Safety monitoring system for marine LNG / diesel oil dual-fuel engine

Abstract

The invention provides a marine LNG / diesel oil dual-fuel engine safety monitoring system, which belongs to the technical field of data processing, and comprises a monitoring module for monitoring LGN supply data and diesel oil supply data in real time; the determination module is used for acquiring safety preset data and determining real-time abnormal data and real-time early warning data; the early warning module is used for acquiring a plurality of historical operation data, determining a real-time early warning automatic parameter set, a real-time automatic control instruction and a real-time early warning non-automatic parameter set, executing the real-time automatic control instruction and sending out a real-time early warning alarm; and the abnormal module is used for determining a historical abnormal parameter set of the ship, determining predicted abnormal data and sending a real-time abnormal alarm. The intelligent level of abnormity processing and early warning processing and the accuracy of emergency response can be improved, the requirement for manual intervention is lowered, the safety and reliability of ship operation are improved, the response speed and decision-making efficiency of the system are improved, and the safety monitoring capacity of the LNG / diesel oil dual-fuel engine for the ship is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a marine LNG / diesel dual-fuel engine safety monitoring system. Background Art

[0002] The continuous development of the marine industry, particularly the widespread use of LNG / diesel dual-fuel engines, has placed higher demands on ship engine safety monitoring systems. Traditional monitoring systems rely primarily on manual experience and simple threshold alarm mechanisms. These systems typically only issue alarms after an anomaly occurs, lack the ability to predict potential problems, and are unable to implement automatic control. For example, when a traditional monitoring system detects a low LNG tank level or high diesel supply pressure, it can only issue a simple alarm without automatically adjusting relevant parameters or taking preventive measures. Furthermore, traditional systems lack the ability to process complex data, predict potential problems, and implement automatic control, making them unable to meet the high safety and reliability requirements of modern ships.

[0003] In recent years, with the rapid development of sensor technology, data processing technology, and automated control technology, intelligent monitoring systems have gradually become a research hotspot. Through real-time monitoring, data analysis, and automated control, these systems can improve the efficiency of identifying and addressing potential safety issues. However, existing technologies still need further improvement in multimodal data fusion, historical data utilization, and the identification of anomalies and warnings.

[0004] Therefore, the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system. Summary of the Invention

[0005] The present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system. The system determines real-time abnormal data and real-time warning data through real-time monitoring of LGN supply data, diesel supply data, and acquired safety preset data. Based on the acquired historical operating data and real-time warning data, the system determines and executes real-time automatic control instructions, determines a real-time warning non-automatic parameter set, and issues a real-time warning alarm. Based on the historical operating data, the system determines a historical abnormal parameter set of the ship, determines predicted abnormal data, and issues a real-time abnormal alarm. The system can accurately identify the ship's abnormal parameters and warning parameters, improve the intelligent level of abnormality processing and warning processing, and the accuracy of emergency response, reduce the need for manual intervention, improve the safety and reliability of ship operation, increase system response speed and decision-making efficiency, and enhance the safety monitoring capability of marine LNG / diesel dual-fuel engines.

[0006] The present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system, comprising: Monitoring module: real-time monitoring of LGN supply data based on LGN supply, real-time monitoring of diesel supply data based on diesel supply; Determination module: obtains safety preset data, determines the real-time abnormal parameter set and the real-time warning parameter set based on LGN supply data, diesel supply data and safety preset data, and determines the real-time abnormal data and real-time warning data; Early warning module: Obtains multiple historical operation data, determines the real-time early warning automatic parameter set, real-time automatic control instructions, and real-time early warning non-automatic parameter set based on all historical operation data and real-time early warning data, executes the real-time automatic control instructions, and issues a real-time early warning alarm; Abnormal module: Determine the historical abnormal parameter set of the ship based on the historical operation data, and based on the historical abnormal parameter set and real-time abnormal data, determine the predicted abnormal data and issue a real-time abnormal alarm.

[0007] According to the present invention, a marine LNG / diesel dual-fuel engine safety monitoring system and a monitoring module are provided, comprising: LGN supply data unit: monitors LGN supply data based on the LGN supply at a current time point in real time based on the first sensor group, wherein the LGN supply data includes LGN storage tank data, gas supply pipeline data, and vaporizer data; the LGN storage tank data includes multiple real-time monitoring values of parameters with parameter labels being LGN storage tanks; the gas supply pipeline data includes multiple real-time monitoring values of parameters with parameter labels being gas supply pipelines; and the vaporizer data includes multiple real-time monitoring values of parameters with parameter labels being vaporizers; Diesel supply data unit: Based on the second sensor group, real-time monitoring of diesel supply data based on diesel supply at the current time point, wherein the diesel supply data includes diesel storage tank data and fuel supply pipeline data. The diesel storage tank data includes multiple parameter labels that are real-time monitoring values of parameters of the diesel storage tank, and the fuel supply pipeline data includes multiple parameter labels that are real-time monitoring values of parameters of the fuel supply pipeline.

[0008] According to the present invention, a marine LNG / diesel dual-fuel engine safety monitoring system is provided, wherein the determination module comprises: Safety preset data unit: obtains safety preset data of the ship, wherein the safety preset data includes LGN storage safety data, gas supply safety data, vaporization safety data, diesel storage safety data, and oil supply safety data. The LGN storage safety data includes the safety range of each parameter labeled as an LGN storage tank, the gas supply safety data includes the safety range of each parameter labeled as a gas supply pipeline parameter, the vaporization safety data includes the safety range of each parameter labeled as a vaporizer parameter, the diesel storage safety data includes the safety range of each parameter labeled as a diesel storage tank parameter, and the oil supply safety data includes the safety range of each parameter labeled as a oil supply pipeline parameter; Real-time temperature value unit: obtains the real-time temperature value of the ship's location; Safety tag unit: determines the first real-time safety tag and the second real-time safety tag of all parameters based on LGN supply data, diesel supply data, real-time temperature value and safety preset data; Parameter set unit: determines a real-time abnormal parameter set and a real-time warning parameter set based on the first safety tags and the second safety tags of all parameters.

