Intelligently-controlled desktop-level ocean ground rotation power simulation system

Abstract

The invention relates to the technical field of marine physical simulation experiments, and discloses an intelligently-controlled desktop-level marine ground rotation force simulation system. The system comprises a central controller, a rotation simulation unit, a modular water tank unit, a fluid driving and tracing unit and an integrated sensor network. And the central controller analyzes the user parameters and generates a control instruction, and dynamically adjusts the instruction according to the feedback data of the sensor. The rotation simulation unit drives the platform to rotate in a stepless speed regulation mode to simulate earth rotation. The modularized water tank units quickly construct different submarine topographies by replacing the prefabricated terrain modules. And the fluid driving and tracing unit generates a flow field according to an instruction and releases a tracer agent. The integrated sensor network monitors various operation parameters in real time. According to the system, flexible reconstruction of an experimental terrain and closed-loop accurate control of an experimental process are realized, and the efficiency of a simulation experiment and the reliability of a result are improved.

Description

Technical Field

[0001] This invention relates to the field of marine physical simulation experimental technology, specifically to an intelligent control desktop marine geostrophic dynamics simulation system. Background Technology

[0002] Existing desktop ocean geostrophic simulation devices mostly use fixed-structure experimental tanks with immutable bottom topography. This design means that a single device can only simulate one specific seabed topographic condition, failing to flexibly adapt to diverse experimental needs. When the experimental objective involves studying the impact of different topographic features on circulation, the tank device must be replaced or completely modified, a complex and inefficient process that severely limits the feasibility of multi-topographic parameter comparison experiments.

[0003] In terms of system control, existing technologies mostly employ open-loop control. After the operator presets parameters such as rotation speed and drive intensity, the system executes the commands unidirectionally. During the experiment, due to equipment operating characteristic drift or environmental interference, the actual operating parameters gradually deviate from the preset values. The system itself cannot detect and correct such deviations, leading to instability in the key physical conditions of the simulation experiment. This makes it difficult to guarantee the repeatability and accuracy of the experimental results, affecting the reliable verification of the geostrophic dynamic mechanism.

[0004] There is a need for a desktop geostrophic dynamics simulation system that can quickly construct different experimental terrains and achieve continuous and precise control of simulated environmental parameters, in order to overcome the shortcomings of existing technologies in terms of terrain adaptability and control precision, and meet the experimental requirements of high-precision, multi-scenario marine dynamic processes. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent control desktop-level marine geostrophic dynamics simulation system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides an intelligent control desktop-level ocean geostrophic dynamics simulation system, the system comprising: The central controller receives and parses the geostrophic dynamics simulation parameters set by the user through the graphical human-machine interface, converts the parsed parameters into corresponding control commands, and receives real-time monitoring data from the integrated sensor network. Based on the difference between the real-time monitoring data and the preset parameters, the control commands are dynamically adjusted. The rotation simulation unit drives the platform carrying the experimental water tank to rotate precisely with stepless speed regulation according to the rotation speed information contained in the control commands issued by the central controller, so as to simulate the Earth's rotation effect at different latitudes. The modular water tank unit, based on the terrain selection information contained in the control commands issued by the central controller, is assembled with corresponding modular terrain boundaries to form an experimental watershed with specific seabed topographic features. The fluid drive and tracer unit controls the fluid drive device located at a specific position in the modular water tank unit to generate a flow field of corresponding intensity according to the drive intensity information contained in the control command issued by the central controller, and simultaneously controls the dyeing injection device to release tracer at a designated position. An integrated sensor network is used to collect real-time data on the rotation speed of the rotating simulation unit, the fluid level in the modular water tank unit, and the operating status of the fluid drive and tracer unit, and transmit all collected real-time monitoring data to the central controller.

[0007] Preferably, the central controller receives and parses the geostrophic dynamics simulation parameters set by the user through the graphical human-machine interface, and converts the parsed parameters into corresponding control commands, including: The graphical human-computer interface receives the latitude simulation value, wind stress simulation value, and experiment duration input by the user in the form of dimensionless parameters. The embedded parameter-physical quantity mapping algorithm library is called to map the latitude simulation value to the target rotation angular velocity of the rotation simulation unit, and the wind stress simulation value to the target driving voltage or power of the fluid driving device in the fluid driving and tracing unit. Based on the experimental duration and the preset experimental process stage division rules, a time control script is generated that includes the target rotation angular velocity and the target driving voltage or power change sequence at different stages. The time control script, terrain selection command, and tracer injection trigger command are integrated to generate a composite control command containing timing logic.

[0008] Preferably, the fluid drive and tracer unit controls a fluid drive device located at a specific position in the modular water tank unit to generate a flow field of corresponding intensity based on the drive intensity information contained in the control command issued by the central controller, including: Receive drive strength information containing the target drive voltage or power from the central controller; The target driving voltage or power is applied to the motor or pump body of the fluid drive device through a high-precision CNC power supply module or power amplifier; The controllable water flow or air flow generated by the fluid driving device acts on the surface or sidewall of the water body in the modular water tank unit, generating shear stress corresponding to the simulated wind stress value in the experimental flow domain, thereby driving the water body to move and forming a simulated flow field. The system synchronously receives the tracer injection trigger command issued by the central controller. At the initial moment or a specific phase of the flow field establishment, it activates the precision metering pump or solenoid valve to inject a dye of a preset concentration into the designated starting position within the modular water tank unit.

[0009] Preferably, the integrated sensor network collects in real time the rotational speed of the rotating simulation unit, the fluid level in the modular water tank unit, and the operating status data of the fluid drive and tracer unit, including: The instantaneous angular displacement pulse signal of the rotating platform is acquired at a fixed sampling frequency by an optical encoder or Hall sensor installed on the rotating shaft of the rotating simulation unit, and the real-time rotation speed is calculated. By installing multiple capacitive or ultrasonic water level sensors at different heights on the side wall of the modular water tank unit, the fluid water level at multiple points in the water tank is measured, and the average water level and water surface slope are calculated. The actual operating current and voltage of the fluid drive and tracer unit are collected by a current and voltage sensor installed in the fluid drive device circuit, and the real-time drive power is calculated. The instantaneous flow rate of the tracer injection pipeline is monitored by a flow sensor to confirm the execution status of the injection action; The real-time rotation speed, average water level and water surface slope, real-time drive power, and instantaneous flow rate data are packaged into a unified real-time monitoring data package.

[0010] Preferably, the central controller receives real-time monitoring data from an integrated sensor network and dynamically adjusts control commands based on the difference between the real-time monitoring data and preset parameters, including: The real-time monitoring data packet is parsed to extract the current values ​​of the real-time rotation speed, the average water level, and the real-time drive power; The current value of the real-time rotational speed is compared with the target rotational angular velocity to calculate the speed deviation value. A rotational speed correction command is generated through a proportional-integral-derivative control algorithm and sent to the rotational simulation unit. The current value of the real-time drive power is compared with the expected power range of the target drive voltage or power mapping. If the deviation exceeds the allowable deviation, a drive power compensation command is generated and sent to the fluid drive and tracer unit. The current value of the average water level is compared with the preset benchmark water level. If the water level drops beyond the threshold due to evaporation or splashing, an alarm message is generated or an execution command for the auxiliary water replenishment mechanism is triggered.

