Marine water body data monitoring buoy system based on buoyancy engine

Abstract

According to the ocean water body data monitoring buoy system based on the buoyancy engine, in the system, a power motor is arranged in a waterproof sealed cabin; the ball screw is arranged in the waterproof sealed cabin and is in transmission connection with the power motor; the injector comprises an injector water suction and drainage buoyancy bin, an injector push rod is in transmission connection with the ball screw and is movably connected with the injector water suction and drainage buoyancy bin, and when the ball screw drives the injector push rod to enable the injector water suction and drainage buoyancy bin to suck water, the system gravity is larger than buoyancy to sink. When a ball screw drives an injector push rod to discharge liquid in the injector water suction and drainage buoyancy bin, the gravity of the system is smaller than buoyancy, and the system floats upwards; a plurality of sensors are arranged in the waterproof sealed cabin to feed back data; the single-chip microcomputer is connected with the power motor and the various sensors so as to receive data and control the power motor to move. The system is high in measurement precision.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater monitoring robots, in particular to an ocean water body data monitoring buoy system based on a buoyancy engine. Background Art

[0002] The marine water monitoring system is a comprehensive monitoring system that integrates marine water data collection, marine information processing, and marine data analysis. It is primarily used for offshore water quality monitoring and vertical profile mapping, providing a reference for selecting marine ranching areas and controlling seawater pollution.

[0003] Currently, there are two common buoy systems: 1. Floating buoy systems. 2. Submersible buoy systems. The floating buoy systems currently used by most companies have a very limited measurement range, focusing only on surface water quality. They struggle to accurately locate underwater pollution sources and are unable to plot depth-related water quality profiles. Submersible buoy systems utilize buoyancy engines to detect the submergence of the buoy itself, acquiring the relationship between ocean data and depth. Existing submersible buoy data collection methods are limited in type, with low motion control accuracy and large measurement errors, making it difficult to collect ocean water quality data.

[0004] The information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0005] In response to the shortcomings or defects of the existing technology, a buoy system for monitoring ocean water data based on a buoyancy engine is provided, which collects more types of data, more accurate data, higher degree of motion control automation and high detection accuracy, reduces operating costs and improves ocean monitoring efficiency.

[0006] The purpose of the present invention is achieved through the following technical solutions.

[0007] A buoyancy engine-based ocean water data monitoring buoy system includes: Waterproof and sealed cabin; A power motor is arranged in a waterproof and sealed cabin; A ball screw is provided in the waterproof sealed cabin and is transmission-connected to the power motor; At least one buoyancy engine, which is provided in the waterproof sealed cabin, the buoyancy engine comprises: A syringe comprising a syringe suction and discharge buoyancy chamber, The syringe push rod is connected to the ball screw and is movably connected to the syringe suction and drainage buoyancy chamber. When the ball screw drives the syringe push rod to make the syringe suction and drainage buoyancy chamber absorb water, the system sinks due to gravity being greater than the buoyancy. When the ball screw drives the syringe push rod to discharge the liquid in the syringe suction and drainage buoyancy chamber, the system floats due to gravity being less than the buoyancy. A variety of sensors are provided in the waterproof and sealed cabin to feedback data; A single chip microcomputer is connected to the power motor and various sensors to receive data and control the movement of the power motor.

[0008] The ocean water body data monitoring buoy system based on the buoyancy engine also includes a wireless communication device connected to the single chip microcomputer.

[0009] In the ocean water data monitoring buoy system based on the buoyancy engine, the wireless communication equipment includes Bluetooth and mobile network communication equipment.

[0010] The ocean water data monitoring buoy system based on the buoyancy engine also includes an onshore data processing center that is communicatively connected to the single-chip microcomputer, which receives the data, performs Kalman filtering processing, and visualizes the data through data mapping.

[0011] In the ocean water data monitoring buoy system based on the buoyancy engine, the onshore data processing center analyzes the data through a neural network algorithm to achieve abnormal data monitoring.

[0012] In the ocean water data monitoring buoy system based on a buoyancy engine, the multiple sensors include a water quality sensor.

[0013] In the ocean water data monitoring buoy system based on the buoyancy engine, multiple sensors collect and store data at a frequency of 5 Hz.