[0009] According to the present invention, a marine LNG / diesel dual-fuel engine safety monitoring system, the determination module further includes: Real-time abnormal data unit: determines real-time abnormal data based on all parameters in the real-time abnormal parameter set and the real-time monitoring value corresponding to each parameter; Real-time warning data unit: determines real-time warning data based on all parameters in the real-time warning parameter set and the real-time monitoring value corresponding to each parameter.

[0010] According to the present invention, a marine LNG / diesel dual-fuel engine safety monitoring system is provided, comprising: Historical operation data unit: obtains historical operation data within multiple specified time periods, wherein the historical operation data includes historical warning data and historical abnormal data within the specified time period; Historical warning data unit: extracts historical warning data from historical operating data within each specified time period, wherein the historical warning data includes the historical warning parameter set within the specified time period and the historical monitoring value, historical monitoring time point, emergency strategy, emergency strategy label, and emergency result of each parameter with a historical safety label as a warning label in the historical warning parameter set. The emergency strategy label includes automatic control strategy and non-automatic control strategy, and the emergency results include excellent, good, and fair. Automatic control parameter subset unit: extracts all parameters whose emergency strategy label is automatic control strategy and whose emergency results are excellent from the historical warning parameter set in the historical warning data of each specified time period, and determines the automatic control parameter subset for each specified time period; Early warning automatic control parameter set unit: determines the early warning automatic control parameter set of the ship based on the automatic control parameter subsets of all specified time periods; Emergency strategy table unit: Based on the historical warning data of all specified time periods, all historical monitoring values and emergency strategies of each parameter in the ship's early warning automatic control parameter set with the emergency strategy label of automatic control strategy and excellent emergency results are extracted to construct an emergency strategy table for each parameter in the ship's early warning automatic control parameter set; Real-time warning automatic parameter set unit: determines the real-time warning automatic parameter set based on all parameters in the real-time warning parameter set in the real-time warning data and the warning automatic control parameter set of the ship; Real-time automatic control strategy unit: Calculate the difference between the real-time monitoring value of each parameter in the real-time warning automatic parameter set in the real-time warning data and all the historical monitoring values in the emergency strategy table of each parameter in the real-time warning automatic parameter set, and select the emergency strategy corresponding to the historical monitoring value with the smallest difference as the real-time automatic control strategy for each parameter in the real-time warning automatic parameter set; Real-time automatic control sub-instruction unit: generates a real-time automatic control sub-instruction for each parameter in the real-time early warning automatic parameter set based on the real-time automatic control strategy of each parameter in the real-time early warning automatic parameter set; The real-time warning non-automatic parameter set unit determines the real-time warning non-automatic parameter set based on the real-time warning parameter set and the real-time warning automatic parameter set in the real-time warning data.

[0011] A marine LNG / diesel dual-fuel engine safety monitoring system provided by the present invention further includes: Real-time automatic control instruction unit: determines the real-time automatic control instruction based on the real-time automatic control sub-instructions of all parameters in the real-time warning automatic parameter set, and executes the real-time automatic control sub-instruction of each parameter in the real-time automatic control instruction; Real-time warning alarm unit: issues a real-time warning alarm for each parameter in the real-time warning non-automatic parameter set.

[0012] According to the present invention, a marine LNG / diesel dual-fuel engine safety monitoring system, an abnormality module, includes: Historical abnormal data unit: extracts historical abnormal data from historical operating data within each specified time period, wherein the historical abnormal data includes a subset of historical abnormal parameters within the specified time period, and historical monitoring values of each parameter with a historical safety label as an abnormal label in the subset of historical abnormal parameters at all historical monitoring time points within the specified time period; Historical abnormal parameter set unit: determines the historical abnormal parameter set of the ship based on the historical abnormal parameter subset in all historical abnormal data within a specified time period.

[0013] According to the present invention, a marine LNG / diesel dual-fuel engine safety monitoring system, an abnormality module, further includes: Construction unit: Builds a ship abnormality prediction model based on the ship's historical abnormal parameter set and all historical operating data of a specified time period; Training unit: Based on the historical abnormal parameter set of the ship, the historical monitoring values of each parameter with a historical safety label as an abnormal label in the historical abnormal parameter subset of all historical abnormal data in a specified time period at all historical monitoring time points, as the input of the abnormality prediction model, and the historical monitoring values and historical monitoring time of each parameter with a historical safety label as an alarm label in the historical alarm parameter set of all historical alarm data in a specified time period as the output of the abnormality prediction model, the ship's abnormality prediction model is trained; Anomaly prediction unit: Inputs the real-time monitoring value of each parameter in the real-time abnormal parameter set in the real-time abnormal data and the current time point into the abnormality prediction model, and determines the predicted abnormal data based on the output result of the abnormality prediction model, wherein the predicted abnormal data includes the predicted warning time points of all parameters in the real-time abnormal parameter set; Time anomaly alarm unit: issues real-time anomaly alarms based on the predicted warning time points of all parameters in each anomaly parameter set and the current time point.