[0011] Preferably, the modular water tank unit is equipped with corresponding modular terrain boundaries according to the terrain selection information contained in the control commands issued by the central controller, including: The modular water tank unit has a standardized tank base and a pluggable boundary mounting interface. The system is equipped with a variety of preset modular terrain boundary components, including sloping panels simulating continental slopes, raised structures simulating mid-ocean ridges, narrow channel templates simulating straits, and flat substrates. Based on the terrain selection information issued by the central controller or manually input by the user, the corresponding components are selected from the modular terrain boundary component library and fixed to the corresponding boundary of the tank base by mechanical snap-fit ​​or magnetic adsorption, and combined to form the target seabed terrain outline.

[0012] Preferably, it also includes a flow field data acquisition and processing unit, used to capture and analyze flow field evolution information within the experimental flow domain based on the tracer released by the fluid drive and tracer unit, including: An industrial camera or high-speed camera deployed directly above the modular water tank unit is used to capture a sequence of experimental watershed images containing the tracer's movement trajectory at time intervals or continuously as set by the central controller. The image processing module preprocesses the experimental watershed image sequence, including background subtraction, color channel separation, and binarization, to highlight the movement trajectory of the tracer. The particle image velocimetry algorithm module analyzes the processed continuous frame images, and calculates the displacement of tracer particles or dye agglomerates through cross-correlation to generate two-dimensional velocity vector field data in the experimental watershed. The two-dimensional velocity vector field data is associated with and stored along with timestamps and corresponding control command parameters issued by the central controller to form a structured flow field evolution database.

[0013] Preferably, the central controller is further configured to reproduce the experimental process and self-calibrate parameters based on the structured flow field evolution database generated by the flow field data acquisition and processing unit, including: Read the complete sequence of control command parameters and the corresponding flow field evolution results from the structured flow field evolution database; When a user selects to reproduce a historical experiment, the central controller automatically calls the control command parameter sequence of that experiment to drive the rotating simulation unit, the modular water tank unit, and the fluid drive and tracer unit to execute in the original sequence. During the reproduction experiment, the real-time monitoring data collected by the current integrated sensor network is compared with the monitoring data stored in the same period of the historical experiment. If the deviation of key parameters persists, the relevant parameters in the control command are automatically fine-tuned to make the experimental state converge to the historical record. The finely tuned control command parameters are used as a new set of optimized parameters and updated to the system parameter library.

[0014] Preferably, the graphical human-computer interaction interface also provides real-time data visualization capabilities, including: The real-time rotational speed, fluid level, and drive power reported by the integrated sensor network are dynamically displayed in digital and dashboard formats. The current terrain boundary outline assembled within the modular water tank unit is drawn in real time on a two-dimensional plan view; A control panel is provided to receive real-time sliding adjustments by the user to the simulated latitude value and the simulated wind stress value, and to send the adjusted parameters to the central controller in real time. A data interface is reserved for receiving and overlaying real-time streamline diagrams or velocity vector fields from the flow field data acquisition and processing unit.

[0015] Preferably, the graphical human-computer interaction interface works in conjunction with the central controller to automate the execution and monitoring of a preset experimental procedure, including: It provides an experimental workflow editing interface, allowing users to arrange different parameter combinations and durations into multiple stages to form a complete custom experimental workflow configuration file; After the custom experimental process is started, the graphical human-computer interaction interface will automatically send the corresponding parameter set to the central controller in the order of the stages. Meanwhile, the graphical human-computer interaction interface marks the current execution stage on the timeline and highlights the target parameters of the current execution stage and the actual parameters fed back by the integrated sensor network. After the experimental procedure is completed, a dialog box will automatically pop up to prompt the user and provide the option to save all control parameters, monitoring data and flow field data of this experiment in a package.

[0016] Compared with the prior art, the beneficial effects of the present invention are: The bottom and boundaries of the experimental water tank are constructed using detachable and combinable standardized modules, allowing a single tank body to be transformed into experimental watersheds with different spatial structures by replacing different prefabricated modules. This enables on-demand reconstruction of the physical morphology of the experimental terrain, solving the problem of fixed-topography water tanks having limited functionality and difficulty in conducting multi-topography comparative studies. Researchers can quickly and easily switch between different seabed terrain configurations on the same hardware platform, shortening the setup and preparation time for different experimental scenarios, expanding the research scope that a single device can cover, and improving experimental efficiency.

[0017] By integrating a sensor network to monitor key operating parameters such as rotational speed and fluid state in real time, the system feeds this data back to the central controller. This data is compared and calculated with preset parameters to automatically generate adjustment commands, dynamically correcting the execution parameters of the drive unit. This constructs a complete sensing-feedback-control closed loop, solving the problem of parameter drift not being automatically compensated in open-loop control. The system can proactively maintain the long-term stability of key experimental conditions such as rotational speed and drive intensity, suppressing errors introduced by changes in equipment characteristics or external disturbances, ensuring the repeatability of the experimental process and the reliability and accuracy of the results. Attached Figure Description

[0018] Figure 1 This is a timing diagram of the intelligent control desktop marine geostrophic simulation system described in this invention; Figure 2 A flowchart for generating composite control commands for the central controller; Figure 3 Comparison diagram of the outline deviation distribution for modular water tank terrain assembly; Figure 4 A flowchart for analyzing the flow field evolution in the flow field data acquisition and processing unit; Figure 5 This is a comprehensive monitoring instrument panel for core parameters during the stable phase of Phase 2 of the ocean geostrophic simulation system. Detailed Implementation

[0019] 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.

[0020] Please see Figure 1This invention provides an intelligent desktop-level marine geostrophic dynamics simulation system. The system includes: a central controller that receives and parses geostrophic dynamics simulation parameters set by the user through a graphical human-computer interaction interface. These parameters are converted into corresponding control commands. Simultaneously, the central controller receives real-time monitoring data from an integrated sensor network and dynamically adjusts the control commands based on the differences between the real-time monitoring data and the preset parameters. A rotation simulation unit drives a platform carrying an experimental water tank to perform precise stepless speed-regulated rotation based on the rotation speed information contained in the control commands issued by the central controller, simulating the Earth's rotation effect at different latitudes. A modular water tank unit assembles corresponding modular terrain boundaries based on terrain selection information contained in the control commands issued by the central controller, forming an experimental watershed with specific seabed topographic features. A fluid drive and tracer unit controls a fluid drive device located at a specific position in the modular water tank unit to generate a flow field of corresponding intensity based on the drive intensity information contained in the control commands issued by the central controller, and simultaneously controls a dye injection device to release tracer at a designated location. The integrated sensor network collects real-time data on the rotation speed of the rotating simulation unit, the fluid level in the modular water tank unit, and the working status of the fluid drive and tracer unit, and transmits all the collected real-time monitoring data to the central controller.

[0021] Example 1: See Figure 2 The graphical user interface receives simulated latitude values, simulated wind stress values, and the experiment duration from the user in the form of dimensionless parameters. The central controller calls the embedded parameter-physical quantity mapping algorithm library to map the simulated latitude values ​​to the target rotational angular velocity of the rotational simulation unit, and the simulated wind stress values ​​to the target driving voltage or power of the fluid drive device in the fluid drive and tracer unit. Based on the experiment duration and the preset experimental process stage division rules, the central controller generates a time control script containing the sequence of changes in target rotational angular velocity and target driving voltage or power at different stages. The central controller integrates the time control script, terrain selection instructions, and tracer injection trigger instructions to generate a composite control instruction containing timing logic.

