An oxygenation machine for aquaculture ponds capable of adaptive regulation

Abstract

This invention relates to an adaptive aerator for aquaculture ponds, comprising: a water quality monitoring module for real-time acquisition of aquatic environmental parameters in the aquaculture pond and transmission to a central processing unit (CPU) module; a CPU module for determining the oxygenation demand and required oxygenation areas based on the aquatic environmental parameters, generating control commands and sending them to an intelligent navigation module and an adaptive aeration module; an intelligent navigation module for controlling the position and direction of the aerator based on the control commands combined with inertial navigation system information and GPS location information, to reach the required oxygenation area; an adaptive aeration module for controlling the aerator to perform oxygenation based on the control commands after reaching the required oxygenation area; and an Internet of Things (IoT) module for connecting all modules to the Internet and providing remote monitoring and control. This invention can automatically detect the dissolved oxygen distribution in the water, adaptively move to areas with low dissolved oxygen for oxygenation, and automatically adjust the aerator's power output according to the dissolved oxygen level.

Description

Technical Field

[0001] This invention relates to the field of aquaculture technology, and in particular to an adaptive aerator for aquaculture ponds. Background Technology

[0002] With the development of aquaculture, the requirements for water quality management are increasing. Traditional aerators often lack intelligence and adaptability, making it difficult to adjust aeration strategies according to real-time changes in the aquaculture environment. This leads to problems such as aerators running 24 / 7, high energy consumption, and unstable aeration effects in aquaculture. Therefore, developing an aerator that can adapt to environmental changes and be intelligently managed is particularly important. Summary of the Invention

[0003] The purpose of this invention is to provide an adaptive aerator for aquaculture ponds, which solves the problems of high energy consumption and unstable oxygenation effect of aerators that are turned on all day in the aquaculture process.

[0004] To achieve the above objectives, the present invention provides the following solution:

[0005] An adaptive aerator for aquaculture ponds, comprising:

[0006] Water quality testing module, central processing unit module, intelligent navigation module, adaptive oxygenation module, Internet of Things module;

[0007] The water quality detection module is used to collect water environment parameters in aquaculture ponds in real time and send them to the central processing unit module.

[0008] The central processing unit module is used to determine the oxygenation requirements and oxygenation areas of the water body based on water environment parameters, generate control commands and send them to the intelligent navigation module and the adaptive oxygenation module.

[0009] The intelligent navigation module is used to control the position and direction of the aerator based on the control commands combined with inertial navigation system information and GPS location information, so as to reach the area requiring aeration;

[0010] The adaptive oxygenation module is used to control the oxygenator to perform oxygenation based on the control command after the oxygenator reaches the area requiring oxygenation.

[0011] The IoT module is used to connect the water quality detection module, central processing unit module, intelligent navigation module, and adaptive oxygenation module to the Internet and provide remote monitoring and control.

[0012] Optionally, the water quality testing module includes a data acquisition unit, a data processing unit, and a communication unit;

[0013] The data acquisition unit is used to collect the water environment parameters;

[0014] The data processing unit is used to analyze the water environment parameters and obtain the water quality change trend;

[0015] The communication unit is used to transmit the water environment parameters and water quality change trends to the central processing unit module.

[0016] Optionally, the central processing unit module includes a memory, a microprocessor, and an input / output interface;

[0017] The memory is used to store data processing algorithms and preset parameters;

[0018] The microprocessor is used to analyze and process the received data based on the data processing algorithm and preset parameters;

[0019] The input / output interface is used for information transmission between the central processing unit module and the water quality detection module, intelligent navigation module, and adaptive oxygenation module.

[0020] Optionally, the intelligent navigation module includes a path planning unit and a path control unit;

[0021] The path planning unit is used to obtain the current location of the aerator and the location of the area requiring aeration, and to perform path planning.

[0022] The path control unit is used to control the movement of the aerator according to the planned path based on control commands.

[0023] Optionally, the path control unit is also used to monitor the positioning and heading information of the aerator in real time during the movement of the aerator, and to adjust the planned path in real time if it encounters obstacles or changes in the environment.

[0024] Optionally, the intelligent navigation module employs a GPS receiver and an INS sensor array. The GPS receiver is used to receive satellite signals and obtain the three-dimensional position, velocity, and time information of the aerator by calculating the pseudorange and pseudorange rate between the satellite signals and the receiver. The INS sensor array is used to measure the angular velocity and acceleration of the aerator and obtain the velocity, attitude, and position information of the aerator by using integral calculations.

[0025] Optionally, the adaptive oxygenation module includes an oxygenation unit and a control unit;

[0026] The oxygenation unit is used to increase the dissolved oxygen in the water body of the area requiring oxygenation.