[0014] In the ocean water body data monitoring buoy system based on the buoyancy engine, a lower counterweight block is provided at the bottom of the waterproof sealed cabin.

[0015] In the ocean water body data monitoring buoy system based on the buoyancy engine, the ocean water body data monitoring buoy system based on the buoyancy engine is a symmetrical structure.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention can acquire three-dimensional ocean data and create vertical profiles of ocean water quality data. Compared to existing submersible buoys, this invention can collect more diverse and accurate data, achieve a higher degree of automated motion control, and provide a more intelligent detection platform. This further reduces the difficulty of collecting ocean water quality data, lowers operational costs, and improves ocean monitoring efficiency.

[0017] The above description is only an overview of the technical solution of the present invention. In order to make the technical means of the present invention clearer and easier to understand, so that those skilled in the art can implement it according to the contents of the description, and in order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are illustrated below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Various other advantages and benefits of the present invention will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are intended only to illustrate preferred embodiments and are not to be construed as limiting the present invention. It should be understood that the drawings described below are merely examples of the present invention, and that those skilled in the art will be able to derive other drawings from these drawings without inventive effort. Throughout the drawings, identical reference numerals are used to denote identical components.

[0019] In the attached figure: Figure 1 It is a structural schematic diagram of the present invention; Figure 2 is a schematic diagram of the depth data visualization over time of the present invention; Figure 3 It is a data processing flow chart of the present invention; Figure 4 This is a schematic diagram of the Kalman filter measuring water parameters of the present invention; Figure 5 is a schematic diagram of the cascade PID controller of the present invention; FIG6 (a) to FIG6 (c) are neural network regression effect diagrams of the present invention, wherein FIG6 (a) is a training regression diagram, FIG6 (b) is a test regression diagram, and FIG6 (c) is a full regression diagram.

[0020] The present invention will be further explained below with reference to the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0021] Specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although specific embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0022] It should be noted that certain words are used in the specification and claims to refer to specific components. Those skilled in the art should understand that technicians may use different nouns to refer to the same component. This specification and claims do not use the difference in nouns as a way to distinguish components, but use the difference in the functions of the components as the criterion for distinction. As mentioned throughout the specification and claims, "including" or "comprising" is an open term, so it should be interpreted as "including but not limited to". The subsequent description of the specification is a preferred embodiment of the present invention, but the description is based on the general principles of the specification and is not intended to limit the scope of the invention. The scope of protection of the present invention shall be as defined in the attached claims.

[0023] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings. However, the accompanying drawings do not limit the embodiments of the present invention.

[0024] For better understanding, Figure 1 As shown in FIG6 (c), a buoy system for monitoring ocean water data based on a buoyancy engine includes: Waterproof sealed cabin 1; A power motor 2 is provided in the waterproof sealed cabin 1; A ball screw, which is provided in the waterproof sealed cabin 1 and is transmission-connected to the power motor 2; At least one buoyancy motor 3 is provided in the waterproof sealed cabin 1, and the buoyancy motor 3 includes: Injector 4, which includes a syringe suction and discharge buoyancy chamber, The syringe push rod 5 is connected to the ball screw and is movably connected to the syringe suction and drainage buoyancy chamber. When the ball screw drives the syringe push rod 5 to make the syringe suction and drainage buoyancy chamber absorb water, the system sinks due to gravity being greater than buoyancy. When the ball screw drives the syringe push rod 5 to discharge the liquid in the syringe suction and drainage buoyancy chamber, the system floats due to gravity being less than buoyancy. When the buoy system receives a sinking command, the microcontroller 8 sends a command to the power motor 2, causing it to begin forward rotation. The motor's forward rotation direction is pre-set and is used to achieve the buoy system's sinking action. The output shaft of the power motor 2 is connected to a ball screw via a coupling. When the motor rotates forward, the ball screw rotates with it. The ball screw's nut is connected to the syringe plunger 5. The rotation of the ball screw converts the motor's rotational motion into linear motion of the syringe plunger. The rotation of the ball screw causes the syringe plunger 5 to move outward from the syringe suction and drainage buoyancy chamber 4. The syringe plunger moves outward, toward the top of the syringe suction and drainage buoyancy chamber. As the plunger moves, the air pressure within the syringe suction and drainage buoyancy chamber decreases, and water is drawn into the chamber. The increase in water within the syringe suction and drainage buoyancy chamber 4 increases the gravity of the buoy system. When the system's gravity exceeds the buoyancy, the buoy begins to sink. During the sinking process, various sensors 6 collect and store water data at a frequency of 5 Hz. During the sinking process, microcontroller 8 monitors the buoy's current depth in real time via depth sensor 6 and compares it with the target depth. If there is a deviation between the current depth and the target depth, the microcontroller adjusts the speed and rotation angle of power motor 2 based on the deviation. The ball screw and syringe plunger 5 further adjust the water volume in the buoyancy chamber, achieving dynamic buoyancy adjustment and ensuring the buoy sinks at the predetermined speed and trajectory.