[0022] The fluid drive and tracer unit receives drive intensity information, including the target drive voltage or power, from the central controller. Through a high-precision CNC power supply module or power amplifier, the fluid drive and tracer unit applies the target drive voltage or power to the motor or pump of the fluid drive device. The fluid drive and tracer unit utilizes the controllable water or airflow generated by the fluid drive device to act on the surface or sidewalls of the water body within the modular water tank unit, generating shear stress corresponding to the simulated wind stress value within the experimental flow domain, thereby driving water movement to form a simulated flow field. The fluid drive and tracer unit synchronously receives tracer injection trigger commands from the central controller. At the initial moment or a specific phase of the flow field establishment, it activates a precision metering pump or solenoid valve to inject a preset concentration of dye into the designated starting position within the modular water tank unit.

[0023] In practice, the graphical user interface receives simulated latitude values, simulated wind stress values, and experimental duration input by the user in the form of dimensionless parameters. For example, the user sets the simulated latitude value to 0.5, the simulated wind stress value to 0.8, and the experimental duration to 600 seconds. These dimensionless parameters are transmitted to the central controller via a communication interface. The central controller calls the embedded parameter-physical quantity mapping algorithm library to map the simulated latitude value to the target rotational angular velocity of the rotating simulation unit, and the simulated wind stress value to the target driving voltage or power of the fluid drive device in the fluid drive and tracer unit. The parameter-physical quantity mapping algorithm library stores preset mapping relationships for the simulated latitude value. Target rotational angular velocity The formula is:

[0024] in: It is the fundamental rotational angular velocity constant. These are rotation mapping coefficients. It is a dimensionless number representing the latitude simulation value input by the user, and for wind stress simulation values... Target driving voltage Through formula Calculate, where: It is the fundamental driving voltage constant. These are the driving mapping coefficients. This refers to the dimensionless value of the simulated wind stress input by the user. The central controller generates a time control script containing sequences of changes in the target rotational angular velocity and target driving voltage for different stages, based on the experiment duration and preset experimental process phase division rules. For example, the experiment duration is divided into a start-up phase, a steady-state phase, and a decay phase. During the start-up phase, the target rotational angular velocity increases linearly from zero to... The target driving voltage increases linearly from zero to... Maintain steady state during the steady state phase and During the decay phase, the target rotational angular velocity and the target driving voltage decrease linearly to zero. The central controller integrates the time control script, terrain selection command, and tracer injection trigger command to generate a composite control command containing timing logic. The composite control command contains a timestamp, phase identifier, target rotational angular velocity value, target driving voltage value, terrain code, and tracer injection flag in the form of a data packet.

[0025] In some embodiments, the fluid drive and tracer unit receives drive intensity information containing the target drive voltage from the central controller, and extracts the target drive voltage by parsing the data packets in the composite control command. The fluid drive and tracer unit uses a high-precision CNC power supply module to transmit the target drive voltage. The high-precision CNC power supply module, applied to the motor of the fluid drive device, operates according to the target drive voltage. The corresponding analog voltage signal is output to the motor drive circuit. The fluid drive and tracer unit uses the controllable water flow generated by the fluid drive device to act on the water surface in the modular water tank unit, generating shear stress corresponding to the simulated wind stress value in the experimental flow domain, thereby driving the water to move and forming a simulated flow field. The fluid drive device includes an impeller and a motor. The motor speed is proportional to the applied voltage. The impeller rotation disturbs the water surface and generates shear stress. The fluid drive and tracer unit synchronously receives the tracer injection trigger command issued by the central controller. At the initial moment of flow field establishment or a specific phase, such as when the tracer injection flag is true in the composite control command and the timestamp matches the initial moment of flow field establishment, the precision metering pump is turned on to inject the dye of the preset concentration into the designated starting position in the modular water tank unit. The injection flow rate of the precision metering pump is preset by the central controller and synchronized with the experimental stage.

[0026] Understandably, the graphical user interface displays input boxes and sliders for simulated latitude, simulated wind stress, and experimental duration. As the user adjusts the slider, the values ​​are updated in real time and sent to the central controller. For example, the latitude simulation slider range of 0 to 1 corresponds to simulating the equatorial to polar effects. In practical implementation, the parameter-physical quantity mapping algorithm library embedded in the central controller contains multiple sets of mapping coefficients. These mapping coefficients are pre-determined through calibration experiments and stored in non-volatile memory. For example, the rotational mapping coefficients are calibrated for different tank sizes and fluid properties. and driving mapping coefficients The central controller generates a time control script containing a sequence of events with millisecond-level time precision. This sequence of events drives the rotary simulation unit and the fluid drive and tracer unit to perform actions chronologically. For example, in the time control script, the event from second 0 to second 10 is for the rotary simulation unit to accelerate to the target rotational angular velocity. The fluid drive and tracer unit accelerates the fluid to the target drive voltage. The events from the 10th to the 590th second are for maintaining parameters, and the events from the 590th to the 600th second are for deceleration and stopping. Composite control commands are sent to each unit via standard communication protocols, such as using the Modbus protocol to distribute composite control commands to the motor controller of the rotary simulation unit and the power controller of the fluid drive and tracer unit.

[0027] Optionally, the mapping relationships in the parameter-physical quantity mapping algorithm library are configurable. Users can upload custom mapping curves through a graphical human-computer interaction interface. The central controller parses the custom mapping curves and updates the algorithm library. For example, a user can upload simulated latitude values. Rotational angular velocity of the target The quadratic function relationship replaces the linear relationship. The high-precision CNC power supply module of the fluid drive and tracer unit has a feedback loop, which monitors the output voltage in real time and correlates it with the target drive voltage. In contrast, closed-loop control adjusts the output to ensure voltage accuracy within ±0.1 volts. The tracer injection trigger command can be set to multiple time points, such as injecting tracer at fixed time intervals after the flow field is established. The central controller inserts multiple injection events into the time control script, and the fluid drive and tracer units execute the injection actions sequentially according to the event sequence.

[0028] Example 2: The integrated sensor network acquires instantaneous angular displacement pulse signals of the rotating platform at a fixed sampling frequency using photoelectric encoders or Hall sensors mounted on the rotating shaft of the rotating simulation unit, and calculates the real-time rotational speed. The integrated sensor network measures the fluid level at multiple points within the tank using multiple capacitive or ultrasonic level sensors mounted at different heights on the sidewall of the modular water tank unit, and calculates the average water level and surface slope. The integrated sensor network acquires the actual operating current and voltage of the fluid drive and tracer units using current and voltage sensors installed in the fluid drive device circuit, and calculates the real-time drive power. The integrated sensor network monitors the instantaneous flow rate of the tracer injection pipeline using a flow sensor to confirm the execution status of the injection action. The integrated sensor network packages the real-time rotational speed, average water level and surface slope, real-time drive power, and instantaneous flow rate data into a unified format real-time monitoring data packet.