[0027] The control unit is used to control and adjust the operation of the oxygenation unit based on control commands and real-time oxygenation effects.

[0028] Optionally, the IoT module includes a user interface for users to set parameters, view data, and perform manual operations.

[0029] Optionally, the aerator further includes a power module, which supplies power to the water quality detection module, central processing unit module, intelligent navigation module, adaptive aeration module, and Internet of Things module.

[0030] Optionally, the power module uses a combination of a battery and a solar panel for power supply.

[0031] The beneficial effects of this invention are as follows:

[0032] This invention employs a combination of GPS and INS technologies, enabling automatic adjustment of the aerator to operate in areas of low dissolved oxygen based on real-time monitored dissolved oxygen data. This ensures uniform dissolved oxygen distribution throughout the water body, thereby improving overall aeration efficiency. It achieves precise positioning and autonomous navigation of the aerator on the water surface, avoiding repetitive operations and ineffective movements, thus enhancing aeration efficiency. Furthermore, this invention automatically adjusts the aerator's power output based on monitored water quality parameters, achieving on-demand aeration and energy conservation, thereby improving energy utilization efficiency. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a schematic diagram of an adaptively adjustable aerator for aquaculture ponds according to an embodiment of the present invention.

[0035] Figure 2 This is a flowchart illustrating the workflow of an adaptively adjustable aerator for aquaculture ponds according to an embodiment of the present invention.

[0036] Figure 3 This is a flowchart illustrating the workflow of the water quality testing module according to an embodiment of the present invention.

[0037] Figure 4 This is a flowchart illustrating the workflow of the intelligent navigation module according to an embodiment of the present invention.

[0038] Figure 5 This is a flowchart illustrating the adaptive oxygenation module of an embodiment of the present invention.

[0039] Figure 6 This is a flowchart of the IoT module in an embodiment of the present invention. Detailed Implementation

[0040] 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.

[0041] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0042] This embodiment provides an adaptively adjustable aerator for aquaculture ponds, such as... Figure 1 As shown, it includes: a water quality testing module, a central processing unit module, an intelligent navigation module, an adaptive oxygenation module, and an Internet of Things module;

[0043] The water quality detection module is used to collect water environmental parameters in aquaculture ponds in real time and send them to the central processing unit module;

[0044] The central processing unit module is used to determine the oxygenation requirements and oxygenation areas of the water body based on water environment parameters, generate control commands and send them to the intelligent navigation module and the adaptive oxygenation module.

[0045] The intelligent navigation module is used to control the position and direction of the aerator based on control commands combined with inertial navigation system information and GPS location information, so as to reach the area that needs oxygenation;

[0046] The adaptive oxygenation module is used to control the oxygenator to perform oxygenation based on control commands after the oxygenator reaches the area requiring oxygenation.

[0047] The Internet of Things (IoT) module is used to connect the water quality detection module, central processing unit module, intelligent navigation module, and adaptive oxygenation module to the Internet, and to provide remote monitoring and control.

[0048] like Figure 2As shown, firstly, the power module starts up, providing stable power support throughout the process, including electrical energy stored in the battery and renewable energy collected by solar panels, and converting DC power to AC power for system use via an inverter. After system initialization, a self-test is performed. After the self-test is complete, it receives user commands or enters automatic mode. If a user command is received, water environment monitoring is performed according to user-set parameters; if automatic mode is entered, water environment monitoring is performed automatically. The water quality detection module uses dissolved oxygen, pH, and temperature sensors to monitor water environment parameters in real time and transmits the data to the central processing unit (CPU) module. After receiving this data, the CPU module analyzes and processes it using a preset algorithm to determine the current oxygenation requirements of the water body. Subsequently, the CPU module sends control commands to the intelligent navigation module and the adaptive oxygenation module. The navigation module adjusts the position and direction of the aerator according to instructions, ensuring that the aerator can reach areas with low dissolved oxygen in the water. Once in these areas, the adaptive aeration module adjusts the operating status of the aerator according to instructions from the central processing unit to achieve precise aeration. It monitors the aeration effect during the process; if the aeration effect is not satisfactory by the end of the cycle, the aeration strategy is adjusted and aeration is repeated until the desired effect is achieved. If the desired effect is achieved, the aeration data is recorded, and the cycle ends. After aeration, the system either goes into standby mode or enters the next aeration cycle for further water environment monitoring. Simultaneously, the system employs an IoT module, enabling the aerator to connect to the internet for remote monitoring and control. Users can view real-time water environment data and the aerator's operating status through an application on their smart devices and intervene manually when necessary.