[0014] Compared with the prior art, the present invention has the following advantages: By monitoring LGN supply and diesel supply data in real time, as well as acquired safety preset data, the system identifies real-time abnormal data and real-time warning data. Based on acquired historical operating data and real-time warning data, it determines and executes real-time automatic control instructions, determines a set of real-time warning non-automatic parameters, and issues real-time warning alarms. Based on historical operating data, it determines a set of historical abnormal parameters for the ship, determines predicted abnormal data, and issues real-time abnormality alarms. This system can accurately identify a ship's abnormal and warning parameters, improving the intelligence level of abnormal and warning processing and the accuracy of emergency response, reducing the need for manual intervention, enhancing the safety and reliability of ship operations, improving system response speed and decision-making efficiency, and strengthening the safety monitoring capabilities of marine LNG / diesel dual-fuel engines. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 This is a schematic structural diagram of a marine LNG / diesel dual-fuel engine safety monitoring system provided by an embodiment of the present invention; Figure 2 This is a structural diagram of a determination module of a marine LNG / diesel dual-fuel engine safety monitoring system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0018] Example 1

[0019] The embodiment of the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system, such as Figure 1 As shown, including: Monitoring module: real-time monitoring of LGN supply data based on LGN supply, real-time monitoring of diesel supply data based on diesel supply; Determination module: obtains safety preset data, determines the real-time abnormal parameter set and the real-time warning parameter set based on LGN supply data, diesel supply data and safety preset data, and determines the real-time abnormal data and real-time warning data; Early warning module: Obtains multiple historical operation data, determines the real-time early warning automatic parameter set, real-time automatic control instructions, and real-time early warning non-automatic parameter set based on all historical operation data and real-time early warning data, executes the real-time automatic control instructions, and issues a real-time early warning alarm; Abnormal module: Determine the historical abnormal parameter set of the ship based on the historical operation data, and based on the historical abnormal parameter set and real-time abnormal data, determine the predicted abnormal data and issue a real-time abnormal alarm.

[0020] In this embodiment, the determination module retrieves a pre-set safety range from the system database, compares the real-time monitoring data with the pre-set safety data, and determines the first and second safety labels for each parameter. The module then determines which parameters belong to the real-time abnormal parameter set and which belong to the real-time warning parameter set.

[0021] In this embodiment, the early warning module obtains multiple historical operation data, determines the real-time early warning automatic parameter set, real-time automatic control instructions and real-time early warning non-automatic parameter set based on the historical early warning data and real-time early warning data in the historical operation data, executes the real-time automatic control instructions and issues a real-time early warning alarm.

[0022] In this embodiment, the parameters in the real-time warning automatic parameter set can be solved through automatic control, while the parameters in the real-time warning non-automatic parameter set require manual intervention.

[0023] In this embodiment, for all parameters that can be resolved through automatic control, real-time automatic control instructions are generated and executed; for all parameters that require manual intervention, real-time early warning alarms are issued.

[0024] The beneficial effects of the above technical solution include: determining real-time abnormal data and real-time warning data through real-time monitoring of LGN supply data, diesel supply data, and acquired safety preset data; determining and executing real-time automatic control instructions based on acquired historical operating data and real-time warning data; determining a set of real-time warning non-automatic parameters and issuing real-time warning alarms; determining a set of historical abnormal parameters for the ship based on historical operating data, determining predicted abnormal data, and issuing real-time abnormal alarms. This system can accurately identify a ship's abnormal and warning parameters, improving the intelligence level of abnormal and warning processing and the accuracy of emergency response, reducing the need for manual intervention, improving the safety and reliability of ship operations, enhancing system response speed and decision-making efficiency, and enhancing the safety monitoring capabilities of marine LNG / diesel dual-fuel engines.

[0025] Example 2

[0026] The embodiment of the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system, including a monitoring module, comprising: LGN supply data unit: monitors LGN supply data based on the LGN supply at a current time point in real time based on the first sensor group, wherein the LGN supply data includes LGN storage tank data, gas supply pipeline data, and vaporizer data; the LGN storage tank data includes multiple real-time monitoring values of parameters with parameter labels being LGN storage tanks; the gas supply pipeline data includes multiple real-time monitoring values of parameters with parameter labels being gas supply pipelines; and the vaporizer data includes multiple real-time monitoring values of parameters with parameter labels being vaporizers; Diesel supply data unit: Based on the second sensor group, real-time monitoring of diesel supply data based on diesel supply at the current time point, wherein the diesel supply data includes diesel storage tank data and fuel supply pipeline data. The diesel storage tank data includes multiple parameter labels that are real-time monitoring values of parameters of the diesel storage tank, and the fuel supply pipeline data includes multiple parameter labels that are real-time monitoring values of parameters of the fuel supply pipeline.

[0027] In this embodiment, the LNG storage tank data includes monitoring multiple parameters of the LNG storage tank, such as liquid level, pressure, temperature, etc. These parameters are collected in real time by sensors to ensure comprehensive monitoring of the storage tank status.

[0028] In this embodiment, for example: Liquid level monitoring: A liquid level sensor monitors the liquid level of the LNG tank in real time to prevent the liquid level from being too low or too high. Pressure monitoring: A pressure sensor monitors the pressure of the LNG tank in real time to prevent excessive pressure from causing the tank to rupture. Temperature monitoring: A temperature sensor monitors the temperature of the LNG tank in real time to ensure that the temperature is within a safe range.

[0029] In this embodiment, the gas supply pipeline data: monitors multiple parameters of the gas supply pipeline, such as pressure, flow, temperature, etc. These data help evaluate the operating status of the gas supply system and promptly detect problems such as leaks or blockages.

[0030] In this embodiment, for example: Pressure monitoring: A pressure sensor monitors the pressure of the gas supply line in real time to ensure stable pressure. Flow monitoring: A flow sensor monitors the flow rate of the gas supply line in real time to ensure it is within the designed range. Temperature monitoring: A temperature sensor monitors the temperature of the gas supply line in real time to prevent it from being too high or too low.