[0029] The central controller parses real-time monitoring data packets, extracting the current values ​​of real-time rotational speed, average water level, and real-time drive power. The central controller compares the current real-time rotational speed with the target rotational angular velocity, calculates the speed deviation, generates a rotational speed correction command using a proportional-integral-derivative (PID) control algorithm, and sends it to the rotational simulation unit. The central controller compares the current real-time drive power with the expected power range of the target drive voltage or power mapping. If the deviation exceeds the allowable range, a drive power compensation command is generated and sent to the fluid drive and tracer unit. The central controller compares the current average water level with a preset reference water level. If the water level drops beyond a threshold due to evaporation or splashing, an alarm message is generated or an execution command for the auxiliary water replenishment mechanism is triggered.

[0030] In practical implementation, the integrated sensor network uses a photoelectric encoder mounted on the rotating shaft of the rotating simulation unit to collect instantaneous angular displacement pulse signals of the rotating platform at a fixed sampling frequency of 100 Hz. The photoelectric encoder generates one pulse for every certain angle of rotation. A counter records the number of pulses within a fixed time interval and calculates the real-time rotational speed. For example, if 50 pulses are counted in 0.01 seconds, corresponding to 1000 pulses per encoder revolution, the real-time rotational speed is calculated to be 3 revolutions per minute. The integrated sensor network also uses four ultrasonic water level sensors installed at different heights on the side wall of the modular water tank unit to measure the fluid water level at four points in the tank. The four ultrasonic water level sensors are installed at heights of 5 cm, 10 cm, 15 cm, and 20 cm from the bottom of the tank, respectively. The sensors emit ultrasonic waves and receive the echoes to measure the distance. The water level at each point is calculated, and the arithmetic mean of the measurements at the four points is used to obtain the average water level. The water surface slope is calculated by linearly fitting the relationship between the height and position of the four points. The integrated sensor network collects the actual operating current and voltage of the fluid drive and tracer unit through current and voltage sensors installed in the motor power circuit of the fluid drive device. For example, if the current sensor measures 1.5 amps and the voltage sensor measures 12.0 volts, the real-time drive power is calculated to be 18.0 watts. The integrated sensor network monitors the instantaneous flow rate of the tracer injection line through a turbine flow sensor to confirm the execution status of the injection action. For example, when the precision metering pump is turned on, the flow sensor detects that the instantaneous flow rate rises from 0 ml / min to a preset 5 ml / min. The integrated sensor network packages the real-time rotation speed, average water level and surface slope, real-time drive power, and instantaneous flow rate data into a unified format real-time monitoring data packet. The data packet includes a frame header, data fields from each sensor, a timestamp field, and a checksum field, and is periodically transmitted to the central controller via a serial communication bus.

[0031] In some embodiments, the central controller parses the real-time monitoring data packets to extract the current values ​​of the real-time rotation speed, the average water level, and the real-time drive power. The central controller compares the current value of the real-time rotation speed with the target rotation angular velocity for the current stage obtained from the time control script, and calculates the speed deviation value.

[0032] in: It is the velocity deviation value at time t. It is the target rotational angular velocity obtained from the time control script at time t. The current rotational speed at time t is the real-time value. The central controller generates a rotational speed correction command through the proportional-integral-derivative (PID) control algorithm. The output command value of the PID control algorithm is:

[0033] in: It is a proportionality coefficient. It is the integral coefficient. These are differential coefficients. It is the rotational speed correction increment, which the central controller will include. The rotational speed correction command is sent to the motor controller of the rotational simulation unit. The central controller compares the current value of the real-time drive power with the expected power range mapped to the target drive voltage. For example, the expected power range corresponding to the target drive voltage of 12.0 volts is 17.5 watts to 18.5 watts. If the current value of the real-time drive power is 19.0 watts and continues to exceed the allowable deviation range for more than 3 seconds, a drive power compensation command is generated. The drive power compensation command includes a voltage adjustment of -0.2 volts and is sent to the high-precision CNC power supply module of the fluid drive and tracer unit. The central controller compares the current value of the average water level with the preset reference water level, which is 15.0 cm. If the current value of the average water level drops to 14.5 cm and exceeds the threshold of 1.0 cm due to evaporation or splashing, an alarm message is generated and displayed on the graphical human-machine interface. At the same time, the execution command of the auxiliary water replenishment mechanism is triggered, controlling the solenoid valve to open and inject deionized water into the modular water tank unit until the average water level returns to near the reference water level.

[0034] It is understood that the angular displacement pulse signals acquired by the photoelectric encoder or Hall sensor are filtered and shaped by the digital signal processing circuit, and the counter uses a 32-bit register to record the pulse count. The measurement data from the ultrasonic water level sensor is averaged in the microprocessor of the integrated sensor network, and the algorithm firmware for calculating the average water level and water surface slope is stored in the microprocessor's read-only memory. The analog signals from the current and voltage sensors are converted into digital quantities by an analog-to-digital converter, and the calculation of real-time drive power is completed in the microprocessor of the integrated sensor network, using floating-point arithmetic. The transmission period of the real-time monitoring data packets is 100 milliseconds. The data packets contain the latest sensor data, and the central controller immediately parses and processes each data packet upon receipt.

[0035] Example 3: The modular water tank unit features a standardized tank base and pluggable boundary mounting interfaces. The system is equipped with various preset modular terrain boundary components, including sloping panels simulating continental slopes, raised structures simulating mid-ocean ridges, narrow channel templates simulating straits, and a flat substrate. Based on terrain selection information issued by the central controller or manually input by the user, the modular water tank unit selects corresponding components from the modular terrain boundary component library and fixes them to the corresponding boundaries of the tank base via mechanical snap-fits or magnetic adsorption, assembling to form the target seabed terrain outline.

[0036] In practical implementation, the modular water tank unit features a standardized tank base and pluggable boundary mounting interfaces. The tank base is a rectangular acrylic tank, measuring 100 cm long, 30 cm wide, and 20 cm high. The top edges of the four sides of the tank base are designed with continuous dovetail grooves as boundary mounting interfaces. The system is equipped with various preset modular terrain boundary components, including sloping panels simulating continental slopes, raised structures simulating mid-ocean ridges, narrow channel templates simulating straits, and a flat substrate. For example, the sloping panels simulating continental slopes are polyethylene sloping plates with a 15-degree inclination; the raised structures simulating mid-ocean ridges are silicone components with a symmetrical ridge-shaped cross-section; the narrow channel templates simulating straits are partitions with a 10 cm wide opening in the center; and the flat substrate is a smooth polycarbonate plate. Based on the terrain selection information issued by the central controller or manually entered by the user, the corresponding components are selected from the modular terrain boundary component library. For example, the central controller receives the terrain code "T03" for "continental slope-ridge combination" selected by the user through the graphical human-computer interaction interface. The terrain selection information includes a list of components to be called: component A (continental slope sloping panel block), component B (ridge uplift structure), and component D (flat seabed). The modular tank unit indicates the physical position of the corresponding component from the storage cabinet according to the component list. It is fixed to the corresponding boundary of the tank base by mechanical snap-fit ​​or magnetic adsorption, forming the target seabed terrain outline. For example, in the mechanical snap-fit ​​method, the bottom edge of the modular terrain boundary component is designed with a protrusion that matches the dovetail groove slide rail of the tank base. After the component is pushed into the predetermined position along the slide rail, the locking mechanism on the side of the component can be rotated to complete the fixation. For example, in the magnetic adsorption method, permanent magnet strips are embedded in the side wall of the tank base, and iron sheets or magnets with opposite magnetic poles are embedded in the corresponding positions on the back of the modular terrain boundary component, which are fixed by magnetic adsorption.