[0049] Furthermore, the water quality testing module includes a data acquisition unit, a data processing unit, and a communication unit;

[0050] The data acquisition unit is used to collect water environment parameters;

[0051] The data processing unit is used to analyze water environment parameters and obtain water quality change trends;

[0052] The communication unit is used to transmit water environment parameters and water quality change trends to the central processing unit module.

[0053] Specifically, such as Figure 3As shown, after initialization, the water quality detection module calibrates the dissolved oxygen sensor, temperature sensor, and pH sensor. Then, using these sensors, the water quality parameters are comprehensively monitored. Each sensor's high-precision AD converter converts analog signals into digital signals. The data acquisition unit receives the data transmitted from each sensor module and performs preliminary processing, such as filtering and amplification, to improve the accuracy and reliability of the data. Subsequently, the data processing unit performs in-depth analysis of the collected data to identify water quality change trends, providing decision support for the intelligent control of the aerator. The collected data is then transmitted to the central processing unit module via the SPI bus for analysis and processing.

[0054] During the oxygenation process, if the water quality monitoring module receives an instruction to adjust the oxygenation strategy, it updates the oxygenation parameters and restarts data acquisition; if it does not receive an instruction to adjust the oxygenation strategy, it returns to standby mode after the oxygenation process is completed.

[0055] Furthermore, the central processing unit module includes memory, a microprocessor, and input / output interfaces;

[0056] The memory is used to store data processing algorithms and preset parameters;

[0057] The microprocessor is used to analyze and process the received data based on data processing algorithms and preset parameters;

[0058] The input / output interface is used for information transmission between the central processing unit module and the water quality detection module, intelligent navigation module, and adaptive oxygenation module.

[0059] The microprocessor in the central processing unit module uses a high-performance chip based on the ARM architecture, which is responsible for data processing, logical judgment and control instruction generation; the software architecture adopts an embedded Linux operating system to ensure the stability and real-time performance of the system; it receives data from various modules, performs comprehensive analysis and then sends control instructions to the intelligent navigation module and the adaptive oxygenation module.

[0060] Furthermore, the intelligent navigation module includes a path planning unit and a path control unit;

[0061] The path planning unit is used to obtain the current location of the aerator and the location of the area requiring aeration, and to perform path planning;

[0062] The path control unit is used to control the movement of the aerator according to the planned path based on control commands. During the movement of the aerator, the unit monitors the aerator's positioning and heading information in real time. If obstacles or environmental changes are encountered, the planned path is adjusted in real time.

[0063] The intelligent navigation module uses a GPS receiver and an INS sensor array. The GPS receiver receives signals from multiple satellites and calculates the pseudorange and pseudorange rate between the satellite signals and the receiver to obtain the three-dimensional position, velocity, and time information of the aerator. The INS sensor array measures the angular velocity and acceleration of the aerator and uses integral calculations to obtain the velocity, attitude, and position information of the aerator.

[0064] Specifically, such as Figure 4 As shown, the intelligent navigation module initializes and, after receiving control commands from the central processing unit module via wireless communication, uses the map data of the aquaculture area, obstacle information, and oxygenation requirements. It treats each point on the map as a node using Dijkstra's algorithm and calculates the shortest path from the aerator's current location to the low dissolved oxygen area. Once an optimal path from the current location to the target area is obtained, the aerator drives the motor for automatic navigation according to the planned path. Simultaneously, the INS provides real-time positioning and heading information to ensure the aerator moves along the predetermined path. During movement, if obstacles or environmental changes occur, the aerator can dynamically adjust its path and recalculate the optimal route to the destination.

[0065] Furthermore, the adaptive oxygenation module includes an oxygenation unit and a control unit;

[0066] The oxygenation unit is used to increase the dissolved oxygen in the water body of the area that needs oxygenation;

[0067] The control unit is used to control and adjust the operation of the oxygenation unit based on control commands and real-time oxygenation effects.

[0068] Specifically, the oxygenation unit includes oxygenation equipment for increasing dissolved oxygen in the water; the control unit includes control and adjustment equipment for controlling the speed and power of the oxygenation equipment motor, and adjusting the angle and direction of the oxygenation equipment to optimize oxygen distribution.

[0069] Specifically, such as Figure 5 As shown, after the adaptive oxygenation module starts, it receives instructions from the central processing unit, analyzes the dissolved oxygen demand based on water quality data, calculates the oxygenation amount, and determines whether the oxygenation amount is sufficient. If it is insufficient, it recalculates; if it is sufficient, it controls the oxygenation equipment to perform oxygenation based on the oxygenation amount. At the same time, it monitors the oxygenation effect during the oxygenation process. If the oxygenation effect still does not meet the standard by the end of the current oxygenation cycle, it re-analyzes the dissolved oxygen demand, calculates the oxygenation amount, and adjusts the oxygenation strategy; if the standard is met, it records the oxygenation data and ends the oxygenation cycle.

