Oxygen delivery control system and method based on Beidou positioning

Abstract

The invention relates to the technical field of oxygen delivery control, in particular to an oxygen delivery control system and method based on Beidou positioning, and the method specifically comprises the steps: constructing a water body dynamic model according to water body environment parameters, and predicting the effective diffusion range of oxygen in a water body according to the water body dynamic model; selecting an oxygen target putting point in a water area where the to-be-put water body is located, and performing longitude and latitude positioning on the oxygen target putting point obtained by screening through a Beidou positioning system; calculating to obtain a bubble diameter coefficient of each water layer; and transmitting the bubble diameter coefficient of each water layer to a central controller, and automatically adjusting oxygen feeding parameters through the central controller. The problems that in the prior art, due to the fact that oxygen feeding precision is not high, oxygen distribution is not uniform, resource waste is caused, and aquatic organisms are possibly threatened are solved; meanwhile, the operation cost is increased, and long-term sustainable development is not facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of oxygen delivery control, and is an oxygen delivery control system and method based on Beidou positioning. Background Art

[0002] Oxygen delivery technology is a key means to increase the dissolved oxygen content in water bodies. By accurately delivering oxygen to water bodies, it can not only provide necessary living conditions for aquatic organisms and promote their healthy growth, but also effectively improve sewage treatment efficiency and maintain the ecological balance of water bodies. However, traditional oxygen delivery technology has exposed many problems in practical applications. For example, the low delivery accuracy leads to uneven oxygen distribution, which wastes resources and may also pose a threat to aquatic organisms; low oxygen utilization increases operating costs and is not conducive to long-term sustainable development; and in the face of complex and changeable water environments, traditional equipment has poor adaptability and is difficult to flexibly adjust according to actual conditions. More importantly, the lack of support from intelligent management systems has caused obvious shortcomings in traditional oxygen delivery equipment in terms of real-time monitoring, data analysis, and automatic control, and cannot meet the high standards of modern aquaculture and environmental protection. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] The technical problem to be solved by the present invention is that in the prior art, the oxygen delivery accuracy is not high, resulting in uneven oxygen distribution, which not only wastes resources but also may pose a threat to aquatic organisms; at the same time, it increases operating costs and is not conducive to long-term sustainable development. An oxygen delivery control system and method based on Beidou positioning is proposed.

[0005] In order to achieve the above object, the present invention provides a technical solution of an oxygen delivery control method based on Beidou positioning, comprising the following steps:

[0006] S1: Collect water environment parameters through the sensor network to form a water environment parameter set;

[0007] S2: Based on the water environment parameters, a water dynamics model is constructed, and the effective diffusion range of oxygen in the water is predicted based on the water dynamics model;

[0008] S3: According to S2, target oxygen delivery points are selected in the waters where the water body to be delivered is located, and the longitude and latitude of the selected target oxygen delivery points are located through the Beidou positioning system;

[0009] S4: extracting the water layer data of each oxygen target delivery point, and importing the water layer data into the bubble size evaluation strategy to calculate and obtain the bubble diameter coefficient of each water layer;

[0010] S5: The bubble diameter coefficient of each water layer is transmitted to the central controller, and the oxygen delivery parameters are automatically adjusted by the central controller.

[0011] Specifically, in S2, the water body dynamics model includes a water body flow model and an oxygen diffusion model.

[0012] Specifically, the construction of the water flow model includes the following specific steps:

[0013] S21: extracting water environment parameter set, and performing data denoising and data window smoothing;

[0014] S22: calculating vorticity data in the water body to be launched, and simulating vorticity distribution in the water body to be launched by using a finite element algorithm;

[0015] S23: Visualize the calculated vorticity data and draw a vorticity cloud map;

[0016] S24: Identify the target vorticity area according to the vorticity distribution characteristics in the vorticity cloud map.

