An intelligent prevention and control method and system for methanol vapor diffusion of a ship

Abstract

The application provides an intelligent prevention and control method and system for methanol vapor diffusion of a ship, the method comprising: collecting operation data of vapor concentration, fuel storage and equipment vibration in the methanol fuel transportation process; constructing a methanol vapor diffusion prediction model according to the collected operation data combined with the ship navigation state and environmental parameters; generating a methanol vapor diffusion path and a corresponding risk level based on the prediction model; formulating a ventilation and fuel transportation control strategy according to the risk level, and sending control instructions to a ventilation linkage control subsystem and a methanol fuel transportation subsystem; executing the control instructions, performing feedback analysis on the control results, and forming a closed-loop correction; storing and analyzing the data in the prevention and control process for safety evaluation and pollutant emission and carbon emission reduction effect evaluation. The application realizes the transformation from passive alarm to active prevention and control, and significantly improves the safety, environmental protection and operation reliability of the methanol fuel ship.

Description

Technical Field

[0001] This invention relates to the field of marine new energy and safety engineering technology, and more specifically, to an intelligent control method and system for methanol vapor diffusion in ships. Background Technology

[0002] With the accelerated green and low-carbon transformation of the global shipping industry, methanol fuel is gradually becoming an important alternative fuel for ocean-going vessels due to its advantages such as low carbon emissions over its life cycle, relatively safe storage and transportation conditions, and high technological maturity. However, methanol is volatile, flammable, has a high vapor density, and is highly toxic. If a leak occurs during storage, transportation, or use on a ship, it can easily accumulate in localized spaces, posing significant safety hazards such as fires, explosions, and poisoning of personnel.

[0003] Currently, safety control technologies for methanol-fueled ships largely follow the same approach as those for liquefied natural gas (LNG) and other gas-fired ships, typically employing methods such as inert gas coverage, forced ventilation, and gas detection alarms. Existing methanol fuel safety control solutions primarily focus on improving individual technological aspects, lacking a holistic design encompassing the fuel delivery source, vapor diffusion path, and monitoring, early warning, and control decision-making, thus failing to form a closed-loop intelligent control system. Under complex ship operating conditions, the lack of collaborative optimization mechanisms between subsystems makes it difficult to achieve proactive risk prevention and dynamic management.

[0004] Therefore, there is an urgent need for a systematic technical solution for the application of methanol fuel in ships, which can dynamically predict and actively control the diffusion behavior of methanol vapor while ensuring the safety of fuel transportation, and achieve synergistic optimization of ship safety operation and pollution reduction and carbon reduction targets through intelligent monitoring and decision-making methods. Summary of the Invention

[0005] This invention addresses the technical problems existing in the prior art by providing an intelligent prevention and control method and system for methanol vapor diffusion in ships. It aims to improve the operational safety of methanol-fueled ships by constructing an intelligent prevention and control system that integrates source-end leakage prevention, vapor diffusion prediction, ventilation linkage control, and real-time monitoring and early warning. This system achieves proactive prediction, dynamic control, and closed-loop management of methanol vapor diffusion risks, while also taking into account the synergistic optimization of pollutant emission reduction and carbon emission reduction.

[0006] According to a first aspect of the present invention, a smart control method for methanol vapor diffusion in ships is provided, comprising the following steps: Collect operational data on methanol vapor concentration, fuel reserves, and equipment vibration during methanol fuel transportation; Based on the collected operational data and combined with the ship's navigation status and environmental parameters, a methanol vapor diffusion prediction model was constructed. Based on the prediction model, methanol vapor diffusion paths and corresponding risk levels are generated. Develop ventilation and fuel delivery control strategies based on risk levels, and send control commands to the ventilation linkage control subsystem and the methanol fuel delivery subsystem. The control command is executed, and the control result is analyzed to form a closed-loop correction. Data from the prevention and control process will be stored and analyzed for use in safety assessments and evaluations of pollutant emissions and carbon reduction effectiveness.

[0007] Based on the above technical solution, the present invention can also be improved as follows.

[0008] Optionally, the construction of the methanol vapor diffusion prediction model includes: A simulation model is established based on the ship's general arrangement drawing and organizational diagram, and the modeling of corresponding small equipment and deck details is simplified according to specific circumstances; The number of grids is determined according to the specific circumstances. The grids are densified in the ventilated mast and areas of interest, and the independence of the grids is verified. The effects of obstacles, temperature, wind direction, and wind speed on gas diffusion are analyzed separately, and the safety assessment and the evaluation of pollutant emissions and carbon reduction effects are based on the analysis data.

[0009] Optionally, generating the methanol vapor diffusion path based on the prediction model includes: The velocity field calculated using the methanol vapor diffusion prediction model was used to simulate the movement trajectory of the vapor emitted from the leak point within the cabin by Lagrange particle tracking or concentration gradient flow direction analysis. By combining ship structural parameters and navigation status, dead zones in the flow field inside the compartment are identified, and the mass concentration distribution of vapor in these areas is calculated. The simulation shows that, with the intervention of the ventilation linkage control subsystem, methanol vapor is guided by forced convection and flows through the methanol gas ventilation device to the dynamic removal path of the ventilation mast.