[0070] The adaptive oxygenation module employs a fuzzy control algorithm. By monitoring water quality data such as dissolved oxygen in real time, the water quality data is fuzzified and then inferred according to preset fuzzy rules. After defuzzification, control commands are obtained, and the operating parameters of the aerator are automatically adjusted to achieve precise oxygenation. During the oxygenation process, the oxygenation effect is continuously monitored, and the control strategy is fine-tuned based on the feedback results to ensure that the dissolved oxygen content in the water body is always kept within the optimal range.

[0071] Furthermore, the IoT module includes a user interface for users to set parameters, view data, and perform manual operations, allowing users to set parameters and receive system status updates.

[0072] Specifically, such as Figure 6 As shown, after the system starts, it initializes the IoT module, establishes a network connection, configures remote access permissions, and then receives remote commands. If a remote command is received, it parses it and adjusts the device status according to the command, updating the device status to the central processing unit. If no remote command is received, it monitors the device status locally, collects device data, and stores it in the cloud. When a user accesses the system remotely, they can operate the device status displayed on the interface and transmit operation commands to the device, which then executes the commands. During operation, the IoT module also monitors the network status. If the network is stable, it maintains the connection until the task ends; if the network is unstable, it re-establishes the network connection.

[0073] The IoT module uses Wi-Fi communication to transmit data and receive commands from a remote server. It enables remote monitoring and management of the aerator through a cloud platform, including real-time data viewing, historical data querying, and control command issuance. It also supports access via mobile APP or web page, allowing users to monitor the aerator's working status anytime, anywhere.

[0074] To further optimize the technical solution, this embodiment provides an adaptive aerator for aquaculture ponds, which also includes a power supply module for supplying power to the water quality detection module, central processing unit module, intelligent navigation module, adaptive aeration module, and Internet of Things module.

[0075] The power module uses a combination of batteries and solar panels for power supply. It includes batteries, solar panels, and inverters. The batteries store electrical energy and provide stable DC power when the solar panels cannot supply power. The solar panels convert solar energy into electrical energy, providing the system with clean and renewable energy and reducing dependence on traditional power sources. The inverter converts DC power into AC power for use by AC equipment.

[0076] Specifically, the power module adopts a switching power supply design to ensure that the aerator can work stably under various operating conditions, and is equipped with a backup power supply to ensure that the aerator can still work normally in case of emergencies.

