting point, the position of γ is taken as the direction, and the actual speed of the device is taken as the speed, the water sampling device can reach γ after time t5 from its initial position, where t5 is t4 minus the response start parameter.

[0027] Example 2, please refer to Figure 4 As shown, Figure 4 A schematic diagram of an electronic device is provided, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, and the processor can call these instructions. When the processor executes a computer-readable instruction, it performs steps as described in a remote control triggering method for nearshore water sampling, to achieve the following functions: First, it monitors the environment of the nearshore waters and obtains nearshore wind direction parameters based on the monitoring results; second, it performs distributed sampling of water bodies in the nearshore waters based on the nearshore wind direction parameters and obtains a multi-real-time parameter database based on the distributed sampling results; third, it simulates remote control triggering of the water sampling device in the nearshore waters and obtains the triggering sampling parameters of the water sampling device based on the simulation results; finally, when sampling water in the nearshore waters, it controls the water sampling device to perform the sampling operation based on the real-time monitored nearshore wind direction parameters, the multi-real-time parameter database, and the triggering sampling parameters.

[0028] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0029] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute a remote control triggering method for nearshore water sample collection provided by the above methods. The method includes: firstly, monitoring the environment of the nearshore waters and obtaining nearshore wind direction parameters based on the monitoring results; secondly, distributing water samples in the nearshore waters based on the nearshore wind direction parameters and obtaining a multi-real-time parameter database based on the distributed collection results; thirdly, performing remote control triggering simulation of the water sample collection equipment in the nearshore waters and obtaining triggering collection parameters of the water sample collection equipment based on the simulation results; and finally, when collecting water samples in the nearshore waters, controlling the water sample collection equipment to perform collection operations based on the nearshore wind direction parameters obtained from real-time monitoring, the multi-real-time parameter database, and the triggering collection parameters.

[0030] Example 4: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the steps of the remote control triggering method for nearshore water sampling described above to achieve the following functions: First, it monitors the environment of the nearshore waters and obtains nearshore wind direction parameters based on the monitoring results; it performs distributed sampling of water bodies in the nearshore waters based on the nearshore wind direction parameters and obtains a multi-real-time parameter database based on the distributed sampling results; then, it performs remote control triggering simulation of the water sampling equipment in the nearshore waters and obtains the triggering sampling parameters of the water sampling equipment based on the simulation results; finally, when water sampling is performed in the nearshore waters, it controls the water sampling equipment to perform sampling operations based on the nearshore wind direction parameters, the multi-real-time parameter database, and the triggering sampling parameters obtained from real-time monitoring.

[0031] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0032] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0033] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A remote control triggering method for collecting water samples in near-shore marine areas, characterized in that, Includes the following steps: The environment of the nearshore sea area is monitored, and nearshore wind direction parameters are obtained based on the monitoring results; the water bodies in the nearshore sea area are collected in a distributed manner based on the nearshore wind direction parameters, and a multi-real-time parameter database is obtained based on the distributed collection results; Remote triggering simulation was conducted on water sampling equipment in nearshore waters, and the triggering and acquisition parameters of the water sampling equipment were obtained based on the simulation results. The triggering and acquisition parameters include response start parameters and path acquisition parameters. When collecting water samples from nearshore waters, the water sampling equipment is controlled to perform the sampling operation based on real-time monitoring of nearshore wind direction parameters, a database of multiple real-time parameters, and triggering sampling parameters.

2. The method of claim 1, wherein the method is a remote control triggering method for collecting water samples in a near-shore sea area. Monitoring the environment of nearshore waters and obtaining nearshore wind direction parameters based on the monitoring results includes: Obtain the area corresponding to the nearshore sea area on the map and denote it as the nearshore area; place the outline of the nearshore area in a Cartesian coordinate system with coordinate axes in meters; obtain the smallest circumcircle of the nearshore area in the Cartesian coordinate system and denote the midpoint of the smallest circumcircle as the nearshore midpoint; A wind speed and direction sensor is placed at the midpoint of the nearshore area, and the wind speed and direction sensor is used to monitor for a duration of T. The data of wind speed monitoring during the monitoring process is recorded as wind speed data, and the data of wind direction monitoring is recorded as wind direction data. The closed interval formed by the minimum and maximum wind speed values ​​in the wind speed data is denoted as the nearshore wind speed interval; the set of all different wind directions in the wind direction data is denoted as the nearshore wind direction set; and the nearshore wind speed interval and the nearshore wind direction set are denoted as the nearshore wind direction parameter.

3. The remote control triggering method for nearshore water sample collection according to claim 2, characterized in that, Distributed data collection was conducted on nearshore waters based on nearshore wind direction parameters, and a multi-real-time parameter database was obtained based on the distributed collection results, including: k points are uniformly acquired in the nearshore area and denoted as distributed sampling point FC1 to distributed sampling point FC2, respectively. k For any distributed sampling point: a current velocity and direction meter is fixedly placed at the location of the distributed sampling point in the nearshore sea area, and is denoted as the parameter acquisition instrument of the distributed sampling point; Based on the parameter acquisition instrument with all distributed sampling points, the nearshore sea area is sampled t times using the multi-real-time acquisition method. A multi-real-time parameter database is constructed, which stores the point flow direction and point flow velocity corresponding to all distributed sampling points, the simulated wind speed, and the simulated wind direction after each distributed acquisition.

