Heating control method for engine gas delivery pipelines of marine gas generator sets

Abstract

This invention discloses a heating control method for the gas delivery pipeline of a marine gas generator set, relating to the field of marine gas propulsion system technology. The method includes real-time acquisition of multi-dimensional environmental state information of the gas delivery pipeline, analysis of gas composition and pressure fluctuation data, calculation of theoretical dew point temperature and potential waxing temperature under real-time pressure using a gas property database, construction of a real-time heat exchange model by integrating the pipeline outer wall temperature gradient and cabin ambient temperature, obtaining theoretical temperature decay curves for different locations within the pipeline, predicting the location and extent of condensation and waxing risks after comparison, and generating differentiated electric heat tracing control strategies for different pipeline sections based on cabin relative humidity data. This method can be adapted to real-time gas properties and pipeline section heat exchange states, optimizing the execution mode of gas pipeline heating control.

Description

Technical Field

[0001] This invention belongs to the technical field of marine gas propulsion systems, specifically a heating control method for the engine gas delivery pipeline of a marine gas generator set. Background Technology

[0002] The heating control of conventional marine gas generator sets' engine gas delivery pipelines often adopts a fixed threshold regulation method, relying solely on the single-point temperature of the pipeline or the ambient temperature of the cabin to set uniform heating parameters. The gas dew point temperature and waxing temperature are both based on fixed empirical values, without combining real-time gas composition and pressure fluctuation data for dynamic calculation. The entire pipeline heating process adopts a unified overall control mode, without implementing differentiated control for the heat exchange status of different sections of the pipeline, and the impact of cabin relative humidity on condensation on the pipe wall is not included in the heating control logic.

[0003] Fixed dew point and waxing temperatures cannot be adapted to the real-time changes in gas composition and pressure during transport. This can easily lead to significant discrepancies between the condensation and waxing risk prediction benchmarks and the actual gas properties. A uniform heating control mode cannot accommodate the temperature decay differences at different locations along the pipeline. In some pipeline sections, heating parameters are not compatible with the actual heat exchange state. The risk of condensation on the pipe walls due to relative humidity in the compartment is not included in the control measures, and pipeline heating control cannot accurately reflect the actual risk conditions in different sections. Therefore, it is necessary to dynamically calculate the theoretical dew point and potential waxing temperature at the corresponding monitoring pressure using real-time gas composition and pressure fluctuation data. A real-time heat exchange model of the pipeline needs to be constructed to obtain the theoretical temperature decay curves of the gas at different locations along the pipeline. Based on the location and degree of condensation and waxing risks, combined with relative humidity data, differentiated electric heat tracing control methods should be developed for different sections of the gas transport pipeline. Summary of the Invention

[0004] This invention aims to solve at least one of the technical problems existing in the prior art;

[0005] Therefore, this invention proposes a heating control method for the engine gas delivery pipeline of a marine gas generator set, including:

[0006] Real-time acquisition of multi-dimensional environmental status information of the engine gas delivery pipeline, including gas composition and pressure fluctuation data at the pipeline inlet, temperature gradient distribution data of the pipeline's metal outer wall, and ambient temperature and relative humidity changes in the compartment where the pipeline is located;

[0007] The gas composition and pressure fluctuation data at the pipeline inlet are analyzed and processed to identify the methane main component content, the proportion of high carbon hydrocarbon by-products, and the period and amplitude of pressure pulsation of the current gas. Combined with a pre-set gas property database, the theoretical dew point temperature and potential waxing temperature of the current gas under the monitored pressure conditions are calculated.

[0008] The temperature gradient distribution data of the outer metal wall of the pipeline is fused and analyzed with the ambient temperature change data of the compartment where the pipeline is located to construct a real-time heat exchange model of the engine gas delivery pipeline. Based on the real-time heat exchange model, the theoretical temperature decay curve of the gas inside the pipeline at different locations is calculated.

[0009] Based on the comparison between the theoretical dew point temperature, the potential waxing temperature and the theoretical temperature decay curve, the risk location and risk level of condensation or waxing of gas inside the pipeline along the transportation path are predicted.

[0010] Based on the risk location and degree of condensation or waxing, and combined with the effect of relative humidity change data on condensation on the pipe wall, a differentiated electric heat tracing control strategy is generated for different sections of the engine gas delivery pipeline.

[0011] Furthermore, the gas composition and pressure fluctuation data at the pipeline inlet are analyzed to identify the methane main component content, the proportion of high-carbon hydrocarbon by-products, and the period and amplitude of pressure pulsations in the current gas, including:

[0012] The gas samples continuously extracted from the pipeline inlet were subjected to component separation and quantitative analysis using online gas chromatography analysis technology to obtain the molar percentage content of methane as the main methane component content;

[0013] In the quantitative analysis results, the total molar percentage content of ethane, propane, butane, and hydrocarbons with 5 or more carbon atoms is calculated as the proportion of the high-carbon hydrocarbon by-components.

[0014] Time-domain analysis is performed on the pressure fluctuation data to extract the periodic fluctuation components in the pressure signal, and the repetition time interval of the fluctuation components is calculated as the period of the pressure pulsation.

[0015] The difference between the maximum and minimum values ​​of the pressure fluctuation data within a single period of the pressure pulsation is calculated as the amplitude of the pressure pulsation.

[0016] The methane main component content, the proportion of high-carbon hydrocarbon by-products, and the period and amplitude of pressure pulsation are associated with timestamps and stored in the current gas state record.