[0031] In this embodiment, the vaporizer data: monitors multiple parameters of the vaporizer, such as medium temperature, inlet and outlet pressures, vaporization efficiency, etc. These data ensure that the vaporizer operates normally and avoid safety issues caused by incomplete vaporization.

[0032] In this embodiment, for example: Medium temperature monitoring: A temperature sensor monitors the temperature of the vaporizer medium in real time to ensure the normal operation of the vaporizer. Inlet and outlet pressure monitoring: A pressure sensor monitors the inlet and outlet pressures of the vaporizer in real time to ensure that the pressures are within a safe range. Vaporization efficiency monitoring: A flow sensor and a temperature sensor comprehensively evaluate the vaporization efficiency of the vaporizer to ensure that the LNG is fully vaporized.

[0033] In this embodiment, diesel tank data: monitors multiple parameters of the diesel tank, such as liquid level, temperature, pressure, etc. These parameters are collected in real time by sensors to ensure comprehensive monitoring of the tank status.

[0034] In this embodiment, for example: Liquid level monitoring: A liquid level sensor monitors the diesel tank's liquid level in real time to prevent it from being too low or too high. Temperature monitoring: A temperature sensor monitors the diesel tank's temperature in real time to ensure it's within a safe range. Pressure monitoring: A pressure sensor monitors the diesel tank's pressure in real time to prevent it from being too high.

[0035] In this embodiment, the fuel supply pipeline data: monitors multiple parameters of the fuel supply pipeline, such as pressure, flow, temperature, etc. These data help evaluate the operating status of the fuel supply system and promptly detect problems such as leaks or blockages.

[0036] In this embodiment, for example: Pressure monitoring: A pressure sensor monitors the pressure of the oil supply line in real time to ensure stable pressure. Flow monitoring: A flow sensor monitors the flow rate of the oil supply line in real time to ensure it is within the designed range. Temperature monitoring: A temperature sensor monitors the temperature of the oil supply line in real time to prevent it from being too high or too low.

[0037] The beneficial effects of the above technical solution are: real-time monitoring of LGN supply data based on LGN supply, and real-time monitoring of diesel supply data based on diesel supply, which can provide data support for determining real-time abnormal parameter sets and real-time warning parameter sets.

[0038] Example 3

[0039] An embodiment of the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system, including a determination module, comprising: Safety preset data unit: obtains safety preset data of the ship, wherein the safety preset data includes LGN storage safety data, gas supply safety data, vaporization safety data, diesel storage safety data, and oil supply safety data. The LGN storage safety data includes the safety range of each parameter labeled as an LGN storage tank, the gas supply safety data includes the safety range of each parameter labeled as a gas supply pipeline parameter, the vaporization safety data includes the safety range of each parameter labeled as a vaporizer parameter, the diesel storage safety data includes the safety range of each parameter labeled as a diesel storage tank parameter, and the oil supply safety data includes the safety range of each parameter labeled as a oil supply pipeline parameter; Real-time temperature value unit: obtains the real-time temperature value of the ship's location; Safety tag unit: determines the first real-time safety tag and the second real-time safety tag of all parameters based on LGN supply data, diesel supply data, real-time temperature value and safety preset data; Parameter set unit: determines a real-time abnormal parameter set and a real-time warning parameter set based on the first safety tags and the second safety tags of all parameters.

[0040] In this embodiment, the LNG storage safety data includes the safety ranges of all parameters with the parameter label "LNG storage tank", such as liquid level, pressure, temperature, etc. The gas supply safety data includes the safety ranges of all parameters with the parameter label "gas supply pipeline", such as pressure, flow rate, temperature, etc. The vaporization safety data includes the safety ranges of all parameters with the parameter label "vaporizer", such as medium temperature, inlet and outlet pressures, etc. The diesel storage safety data includes the safety ranges of all parameters with the parameter label "diesel storage tank", such as liquid level, temperature, pressure, etc. The oil supply safety data includes the safety ranges of all parameters with the parameter label "oil supply pipeline", such as pressure, flow rate, temperature, etc.

[0041] In this embodiment, the ambient temperature of the vessel is collected in real time by an ambient temperature sensor installed on the vessel.

[0042] In this embodiment, the safety tag unit determines the first real-time safety tag of all parameters based on the LGN supply data, the diesel supply data, and the safety preset data. The determination formula can be expressed as: ; in, Indicates the first security label of the bth parameter in the a data. , a=1 represents LGN storage tank data, a=2 represents air supply pipeline data, a=3 represents carburetor data, a=4 represents diesel storage tank data, a=5 represents oil supply pipeline data, Indicates the real-time monitoring value of the bth parameter in the a data. Indicates the lower limit of the safety range of the bth parameter in the a data. Indicates the upper limit of the safety range of the bth parameter in the a data. Indicates the upper limit closeness of the bth parameter in the a data, It represents the lower limit proximity of the bth parameter in the a data, and TP represents the preset proximity threshold.

[0043] In this embodiment, when a=1, Indicates that the bth parameter label in the LGN storage tank data is the parameter of the LGN storage tank. When a=2, Indicates that the bth parameter label in the gas supply pipeline data is the parameter of the gas supply pipeline. When a=3, Indicates that the bth parameter label in the vaporizer data is the parameter of the vaporizer. When a=4, Indicates that the bth parameter label in the diesel storage tank data is the parameter of the diesel storage tank. When a=5, Indicates that the bth parameter label in the oil supply pipeline data is the parameter of the oil supply pipeline.