[0017] Specifically, S24 includes the following specific steps:

[0018] S241: Calculate the vorticity modulus at each location in the vorticity cloud map , where the calculation strategy of the vorticity modulus is as follows: , p is any point in the water body to be put into, represents the vorticity modulus at point p; Respectively represent the rotational components of the water body to be released in the x, y, and z directions;

[0019] S242: Set the global threshold of vorticity , perform the first vortex screening process, wherein the first vortex screening strategy is specifically: ; represents the set of vorticity centers after the first vorticity screening process;

[0020] S243: Setting the local threshold of vorticity , and simultaneously perform a second vortex screening process, wherein the second vortex screening process is specifically as follows:

[0021] ;

[0022] in, represents the set of vorticity centers after the second vorticity screening process;

[0023] Represents the neighborhood of point p, with a neighborhood length of 5;

[0024] is another point in the neighborhood of point p that is different from point p;

[0025] S244: Calculate the local velocity gradient modulus of each position point in the vorticity cloud map, wherein the calculation strategy of the local velocity gradient modulus is: , represents the local velocity gradient modulus at point p, Respectively represent the flow velocity of the water body to be released in the x, y, and z directions; Respectively represent the partial derivatives of flow velocity in the x, y, and z directions;

[0026] S245: Set vorticity gradient threshold , and perform a third vortex screening process, wherein the third vortex screening process is specifically: ,in, represents the set of vorticity centers after the third vorticity screening process;

[0027] S246: Calculate the vorticity change rate of each position point in the vorticity cloud map within the unit monitoring period, wherein the calculation strategy of the vorticity change rate is: , Respectively represent the monitoring time points When , the vorticity modulus of point p in the water body to be launched;

[0028] S247: Set vorticity evolution threshold , and perform a fourth vortex screening process, wherein the fourth vortex screening process is specifically: , represents the set of vorticity centers after the fourth vorticity screening process;

[0029] S248: Extract the vorticity center set after the fourth vorticity screening process is completed , obtain the initial target oxygen delivery point set.

[0030] Specifically, the construction of the oxygen diffusion model includes the following specific steps:

[0031] S25: Extract real-time water concentration data from water environment parameters , real-time water temperature data and real-time water salt concentration data, and perform dimensionless processing on the real-time water temperature data and real-time water salt concentration data;

[0032] S26: Construct an oxygen diffusion model, input water temperature data and water salt concentration data into the oxygen diffusion model, and predict and output the oxygen concentration data at the same location in the next unit monitoring period. , where the oxygen concentration output formula in the oxygen diffusion model is:

[0033] ;

[0034] in, is the duration of the unit monitoring period; Real-time water concentration data The Laplace operator of ; is the diffusion coefficient of oxygen in the water to be released, , is the diffusion coefficient under standard water environment, They are the dimensionless values ​​corresponding to the real-time water temperature data and the water temperature data under the standard water environment; is the dimensionless value of real-time water salinity data; are temperature influence factor and salinity influence factor respectively; e is natural index;

[0035] S27: Calculate oxygen diffusion efficiency based on S26 , where oxygen diffusion efficiency The calculation formula is: .

[0036] Specifically, S3 includes the following specific steps:

[0037] S31: According to S2, the target oxygen delivery point is selected in the water area where the oxygen delivery is to be delivered, and the target oxygen delivery point is selected specifically by: extracting the initial target delivery point in the set of initial oxygen delivery points;

[0038] S32: calculating the oxygen diffusion efficiency of each initial target delivery point through the oxygen diffusion model, arranging the oxygen diffusion efficiency of each initial target delivery point in descending order, and preferentially selecting the top five initial target delivery points in the oxygen diffusion efficiency sequence as the final target delivery points of oxygen;

[0039] S33: The longitude and latitude of the final target delivery point of the oxygen obtained by screening are located through the Beidou positioning system, and the coordinates of the final target delivery point of the oxygen are visualized to the central controller of the oxygen delivery.

[0040] Specifically, in S4, the bubble size evaluation strategy is:

[0041] ;

[0042] The water body to be oxygenated is evenly divided into multiple water layers, where I is the total number of water layers. is the bubble diameter coefficient of the i-th water layer; is the bubble diameter coefficient of the water layer under standard water environment;

[0043] is the water viscosity of the ith water layer; is the water viscosity of the water layer under standard water environment; are the maximum and minimum water viscosity in the water layer, respectively;

[0044] is the water flow velocity of the i-th water layer; is the water flow velocity of the water layer under standard water environment; are the maximum and minimum water flow velocity in I water layer respectively; They are the water body viscosity ratio factor and the water layer water flow velocity ratio factor respectively.