[0025] When the buoy system completes its sinking mission or triggers the emergency resurfacing procedure, the microcontroller 8 sends a reverse command to the power motor 2. The power motor begins to rotate in the reverse direction relative to the forward rotation during sinking. The ball screw drives in reverse, transmitting the reverse rotation of the power motor 2 through the coupling to the ball screw, causing it to rotate in the opposite direction. This reverse rotation of the ball screw causes the connected syringe plunger 5 to move into the suction and drainage buoyancy chamber 4. As the syringe plunger 5 moves inward, it pushes the water inside the syringe suction and drainage buoyancy chamber 4 outward. As the water is drained, the amount of water in the buoyancy chamber decreases, and the gravity of the buoy system decreases accordingly. When the gravity of the buoy system becomes less than the buoyancy, the buoy begins to float. During the resurfacing process, various sensors 6 continue to collect and store water data at a frequency of 5 Hz until the buoy reaches the surface. During the resurfacing process, the microcontroller 8 uses the depth sensor 6 to monitor the buoy's current depth in real time and compares it with the target depth. If there is a deviation between the current depth and the target depth, the single chip microcomputer adjusts the speed and rotation angle of the power motor 2 according to the deviation value, and further adjusts the water volume in the buoyancy chamber through the ball screw and the syringe push rod 5 to achieve dynamic buoyancy adjustment and ensure that the buoy system floats up according to the predetermined speed and trajectory.

[0026] Various sensors 6 are provided in the waterproof and sealed cabin 1 to feed back data; The single chip microcomputer 8 is connected to the power motor 2 and various sensors 6 to receive data and control the movement of the power motor 2.

[0027] In a preferred embodiment of the ocean water data monitoring buoy system based on a buoyancy engine, a wireless communication device connected to the single chip computer 8 is also included.

[0028] In a preferred embodiment of the buoyancy engine-based ocean water data monitoring buoy system, the wireless communication device includes Bluetooth and mobile network communication equipment.

[0029] In a preferred embodiment of the ocean water data monitoring buoy system based on a buoyancy engine, it also includes an onshore data processing center that is communicatively connected to the single-chip computer 8, which receives the data, performs Kalman filtering processing, and visualizes the data through data mapping.

[0030] In a preferred embodiment of the buoyancy engine-based ocean water data monitoring buoy system, an onshore data processing center analyzes the data using a neural network algorithm to monitor abnormal data.

[0031] In a preferred embodiment of the ocean water data monitoring buoy system based on a buoyancy engine, the multiple sensors 6 include a water quality sensor 6 .

[0032] In a preferred embodiment of the buoyancy engine-based ocean water data monitoring buoy system, the various sensors 6 collect and store data at a frequency of 5 Hz.

[0033] In a preferred embodiment of the ocean water data monitoring buoy system based on a buoyancy engine, a lower counterweight 7 is provided at the bottom of the waterproof sealed cabin 1 .

[0034] In a preferred embodiment of the ocean water body data monitoring buoy system based on a buoyancy engine, the ocean water body data monitoring buoy system based on a buoyancy engine is a symmetrical structure.