[0010] Optionally, based on the prediction model, generating corresponding risk levels includes: Multiple risk levels are set, which are defined as extremely high risk area, high risk area, medium risk area and low risk area. Different levels of protective measures are set according to different areas, and the risk levels are dynamically corrected according to the concentration change rate.

[0011] Optionally, the risk levels are classified as follows: Methanol concentration in area A This area is an extremely high-risk zone with extremely high concentrations of methanol vapor. Immediate emergency measures must be taken to prohibit personnel from entering. Area B methanol concentration This area is a high-risk zone with high concentrations of methanol vapor. Ventilation should be strengthened, personnel entry should be restricted, and appropriate protective equipment should be worn. Area C methanol concentration This area is a medium-hazard zone with a medium concentration of methanol vapor. Entry is permitted to designated personnel only, with appropriate protective measures in place. Methanol concentration in zone D This area is a low-risk zone with low methanol vapor concentration and is generally safe, but continuous monitoring and good ventilation should be maintained.

[0012] Optionally, the ventilation linkage control subsystem is used to provide feedback on the real-time speed of the fan, the pressure difference in the duct, and the angle of the guide vanes; the methanol fuel delivery subsystem is used to provide feedback on the delivery flow rate and outlet pressure data of the delivery pump.

[0013] Optionally, the ventilation and fuel delivery control strategy is automatically executed by the control decision unit based on the risk level output by real-time monitoring data and predictive models, including: When the risk level reaches the medium danger zone, when an abnormal increase in methanol concentration is detected or an accumulation risk is predicted in the area, the ventilation linkage control subsystem switches from "energy saving mode" to "directional dilution mode". The "decision platform" instructs the methanol gas ventilation device to increase the local exhaust power according to the predicted diffusion path. When the risk level reaches the high-risk zone, the gas ventilation device is instructed to be turned on to the maximum power and the angle of the guide vanes is adjusted to force the mixed gas to be safely discharged from the ship's space through the vent mast. At the same time, the fuel pump triggers the "function degradation" mechanism, and the control command is sent to the methanol transfer pump to reduce the operating frequency of the methanol transfer pump and reduce the transfer pressure in the pipeline to slow down the possible leakage rate. When the risk level reaches the extremely high danger zone, the control decision unit immediately sends an "emergency shutdown" command, the methanol transfer pump stops running, the emergency shut-off valve at the fuel storage tank outlet is closed to completely block the leak source, and a full-volume forced ventilation strategy is implemented. At the same time, the management and display platform issues an audible and visual alarm to the entire ship. When the methanol concentration drops to the low danger zone level, management personnel put on protective clothing and enter the maintenance equipment.

[0014] Optionally, executing the control command and performing feedback analysis on the control results includes: After receiving the command, the ventilation linkage control subsystem provides real-time feedback of fan speed and duct pressure differential data. The real-time monitoring subsystem continuously tracks changes in methanol concentration. If the concentration does not decrease as expected after the strategy is implemented, the control decision unit will automatically raise the risk level and trigger a higher-level safety shutdown response. If the rate of decrease in methanol concentration is lower than the preset threshold, it is determined that the current ventilation strategy is insufficient or there is a deviation in the wind direction guidance. The fluctuation of fuel delivery pressure after the command adjustment is continuously monitored to ensure that the pressure reduction process does not cause system resonance or instability of the delivery flow. The cause of the concentration increase is determined by combining multi-source data.

[0015] Optionally, the implementation path of the closed-loop correction is as follows: Based on the deviation between the control results and the preset target, the calculation parameters of the prediction model and the execution intensity of the ventilation and fuel delivery control strategies are dynamically adjusted; if the concentration removal is slow, the control decision unit automatically adjusts the control parameters, increasing the ventilation volume or reducing the fuel delivery pressure. Based on the actual diffusion trajectory, the operating conditions in the prediction model are corrected; if the risk cannot be effectively controlled after multiple attempts at closed-loop correction, the system automatically downgrades from "intelligent optimization mode" to "safety protection mode" and sends a manual intervention request to the management and display platform.

[0016] According to a second aspect of the present invention, an intelligent control system for methanol vapor diffusion in ships is provided, comprising: The methanol fuel delivery subsystem is used to provide feedback on the delivery flow rate and outlet pressure data of the delivery pump, thereby reducing the probability of methanol fuel leakage during the delivery process. The methanol vapor diffusion prediction subsystem is used to analyze and assess the diffusion behavior of methanol vapor in the ship environment in the event of fuel leaks or abnormal volatilization. The ventilation linkage control subsystem is used to provide feedback on the real-time speed of the fan, the pressure difference in the air duct, and the angle of the guide vanes, and to dynamically adjust the ship's ventilation system when the risk of methanol vapor diffusion occurs or is about to occur. The real-time monitoring subsystem is used to acquire status information of the methanol fuel system and the ship during operation; The control and decision-making unit and management and display platform are used to enable the coordinated operation of various sub-modules of the system.