[0044] In this embodiment, Indicates the real-time monitoring value of the bth parameter in the a data. For example, when a=1, Indicates the real-time monitoring value of the bth LGN storage tank parameter in the LGN storage tank data. When a=2, Indicates the real-time monitoring value of the bth gas supply pipeline parameter in the gas supply pipeline data. When a=3, Indicates the real-time monitoring value of the bth vaporizer parameter in the vaporizer data. When a=4, Indicates the real-time monitoring value of the bth diesel storage tank parameter in the diesel storage tank data. When a=5, Indicates the real-time monitoring value of the bth fuel supply pipeline parameter in the fuel supply pipeline data.

[0045] In this embodiment, the safety tag unit determines the second real-time safety tag of all parameters based on the LGN supply data, the diesel supply data, and the safety preset data. The determination formula can be expressed as: ; in, Indicates the second security label of the bth parameter in the a data. Indicates the safety buffer value of the bth parameter in the a data. represents the temperature sensitivity factor, Indicates the real-time temperature value. represents the high temperature critical value, represents the low temperature critical value, Indicates the historical standard deviation of the bth parameter in the a data. represents the buffer adjustment factor, Indicates the coordinated risk value of LGN supply data and diesel supply data, Indicates the early warning risk threshold, Indicates the abnormal risk threshold, It represents the abnormal judgment sub-condition of the abnormal label, and aN1 represents the number of parameters in the a data.

[0046] In this embodiment, the real-time abnormal parameter set and the real-time warning parameter set labels: the parameter set unit: determines the real-time abnormal parameter set and the real-time warning parameter set based on the security labels of all parameters. The determination formula can be expressed as: ; ; ; Among them, EW represents the real-time warning parameter set, AB represents the real-time abnormal parameter set, A data parameter set representing all parameters of all data in LGN supply data and diesel supply data. Indicates the bth parameter in the a data.

[0047] The beneficial effects of the above technical solution are: obtaining safety preset data, determining the real-time abnormal parameter set and the real-time warning parameter set based on LGN supply data, diesel supply data and safety preset data, accurately identifying the ship's abnormal parameters and warning parameters, improving the safety and reliability of ship operation, and reducing the risk of accidents.

[0048] Example 4

[0049] An embodiment of the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system, wherein the determination module further includes: Real-time abnormal data unit: determines real-time abnormal data based on all parameters in the real-time abnormal parameter set and the real-time monitoring value corresponding to each parameter; Real-time warning data unit: determines real-time warning data based on all parameters in the real-time warning parameter set and the real-time monitoring value corresponding to each parameter.

[0050] In this embodiment, all parameters in the real-time abnormal parameter set and their corresponding real-time monitoring values are integrated to determine real-time abnormal data.

[0051] In this embodiment, all parameters in the real-time warning parameter set and their corresponding real-time monitoring values are integrated to determine real-time warning data.

[0052] The beneficial effects of the above technical solution are: determining real-time abnormal data and real-time warning data can improve the accuracy and reliability of real-time warning alarms and real-time abnormal alarms, reduce false alarm rates, and enhance the intelligence level and emergency response capabilities of the security monitoring system.

[0053] Example 5

[0054] The embodiment of the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system and an early warning module, comprising: Historical operation data unit: obtains historical operation data within multiple specified time periods, wherein the historical operation data includes historical warning data and historical abnormal data within the specified time period; Historical warning data unit: extracts historical warning data from historical operating data within each specified time period, wherein the historical warning data includes the historical warning parameter set within the specified time period and the historical monitoring value, historical monitoring time point, emergency strategy, emergency strategy label, and emergency result of each parameter with a historical safety label as a warning label in the historical warning parameter set. The emergency strategy label includes automatic control strategy and non-automatic control strategy, and the emergency results include excellent, good, and fair. Automatic control parameter subset unit: extracts all parameters whose emergency strategy label is automatic control strategy and whose emergency results are excellent from the historical warning parameter set in the historical warning data of each specified time period, and determines the automatic control parameter subset for each specified time period; Early warning automatic control parameter set unit: determines the early warning automatic control parameter set of the ship based on the automatic control parameter subsets of all specified time periods; Emergency strategy table unit: Based on the historical warning data of all specified time periods, all historical monitoring values and emergency strategies of each parameter in the ship's early warning automatic control parameter set with the emergency strategy label of automatic control strategy and excellent emergency results are extracted to construct an emergency strategy table for each parameter in the ship's early warning automatic control parameter set; Real-time warning automatic parameter set unit: determines the real-time warning automatic parameter set based on all parameters in the real-time warning parameter set in the real-time warning data and the warning automatic control parameter set of the ship; Real-time automatic control strategy unit: Calculate the difference between the real-time monitoring value of each parameter in the real-time warning automatic parameter set in the real-time warning data and all the historical monitoring values in the emergency strategy table of each parameter in the real-time warning automatic parameter set, and select the emergency strategy corresponding to the historical monitoring value with the smallest difference as the real-time automatic control strategy for each parameter in the real-time warning automatic parameter set; Real-time automatic control sub-instruction unit: generates a real-time automatic control sub-instruction for each parameter in the real-time early warning automatic parameter set based on the real-time automatic control strategy of each parameter in the real-time early warning automatic parameter set; The real-time warning non-automatic parameter set unit determines the real-time warning non-automatic parameter set based on the real-time warning parameter set and the real-time warning automatic parameter set in the real-time warning data.

[0055] In this embodiment, the historical operation data unit extracts historical operation data from the system database for multiple time periods (e.g., the past week, month, three months, etc.). The historical operation data includes historical warning data and historical abnormality data, which record various situations in the past system operation and their processing results.

[0056] In this embodiment, parameters with an emergency strategy label of automatic control strategy and excellent emergency response results within each specified time period are extracted to determine an automatic control parameter subset. The automatic control parameter subset unit traverses the historical warning data for each time period and selects parameters that meet the criteria. These parameters are those that have shown good automatic control results in historical operations.