[0035] In one embodiment, after the buoy system receives a dive command, a dual-loop PID control system integrated into the system's single-chip microcomputer is activated: the outer loop (position loop) generates a speed command based on the target depth, such as 50 meters. Using the depth sensor to provide real-time feedback on the current depth, the system calculates the depth deviation and outputs a set speed value, such as a constant dive speed of 0.3 m / s. The inner loop (speed loop) adjusts the displacement of the buoyancy chamber using the thrusters. In combination with a Doppler current meter to monitor the descent speed in real time, the thruster power is dynamically adjusted to ensure a speed error of ≤2%. During the dive, multiple sensors (such as high-precision pressure sensors, CTD sensors, and pH sensors) synchronously collect parameters at fixed intervals. Dynamic buoyancy adjustment: Based on the real-time depth deviation (target depth minus current depth), a motor-driven syringe dynamically adjusts the buoyancy of the buoyancy unit. If the pressure sensor detects a sudden drop in the depth change rate (e.g., >10 cm / s²) and the echo intensity from the micro-bottom-detection ultrasonic sensor exceeds a certain threshold, a bottom-contact risk is determined and an emergency ascent procedure is immediately initiated. For precise hovering control: After reaching the target depth, the aircraft switches to position hold mode. Using a dual-loop PID controller and attitude sensor, the aircraft integrates IMU attitude data with a depth compensation algorithm to eliminate depth measurement jitter caused by water. Dive termination conditions will terminate and the aircraft will ascend if any of the following conditions are met: successful acquisition of complete data at the target depth layer (ensuring multiple data sets and fluctuation errors are no more than 2%), battery charge falls below a safety threshold (e.g., less than 10%), or the aircraft detects a sensor failure or excessive water flow, preventing the aircraft from meeting depth control requirements.

[0036] The buoy system, based on a buoyancy engine, uses its buoyancy to adjust its own gravity by drawing in or out water through two motor-driven syringes within a sealed chamber. When water is drawn in, gravity becomes greater than buoyancy, causing the buoy to sink. When water is expelled, gravity becomes less than buoyancy, causing the buoy to float. The device incorporates sensors for depth, temperature, pH, and salinity, and uses a Kalman filter to accurately measure water quality. This data is transmitted via high-power Bluetooth to onshore monitoring equipment for visualization and abnormal data detection. The motion control core is an ESP32 development board, which uses a cascaded PID closed-loop control motor to achieve suction and discharge. Depth closed-loop monitoring enables automatic bottom detection and automatic sinking and buoyancy.

[0037] In one embodiment, the present invention realizes the suction and drainage action of the buoyancy engine 3 by pushing and pulling two syringe push rods 5 located in the center of the sealed cabin, thereby changing the gravity of the buoy itself and achieving sinking and floating. The ESP32 single-chip microcomputer 8 receives the data feedback from each sensor 6 through the serial port and controls the movement of the motor. The ESP32 single-chip microcomputer 8 and the shore control system realize data transmission and communication via high-power Bluetooth. When the ESP32 single-chip microcomputer 8 receives the confirmation signal transmitted from the shore, it disconnects the shore communication and simultaneously realizes the forward rotation of the motor by a fixed angle through PID cascade control. The forward direction here is defined relative to the rotation direction during floating. The motor drives the syringe push rod 5 upward through the ball screw to absorb and drain the gas in the buoyancy chamber, increasing the gravity of the buoy. At this time, the gravity is greater than the buoyancy, causing the buoy to begin to sink. During the sinking process, each sensor 6 collects and stores water data at a frequency of 5Hz. If the depth data changes less than a certain value for five consecutive times during the dive, it is considered that the buoy has touched the bottom, and ESP32 executes the floating program. The motor reverses and drives the syringe push rod 5 downward through the ball screw to discharge the liquid in the syringe, reducing the gravity of the buoy. At this time, the buoy's gravity is less than the buoyancy, and the buoy begins to float up. During the floating process, each sensor 6 still collects and stores underwater data at a frequency of 5Hz. When the depth data changes less than a certain value for five consecutive times, it is considered that the buoy has floated to the surface, each sensor 6 is turned off, and the Bluetooth module starts broadcasting. After successfully connecting to the shore data processing center, high-power Bluetooth data transmission is turned on. After receiving the raw data on shore, Kalman filtering is performed and the data is visualized by plotting, such as Figure 2 As shown, the abnormal data is analyzed by the neural network algorithm to realize the monitoring of abnormal data.