4. The method of claim 3, wherein the method is characterized by, Distributed data collection includes: A wind speed and wind direction are randomly selected from the nearshore wind speed range and the nearshore wind direction set, and are respectively recorded as the collected simulated wind speed and collected simulated wind direction; a mobile marine wind simulation vehicle integrating variable frequency wind turbine, wind vane and meteorological sensor is used to conduct a wind field simulation in the nearshore area for a duration of T1, and the wind speed and wind direction during the simulation are respectively the collected simulated wind speed and collected simulated wind direction. When the mobile ocean wind simulator is used to simulate a wind field, the parameter acquisition instrument at the distributed sampling point is used to collect the water flow velocity and direction at the distributed sampling point, and the collected data are recorded as the flow velocity data and flow direction data of the distributed sampling point, respectively.

5. The remote control triggering method for nearshore water sampling according to claim 4, characterized in that, Distributed acquisition also includes: For any distributed sampling point: the water flow direction that is recorded most frequently in the flow direction data of the distributed sampling point after the wind field simulation is recorded as the point flow direction corresponding to the collected simulated wind speed and collected simulated wind direction; the average flow velocity of all flow velocities recorded in the flow velocity data of the distributed sampling point after the wind field simulation is recorded as the point flow velocity corresponding to the collected simulated wind speed and collected simulated wind direction. Acquire all distributed sampling points and the simulated wind speed, as well as the point flow direction and point flow velocity corresponding to the simulated wind direction.

6. The method of claim 5, wherein the method is a remote control method for triggering the collection of water samples in a coastal area. Remote trigger simulation includes: For any distributed acquisition where the simulated wind speed and simulated wind direction are α and β respectively: For distributed sampling points FC1 to distributed sampling points FC k Any distributed sampling point FC in j When the water sampling device is in its initial position, at any time t1 during the distributed sampling process, a sampling command is sent to the water sampling device, and the sampling target point is the distributed sampling point FC. j , where j is a positive integer less than or equal to k and greater than or equal to 1, and the initial position is the location where the water sampling equipment is deployed in the nearshore waters; The moment when the water sample collecting device starts to start at the rated power after sending the collecting instruction is recorded as t2, and the moment when the water sample collecting device reaches the distributed sampling point FC j is recorded as t3. The value of t2 minus t1 is noted as the distributed sampling point FC j The corresponding device response time; the average speed of the water sampling device between t2 and t3 is noted as the distributed sampling point FC j The corresponding collection path speed.

7. The method of claim 6, wherein the method is a remote control method for triggering the collection of water samples in coastal waters. Remote trigger simulation also includes: The average response time of all devices corresponding to all distributed sampling points is recorded as the average response parameter; the acquisition path speed corresponding to all distributed sampling points is recorded as the average acquisition speed. The average value of all average response parameters obtained from all distributed acquisitions is recorded as the response start parameter; the average acquisition speed corresponding to all distributed acquisitions is recorded as the path acquisition parameter.

8. The method of claim 7, wherein the method is a remote control method for triggering the collection of water samples in a coastal area. When collecting water samples from nearshore waters, the water sampling equipment is controlled to perform sampling operations based on real-time monitored nearshore wind direction parameters, a multi-real-time parameter database, and triggering parameters. When collecting water samples from nearshore waters, wind speed and direction are acquired in real time based on wind speed and direction sensors at the midpoint of the nearshore area, and recorded as real-time wind speed and real-time wind direction, respectively. Obtain the angle between all the simulated wind directions and the real-time wind directions recorded in the multi-real-time parameter database, and sort all the simulated wind directions from smallest to largest based on the angle; obtain the absolute value of the difference between all the simulated wind speeds and the real-time wind speeds recorded in the multi-real-time parameter database, and sort all the simulated wind speeds from smallest to largest based on the absolute value. For any distributed acquisition corresponding to the acquisition simulation wind speed and acquisition simulation wind direction, the sum of the number of digits of the acquisition simulation wind speed in the sorting and the number of digits of the acquisition simulation wind direction in the sorting is recorded as the real-world similarity number of the distributed acquisition. Obtain the real-world similarity number of all distributed acquisitions, and denote the distributed acquisition corresponding to the smallest real-world similarity number as the real-world similar acquisition; denote the acquired simulated wind speed and acquired simulated wind direction in the real-world similar acquisition as α1 and β1, respectively.

9. The method of claim 8, wherein the method further comprises: When collecting water samples from nearshore waters, the control of the water sampling equipment to perform sampling operations, based on real-time monitored nearshore wind direction parameters, a multi-real-time parameter database, and triggering sampling parameters, also includes: The average acquisition speed corresponding to the real-world similar acquisition in the path acquisition parameters is recorded as the real-world device speed. In the nearshore area, the points where water samples need to be collected are marked and recorded as the sampling points; the distributed sampling points that are closest to the sampling points in a straight line are recorded as the feature sampling points, and the point flow direction and point flow velocity corresponding to the feature sampling points and α1 and β1 in the multi-real-time parameter database are recorded as the real-time flow direction and real-time flow velocity of the feature sampling points, respectively.

10. A remote control triggering method for nearshore water sampling according to claim 9, characterized in that, When collecting water samples from nearshore waters, the control of the water sampling equipment to perform sampling operations, based on real-time monitored nearshore wind direction parameters, a multi-real-time parameter database, and triggering sampling parameters, also includes: When collecting data from the point to be collected, a point γ is obtained in the area where the nearshore area is located, such that γ satisfies both conditions 1 and 2. The Bluetooth module is used to send a collection command to the water sample collection device to collect data from the target point γ. When there are multiple γ points, the γ point closest to the point to be collected is set as the target collection point. Condition 1 is: when the point to be collected is taken as the starting point, the real-time flow direction is taken as the direction, and the real-time flow velocity is taken as the speed, the point to be collected can reach γ after time t4. Condition 2 is: when the initial position of the water sampling device is taken as the starting point, the position of γ is taken as the direction, and the actual speed of the device is taken as the speed, the water sampling device can reach γ after time t5 from its initial position, where t5 is t4 minus the response start parameter.

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