[0017] The technical effects and advantages of this invention are as follows: This invention provides an intelligent prevention and control method and system for methanol vapor diffusion in ships. By constructing an intelligent prevention and control system that integrates source-end leakage prevention, vapor diffusion prediction, ventilation linkage control and real-time monitoring and early warning, it realizes proactive prediction, dynamic control and closed-loop management of methanol vapor diffusion risk, thereby improving the operational safety of methanol fuel ships and taking into account the synergistic optimization of pollutant emission reduction and carbon emission reduction.

[0018] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0019] Figure 1 A flowchart of an intelligent control method for methanol vapor diffusion on ships provided in an embodiment of the present invention; Figure 2 A flowchart illustrating the intelligent control system for methanol vapor diffusion on ships provided in this embodiment of the invention; Figure 3 Installation diagram of the intelligent prevention and control system for methanol vapor diffusion on ships provided in an embodiment of the present invention.

[0020] In the diagram, 1. Ventilation mast; 2. Gas ventilation system; 3. Storage tank; 4. Liquid level gauge; 5. Gas alarm; 6. Pipeline interface; 7. Transfer pump; 8. Decision platform; 9. Main engine of the ship. Detailed Implementation

[0021] 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.

[0022] It is understandable that, based on the deficiencies in the background technology, this invention proposes an intelligent control method for methanol vapor diffusion in ships, specifically as follows: Figure 1 As shown, it includes the following steps: S1. Collect operational data on methanol vapor concentration, fuel reserves, and equipment vibration during the methanol fuel transportation process; In this embodiment, the operational data specifically includes: Methanol vapor concentration values ​​at key locations (e.g., press-fit interfaces, delivery pumps, vent masts, main units, etc., where methanol is prone to leakage), and the concentration change rate calculated based on these concentration values; The sensor's own drift value, zero-point state, etc.; Fuel reserves, liquid level and remaining capacity, flow rate and pressure; Vibration data, equipment energy consumption, and surface temperature of methanol fuel delivery pumps, pipelines, main units, etc.; The ship's speed, course, and relative wind speed and direction; The fan speed, air velocity in the duct, and exhaust pressure difference of the ventilation system.

[0023] S2. Based on the collected operational data and combined with ship navigation status parameters and environmental parameters, a methanol vapor diffusion prediction model is constructed. In this embodiment, the ship's navigation status parameters include: speed and heading (which affect the speed and direction of methanol vapor diffusion and dissipation), attitude data (including the ship's roll and pitch angles, which affect the degree of vapor accumulation and cause danger), and draft (which affects the relative height of the methanol gas ventilation device outlet to the sea level, and thus affects the exhaust resistance). Environmental parameters include: relative wind speed and direction (which affect the diffusion of exhaust gas from the ventilated mast), ambient temperature and humidity (methanol is volatile, temperature directly affects the evaporation rate, and humidity affects the density of the mixed gas), and atmospheric pressure (used to correct for the vapor diffusion coefficient).

[0024] The construction of the methanol vapor diffusion prediction model includes: A simulation model (from bottom to top: sea level, hull, superstructure, etc.) is established based on the ship's general arrangement drawing and organizational diagram, and the modeling of corresponding small equipment and deck details is simplified according to the specific situation. Grid division: Divide the number of grids according to the specific situation, refine the grid in the air-permeable mast and areas of interest, and verify the independence of the grids; The effects of obstacles, temperature, wind direction, and wind speed on gas diffusion are analyzed separately, and the safety assessment and the evaluation of pollutant emissions and carbon reduction effects are based on the analysis data.

[0025] It should be noted that when setting simulation scene parameters (initial conditions include: ground stability, ground roughness, relative turbulence intensity, boundary conditions, gravitational acceleration, etc.), the condition parameters for the gas model should be set according to the actual situation. The coordinates of the release point need to be determined based on the specific release situation of the actual ship. At the same time, it is necessary to ensure that the airflow field in the calculation model space is in a stable state before release and to conduct ventilation simulation. Simulated scenario settings are designed based on methanol vapor pipelines and other equipment and facilities to simulate gas emission scenarios, including wind direction, wind speed and temperature. Among them, the wind direction design also needs to be set according to the actual situation. In the numerical model of methanol gas diffusion, the gas flow is considered to be an incompressible Newtonian fluid that satisfies the continuity equation, the momentum conservation equation, and the energy conservation equation. Since methanol does not react with air under normal conditions, a non-reactive model is used for analysis.