[0045] Specifically, S5 includes the following specific steps:

[0046] S51: Extract the bubble diameter coefficient of each water layer and calculate the bubble mixing ratio coefficient of the bubble generator: ,in, Indicates the bubble diameter coefficient in the bubble generator when oxygen is needed in the i-th water layer. The bubble mixing ratio coefficient;

[0047] represents the vertical distance between the ith water layer and the horizontal plane; H represents the maximum depth of the water body to be oxygenated;

[0048] S52: The bubble mixing ratio coefficient is transmitted to the central controller, and the oxygen delivery parameters are automatically adjusted through the central controller.

[0049] In addition, the present invention provides an oxygen delivery control system based on Beidou positioning, comprising the following modules:

[0050] Water body environmental parameter acquisition module, water body dynamics model construction module, oxygen target delivery point selection module, bubble adjustment parameter calculation module and bubble generator control module;

[0051] The water body environment parameter collection module collects water body environment parameters through a sensor network to form a water body environment parameter set;

[0052] The water body dynamics model building module builds a water body dynamics model according to water body environmental parameters, and predicts the effective diffusion range of oxygen in the water body according to the water body dynamics model;

[0053] The oxygen target delivery point selection module is used to select the oxygen target delivery point in the water area where the delivery water body is located, and to locate the longitude and latitude of the selected oxygen target delivery point through the Beidou positioning system;

[0054] The bubble adjustment parameter calculation module is used to extract the water layer data of each oxygen target delivery point, and import the water layer data into the bubble size evaluation strategy to calculate and obtain the bubble diameter coefficient of each water layer;

[0055] The bubble generator control module is used to transmit the bubble diameter coefficient of each water layer to the central controller, and automatically adjust the oxygen delivery parameters through the central controller.

[0056] A storage medium stores instructions, and when a computer reads the instructions, the computer executes the oxygen delivery control method based on Beidou positioning.

[0057] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned oxygen delivery control method based on Beidou positioning when executing the computer program.

[0058] Compared with the prior art, the technical effects of the present invention are as follows: The oxygen delivery control method based on Beidou positioning realizes high-precision, dynamic adjustment and intelligent management of oxygen delivery to water bodies by integrating sensor networks, water body dynamics models and intelligent control systems. Its main advantage is that it can accurately identify and select the best oxygen delivery point to ensure uniform and effective diffusion of oxygen, thereby greatly improving oxygen utilization and reducing resource waste. At the same time, by real-time monitoring of water body environmental parameters, the solution can automatically adjust the oxygen delivery strategy according to real-time changes to adapt to the diverse needs of different waters, solving the shortcomings of traditional oxygen delivery technology in delivery accuracy, adaptability and intelligent management, and providing an efficient, reliable and sustainable solution for aquaculture and water quality improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0060] Figure 1 It is a flow chart of an oxygen delivery control method based on Beidou positioning of the present invention;

[0061] Figure 2It is a structural schematic diagram of an oxygen delivery control system based on Beidou positioning according to the present invention. DETAILED DESCRIPTION

[0062] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0063] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0064] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0065] Embodiment 1:

[0066] like Figure 1 As shown, an oxygen delivery control method based on Beidou positioning in an embodiment of the present invention includes the following specific steps:

[0067] S1: Collect water environment parameters through the sensor network to form a water environment parameter set;

[0068] S2: Based on the water environment parameters, a water dynamics model is constructed, and the effective diffusion range of oxygen in the water is predicted based on the water dynamics model;

[0069] In S2, the water body dynamics model includes a water body flow model and an oxygen diffusion model.

[0070] The construction of the water flow model includes the following specific steps:

[0071] S21: extracting water environment parameter set, and performing data denoising and data window smoothing;

[0072] S22: calculating vorticity data in the water body to be launched, and simulating vorticity distribution in the water body to be launched by using a finite element algorithm;

[0073] S23: Visualize the calculated vorticity data and draw a vorticity cloud map;

[0074] S24: Identify the target vorticity area according to the vorticity distribution characteristics in the vorticity cloud map.