[0037] In some embodiments, the standardized tank base of the modular water tank unit is designed with positioning reference marks, which are used to assist in the precise alignment of modular terrain boundary components. When the user manually inputs terrain selection information, they can drag and drop iconized terrain components on the two-dimensional water tank diagram in the graphical human-computer interaction interface to combine them. The graphical human-computer interaction interface generates a real-time preview of the corresponding terrain contour and outputs a component list and assembly sequence prompts. The process of selecting components from the modular terrain boundary component library can be completed manually by the user or by an automated robotic arm. The automated robotic arm picks up the corresponding components from the component storage rack and transports them to the tank base for assembly based on the component list and position coordinates sent by the central controller. After the target seabed terrain contour is formed, the internal contour of the assembled water tank is scanned by a laser contour scanner. The actual contour data obtained by scanning is compared with the theoretical data of the target terrain contour, and the contour deviation value is calculated. formula:

[0038] in: It is the average profile deviation. It is the number of sampling points. In position coordinates The actual contour height value obtained from the scan. In position coordinates The theoretical height value of the target terrain contour, if the average contour deviation If the error exceeds 0.5 mm, the system will display the assembly error on the graphical human-machine interface and suggest readjusting the component position.

[0039] It is understandable that each component in the modular terrain boundary component library has a unique physical identification code, such as a QR code or RFID tag. Scanning the identification code can confirm the component type and specifications. The mechanical latch locking mechanism is designed with torque limitation; a click sound is emitted when the knob is rotated to the preset torque, indicating that the component has been securely locked onto the slide rail. The dovetail groove slide rail surface of the groove base is coated with a low-friction coefficient coating, facilitating the smooth insertion and removal of the modular terrain boundary components. The assembly sequence prompts displayed on the graphical human-machine interface are calculated based on the spatial interference relationship between components. For example, prompts may suggest installing the flat bottom bed component first, then the sloping side panel block, and finally the internal ridge ridge structure.

[0040] In practical implementation, the terrain selection information for the modular tank unit can be imported through a configuration file, which contains the mapping relationship between terrain codes and component coordinates. The edges of the modular terrain boundary components are designed with waterproof sealing strips. After the component is fixed to the tank base, the sealing strips deform under pressure to fill the gap between the component and the tank base, preventing fluid leakage during the experiment. After assembling to form the target seabed terrain outline, the system can save the current terrain configuration, including the identification codes of all used components and their precise position coordinates on the tank base, facilitating quick recall of the same terrain in subsequent experiments. For complex combined terrains, such as those containing continental slopes, mid-ocean ridges, and straits simultaneously, the assembly of the modular terrain boundary components must follow specific spatial logic. Narrow strait passage templates must be installed between two opposite sidewalls, and mid-ocean ridge structures must be placed on a flat seabed.

[0041] Optionally, modular terrain boundary components can be made of transparent or semi-transparent materials, facilitating external observation of the flow field inside the tank. Magnetic adsorption can utilize electromagnets, with a central controller controlling energization and de-energization for rapid locking and releasing of the components. The modular terrain boundary component library is expandable, allowing users to design and 3D print new components. New components must have standard-compliant interfaces and be entered into the system database before use. The boundary mounting interface of the tank base can be designed as a modular splicing system, allowing for changes in the overall size and shape of the tank by adding or removing interface segments.

[0042] See Figure 3 In the verification of the terrain assembly accuracy of the modular water tank unit, this figure shows the deviation distribution between the actual contour and the target contour of different terrain combinations (continental slope-ridge combination T03, continental slope-strait combination T07, and all-terrain combination T10). The horizontal axis represents the coordinates of the sampling points along the longitudinal direction (100cm) of the tank base, and the vertical axis represents the contour deviation value (unit: mm). The red dashed line in the figure represents the deviation threshold set by the system (0.5mm). In specific operation, the laser contour scanner collects the actual contour height of 50 sampling points along the length of the tank and calculates the deviation value with the theoretical height of the target terrain: the all-terrain combination T10 has a peak deviation exceeding 1.0mm near the 20cm sampling point, and the continental slope-ridge combination T03 has a deviation close to 0.8mm in some areas, both exceeding the threshold range; while the deviation of the continental slope-strait combination T07 is generally in the range of 0.2-0.5mm, which meets the assembly accuracy requirements. In the parameter configuration, the sampling point spacing is 2cm, and the deviation calculation adopts the absolute value statistics of the height difference of each point. This result can be directly used as the triggering basis for system assembly error warning. When the average deviation of a certain terrain combination exceeds the threshold, the graphical human-computer interaction interface will prompt the component position to be readjusted.

[0043] Example 4: See Figure 4 The flow field data acquisition and processing unit, equipped with an industrial camera or high-speed camera positioned directly above the modular water tank unit, captures a sequence of experimental flow field images containing the tracer's trajectory at time intervals or continuously, as set by the central controller. The image processing module within the flow field data acquisition and processing unit preprocesses the experimental flow field image sequence, including background subtraction, color channel separation, and binarization, to highlight the tracer's trajectory. The particle image velocimetry algorithm module within the flow field data acquisition and processing unit analyzes the processed consecutive frames, matching the displacement of tracer particles or dye agglomerates through cross-correlation calculations to generate two-dimensional velocity vector field data within the experimental flow field. The flow field data acquisition and processing unit associates and stores the two-dimensional velocity vector field data with timestamps and corresponding control command parameters issued by the central controller, forming a structured flow field evolution database.

[0044] The central controller reads the complete control command parameter sequence and corresponding flow field evolution results from a structured flow field evolution database. When a user selects to reproduce a historical experiment, the central controller automatically calls the control command parameter sequence for that experiment, driving the rotating simulation unit, modular water tank unit, and fluid drive and tracer unit to execute in the original sequence. During the reproduction process, the central controller compares the real-time monitoring data collected by the integrated sensor network with the monitoring data stored concurrently in the historical experiments. If the deviation of key parameters persists, the central controller automatically fine-tunes the relevant parameters in the control commands to bring the experimental state closer to the historical records. The central controller then updates the system parameter library with the fine-tuned control command parameters as a new optimized parameter set.

[0045] In practice, the flow field data acquisition and processing unit is deployed above an industrial camera located directly above the modular water tank unit. The industrial camera captures a sequence of experimental flow field images containing the tracer's trajectory at time intervals set by the central controller. For example, the central controller is set to acquire 10 frames per second during the steady-state phase of the experiment. Upon receiving a trigger signal, the industrial camera captures a 1920×1080 pixel color image with a fixed exposure time. The image processing module within the flow field data acquisition and processing unit preprocesses the experimental flow field image sequence. Preprocessing includes background subtraction, color channel separation, and binarization to highlight the tracer's trajectory. Background subtraction involves subtracting each frame of the experimental image from a background image taken before the experiment (without the tracer). Color channel separation is used when a specific color tracer is employed, such as blue dye, by extracting the blue channel component of the image. Binarization converts the grayscale image to a black and white image by setting a threshold, where the tracer area is white and the background is black. The particle image velocimetry algorithm module in the flow field data acquisition and processing unit analyzes the processed continuous frame images and generates two-dimensional velocity vector field data within the experimental flow domain by matching the displacement of tracer particles or dye agglomerates through cross-correlation calculations. The flow field data acquisition and processing unit associates and stores the two-dimensional velocity vector field data with timestamps and corresponding control command parameters issued by the central controller, forming a structured flow field evolution database. This structured database uses relational tables, with each velocity vector field data file associated with a data record containing control parameters such as experiment number, time point, rotational speed, and driving voltage. See Table 1.