[0026] S3. Based on the prediction model, generate the methanol vapor diffusion path and the corresponding risk level; In this embodiment, generating the methanol vapor diffusion path based on the prediction model specifically includes: Trajectory tracking: Using the velocity field calculated by the methanol vapor diffusion prediction model, the movement trajectory of the vapor discharged from the leak point (such as the press-fit pipe interface, the transfer pump, the main unit, etc.) in the cabin is simulated by Lagrange particle tracking method or concentration gradient flow direction analysis.

[0027] Accumulation zone identification: Combining ship structural parameters and navigation status, identify dead zones in the flow field inside the compartment (such as the bottom of the engine room and the back of equipment), and calculate the mass concentration distribution of vapor in these areas; Emission path simulation: The simulation shows that, with the intervention of the ventilation linkage control subsystem, methanol vapor is guided by forced convection and flows through the methanol gas ventilation device to the dynamic removal path of the ventilation mast.

[0028] Based on the prediction model, the corresponding risk levels are generated as follows: Multiple risk levels are set up, which are defined as extremely high risk area, high risk area, medium risk area and low risk area. Different levels of protective measures are set up according to different classification areas, and the risk levels are dynamically corrected according to the concentration change rate.

[0029] Specifically, based on the prediction model, four levels are set: A, B, C, and D. Methanol concentration in area A (Lower explosive limit) This area is an extremely high-risk zone with extremely high concentrations of methanol vapor. Immediate emergency measures must be taken to prohibit personnel from entering. Area B methanol concentration (Lower explosive limit) This area is a high-risk zone with high concentrations of methanol vapor. Ventilation should be strengthened, personnel entry should be restricted, and appropriate protective equipment should be worn. Area C methanol concentration (Lower explosive limit) This area is a medium-hazard zone with a medium concentration of methanol vapor. Entry is permitted only by designated personnel, with appropriate protective measures in place. Methanol concentration in zone D (Lower explosive limit) This area is a low-hazard zone with low methanol vapor concentration, and is generally safe (8 hours), but continuous monitoring and good ventilation should be maintained.

[0030] It should be noted that the risk level is not fixed, but is dynamically adjusted based on the "concentration change rate". For example, even if the current concentration is low, if the model predicts that the diffusion path points directly to high heat source equipment (such as near the main unit), the system will automatically raise the risk level.

[0031] S4. Formulate ventilation and fuel delivery control strategies based on risk levels, and send control commands to the ventilation linkage control subsystem and the methanol fuel delivery subsystem. It should be noted that the ventilation and fuel delivery control strategy is automatically executed by the control decision unit based on the risk level output by real-time monitoring data and predictive models, specifically including: When the risk level reaches C, the system identifies an abnormally high methanol concentration or predicts a risk of accumulation in a specific area, and the ventilation linkage control subsystem switches from "energy-saving mode" to "directional dilution mode". The "decision platform" instructs the methanol gas ventilation device to increase the local exhaust power according to the predicted diffusion path.

[0032] When the risk level reaches B, the gas ventilation system is instructed to operate at maximum power and adjust the guide vane angle to force the mixed gas to be safely discharged from the ship's space via the vent mast. Simultaneously, the fuel pumps trigger the "function degradation" mechanism. Control commands are issued to the methanol transfer pumps, reducing their operating frequency to decrease the transfer pressure in the pipeline and mitigate potential leakage rates.

[0033] When the risk level reaches A, the control decision unit immediately sends an "emergency shutdown" command. The methanol transfer pump stops operating, the emergency shut-off valve at the fuel storage tank outlet is closed to completely block the leak source, the system executes a full-volume forced ventilation strategy, and the management and display platform issues audible and visual alarms to the entire ship. Once the methanol concentration drops to a low-hazard level, designated personnel wearing protective clothing enter the maintenance equipment.

[0034] The ventilation linkage control subsystem provides feedback on the real-time speed of the fan, the pressure difference in the air duct, and the angle of the guide vanes. The methanol fuel delivery subsystem provides feedback on key data such as the delivery flow rate and outlet pressure of the delivery pump. The real-time monitoring subsystem acquires the change curves of methanol vapor concentration at each location; the actual monitored vapor diffusion path is compared with the previous estimate of the methanol vapor diffusion prediction subsystem, and the deviation is calculated.

[0035] S5. Execute the control command, perform feedback analysis on the control result, and form a closed-loop correction; To ensure the effective execution of the strategy, the system includes a feedback mechanism to analyze the control results and form a closed-loop correction. The feedback mechanism specifically includes: Execution confirmation: After receiving the instruction, the ventilation linkage control subsystem must provide real-time feedback on fan speed and duct pressure difference data.

[0036] Effectiveness Evaluation: The real-time monitoring subsystem continuously tracks changes in methanol concentration. If the concentration does not decrease as expected after the strategy is implemented, the control decision unit will automatically increase the risk level and trigger a higher-level safety shutdown response.