[0075] S24 includes the following specific steps:

[0076] S241: Calculate the vorticity modulus at each location in the vorticity cloud map , where the calculation strategy of the vorticity modulus is as follows: , p is any point in the water body to be put into, represents the vorticity modulus at point p; Respectively represent the rotational components of the water body to be released in the x, y, and z directions;

[0077] S242: Set the global threshold of vorticity , perform the first vortex screening process, wherein the first vortex screening strategy is specifically: ; represents the set of vorticity centers after the first vorticity screening process;

[0078] S243: Setting the local threshold of vorticity , and simultaneously perform a second vortex screening process, wherein the second vortex screening process is specifically as follows:

[0079] ;

[0080] in, represents the set of vorticity centers after the second vorticity screening process;

[0081] Represents the neighborhood of point p, with a neighborhood length of 5;

[0082] is another point in the neighborhood of point p that is different from point p;

[0083] S244: Calculate the local velocity gradient modulus of each position point in the vorticity cloud map, wherein the calculation strategy of the local velocity gradient modulus is: , represents the local velocity gradient modulus at point p, Respectively represent the flow velocity of the water body to be released in the x, y, and z directions; Respectively represent the partial derivatives of flow velocity in the x, y, and z directions;

[0084] S245: Set vorticity gradient threshold , and perform a third vortex screening process, wherein the third vortex screening process is specifically: ,in, represents the set of vorticity centers after the third vorticity screening process;

[0085] S246: Calculate the vorticity change rate of each position point in the vorticity cloud map within the unit monitoring period, wherein the calculation strategy of the vorticity change rate is: , Respectively represent the monitoring time points When , the vorticity modulus of point p in the water body to be launched;

[0086] S247: Set vorticity evolution threshold , and perform a fourth vortex screening process, wherein the fourth vortex screening process is specifically: , represents the set of vorticity centers after the fourth vorticity screening process;

[0087] S248: Extract the vorticity center set after the fourth vorticity screening process is completed , obtain the initial target oxygen delivery point set.

[0088] The construction of the oxygen diffusion model includes the following specific steps:

[0089] S25: Extract real-time water concentration data from water environment parameters , real-time water temperature data and real-time water salt concentration data, and perform dimensionless processing on the real-time water temperature data and real-time water salt concentration data;

[0090] S26: Construct an oxygen diffusion model, input water temperature data and water salt concentration data into the oxygen diffusion model, and predict and output the oxygen concentration data at the same location in the next unit monitoring period. , where the oxygen concentration output formula in the oxygen diffusion model is:

[0091] ;

[0092] in, is the duration of the unit monitoring period; Real-time water concentration data The Laplace operator of ; is the diffusion coefficient of oxygen in the water to be released, , is the diffusion coefficient under standard water environment, They are the dimensionless values ​​corresponding to the real-time water temperature data and the water temperature data under the standard water environment; is the dimensionless value of real-time water salinity data; are temperature influence factor and salinity influence factor respectively; e is natural index;

[0093] S27: Calculate oxygen diffusion efficiency based on S26 , where oxygen diffusion efficiency The calculation formula is: .

[0094] S3: According to S2, target oxygen delivery points are selected in the waters where the water body to be delivered is located, and the longitude and latitude of the selected target oxygen delivery points are located through the Beidou positioning system;

[0095] S3 includes the following specific steps:

[0096] S31: According to S2, the target oxygen delivery point is selected in the water area where the oxygen delivery is to be delivered, and the target oxygen delivery point is selected specifically by: extracting the initial target delivery point in the set of initial oxygen delivery points;

[0097] S32: calculating the oxygen diffusion efficiency of each initial target delivery point through the oxygen diffusion model, arranging the oxygen diffusion efficiency of each initial target delivery point in descending order, and preferentially selecting the top five initial target delivery points in the oxygen diffusion efficiency sequence as the final target delivery points of oxygen;

[0098] S33: The longitude and latitude of the final target delivery point of the oxygen obtained by screening are located through the Beidou positioning system, and the coordinates of the final target delivery point of the oxygen are visualized to the central controller of the oxygen delivery.

[0099] S4: extracting the water layer data of each oxygen target delivery point, and importing the water layer data into the bubble size evaluation strategy to calculate and obtain the bubble diameter coefficient of each water layer;

[0100] In S4, the bubble size evaluation strategy is specifically:

[0101] ;

[0102] The water body to be oxygenated is evenly divided into multiple water layers, where I is the total number of water layers. is the bubble diameter coefficient of the i-th water layer; is the bubble diameter coefficient of the water layer under standard water environment;

[0103] is the water viscosity of the ith water layer; is the water viscosity of the water layer under standard water environment; are the maximum and minimum water viscosity in the water layer, respectively;

[0104] is the water flow velocity of the i-th water layer; is the water flow velocity of the water layer under standard water environment; are the maximum and minimum water flow velocity in I water layer respectively; They are the water body viscosity ratio factor and the water layer water flow velocity ratio factor respectively.