[0046] Table 1: Structure of the Flow Field Data File Index Table

[0047] In some embodiments, the central controller reads the complete control command parameter sequence and corresponding flow field evolution results of historical experiments from a structured flow field evolution database. For example, if the user selects to reproduce a historical experiment with the experiment number "EXP_20231027_001", the central controller performs a database query operation to obtain the target rotational angular velocity sequence, target driving voltage sequence, and recorded time points from all time control scripts from 0 seconds to 600 seconds of that experiment. When the user selects to reproduce a historical experiment, the central controller automatically calls the control command parameter sequence of that experiment, driving the rotational simulation unit, modular water tank unit, and fluid drive and tracer unit to execute in the original timing sequence. The central controller regenerates the obtained target rotational angular velocity sequence and target driving voltage sequence into a time control script, and combines it with the terrain code "T03" in the historical record to generate a composite control command for issuance. During the replication experiment, the central controller compares the real-time monitoring data collected by the integrated sensor network with the monitoring data stored in the historical data from the same period of the experiment. For example, at 15.2 seconds into the replication experiment, it reads the real-time rotation speed stored in the historical data for 15.2 seconds as 5.01 rpm, while simultaneously acquiring the real-time rotation speed reported by the integrated sensor network for 15.2 seconds as 5.20 rpm. If the deviation of key parameters persists, the relevant parameters in the control command are automatically fine-tuned to bring the experimental state closer to the historical record. For example, if the real-time rotation speed is higher than the historical value by more than 0.15 rpm for three consecutive sampling periods, the deviation is determined to persist, and the central controller generates a fine-tuning command to adjust the target rotational angular velocity value for the subsequent stages in the current time control script. Adjusted to:

[0048] in: It is the target rotational angular velocity after fine-tuning. It is the target rotational angular velocity in the original historical record. It is the convergence coefficient. This is the average deviation between the current real-time rotation speed and the historical value. The central controller updates the system parameter library with the finely tuned control command parameters as the new optimized parameter set. The update operation is performed after the reproduction experiment is completed, storing the finely tuned complete time control script along with the experimental condition labels in the system's callable parameter library for future use in experiments.

[0049] It is understandable that the shooting trigger of industrial cameras or high-speed cameras is strictly synchronized with the experimental stage clock of the central controller. The central controller ensures the timing accuracy of image acquisition through hardware trigger signal lines. The preprocessing algorithm of the image processing module runs on the graphics processor built into the flow field data acquisition and processing unit to improve processing speed. The two-dimensional velocity vector field data file generated by the particle image velocimetry algorithm module contains the center coordinates of each interrogation window and the corresponding U (horizontal) and V (vertical) velocity components. The structured flow field evolution database is connected to the central controller via Ethernet, and the central controller uses a structured query language to read and write to the database.

[0050] In practical implementation, when the central controller reads historical experimental data, it simultaneously loads auxiliary monitoring data sequences such as the average water level and water surface slope recorded in that experiment, for the purpose of reproducing a comprehensive comparison of the experimental process. The logic of the automatic fine-tuning control commands is not limited to rotational speed but also applies to drive power parameters. If there is a continuous deviation between the current real-time drive power and the historical value, the fine-tuning formula is as follows:

[0051] in: This is the fine-tuned target drive voltage. It is the target driving voltage in the original historical record. It is the driving convergence coefficient. This refers to power deviation. Fine-tuning commands are issued in real-time and dynamically. Within the remaining time period of the reproduction experiment, the adjusted parameters will immediately take effect and overwrite the corresponding values ​​in the original historical parameter sequence. The system parameter library update operation includes version management; each time a new set of optimized parameters is generated, it is assigned an incrementing version number, and its source historical experiment number and fine-tuning summary are recorded.

[0052] Example 5: The graphical human-machine interface (HMI) dynamically displays real-time rotational speed, fluid level, and drive power reported by the integrated sensor network in digital and dashboard formats. The HMI also draws the current terrain boundary outline of the modular water tank unit in real-time on a two-dimensional plan view. The HMI provides a control panel that receives real-time sliding adjustments to the simulated latitude and wind stress values ​​from the user and immediately sends the adjusted parameters to the central controller. The HMI also reserves a data interface for receiving and overlaying real-time streamline diagrams or velocity vector fields from the flow field data acquisition and processing unit.

[0053] The graphical user interface (GUI) provides an experimental procedure editing interface, allowing users to arrange different parameter combinations and durations into multiple stages, forming a complete custom experimental procedure configuration file. After starting the custom experimental procedure, the GUI automatically sends the corresponding parameter sets to the central controller in the order of stages. The GUI marks the current execution stage on the timeline and highlights the target parameters and actual parameters fed back by the integrated sensor network for the current execution stage. After the experimental procedure is completed, the GUI automatically pops up a dialog box to prompt the user and provides the option to package and save all control parameters, monitoring data, and flow field data of this experiment.

[0054] In practical implementation, the graphical human-machine interface dynamically displays the real-time rotation speed, fluid level, and drive power reported by the integrated sensor network in the form of numbers and dashboards. For example, on the left side of the main interface panel, a semi-circular dashboard pointer indicates the real-time rotation speed, with a scale range of 0-10 revolutions per minute. A numerical text box simultaneously displays a value accurate to one decimal place, such as "5.2 rpm". The fluid level is represented by a vertical bar graph with "15.3 cm" marked next to it. The drive power is displayed together with a horizontal progress bar and the number "18.0 W". The graphical human-machine interface draws the current terrain boundary outline of the modular water tank unit in real time on a two-dimensional plan view. The two-dimensional plan view is a top view of the modular water tank unit. Based on the current terrain code "T03" and the corresponding component position data obtained from the central controller, the diagram uses geometric shapes of different colors and line types to draw the trapezoidal area of ​​the continental slope sloping panel, the wavy area of ​​the mid-ocean ridge uplift structure, and the rectangular area of ​​the flat bottom. The graphical user interface (GUI) provides a control panel that receives real-time adjustments to the simulated latitude and wind stress values ​​from the user and immediately sends the adjusted parameters to the central controller. The control panel includes two slider controls: one for latitude simulation values ​​labeled "Latitude Parameter" and "Current Value 0.5," and another for wind stress simulation values ​​labeled "Wind Stress Parameter" and "Current Value 0.8." As the user drags the sliders, the corresponding values ​​change in real-time and are sent to the central controller via a background communication thread. Upon receiving the new parameters, the central controller immediately initiates calculations using the parameter-physical quantity mapping algorithm library and updates the control commands. The GUI also reserves a data interface for receiving and overlaying real-time streamline diagrams or velocity vector fields from the flow field data acquisition and processing unit. This data interface defines a standardized data packet format, including timestamps, grid point coordinates, and velocity vectors. When the flow field data acquisition and processing unit sends real-time flow field data packets via Ethernet, the GUI's rendering engine parses the data packets and overlays the velocity vector field above a two-dimensional plan view with drawn terrain contours, using arrows or streamlines. The arrow length and color depth indicate the velocity magnitude.