[0038] like Figure 3 As shown in the figure, due to the inevitable errors in the original sensor, the data is simply filtered by the hardware circuit and then subjected to classic Kalman filtering. A neural network algorithm is then used to detect abnormal data. During the data processing process of the Kalman filter algorithm, different Kalman filter codes can be obtained by estimating and modeling the reasonable intervals of different physical quantities. In the actual water body detection process, the salinity, temperature, and pH value of the water body along the longitudinal direction do not change significantly and can be approximately regarded as a constant during the measurement process. Physical quantities such as depth are subjected to segmented Kalman filtering according to different control programs. During a period of detection, the data is transmitted to the onshore monitoring equipment via a high-power Bluetooth device for data analysis and processing.

[0039] In the cascade PID processing process of this invention, the amount of water in the syringe is controlled by adjusting the movement of the syringe plunger, thereby accurately controlling the depth data of the buoy and realizing vertical data collection of ocean water quality data. Motor PID control is a method that achieves precise control through proportional (P), integral (I), and differential (D) regulation. Its output formula is as follows:

[0040] u(t): The controller's output signal (the controlled variable), a function that varies with time t and is used to regulate the controlled system. Kp: The proportional gain factor, which determines the proportional term's response to error. e(t): The error signal. Ki: The integral gain factor; Kd: The differential gain factor.

[0041] This system adopts dual-loop cascade PID control, which can be divided into main loop and inner loop. The main loop is the depth control loop and the sub-loop is the motor control loop. Figure 5 As shown. The main loop uses a PID algorithm to calculate the required adjustment of the gravity system to maintain the target depth. The absolute value of the difference between the current depth and the target depth is input, and the output is the target displacement of the syringe, which is reflected in the amount of water to be inhaled or expelled. The secondary loop uses the difference between the target displacement output by the main loop and the current actual offset provided by the Hall encoder as input, outputting the rotation of the motor, thereby accurately controlling the movement of the syringe push rod and achieving the sinking and floating function. The control process is as follows: 1. Depth closed-loop feedback: The depth sensor equipped with the present invention monitors the current depth of the buoy in real time. The measured data is de-noised through a Kalman filter and then input into the main loop PID. The main loop PID calculates the current required push rod displacement based on the error between the target depth and the current depth. 2. Motor position closed-loop control: The secondary loop PID receives the target displacement output by the main loop and, combined with the actual displacement feedback from the current Hall encoder, adjusts the motor speed and direction. The motor drives the push rod displacement via a ball screw, thereby changing the amount of water in the buoyancy chamber and dynamically adjusting the system's gravity. If the depth changes by less than a threshold for five consecutive times, the buoy is determined to have touched the bottom (sinking) or surfaced (rising), triggering the motor reversal program to automatically switch between sinking and floating. Regarding abnormal data processing, a neural network algorithm detects data anomalies (such as sensor failure) and triggers alarms or adjusts PID parameters to ensure system robustness.

[0042] For neural networks, the present invention is equipped with a feedforward neural network trained and generated, and a regression function is obtained through data preprocessing, training, and testing. The STM32 of the present invention transmits the measured data back to the onshore data center through communication. The onshore data center integrates the regression function trained by the neural network. If the detection amount of a large area does not conform to the actual situation, the software level will warn whether there is a sensor abnormality. For data, the local river parameter changes in the past three months (excluding data caused by extreme weather) are used, including air temperature, water temperature, water flow, water surface pressure, pH, salinity and time. Among them, water flow speed and depth are used as output, and other data are used as input to predict the current depth and water flow speed.

[0043] The neural network architecture consists of six nodes in the input layer, corresponding to the input parameters (air temperature, water temperature, surface pressure, pH, salinity, and time). Five fully connected hidden layers, each with 25 neurons, and a two-node output layer, outputting water velocity and depth. The neural network's connections are: input layer → hidden layer 1 → hidden layer 2 → … → hidden layer 25 → output layer, with each layer fully connected. Reinforced Luminance (ReLU) is used in the hidden layers, and linear activation suitable for regression is used in the output layer. Bayesian regularization is used to optimize the neural network.