[0057] In this embodiment, the early warning automatic control parameter collection unit aggregates the automatic control parameter subsets of all time periods to form a comprehensive early warning automatic control parameter collection. This collection includes all parameters with good automatic control effects in the past, providing a basis for subsequent real-time early warning processing.

[0058] In this embodiment, the emergency strategy table unit extracts all historical monitoring values and corresponding emergency strategies for each parameter in the early warning automatic control parameter set. The emergency strategy table records the emergency strategies for each parameter under different historical monitoring values, providing a decision basis for real-time early warning processing.

[0059] In this embodiment, the real-time warning automatic parameter set unit compares the parameters in the real-time warning data with the warning automatic control parameter set to select the parameters that can be automatically controlled. These parameters are considered to be parameters to which the automatic control strategy can be applied.

[0060] In this embodiment, the real-time automatic control strategy unit calculates the difference between the real-time monitored value of each parameter in the real-time warning automatic parameter set and all historical monitored values in the emergency strategy table. The emergency strategy corresponding to the historical monitored value with the smallest difference is selected as the real-time automatic control strategy. This method ensures that the real-time control strategy is selected based on historical optimal experience, improving control accuracy.

[0061] In this embodiment, the real-time automatic control sub-instruction unit generates specific control instructions according to the selected real-time automatic control strategy.

[0062] In this embodiment, a real-time warning parameter set and a real-time warning automatic parameter set in the real-time warning data are subtracted to determine a real-time warning non-automatic parameter set, wherein all parameters in the real-time warning non-automatic parameter set require manual intervention.

[0063] The beneficial effects of the above technical solution are: obtaining multiple historical operation data, determining the real-time warning automatic parameter set, real-time automatic control instructions and real-time warning non-automatic parameter set based on all historical warning data and real-time warning data, which can improve the intelligence level of warning processing and the accuracy of emergency response, reduce the need for manual intervention, and enhance the safety and reliability of the system.

[0064] Example 6

[0065] The embodiment of the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system, including an early warning module, further comprising: Real-time automatic control instruction unit: determines the real-time automatic control instruction based on the real-time automatic control sub-instructions of all parameters in the real-time warning automatic parameter set, and executes the real-time automatic control sub-instruction of each parameter in the real-time automatic control instruction; Real-time warning alarm unit: issues a real-time warning alarm for each parameter in the real-time warning non-automatic parameter set.

[0066] In this embodiment, the real-time automatic control instruction unit integrates all the real-time automatic control sub-instructions in the real-time warning automatic parameter set to form a comprehensive real-time automatic control instruction. The comprehensive real-time automatic control instruction is executed to ensure that the real-time automatic control sub-instructions of each parameter can be accurately executed.

[0067] In this embodiment, during the execution process, the execution effect of each sub-command is monitored in real time to ensure the effectiveness of the control measures. If a sub-command fails to execute or the effect is poor, the system will record it and issue a reminder alarm to remind the operator to intervene manually.

[0068] In this embodiment, the real-time warning alarm unit generates a corresponding real-time warning alarm for each parameter in the real-time warning non-automatic parameter set. The alarm content includes detailed information such as the parameter name, real-time monitoring value, and the warning reason. The alarm is issued to the operator through an audible and visual alarm, a display prompt, or a remote notification, ensuring that the operator receives the alarm in a timely manner and takes appropriate measures.

[0069] In this embodiment, all issued alarms are recorded in the system database, including the alarm time, parameter name, real-time monitoring value, warning reason, etc. By issuing real-time early warning alarms, operators are reminded to pay attention to parameters that require manual intervention, ensuring that operators can take timely measures to avoid potential safety issues.

[0070] The beneficial effects of the above technical solution are: executing real-time automatic control instructions and issuing real-time early warning alarms can improve the system's degree of automation and response speed, ensure the timeliness and effectiveness of manual intervention, enhance the safety monitoring capabilities of marine LNG / diesel dual-fuel engines, reduce accident risks, and improve overall operational efficiency.

[0071] Example 7

[0072] The embodiment of the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system, including an abnormality module, comprising: Historical abnormal data unit: extracts historical abnormal data from historical operating data within each specified time period, wherein the historical abnormal data includes a subset of historical abnormal parameters within the specified time period, and historical monitoring values of each parameter with a historical safety label as an abnormal label in the subset of historical abnormal parameters at all historical monitoring time points within the specified time period; Historical abnormal parameter set unit: determines the historical abnormal parameter set of the ship based on the historical abnormal parameter subset in all historical abnormal data within a specified time period.

[0073] In this embodiment, the historical abnormality data unit extracts historical operating data from the database for each specified time period. The system then filters out abnormal historical data within this extracted data. This data identifies which parameters have exhibited abnormalities during historical operations. For example, the system can filter out abnormal historical data such as low LNG tank liquid levels, excessive gas pipeline pressure, and abnormal vaporizer medium temperatures.

[0074] In this embodiment, the abnormal parameter subset refers to the set of all parameters with the historical safety tag "abnormal tag" within a corresponding specified time period. For example, if the LNG tank liquid level and gas supply pipeline pressure have been abnormal within a certain time period, these two parameters will be included in the historical abnormal parameter subset.

[0075] In this embodiment, the historical abnormal parameter collection unit aggregates all historical abnormal parameter subsets within a specified time period to form a comprehensive historical abnormal parameter collection.

[0076] The beneficial effects of the above technical solution are: by determining the historical abnormal parameter set of the ship based on historical operating data, potential anomalies can be accurately identified and predicted, measures can be taken in advance, the system's abnormality identification ability and abnormality handling efficiency can be improved, the risk of accidents can be reduced, and the safety and reliability of ship operation can be enhanced.