[0055] In some embodiments, the graphical human-computer interaction interface provides an experimental procedure editing interface, allowing users to arrange different parameter combinations and durations into multiple stages to form a complete custom experimental procedure configuration file. The experimental procedure editing interface provides a timeline panel, where users can add multiple stage nodes on the timeline and set parameters such as target rotation speed, target driving voltage, terrain coding, and the duration of the stage for each node. For example, a user can add "Stage 1" at time 0 seconds, setting the parameters as "rotation speed: 0 rpm, driving voltage: 0 volts, terrain: T01, duration 10 seconds", and add "Stage 2" at time 10 seconds, setting the parameters as "rotation speed: 5 rpm, driving voltage: 12 volts, terrain: T01, duration 290 seconds". After editing, it can be saved as a custom experimental procedure configuration file with the extension ".expcfg".

[0056] After initiating the custom experimental process, the graphical user interface (GUI) automatically sends the corresponding parameter sets to the central controller in the order of stages. Internally, the GUI maintains a stage execution queue and a timer. When the user clicks the start button, the interface reads the first-stage parameters from the configuration file and sends them, simultaneously starting the timer. When the timer reaches the end of the first-stage duration, it automatically reads and sends the second-stage parameters. This process continues until all stages are completed. The GUI marks the current execution stage on the timeline and highlights the target parameters and the actual parameters fed back by the integrated sensor network for the current stage. During operation, a vertical red time marker line moves along the timeline as the experiment progresses. The time period of the current execution stage is highlighted on the timeline. Simultaneously, a comparison panel pops up or remains fixed on the interface, displaying the target rotation speed, target drive voltage, and the rotation speed and drive power values ​​reported in real-time by the integrated sensor network for the current stage. Target values ​​are displayed in black, and actual values ​​are displayed in green or red to visually reflect the deviation. After the experimental procedure is completed, a dialog box will automatically pop up to prompt the user and provide the option to package and save all control parameters, monitoring data and flow field data of this experiment. When all stages are completed, a modal dialog box will pop up on the graphical human-computer interaction interface, displaying "Experimental procedure completed" and with "Save Data" and "Close" buttons. After the user clicks the "Save Data" button, the interface calls the data archiving function to package and compress the custom experimental procedure configuration file, all control command logs issued by the central controller, all real-time monitoring data packets reported by the integrated sensor network, and all flow field data files generated by the flow field data acquisition and processing unit into an archive file named with a timestamp.

[0057] It is understandable that the dashboard and digital displays are implemented through instrument controls and label controls within the GUI framework of the graphical human-computer interaction interface, and their values ​​are bound to data update events from the central controller. The terrain outline on the 2D plan is drawn based on vector graphics, and the outline coordinate data of modular terrain boundary components are pre-stored in the system configuration file. Changes to the value of the control panel slider control trigger a de-jittering network transmission function to avoid excessive network requests caused by rapid user dragging.

[0058] See Figure 5 In the Phase 2 stabilization monitoring of the ocean geostrophic simulation system, this integrated data dashboard visualizes the real-time status of three types of core sensors. Specifically, the left side uses a circular dashboard to display the rotation speed (current value 5.0 rpm), with a scale covering the system's operating range of 0-10 rpm, and the pointer position directly reflects the actual operating status of the rotation simulation unit; the middle uses a vertical bar chart to display the fluid water level height (current value 15.2 cm), with the horizontal axis scale focusing on the experimental reference water level range of 14.6-15.4 cm, and the bar length intuitively reflects the water level stability of the modular tank unit; the right side uses a horizontal bar chart to display the drive power (current value 18.0 W), with the horizontal axis covering the drive power range of 0-25 W, and the bar percentage corresponding to the actual power output of the fluid drive and tracer units. The data from all three visualization components are synchronized in real time from the monitoring data packets of the integrated sensor network, realizing a centralized and intuitive presentation of key operating parameters during the Phase 2 stabilization period.

[0059] In practice, the timeline panel of the experimental workflow editing interface allows users to adjust the start time and duration of stages by dragging. Parameter changes between stages can be set to either a "step" or "linear gradient" mode. When the graphical user interface sends stage parameters to the central controller, it uses a structured message containing the stage number, a list of target parameters, and the stage duration. In the comparison panel, the color of the actual value is highlighted according to the percentage deviation from the target value. Dynamic changes, of which: It's a percentage of deviation. It is the actual parameter value fed back by the integrated sensor network. It is the target parameter value for the current execution phase. The actual value is displayed in green when... It is displayed in orange when... The data is displayed in red. The packaging and saving function creates a temporary folder in the background, copies the scattered data files to this folder, and uses an open-source compression library to generate a ZIP archive. The save path can be selected by the user in the file dialog box.

[0060] Optionally, the graphical user interface (GUI) can also plot historical trend curves of key parameters in real time, such as simultaneously plotting the target rotational speed curve and the actual rotational speed curve in a scalable time-numerical coordinate system. The experimental procedure editing interface supports importing and modifying existing custom experimental procedure configuration files, and also supports saving the parameter settings on the current interface as a new configuration file. During automated execution, users can intervene in the experimental procedure execution at any time through the pause, continue, or terminate buttons on the GUI. The packaged archive file can contain a metadata file describing the experimental configuration and results, recording the experiment name, operator, creation time, and key statistical information.

[0061] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0062] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smartly controlled desktop level ocean geotranslational dynamic simulation system, characterized in that, The system comprises: a central controller receiving and analyzing the geostrophic dynamic simulation parameters set by the user through the graphical human-computer interaction interface, converting the analyzed parameters into corresponding control instructions, and receiving real-time monitoring data from the integrated sensor network, and dynamically adjusting the control instructions based on the differences between the real-time monitoring data and the preset parameters; a rotation simulation unit driving the platform carrying the experimental flume to rotate accurately and steplessly according to the rotation speed information contained in the control instructions issued by the central controller, so as to simulate the effect of the earth rotation at different latitudes; a modularized flume unit assembling the corresponding modularized terrain boundary according to the terrain selection information contained in the control instructions issued by the central controller, so as to form an experimental flow field with specific seafloor terrain characteristics; a fluid driving and tracing unit controlling the fluid driving device arranged at a specific position of the modularized flume unit to generate a flow field with a corresponding intensity according to the driving intensity information contained in the control instructions issued by the central controller, and synchronously controlling the dye injection device to release the tracer at the specified position; an integrated sensor network collecting the rotation speed of the rotation simulation unit, the fluid water level height in the modularized flume unit, and the working state data of the fluid driving and tracing unit in real time, and transmitting all the collected real-time monitoring data to the central controller.

2. The smartly controlled desktop level ocean geotranslational dynamic simulation system according to claim 1, wherein, The central controller receives and analyzes the geostrophic dynamic simulation parameters set by the user through the graphical human-computer interaction interface, and converts the analyzed parameters into corresponding control instructions, including: receiving the latitude simulation value, the wind stress simulation value, and the experimental duration input by the user in the form of dimensionless parameters through the graphical human-computer interaction interface; calling the embedded parameter-physical quantity mapping algorithm library to map the latitude simulation value to the target rotation angular velocity of the rotation simulation unit, and to map the wind stress simulation value to the target driving voltage or power of the fluid driving device in the fluid driving and tracing unit; generating a time control script containing the change sequence of the target rotation angular velocity and the target driving voltage or power at different stages according to the experimental duration and the preset experimental procedure stage division rule; integrating the time control script, the terrain selection instruction, and the tracer injection trigger instruction to generate a composite control instruction containing time sequence logic.