[0037] Calculate the rate of concentration decrease; if the rate of decrease is lower than the preset threshold, it is determined that the current ventilation strategy is insufficient or there is a deviation in the wind direction guidance; monitor the fluctuation of fuel delivery pressure after the command adjustment to ensure that the pressure reduction process does not cause system resonance or delivery flow instability; combine multi-source data to determine whether the concentration increase is due to the actual expansion of the leak or a false alarm caused by the sensor being affected by environmental factors.

[0038] The implementation path of the closed-loop correction is as follows: based on the deviation between the control result and the preset target, the calculation parameters of the prediction model and the execution intensity of the ventilation and fuel delivery control strategy are dynamically corrected to form a responsive closed-loop adjustment mechanism.

[0039] Furthermore, the closed-loop correction specifically includes: if the concentration removal is slow, the control decision unit automatically corrects the control parameters, increases the ventilation volume or further reduces the fuel delivery pressure; based on the actual diffusion trajectory, it corrects the operating conditions in the prediction model to make the next prediction more accurate; if the closed-loop correction still cannot effectively control the risk after multiple attempts, the system will automatically downgrade from "intelligent optimization mode" to "safety protection mode" and send a manual intervention request to the management and display platform.

[0040] S6. Store and analyze data from the prevention and control process for safety assessment and evaluation of pollutant emissions and carbon reduction effects.

[0041] Specifically, such as Figure 2 As shown, the implementation process of the intelligent control method for methanol vapor diffusion in ships provided by this invention in practical applications is as follows: 1. Initial state monitoring; After the system starts up, the real-time monitoring subsystem collects vibration frequency, pressure, and flow data in real time during the transportation process through sensors distributed at the methanol transfer pump 7 and the press-fit pipe interface 6. For example, when the ship is traveling at 12 knots and the ambient wind direction is 30 degrees to the port, the system continuously records the baseline operating parameters under the current conditions.

[0042] 2. Anomaly identification and diffusion prediction; The control decision unit 8 performs fusion analysis on the collected multi-source data. If the vibration characteristics at the clamp-type interface 6 deviate from the preset normal threshold, the system determines that there is a minor leakage risk. At this time, the methanol vapor diffusion prediction subsystem immediately retrieves the current speed, wind direction, and cabin layout parameters, constructs a diffusion analysis model, and calculates the trend of leaked vapor accumulating upwards along the right side wall of the cabin.

[0043] 3. Proactive and coordinated intervention; Before the methanol gas alarm 5 reaches the legally mandated upper limit alarm concentration, the ventilation linkage control subsystem executes an active prevention and control strategy based on the predicted accumulation path. The system automatically increases the exhaust power of the methanol gas ventilation device 2 on the right side of the engine room, and by changing the local airflow pressure difference, guides the methanol vapor that has not yet accumulated to be safely discharged from the ship's space through the vent mast 1.

[0044] 4. Closed-loop feedback and safety shutdown; If the real-time monitoring subsystem shows that the methanol vapor concentration is still rising, it indicates that the leakage exceeds the ventilation dilution capacity. The control decision unit 8 will trigger the function degradation mechanism and safety shutdown procedure, urgently stopping the operation of the methanol delivery pump 7, and sending fault location and manual maintenance instructions to the management platform. After the maintenance is completed and the sensor confirms that the concentration has dropped below the safe threshold, the system will de-alarm and store the data on this diffusion behavior and control effect in the database for subsequent parameter correction and optimization of the prevention and control model.

[0045] In summary, this invention provides an intelligent prevention and control method for methanol vapor diffusion in ships. By constructing an intelligent prevention and control system that integrates source-end leakage prevention, vapor diffusion prediction, ventilation linkage control, and real-time monitoring and early warning, it achieves proactive prediction, dynamic control, and closed-loop management of methanol vapor diffusion risks, thereby improving the operational safety of methanol-fueled ships and taking into account the synergistic optimization of pollutant emission reduction and carbon emission reduction.

[0046] This invention also provides an intelligent control system for methanol vapor diffusion in ships. The system includes: a methanol fuel delivery subsystem, a real-time monitoring subsystem, a methanol vapor diffusion prediction subsystem, a ventilation-linked control subsystem, a control decision unit, and a management and display platform. The methanol fuel delivery subsystem is used to provide feedback on the delivery flow rate and outlet pressure data of the delivery pump, thereby reducing the probability of methanol fuel leakage during the delivery process. The methanol vapor diffusion prediction subsystem is used to analyze and assess the diffusion behavior of methanol vapor in the ship environment in the event of fuel leaks or abnormal volatilization. The ventilation linkage control subsystem is used to provide feedback on the real-time speed of the fan, the pressure difference in the air duct, and the angle of the guide vanes, and to dynamically adjust the ship's ventilation system when the risk of methanol vapor diffusion occurs or is about to occur. The real-time monitoring subsystem is used to acquire status information of the methanol fuel system and the ship during operation; The control and decision-making unit and management and display platform are used to enable the coordinated operation of various sub-modules of the system.