[0077] Example 8

[0078] An embodiment of the present invention provides a marine LNG / diesel dual-fuel engine safety monitoring system, including an abnormality module, further comprising: Construction unit: Builds a ship abnormality prediction model based on the ship's historical abnormal parameter set and all historical operating data of a specified time period; Training unit: Based on the historical abnormal parameter set of the ship, the historical monitoring values of each parameter with a historical safety label as an abnormal label in the historical abnormal parameter subset of all historical abnormal data in a specified time period at all historical monitoring time points, as the input of the abnormality prediction model, and the historical monitoring values and historical monitoring time of each parameter with a historical safety label as an alarm label in the historical alarm parameter set of all historical alarm data in a specified time period as the output of the abnormality prediction model, the ship's abnormality prediction model is trained; Anomaly prediction unit: Inputs the real-time monitoring value of each parameter in the real-time abnormal parameter set in the real-time abnormal data and the current time point into the abnormality prediction model, and determines the predicted abnormal data based on the output result of the abnormality prediction model, wherein the predicted abnormal data includes the predicted warning time points of all parameters in the real-time abnormal parameter set; Time anomaly alarm unit: issues real-time anomaly alarms based on the predicted warning time points of all parameters in each anomaly parameter set and the current time point.

[0079] In this embodiment, the construction unit integrates the historical abnormal parameter set and historical operating data from all specified time periods to form a comprehensive dataset. A suitable prediction model is selected, such as a time series analysis model (e.g., ARIMA), a machine learning model (e.g., random forest, support vector machine), or a deep learning model (e.g., LSTM). Based on this integrated dataset, an anomaly prediction model is constructed to predict the time when each abnormal parameter will exceed its corresponding safety range.

[0080] In this embodiment, the training unit uses the historical monitoring values of each parameter with a historical safety label as an anomaly label in the historical anomaly parameter set at all historical monitoring time points as the model input. The model outputs the historical monitoring values of each parameter with a historical safety label as an alarm label in the historical alarm parameter set, as well as the historical monitoring time, from all historical alarm data for a specified time period. The input and output data are used to train the anomaly prediction model, optimize model parameters, and improve prediction accuracy and reliability.

[0081] In this embodiment, the real-time monitoring value of each parameter in the real-time abnormal parameter set and the current time point are input into the trained abnormality prediction model. The model predicts the occurrence time point of the potential warning of each parameter based on the input data.

[0082] In this embodiment, the real-time abnormality alarm unit compares the predicted warning time point with the current time point. If the predicted warning time point is close to the current time point, a real-time abnormality alarm is triggered. The alarm content includes detailed information such as the parameter name, real-time monitoring value, and predicted warning time point. The alarm method can be through an audible and visual alarm, a display prompt, or a remote notification to alert the operator to take appropriate measures.

[0083] The beneficial effects of the above technical solution include determining predicted abnormal data and issuing real-time abnormality alerts based on a set of historical abnormality parameters and real-time abnormality data. This improves the accuracy and timeliness of early warnings for real-time abnormality data, enhances the intelligence level of the system, reduces accident risks, and improves the safety and reliability of ship operations.

[0084] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0085] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A marine LNG / diesel dual-fuel engine safety monitoring system, characterized in that: include: Monitoring module: real-time monitoring of LGN supply data based on LGN supply, real-time monitoring of diesel supply data based on diesel supply; Determination module: obtains safety preset data, determines the real-time abnormal parameter set and the real-time warning parameter set based on LGN supply data, diesel supply data and safety preset data, and determines the real-time abnormal data and real-time warning data; Early warning module: Obtains multiple historical operation data, determines the real-time early warning automatic parameter set, real-time automatic control instructions, and real-time early warning non-automatic parameter set based on all historical operation data and real-time early warning data, executes the real-time automatic control instructions, and issues a real-time early warning alarm; Abnormal module: Determine the historical abnormal parameter set of the ship based on the historical operation data, and based on the historical abnormal parameter set and real-time abnormal data, determine the predicted abnormal data and issue a real-time abnormal alarm.

2. A marine LNG / diesel dual-fuel engine safety monitoring system according to claim 1, characterized in that: Monitoring module, including: LGN supply data unit: monitors LGN supply data based on the LGN supply at a current time point in real time based on the first sensor group, wherein the LGN supply data includes LGN storage tank data, gas supply pipeline data, and vaporizer data; the LGN storage tank data includes multiple real-time monitoring values of parameters with parameter labels being LGN storage tanks; the gas supply pipeline data includes multiple real-time monitoring values of parameters with parameter labels being gas supply pipelines; and the vaporizer data includes multiple real-time monitoring values of parameters with parameter labels being vaporizers; Diesel supply data unit: Based on the second sensor group, real-time monitoring of diesel supply data based on diesel supply at the current time point, wherein the diesel supply data includes diesel storage tank data and fuel supply pipeline data. The diesel storage tank data includes multiple parameter labels that are real-time monitoring values of parameters of the diesel storage tank, and the fuel supply pipeline data includes multiple parameter labels that are real-time monitoring values of parameters of the fuel supply pipeline.