[0105] S5: The bubble diameter coefficient of each water layer is transmitted to the central controller, and the oxygen delivery parameters are automatically adjusted by the central controller.

[0106] S5 includes the following specific steps:

[0107] S51: Extract the bubble diameter coefficient of each water layer and calculate the bubble mixing ratio coefficient of the bubble generator: ,in, Indicates the bubble diameter coefficient in the bubble generator when oxygen is needed in the i-th water layer. The bubble mixing ratio coefficient;

[0108] represents the vertical distance between the ith water layer and the horizontal plane; H represents the maximum depth of the water body to be oxygenated;

[0109] S52: The bubble mixing ratio coefficient is transmitted to the central controller, and the oxygen delivery parameters are automatically adjusted through the central controller.

[0110] Embodiment 2:

[0111] like Figure 2 As shown, an oxygen delivery control system based on Beidou positioning according to an embodiment of the present invention includes the following modules:

[0112] Water body environmental parameter acquisition module, water body dynamics model construction module, oxygen target delivery point selection module, bubble adjustment parameter calculation module and bubble generator control module;

[0113] The water body environment parameter collection module collects water body environment parameters through a sensor network to form a water body environment parameter set;

[0114] The water body dynamics model building module builds a water body dynamics model according to water body environmental parameters, and predicts the effective diffusion range of oxygen in the water body according to the water body dynamics model;

[0115] The oxygen target delivery point selection module is used to select the oxygen target delivery point in the water area where the delivery water body is located, and to locate the longitude and latitude of the selected oxygen target delivery point through the Beidou positioning system;

[0116] The bubble adjustment parameter calculation module is used to extract the water layer data of each oxygen target delivery point, and import the water layer data into the bubble size evaluation strategy to calculate and obtain the bubble diameter coefficient of each water layer;

[0117] The bubble generator control module is used to transmit the bubble diameter coefficient of each water layer to the central controller, and automatically adjust the oxygen delivery parameters through the central controller.

[0118] Embodiment three:

[0119] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0120] The processor executes the above-mentioned oxygen delivery control method based on Beidou positioning by calling the computer program stored in the memory.

[0121] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement a method for controlling oxygen delivery based on Beidou positioning provided in the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0122] Embodiment 4:

[0123] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0124] When the computer program runs on a computer device, the computer device executes the above-mentioned oxygen delivery control method based on Beidou positioning.

[0125] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0126] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0127] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0128] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0129] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0130] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0131] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0132] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0133] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0134] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0135] In summary, the system comprehensively collects water environment parameters through a high-precision sensor network and constructs a scientific water dynamics model to accurately predict the diffusion behavior of oxygen in the water. With the help of the precise positioning function of the Beidou positioning system, the system can intelligently select the best oxygen delivery point to ensure that oxygen can be evenly and efficiently distributed in the target waters. At the same time, combined with advanced bubble regulation technology and intelligent control algorithms, the system can dynamically adjust oxygen delivery parameters according to real-time changes in the water environment, thereby significantly improving the utilization rate and delivery effect of oxygen. Through an integrated data management platform, the system can also realize real-time monitoring, data analysis and remote control of the oxygen delivery process, providing users with a convenient and efficient intelligent management experience. In summary, the technical solution of this patent has shown significant advantages and practical application value in solving the problems and difficulties existing in traditional oxygen delivery technology.

[0136] Compared with the prior art, the technical effects of the present invention are as follows: The oxygen delivery control method based on Beidou positioning realizes high-precision, dynamic adjustment and intelligent management of oxygen delivery to water bodies by integrating sensor networks, water body dynamics models and intelligent control systems. Its main advantage is that it can accurately identify and select the best oxygen delivery point to ensure uniform and effective diffusion of oxygen, thereby greatly improving oxygen utilization and reducing resource waste. At the same time, by real-time monitoring of water body environmental parameters, the solution can automatically adjust the oxygen delivery strategy according to real-time changes to adapt to the diverse needs of different waters, solving the shortcomings of traditional oxygen delivery technology in delivery accuracy, adaptability and intelligent management, and providing an efficient, reliable and sustainable solution for aquaculture and water quality improvement.