3. The smartly controlled desktop level ocean geotranslational dynamic simulation system according to claim 2, wherein, The fluid driving and tracing unit controls the fluid driving device arranged at a specific position of the modularized flume unit to generate a flow field with a corresponding intensity according to the driving intensity information contained in the control instructions issued by the central controller, including: receiving the driving intensity information containing the target driving voltage or power issued by the central controller; applying the target driving voltage or power to the motor or pump body of the fluid driving device through a high-precision numerical control power supply module or a power amplifier; using the controllable water flow or air flow generated by the fluid driving device to act on the water surface or side wall in the modularized flume unit to generate a shear stress corresponding to the wind stress simulation value in the experimental flow field, thereby driving the water movement to form a simulated flow field; Synchronously receive the tracer injection trigger instruction issued by the central controller, and at the initial moment or a specific phase of the flow field establishment, start the precision metering pump or the electromagnetic valve to inject the dyeing agent with a preset concentration into the designated starting position in the modular water tank unit.

4. The smartly controlled desktop level ocean geotranslational dynamic simulation system according to claim 3, wherein, The integrated sensor network collects the rotating speed of the rotating simulation unit, the fluid water level in the modular water tank unit, and the working state data of the fluid driving and tracing unit in real time, including: Through the photoelectric encoder or Hall sensor installed on the rotating shaft of the rotating simulation unit, the instantaneous angular displacement pulse signal of the rotating platform is collected at a fixed sampling frequency, and the real-time rotating speed is calculated; Through the multiple capacitive or ultrasonic water level sensors installed at different heights on the side wall of the modular water tank unit, the fluid water level at multiple points in the water tank is measured, and the average water level and water surface slope are calculated; Through the current and voltage sensor installed in the circuit of the fluid driving device, the actual working current and voltage of the fluid driving and tracing unit are collected, and the real-time driving power is calculated; Through the flow sensor, the instantaneous flow of the tracer injection pipeline is monitored to confirm the execution state of the injection action; The real-time rotating speed, the average water level and water surface slope, the real-time driving power, and the instantaneous flow data are packaged into real-time monitoring data packets in a unified format.

5. The smartly controlled desktop level ocean geotranslational dynamic simulation system according to claim 4, wherein, The central controller receives real-time monitoring data from the integrated sensor network, dynamically adjusts the control instruction based on the difference between the real-time monitoring data and the preset parameters, including: Analyzing the real-time monitoring data packet, extracting the current values of the real-time rotating speed, the average water level, and the real-time driving power; Comparing the current value of the real-time rotating speed with the target rotating angular velocity, calculating the speed deviation value, generating a rotating speed correction instruction through a proportional-integral-derivative control algorithm, and sending it to the rotating simulation unit; Comparing the current value of the real-time driving power with the expected power range mapped by the target driving voltage or power, if it exceeds the allowable deviation, generating a driving power compensation instruction and sending it to the fluid driving and tracing unit; Comparing the current value of the average water level with the preset reference water level, if the water level drops more than the threshold due to evaporation or sputtering, generating an alarm information or triggering an execution instruction of the auxiliary water replenishment mechanism.

6. The smartly controlled desktop level ocean geotranslational dynamic simulation system according to claim 1, wherein, The modular water tank unit assembles corresponding modular terrain boundaries according to the terrain selection information included in the control instruction issued by the central controller, including: The modular water tank unit has a standardized tank base and a pluggable boundary mounting interface; The system is equipped with multiple preset modular terrain boundary components, including a slope plate simulating a continental slope, a raised structure simulating a sea ridge, a narrow channel template simulating a strait, and a flat bottom bed; According to the terrain selection information input by the central controller or manually by the user, corresponding components are selected from the modular terrain boundary component library and fixed to the corresponding boundaries of the tank base through mechanical buckling or magnetic attraction, to form the target seafloor terrain profile.

7. The smartly controlled desktop level ocean geotranslational dynamic simulation system according to claim 6, wherein, Further comprising a flow field data acquisition and processing unit for capturing and analyzing the evolution information of the flow field in the experimental flow domain based on the tracer released by the fluid driving and tracing unit, including: An industrial camera or high-speed video camera deployed directly above the modular flume unit for shooting image sequences of the experimental flow domain containing the tracer trajectory at time intervals set by the central controller or continuously; An image processing module for pre-processing the experimental flow domain image sequences, including background subtraction, color channel separation and binary processing to highlight the tracer trajectory; A particle image velocimetry algorithm module for analyzing the processed continuous frame images, matching the displacement of tracer particles or dye blobs through cross-correlation calculation, and generating two-dimensional velocity vector field data in the experimental flow domain; The two-dimensional velocity vector field data is associated with the time stamp and the corresponding control instruction parameters issued by the central controller, forming a structured flow field evolution database.

8. The smartly controlled desktop level oceanic geotourism power simulation system according to claim 7, wherein, The central controller is also used to reproduce the experimental process and self-correct the parameters according to the structured flow field evolution database generated by the flow field data acquisition and processing unit, including: Reading the complete control instruction parameter sequence and the corresponding flow field evolution result of the historical experiment from the structured flow field evolution database; When the user chooses to reproduce a certain historical experiment, the central controller automatically calls the control instruction parameter sequence of the experiment, drives the rotating simulation unit, the modular flume unit and the fluid driving and tracing unit to execute according to the original time sequence; During the execution of the reproduced experiment, the real-time monitoring data collected by the integrated sensor network is compared with the monitoring data stored at the same period of the historical experiment. If the deviation of the key parameters persists, the related parameters in the control instruction are automatically fine-tuned to make the experimental state converge to the historical record; The fine-tuned control instruction parameters are updated to the system parameter library as a new set of optimized parameters.

9. The smartly controlled desktop level ocean geotranslational dynamic simulation system according to claim 1, wherein, The graphical human-computer interaction interface also provides real-time data visualization functions, including: Dynamically displaying the real-time rotating speed, fluid water level and driving power reported by the integrated sensor network in the form of numbers and instrument panels; Real-time drawing the current terrain boundary profile assembled in the modular flume unit on the two-dimensional plan view; Providing a control panel to receive the user's real-time sliding adjustment of the latitude simulation value and the wind stress simulation value, and sending the adjusted parameters to the central controller in real time; Reserving a data interface for receiving and superimposedly displaying real-time streamline diagrams or velocity vector fields from the flow field data acquisition and processing unit.

10. The smartly controlled desktop level ocean geotranslational dynamic simulation system according to claim 9, wherein, The graphical human-computer interaction interface and the central controller cooperate to realize the automatic execution and monitoring of the preset experimental process, including: Providing an experimental process editing interface to allow users to combine different parameter sets and durations into multiple stages to form a complete custom experimental process configuration file; After starting the custom experimental process, the graphical human-computer interaction interface will automatically send the corresponding parameter set to the central controller in sequence. Meanwhile, the graphical man-machine interaction interface marks the current execution stage on a time axis and highlights the target parameters of the current execution stage and the actual parameters fed back by the integrated sensor network. After the experiment flow is executed, a dialog box is automatically popped up to prompt the user and provide an option of packing and saving all the control parameters, monitoring data and flow field data of the current experiment.

Images