[0047] Specifically, the installation of an intelligent control system for methanol vapor diffusion on ships is as follows: Figure 3As shown, the intelligent control system consists of a methanol fuel delivery subsystem, a real-time monitoring subsystem, a methanol vapor diffusion prediction subsystem, a ventilation linkage control subsystem, a control decision unit, and a management and display platform. The ventilation linkage control subsystem includes 1 ventilation mast and 2 methanol gas ventilation devices. The real-time monitoring subsystem includes 4 methanol level meters and 5 methanol gas alarms. The methanol fuel delivery subsystem includes 3 methanol storage tanks, 7 methanol delivery pumps, 6 press-fit pipe interfaces, and 9 ship main engine. The methanol vapor diffusion prediction subsystem is a multi-functional control system integrated from all the devices, and it is included in the decision platform along with the control decision unit and the management and display platform.

[0048] The methanol fuel delivery subsystem is primarily used to reduce the probability of methanol fuel leakage during transportation, serving as the source-end protection unit of the control system. In this subsystem, methanol fuel is transported from the storage unit to the main unit via a delivery pump, employing a reliable press-fit sealed pipeline connection structure. Through the overall design and optimization of the fuel delivery path, a stable flow state is maintained during transportation, reducing the risk of leakage caused by pressure fluctuations, vibration, or connection failure. Simultaneously, by monitoring the operating status of the delivery pump, and combining vibration characteristics and flow rate changes, abnormal operating conditions during fuel transportation are identified, providing fundamental data for subsequent control decisions.

[0049] The methanol vapor diffusion prediction subsystem is primarily used to analyze and assess the diffusion behavior of methanol vapor in the ship's environment in the event of fuel leaks or abnormal volatilization. Within this subsystem, a methanol vapor diffusion analysis model is constructed based on ship structural parameters, compartment layout information, navigation status parameters, and environmental parameters. By calculating the diffusion path, concentration changes, and accumulation trends of the vapor under different operating conditions, the risk distribution of methanol vapor in the ship's space is obtained. This prediction scheme can identify potential risk areas before the methanol vapor concentration reaches a hazardous threshold, providing a basis for early intervention in ventilation control and prevention measures, thereby avoiding the response lag problem caused by relying solely on threshold alarms.

[0050] The ventilation linkage control subsystem is used to dynamically adjust the ship's ventilation system when a methanol vapor diffusion risk occurs or is about to occur. Based on the risk level and diffusion path information output by the methanol vapor diffusion prediction scheme, the operating parameters of the ventilation system are adjusted, including but not limited to ventilation volume, wind direction, and supply / exhaust modes, to guide methanol vapor to a safe area or quickly exhaust it from the ship's space. By combining the ventilation system's operating strategy with diffusion prediction results, ventilation control is transformed from a traditional passive response approach to a proactive control approach based on risk assessment, improving vapor dilution efficiency and safety control effectiveness.

[0051] The real-time monitoring subsystem is used to acquire critical status information of the methanol fuel system and ship operation. By installing various types of sensors at key locations in methanol fuel pipelines, valves, storage unit interfaces, and compartments, the subsystem monitors methanol vapor concentration, fuel reserves, and equipment operating status in real time. Continuous acquisition of multi-source data provides a reliable and timely data foundation for the system. Furthermore, by monitoring the vibration characteristics of equipment operation, it can assist in the identification of potential structural loosening, seal failure, and other anomalies, improving the system's ability to detect early risks.

[0052] The control decision unit and management and display platform enable coordinated operation among the various sub-modules of the system. The control decision unit integrates and analyzes data from real-time monitoring and data acquisition schemes and methanol vapor diffusion prediction schemes to generate control strategies for the fuel delivery system and ventilation system. After execution, the results of these control strategies are fed back to the control decision unit for adjustments to model parameters and control strategies, thus forming a closed-loop regulation mechanism. This approach enables dynamic optimization of the system's operating status, improving the overall stability and reliability of the control system. The management and display platform presents real-time visuals to staff, facilitating decision-making and management.

[0053] Fault handling is embedded in the main process as a parallel closed loop, beginning with continuous self-checks and health status reporting by each subsystem. The control decision unit determines the authenticity, location, and severity of the fault based on this information, automatically executing preset responses. Simultaneously, the management platform provides clear fault location, impact descriptions, and manual handling guidelines. All process data is recorded in detail for post-event analysis and model optimization, thus achieving a complete closed loop from fault diagnosis and automatic response to experience learning.

[0054] Given the high toxicity of methanol, prolonged personnel stay in the fuel tanks is not recommended under normal circumstances. This system enables real-time monitoring and automated emergency response of the fuel tanks while they are unmanned, ensuring the safety of the tanks. Even in the absence of a leak, the decision-making platform continues to monitor the operational status of each subsystem and feeds real-time data and operational status back to personnel, achieving full-time intelligent control of the ship's methanol fuel system.