3. A marine LNG / diesel dual-fuel engine safety monitoring system according to claim 2, characterized in that: Identify modules, including: Safety preset data unit: obtains safety preset data of the ship, wherein the safety preset data includes LGN storage safety data, gas supply safety data, vaporization safety data, diesel storage safety data, and oil supply safety data. The LGN storage safety data includes the safety range of each parameter labeled as an LGN storage tank, the gas supply safety data includes the safety range of each parameter labeled as a gas supply pipeline parameter, the vaporization safety data includes the safety range of each parameter labeled as a vaporizer parameter, the diesel storage safety data includes the safety range of each parameter labeled as a diesel storage tank parameter, and the oil supply safety data includes the safety range of each parameter labeled as a oil supply pipeline parameter; Real-time temperature value unit: obtains the real-time temperature value of the ship's location; Safety tag unit: determines the first real-time safety tag and the second real-time safety tag of all parameters based on LGN supply data, diesel supply data, real-time temperature value and safety preset data; Parameter set unit: determines a real-time abnormal parameter set and a real-time warning parameter set based on the first safety tags and the second safety tags of all parameters.

4. A marine LNG / diesel dual-fuel engine safety monitoring system according to claim 3, characterized in that: Determine the module, also includes: Real-time abnormal data unit: determines real-time abnormal data based on all parameters in the real-time abnormal parameter set and the real-time monitoring value corresponding to each parameter; Real-time warning data unit: determines real-time warning data based on all parameters in the real-time warning parameter set and the real-time monitoring value corresponding to each parameter.

5. A marine LNG / diesel dual-fuel engine safety monitoring system according to claim 4, characterized in that: Early warning module, including: Historical operation data unit: obtains historical operation data within multiple specified time periods, wherein the historical operation data includes historical warning data and historical abnormal data within the specified time period; Historical warning data unit: extracts historical warning data from historical operating data within each specified time period, where the historical warning data includes a historical warning parameter set within the specified time period and the historical monitoring value, historical monitoring time point, emergency strategy, emergency strategy label, and emergency result of each parameter with a historical safety label as a warning label, where the emergency strategy label includes automatic control strategy and non-automatic control strategy, and the emergency results include excellent, good, and fair. Automatic control parameter subset unit: extracts all parameters whose emergency strategy label is automatic control strategy and whose emergency results are excellent from the historical warning parameter set in the historical warning data of each specified time period, and determines the automatic control parameter subset for each specified time period; Early warning automatic control parameter set unit: determines the early warning automatic control parameter set of the ship based on the automatic control parameter subsets of all specified time periods; Emergency strategy table unit: Based on the historical warning data of all specified time periods, all historical monitoring values and emergency strategies of each parameter in the ship's early warning automatic control parameter set with the emergency strategy label of automatic control strategy and excellent emergency results are extracted to construct an emergency strategy table for each parameter in the ship's early warning automatic control parameter set; Real-time warning automatic parameter set unit: determines the real-time warning automatic parameter set based on all parameters in the real-time warning parameter set in the real-time warning data and the warning automatic control parameter set of the ship; Real-time automatic control strategy unit: Calculate the difference between the real-time monitoring value of each parameter in the real-time warning automatic parameter set in the real-time warning data and all the historical monitoring values in the emergency strategy table of each parameter in the real-time warning automatic parameter set, and select the emergency strategy corresponding to the historical monitoring value with the smallest difference as the real-time automatic control strategy for each parameter in the real-time warning automatic parameter set; Real-time automatic control sub-instruction unit: generates a real-time automatic control sub-instruction for each parameter in the real-time early warning automatic parameter set based on the real-time automatic control strategy of each parameter in the real-time early warning automatic parameter set; The real-time warning non-automatic parameter set unit determines the real-time warning non-automatic parameter set based on the real-time warning parameter set and the real-time warning automatic parameter set in the real-time warning data.

6. A marine LNG / diesel dual-fuel engine safety monitoring system according to claim 5, characterized in that: The early warning module also includes: Real-time automatic control instruction unit: determines the real-time automatic control instruction based on the real-time automatic control sub-instructions of all parameters in the real-time warning automatic parameter set, and executes the real-time automatic control sub-instruction of each parameter in the real-time automatic control instruction; Real-time warning alarm unit: issues a real-time warning alarm for each parameter in the real-time warning non-automatic parameter set.

7. A marine LNG / diesel dual-fuel engine safety monitoring system according to claim 4, characterized in that: Exception modules, including: Historical abnormal data unit: extracts historical abnormal data from historical operating data within each specified time period, wherein the historical abnormal data includes a subset of historical abnormal parameters within the specified time period, and historical monitoring values of each parameter with a historical safety label as an abnormal label in the subset of historical abnormal parameters at all historical monitoring time points within the specified time period; Historical abnormal parameter set unit: determines the historical abnormal parameter set of the ship based on the historical abnormal parameter subset in all historical abnormal data within a specified time period.

8. A marine LNG / diesel dual-fuel engine safety monitoring system according to claim 7, characterized in that: The exception module also includes: Construction unit: Builds a ship abnormality prediction model based on the ship's historical abnormal parameter set and all historical operating data of a specified time period; Training unit: Based on the historical abnormal parameter set of the ship, the historical monitoring values of each parameter with a historical safety label as an abnormal label in the historical abnormal parameter subset of all historical abnormal data in a specified time period at all historical monitoring time points, as the input of the abnormality prediction model, and the historical monitoring values and historical monitoring time of each parameter with a historical safety label as an alarm label in the historical alarm parameter set of all historical alarm data in a specified time period as the output of the abnormality prediction model, the ship's abnormality prediction model is trained; Anomaly prediction unit: Inputs the real-time monitoring value of each parameter in the real-time abnormal parameter set in the real-time abnormal data and the current time point into the abnormality prediction model, and determines the predicted abnormal data based on the output result of the abnormality prediction model, wherein the predicted abnormal data includes the predicted warning time points of all parameters in the real-time abnormal parameter set; Time anomaly alarm unit: issues real-time anomaly alarms based on the predicted warning time points of all parameters in each anomaly parameter set and the current time point.

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