[0077] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. An aquaculture pond oxygenator capable of self-adapting adjustment, characterized in that, The application relates to an intelligent water quality monitoring and oxygen increasing system. The system comprises a water quality monitoring module, a central processor module, an intelligent navigation module, an adaptive oxygen increasing module and an Internet of Things module. The water quality monitoring module is used for collecting water body environmental parameters in a water product breeding pond in real time and sending the parameters to the central processor module. The central processor module is used for determining oxygen increasing demand and an oxygen increasing area of the water body based on the water body environmental parameters, generating a control instruction and sending the control instruction to the intelligent navigation module and the adaptive oxygen increasing module. The intelligent navigation module is used for controlling the position and direction of an oxygen increasing machine based on the control instruction, inertial navigation system (INS) information and GPS position information, and reaching the oxygen increasing area. The adaptive oxygen increasing module is used for controlling the oxygen increasing machine to increase oxygen based on the control instruction after the oxygen increasing machine reaches the oxygen increasing area. The Internet of Things module is used for connecting the water quality monitoring module, the central processor module, the intelligent navigation module and the adaptive oxygen increasing module to the Internet and providing remote monitoring and control. The water quality monitoring module comprises a data acquisition unit, a data processing unit and a communication unit. The data acquisition unit is used for collecting the water body environmental parameters. The data processing unit is used for analyzing the water body environmental parameters and obtaining a water quality change trend. The communication unit is used for transmitting the water body environmental parameters and the water quality change trend to the central processor module. The working process of the water quality monitoring module is as follows: after initialization, a dissolved oxygen sensor, a temperature sensor and a pH value sensor are calibrated, then the water quality parameters are monitored by using the dissolved oxygen sensor, the temperature sensor and the pH value sensor, analog signals are converted into digital signals by a high-precision AD converter of each sensor, data transmitted by each sensor is received by a data acquisition unit and is preliminarily processed, then the collected data are deeply analyzed by a data processing unit, a water quality change trend is recognized, and the collected data are transmitted to a central processor module through an SPI bus for analysis and processing. The central processor module comprises a memory, a microprocessor and an input / output interface. The memory is used for storing data and preset parameters. The microprocessor is used for analyzing and processing the received data based on a data processing algorithm and preset parameters, adopts a high-performance chip based on an ARM architecture, and is responsible for data processing, logical judgment and generation of control instructions. The input / output interface is used for information transmission between the central processor module and the water quality monitoring module, the intelligent navigation module and the adaptive oxygen increasing module. The intelligent navigation module comprises a path planning unit and a path control unit. The path planning unit is used for obtaining the current position of the oxygen increasing machine and the position of the oxygen increasing area, and planning a path. The path control unit is used for controlling the oxygen increasing machine to move along the planned path based on the control instruction. The path control unit is also used for monitoring the positioning and heading information of the oxygen increasing machine in real time during the movement of the oxygen increasing machine, and adjusting the planned path in real time if an obstacle or an environmental change is encountered. The intelligent navigation module adopts a GPS receiver and an INS sensor group, the GPS receiver is used for receiving satellite signals, and three-dimensional position, speed and time information of the oxygenator are obtained by solving the pseudo-range and pseudo-range rate between the satellite signals and the receiver; the INS sensor group is used for measuring the angular velocity and acceleration of the oxygenator, and the speed, attitude and position information of the oxygenator are obtained by using integral operation; The working process of the intelligent navigation module is as follows: after initialization, the control instruction of the central processor module is received through wireless communication, according to the map data, obstacle information and oxygenation demand of the aquaculture water area, each point on the map is regarded as a node in the graph by Dijkstra algorithm, the shortest path from the current position of the oxygenator to the low oxygen dissolving area is calculated by using Dijkstra algorithm, and an optimal path from the current position to the target area is obtained, then the oxygenator drives the motor according to the planned path to automatically navigate, and the INS provides real-time positioning and heading information to ensure that the oxygenator moves along the predetermined path, in the moving process, if an obstacle or environmental change is encountered, the oxygenator can dynamically adjust the path and recalculate the optimal route to the destination; The adaptive oxygenation module comprises an oxygenation unit and a control unit; The oxygenation unit is used for increasing the dissolved oxygen in the water body of the oxygenation area; The control unit is used for controlling and adjusting the work of the oxygenation unit based on the control instruction and the real-time oxygenation effect; The working process of the adaptive oxygenation module is as follows: after starting, the central processor instruction is received, the dissolved oxygen demand is analyzed according to the water quality data, the oxygenation amount is calculated, and the oxygenation equipment is controlled to execute oxygenation according to the oxygenation amount; at the same time, the oxygenation effect is monitored during the oxygenation process, if the oxygenation effect does not meet the standard until the end of the current oxygenation period, the dissolved oxygen demand is reanalyzed, the oxygenation amount is calculated, and the oxygenation strategy is adjusted; if the standard is met, the oxygenation data is recorded, and the oxygenation period is ended; The adaptive oxygenation module adopts a fuzzy control algorithm, the water quality data is fuzzy processed according to the real-time water quality data, the control instruction is obtained by reasoning according to the preset fuzzy rules and defuzzy, the operation parameters of the oxygenator are automatically adjusted, and precise oxygenation is realized; in the oxygenation process, the oxygenation effect is continuously monitored, and the control strategy is fine-tuned according to the feedback result; The Internet of Things module comprises a user interface for user to set parameters, view data and manually operate; The working process of the Internet of Things module is as follows: after initialization and network connection, remote access permission is configured, then remote instruction is received, if the remote instruction is received, the device state is adjusted according to the instruction, and the device state is updated to the central processor; if the remote instruction is not received, the device state is monitored and the device data is collected, and the device data is stored to the cloud; when the user remotely accesses, the device displayed on the operation interface can be operated, the operation instruction is input and transmitted to the device, and the device executes the corresponding instruction; the Internet of Things module also monitors the network state in the working process, if the network is stable, the connection is maintained until the end of the current task, if the network is unstable, the network connection is reestablished.

2. The self-adjustable oxygenation machine for aquaculture ponds according to claim 1, characterized in that, The oxygen increasing machine further comprises a power module, which is used for supplying power to the water quality detection module, the central processor module, the intelligent navigation module, the self-adaptive oxygen increasing module and the Internet of Things module.

3. The self-adjustable oxygenation machine for aquaculture ponds according to claim 2, characterized in that, The power module adopts a power supply mode combining a storage battery and a solar panel.

Images