[0055] This system adheres to the principles of "fail-safe" and functional degradation to ensure that no single failure leads to the loss of overall safety functions. Through a strategy combining redundant design, cross-validation, and manual intervention, the system implements layered fault diagnosis and response: at the data layer, cross-validation and redundancy switching are used to address sensor failures; at the execution layer, ventilation or conveying equipment failures are handled through backup equipment activation, path switching, or safety shutdown; at the decision-making layer, mode degradation to threshold-based rule control is adopted, and core functions are protected through responsibility transfer; at the human-machine interaction layer, information availability is ensured through multi-terminal redundancy, local hard alarms, and mobile push notifications.

[0056] The workflow of this intelligent control system is as follows: Methanol fuel is stored in methanol storage tank 3, and its level is monitored in real time by methanol level meter 4. When the ship's main engine 9 is running, methanol transfer pump 7 starts, drawing methanol from the storage tank through pipelines. The pipeline connections use press-fit pipe interfaces 6 to ensure sealing. If methanol vapor leaks from the pipeline or transfer pump, the methanol gas alarm 5 installed at the corresponding location immediately triggers an alarm and transmits the signal to the decision platform 8. Upon receiving the alarm signal, the decision platform sends handling instructions to the personnel and automatically activates the methanol gas ventilation device 2 to perform vapor removal operations, safely discharging the gas through the vent mast 1. Once the methanol vapor concentration in the cabin drops below the safe threshold and the personnel have completed the repair of the leak point, the system alarm is deactivated. During this period, the decision platform continuously collects and stores operational data for subsequent analysis and system optimization.

[0057] In summary, the intelligent control method and system for methanol vapor diffusion in ships provided by the embodiments of the present invention have the following technical advantages: 1) To realize the transformation from the passive response of traditional threshold alarm to the closed-loop prevention and control mode of "prediction-control-feedback", which significantly improves the timeliness and accuracy of methanol vapor diffusion risk prevention and control.

[0058] 2) Effectively solves the problems of decentralized monitoring and fragmented control in existing technologies, enabling the prevention and control system to adapt to the complex working conditions of constantly changing wind direction, speed and cabin environment during ship navigation.

[0059] 3) By optimizing ventilation control strategies and fuel delivery management, disorderly emissions of methanol vapor and fuel loss can be reduced, which helps to reduce pollutant emissions and improve fuel utilization efficiency. This aligns with the green and low-carbon development direction of the shipping industry and has good engineering promotion value and application prospects.

[0060] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0061] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0062] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A smart control method for methanol vapor diffusion in ships, characterized in that, Includes the following steps: Collect operational data on methanol vapor concentration, fuel reserves, and equipment vibration during methanol fuel transportation; Based on the collected operational data and combined with the ship's navigation status and environmental parameters, a methanol vapor diffusion prediction model was constructed. Based on the prediction model, methanol vapor diffusion paths and corresponding risk levels are generated. Develop ventilation and fuel delivery control strategies based on risk levels, and send control commands to the ventilation linkage control subsystem and the methanol fuel delivery subsystem. The control command is executed, and the control result is analyzed to form a closed-loop correction. Data from the prevention and control process will be stored and analyzed for use in safety assessments and evaluations of pollutant emissions and carbon reduction effectiveness.

2. The intelligent control method for methanol vapor diffusion in ships according to claim 1, characterized in that, The construction of the methanol vapor diffusion prediction model includes: A simulation model is established based on the ship's general arrangement drawing and organizational diagram, and the modeling of corresponding small equipment and deck details is simplified according to specific circumstances; The number of grids is determined according to the specific circumstances. The grids are densified in the ventilated mast and areas of interest, and the independence of the grids is verified. The effects of obstacles, temperature, wind direction, and wind speed on gas diffusion are analyzed separately, and the safety assessment and the evaluation of pollutant emissions and carbon reduction effects are based on the analysis data.

3. The intelligent control method for methanol vapor diffusion in ships according to claim 1, characterized in that, The generation of methanol vapor diffusion pathways based on the prediction model includes: The velocity field calculated using the methanol vapor diffusion prediction model was used to simulate the movement trajectory of the vapor emitted from the leak point within the cabin by Lagrange particle tracking or concentration gradient flow direction analysis. By combining ship structural parameters and navigation status, dead zones in the flow field inside the compartment are identified, and the mass concentration distribution of vapor in these areas is calculated. The simulation shows that, with the intervention of the ventilation linkage control subsystem, methanol vapor is guided by forced convection and flows through the methanol gas ventilation device to the dynamic removal path of the ventilation mast.

4. The intelligent control method for methanol vapor diffusion in ships according to claim 1, characterized in that, Based on the prediction model, the corresponding risk levels are generated as follows: Multiple risk levels are set, which are defined as extremely high risk area, high risk area, medium risk area and low risk area. Different levels of protective measures are set according to different areas, and the risk levels are dynamically corrected according to the concentration change rate.