[0137] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An oxygen delivery control method based on Beidou positioning, characterized in that: The method comprises the following specific steps: S1: Collect water environment parameters through the sensor network to form a water environment parameter set; S2: Based on the water environment parameters, a water dynamics model is constructed, and the effective diffusion range of oxygen in the water is predicted based on the water dynamics model; S3: According to S2, target oxygen delivery points are selected in the waters where the water body to be delivered is located, and the longitude and latitude of the selected target oxygen delivery points are located through the Beidou positioning system; S4: extracting the water layer data of each oxygen target delivery point, and importing the water layer data into the bubble size evaluation strategy to calculate and obtain the bubble diameter coefficient of each water layer; S5: The bubble diameter coefficient of each water layer is transmitted to the central controller, and the oxygen delivery parameters are automatically adjusted by the central controller.

2. The oxygen delivery control method based on Beidou positioning according to claim 1 is characterized in that: In S2, the water body dynamics model includes a water body flow model and an oxygen diffusion model.

3. The oxygen delivery control method based on Beidou positioning according to claim 2 is characterized in that: The construction of the water flow model includes the following specific steps: S21: extracting water environment parameter set, and performing data denoising and data window smoothing; S22: calculating vorticity data in the water body to be launched, and simulating vorticity distribution in the water body to be launched by using a finite element algorithm; S23: Visualize the calculated vorticity data and draw a vorticity cloud map; S24: Identify the target vorticity area according to the vorticity distribution characteristics in the vorticity cloud map.

4. The oxygen delivery control method based on Beidou positioning according to claim 3 is characterized in that: S24 includes the following specific steps: S241: Calculate the vorticity modulus at each location in the vorticity cloud map , where the calculation strategy of the vorticity modulus is as follows: , p is any point in the water body to be put into, represents the vorticity modulus at point p; Respectively represent the rotational components of the water body to be released in the x, y, and z directions; S242: Set the global threshold of vorticity , perform the first vortex screening process, wherein the first vortex screening strategy is specifically: ; represents the set of vorticity centers after the first vorticity screening process; S243: Setting the local threshold of vorticity , and simultaneously perform a second vortex screening process, wherein the second vortex screening process is specifically as follows: ； in, represents the set of vorticity centers after the second vorticity screening process; Represents the neighborhood of point p, with a neighborhood length of 5; is another point in the neighborhood of point p that is different from point p; S244: Calculate the local velocity gradient modulus of each position point in the vorticity cloud map, wherein the calculation strategy of the local velocity gradient modulus is: , represents the local velocity gradient modulus at point p, Respectively represent the flow velocity of the water body to be released in the x, y, and z directions; Respectively represent the partial derivatives of flow velocity in the x, y, and z directions; S245: Set vorticity gradient threshold , and perform a third vortex screening process, wherein the third vortex screening process is specifically: ,in, represents the set of vorticity centers after the third vorticity screening process; S246: Calculate the vorticity change rate of each position point in the vorticity cloud map within the unit monitoring period, wherein the calculation strategy of the vorticity change rate is: , Respectively represent the monitoring time points When , the vorticity modulus of point p in the water body to be launched; S247: Set vorticity evolution threshold , and perform a fourth vortex screening process, wherein the fourth vortex screening process is specifically: , represents the set of vorticity centers after the fourth vorticity screening process; S248: Extract the vorticity center set after the fourth vorticity screening process is completed , obtain the initial target oxygen delivery point set.