[0044] The complete training method is described below. Data preprocessing uses local river parameters from the past three months (excluding extreme weather data). Input features include air temperature, water temperature, air pressure, pH, salinity, and time (normalized). Output labels are water velocity and depth (normalized to the same magnitude). Outliers are removed according to the 3σ principle, and missing values are filled using linear interpolation. The training process begins with data partitioning. A 70% training step is used for the 20,000 data points to prevent overfitting, with 15% used for testing and 15% for validation. A Bayesian regularized optimization algorithm is used to balance model complexity and fitting ability. The water flow prediction function is obtained after 1,000 training rounds. An early stopping mechanism is implemented; if the validation error does not decrease after 50 consecutive rounds, the training is terminated early. The batch size is set to 32. Performance metrics ensure that the R value of the trained regression function is above 0.9. Figures 6(a) to 6(c) show the training and testing results. The trained model is then fed with parameter changes from the local river over the past month. The model's prediction function continuously predicts the output data and compares the predicted data with validation data. One month's worth of data is then used for data verification, ensuring that the error for each validation data point does not exceed 5%. If significant data error exists, the neural network training parameters are revised, including but not limited to the number of hidden layers, the ratio of training to validation data, the number of training rounds, or the strength of regularization. This cycle of adjustment, retraining, and validation continues until R > 0.9 and the error is ≤ 5%. Using the trained model, after data enters the system, the current depth and water velocity are predicted by calculating the input. The depth data is then compared with the depth sensor. If the difference between the two reaches a set threshold, an abnormal data warning is triggered. The predicted water velocity is then recorded.

[0045] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this application are merely illustrative and not restrictive, and it should not be assumed that these advantages, strengths, and effects are required of each embodiment of this application. In addition, the specific details disclosed above are merely illustrative and facilitating understanding, and are not restrictive. The above details do not limit this application to necessarily being implemented using the above specific details.

[0046] The above description has been provided for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A buoyancy engine-based ocean water data monitoring buoy system, characterized in that: It includes, Waterproof and sealed cabin; A power motor is arranged in a waterproof and sealed cabin; A ball screw is provided in the waterproof sealed cabin and is transmission-connected to the power motor; At least one buoyancy engine, which is provided in the waterproof sealed cabin, the buoyancy engine comprises: A syringe comprising a syringe suction and discharge buoyancy chamber, The syringe push rod is connected to the ball screw and is movably connected to the syringe suction and drainage buoyancy chamber. When the ball screw drives the syringe push rod to make the syringe suction and drainage buoyancy chamber absorb water, the system sinks due to gravity being greater than the buoyancy. When the ball screw drives the syringe push rod to discharge the liquid in the syringe suction and drainage buoyancy chamber, the system floats due to gravity being less than the buoyancy. A variety of sensors are provided in the waterproof and sealed cabin to feedback data; A single chip microcomputer is connected to the power motor and various sensors to receive data and control the movement of the power motor.

2. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 1, characterized in that: Preferably, it also includes a wireless communication device connected to the single chip microcomputer.

3. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 2, characterized in that: Wireless communication devices include Bluetooth and mobile network communication devices.

4. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 1, characterized in that: It also includes an onshore data processing center that is communicatively connected to the single-chip microcomputer, which receives the data, performs Kalman filtering processing, and visualizes the data through plotting.

5. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 4, characterized in that: The onshore data processing center analyzes the data through a neural network algorithm to monitor abnormal data.

6. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 1, characterized in that: A variety of sensors including water quality sensors.

7. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 6, characterized in that: Various sensors collect and store data at a frequency of 5 Hz.

8. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 1, characterized in that: A lower counterweight is provided at the bottom of the waterproof sealed cabin.

9. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 1, characterized in that: The ocean water data monitoring buoy system based on the buoyancy engine has a symmetrical structure.

10. The ocean water data monitoring buoy system based on a buoyancy engine according to claim 1, characterized in that: A pair of buoyancy engines are symmetrically arranged in parallel in a waterproof and sealed cabin.

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