5. The intelligent control method for methanol vapor diffusion in ships according to claim 4, characterized in that, The risk levels are classified as follows: Methanol concentration in area A is greater than This area is an extremely high-risk zone with extremely high concentrations of methanol vapor. Immediate emergency measures must be taken to prohibit personnel from entering. The methanol concentration in zone B is within the range [ This area is a high-risk zone with high concentrations of methanol vapor. Ventilation should be strengthened, personnel entry should be restricted, and appropriate protective equipment should be worn. The methanol concentration in region C is within the range [ This area is a medium-hazard zone with a medium concentration of methanol vapor. Entry is permitted only to designated personnel, with appropriate protective measures in place. The methanol concentration in zone D is less than This area is a low-risk zone with low methanol vapor concentration and is generally safe, but continuous monitoring and good ventilation should be maintained.

6. The intelligent control method for methanol vapor diffusion in ships according to claim 1, characterized in that, The ventilation linkage control subsystem is used to provide feedback on the real-time speed of the fan, the pressure difference in the duct, and the angle of the guide vanes; the methanol fuel delivery subsystem is used to provide feedback on the delivery flow rate and outlet pressure data of the delivery pump.

7. The intelligent control method for methanol vapor diffusion in ships according to claim 1, characterized in that, The ventilation and fuel delivery control strategy is automatically executed by the control decision unit based on the risk level output by real-time monitoring data and predictive models, including: When the risk level reaches the medium danger zone, when an abnormal increase in methanol concentration is detected or an accumulation risk is predicted in the area, the ventilation linkage control subsystem switches from "energy saving mode" to "directional dilution mode". The "decision platform" instructs the methanol gas ventilation device to increase the local exhaust power according to the predicted diffusion path. When the risk level reaches the high-risk zone, the gas ventilation device is instructed to be turned on to the maximum power and the angle of the guide vanes is adjusted to force the mixed gas to be safely discharged from the ship's space through the vent mast. At the same time, the fuel pump triggers the "function degradation" mechanism, and the control command is sent to the methanol transfer pump to reduce the operating frequency of the methanol transfer pump and reduce the transfer pressure in the pipeline. When the risk level reaches the extremely high danger zone, the control decision unit sends an "emergency shutdown" command, the methanol transfer pump stops running, the emergency shut-off valve at the fuel storage tank outlet is closed to block the leak source, and a full-volume forced ventilation strategy is implemented. The management and display platform issues an audible and visual alarm to the entire ship. When the methanol concentration drops to the low danger zone level, management personnel put on protective clothing and enter the maintenance equipment.

8. The intelligent control method for methanol vapor diffusion in ships according to claim 1, characterized in that, The execution of the control command and the feedback analysis of the control result include: After receiving the command, the ventilation linkage control subsystem provides real-time feedback of fan speed and duct pressure differential data. The real-time monitoring subsystem continuously tracks changes in methanol concentration. If the concentration does not decrease as expected after the strategy is executed, the control decision unit automatically raises the risk level and triggers a higher-level safety shutdown response. If the rate of decrease in methanol concentration is lower than the preset threshold, it is determined that the current ventilation strategy is insufficient or there is a deviation in the wind direction guidance. The fluctuation of fuel delivery pressure after the command adjustment is continuously monitored to ensure that the pressure reduction process does not cause system resonance or instability of the delivery flow. The cause of the concentration increase is determined by combining multi-source data.

9. The intelligent control method for methanol vapor diffusion in ships according to claim 1, characterized in that, The implementation path for the closed-loop correction is as follows: Based on the deviation between the control results and the preset target, the calculation parameters of the prediction model and the execution intensity of the ventilation and fuel delivery control strategies are dynamically adjusted; if the concentration removal is slow, the control decision unit automatically adjusts the control parameters, increasing the ventilation volume or reducing the fuel delivery pressure. Based on the actual diffusion trajectory, the operating conditions in the prediction model are corrected. If the risk cannot be effectively controlled after multiple attempts at closed-loop correction, the system automatically downgrades from "intelligent optimization mode" to "safety protection mode" and sends a request for manual intervention to the management and display platform.

10. An intelligent control system for methanol vapor diffusion in ships, used in the intelligent control method for methanol vapor diffusion in ships as described in any one of claims 1 to 9, characterized in that, The system includes: The methanol fuel delivery subsystem is used to provide feedback on the delivery flow rate and outlet pressure data of the delivery pump, thereby reducing the probability of methanol fuel leakage during the delivery process. The methanol vapor diffusion prediction subsystem is used to analyze and assess the diffusion behavior of methanol vapor in the ship environment in the event of fuel leaks or abnormal volatilization. The ventilation linkage control subsystem is used to provide feedback on the real-time speed of the fan, the pressure difference in the air duct, and the angle of the guide vanes, and to dynamically adjust the ship's ventilation system when the risk of methanol vapor diffusion occurs or is about to occur. The real-time monitoring subsystem is used to acquire status information of the methanol fuel system and the ship during operation; The control and decision-making unit and management and display platform are used to enable the coordinated operation of various sub-modules of the system.

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