5. The oxygen delivery control method based on Beidou positioning according to claim 4 is characterized in that: The construction of the oxygen diffusion model includes the following specific steps: S25: Extract real-time water concentration data from water environment parameters , real-time water temperature data and real-time water salt concentration data, and perform dimensionless processing on the real-time water temperature data and real-time water salt concentration data; S26: Construct an oxygen diffusion model, input water temperature data and water salt concentration data into the oxygen diffusion model, and predict and output the oxygen concentration data at the same location in the next unit monitoring period. , where the oxygen concentration output formula in the oxygen diffusion model is: ； in, is the duration of the unit monitoring period; Real-time water concentration data The Laplace operator of ; is the diffusion coefficient of oxygen in the water to be released, , is the diffusion coefficient under standard water environment, They are the dimensionless values ​​corresponding to the real-time water temperature data and the water temperature data under the standard water environment; is the dimensionless value of real-time water salinity data; are temperature influence factor and salinity influence factor respectively; e is natural index; S27: Calculate oxygen diffusion efficiency based on S26 , where oxygen diffusion efficiency The calculation formula is: .

6. The oxygen delivery control method based on Beidou positioning according to claim 5 is characterized in that: S3 includes the following specific steps: S31: According to S2, the target oxygen delivery point is selected in the water area where the oxygen delivery is to be delivered, and the target oxygen delivery point is selected specifically by: extracting the initial target delivery point in the set of initial oxygen delivery points; S32: calculating the oxygen diffusion efficiency of each initial target delivery point through the oxygen diffusion model, arranging the oxygen diffusion efficiency of each initial target delivery point in descending order, and preferentially selecting the top five initial target delivery points in the oxygen diffusion efficiency sequence as the final target delivery points of oxygen; S33: The longitude and latitude of the final target delivery point of the oxygen obtained by screening are located through the Beidou positioning system, and the coordinates of the final target delivery point of the oxygen are visualized to the central controller of the oxygen delivery.

7. The oxygen delivery control method based on Beidou positioning according to claim 6 is characterized in that: In S4, the bubble size evaluation strategy is specifically: ； The water body to be oxygenated is evenly divided into multiple water layers, where I is the total number of water layers. is the bubble diameter coefficient of the i-th water layer; is the bubble diameter coefficient of the water layer under standard water environment; is the water viscosity of the ith water layer; is the water viscosity of the water layer under standard water environment; are the maximum and minimum water viscosity in the water layer, respectively; is the water flow velocity of the i-th water layer; is the water flow velocity of the water layer under standard water environment; are the maximum and minimum water flow velocity in I water layer respectively; They are the water body viscosity ratio factor and the water layer water flow velocity ratio factor respectively.

8. The oxygen delivery control method based on Beidou positioning according to claim 7 is characterized in that: S5 includes the following specific steps: S51: Extract the bubble diameter coefficient of each water layer and calculate the bubble mixing ratio coefficient of the bubble generator: ,in, Indicates the bubble diameter coefficient in the bubble generator when oxygen is needed in the i-th water layer. The bubble mixing ratio coefficient; represents the vertical distance between the ith water layer and the horizontal plane; H represents the maximum depth of the water body to be oxygenated; S52: The bubble mixing ratio coefficient is transmitted to the central controller, and the oxygen delivery parameters are automatically adjusted through the central controller.

9. An oxygen delivery control system based on Beidou positioning, which is used to implement an oxygen delivery control method based on Beidou positioning as described in any one of claims 1 to 8, characterized in that: The system includes the following modules: Water body environmental parameter acquisition module, water body dynamics model construction module, oxygen target delivery point selection module, bubble adjustment parameter calculation module and bubble generator control module; The water body environment parameter collection module collects water body environment parameters through a sensor network to form a water body environment parameter set; The water body dynamics model building module builds a water body dynamics model according to water body environmental parameters, and predicts the effective diffusion range of oxygen in the water body according to the water body dynamics model; The oxygen target delivery point selection module is used to select the oxygen target delivery point in the water area where the delivery water body is located, and to locate the longitude and latitude of the selected oxygen target delivery point through the Beidou positioning system; The bubble adjustment parameter calculation module is used to extract the water layer data of each oxygen target delivery point, and import the water layer data into the bubble size evaluation strategy to calculate and obtain the bubble diameter coefficient of each water layer; The bubble generator control module is used to transmit the bubble diameter coefficient of each water layer to the central controller, and automatically adjust the oxygen delivery parameters through the central controller.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, an oxygen delivery control method based on Beidou positioning as described in any one of claims 1 to 8 is implemented.

11. An electronic device, characterized in that: include: A memory for storing instructions; The processor is used to execute the instruction so that the device performs the operation of implementing the oxygen delivery control method based on Beidou positioning as described in any one of claims 1-8.

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