[0017] Furthermore, the calculation of the theoretical dew point temperature and potential wax deposition temperature of the current gas under the monitored pressure conditions, based on a pre-set gas property database, includes:

[0018] Using the methane main component content and the proportion of high carbon hydrocarbon by-components as the query index, the saturated vapor pressure data and heavy hydrocarbon crystallization characteristic data of the corresponding component gas under different pressures are retrieved from the preset gas physical property database.

[0019] Extract the real-time average pressure value from the gas pressure fluctuation data at the pipeline inlet;

[0020] Based on the real-time average pressure value and the retrieved saturated vapor pressure data, the temperature at which water vapor in the gas reaches saturation is determined through iterative calculation and used as the theoretical dew point temperature.

[0021] Based on the real-time average pressure value, the proportion of high-carbon hydrocarbon by-products, and the retrieved heavy hydrocarbon crystallization characteristic data, the temperature at which the high-carbon hydrocarbon components in the fuel gas begin to precipitate solid wax crystals is determined by a phase equilibrium calculation model, and is taken as the potential waxing temperature.

[0022] The calculated theoretical dew point temperature and potential wax deposition temperature are correlated with the current gas state record.

[0023] Furthermore, a real-time heat exchange model of the engine gas delivery pipeline is constructed, and the theoretical temperature decay curves of the gas inside the pipeline at different locations are calculated based on the real-time heat exchange model, including:

[0024] The temperature gradient distribution data of the outer metal wall of the pipeline is converted into the temperature of a series of outer wall temperature measuring points distributed along the pipeline axis.

[0025] The ambient temperature change data of the compartment where the pipeline is located is converted into an ambient reference temperature corresponding to the series of external wall temperature measurement points;

[0026] Based on the gas flow characteristics and pipeline geometric parameters, the engine gas delivery pipeline is divided into multiple continuous micro-element pipe segments;

[0027] For each micro-pipe segment, based on its inlet gas temperature, the temperature of the outer wall temperature measuring point, the ambient reference temperature, and the thermal conductivity parameters of the pipe material, the theoretical outlet temperature of the gas after flowing through the micro-pipe segment is calculated based on the energy conservation equation. The theoretical outlet temperature is then used as the inlet gas temperature of the next adjacent micro-pipe segment.

[0028] Starting from the known actual gas temperature at the pipeline inlet, the gas temperature change of all micro-pipe segments is calculated sequentially according to the gas flow direction, and finally a sequence of predicted gas temperature values ​​distributed along the entire pipeline axis is obtained. The sequence of predicted gas temperature values ​​constitutes the theoretical temperature decay curve.

[0029] Furthermore, based on the comparison between the theoretical dew point temperature, the potential wax deposition temperature, and the theoretical temperature decay curve, the risk location and degree of condensation or wax deposition of the gas inside the pipeline along the transportation path are predicted, including:

[0030] Along the theoretical temperature decay curve, the theoretical gas temperature value at each location is compared with the theoretical dew point temperature.

[0031] The location where the theoretical gas temperature is lower than the theoretical dew point temperature is marked as a condensation risk point. The difference between the theoretical dew point temperature and the theoretical gas temperature is calculated as the theoretical condensation risk level of the condensation risk point.

[0032] Along the theoretical temperature decay curve, the theoretical gas temperature value at each location is compared with the potential wax deposition temperature.

[0033] The locations where the theoretical gas temperature is lower than the potential waxing temperature are marked as waxing risk points. The difference between the potential waxing temperature and the theoretical gas temperature is calculated as the theoretical waxing risk level of the waxing risk point.

[0034] The location coordinates, risk types, and theoretical risk levels of condensation risk points and wax deposition risk points are summarized to generate a pipeline risk prediction map.

[0035] Furthermore, by combining the relative humidity change data with the effect of promoting condensation on the pipe wall, a differentiated electric heat tracing control strategy is generated for different sections of the engine gas delivery pipeline, including:

[0036] The differentiated electric heat tracing control strategy includes the heating power setting, heating rate, and heating start-up time for a specified pipeline section;

[0037] Based on the relative humidity change data of the compartment where the pipeline is located, the absolute humidity of the air in the compartment is calculated, and combined with the ambient temperature change data, the critical conditions for condensation to occur on the outer wall of the pipeline are estimated.

[0038] The estimated critical conditions for surface condensation on the outer wall of the pipeline are superimposed on the pipeline risk prediction map. For pipeline sections with theoretical condensation risk or waxing risk, if their external environment simultaneously meets or approaches the critical conditions for surface condensation, the risk level of the pipeline section is increased.

[0039] Based on the risk points and risk levels marked in the pipeline risk prediction map, and combined with the electric heat tracing zoning design of the gas transmission pipeline, control parameters are formulated for each electric heat tracing zone.

[0040] For pipeline sections with high risk levels, a heating power setting value determined based on a first preset power mapping table and a heating rate determined based on a first preset rate mapping table are set, and heating is set to start immediately or start heating based on a first time threshold preset in advance based on the risk level.

[0041] For pipeline sections with low risk levels, set the heating power setting value based on the second preset power mapping table and the heating rate based on the second preset rate mapping table, and set the heating to start with a preset second time threshold or to perform intermittent heating according to a preset duty cycle.

[0042] Wherein, the reference power value corresponding to the first preset power mapping table is higher than that of the second preset power mapping table, and the reference heating rate corresponding to the first preset rate mapping table is higher than that of the second preset rate mapping table.

[0043] The heating power settings, heating rate, and heating start-up time of all electric heat tracing zones are integrated to form a global differentiated electric heat tracing control strategy.

[0044] Further, the step of determining the temperature at which high-carbon hydrocarbon components in the fuel gas begin to precipitate solid wax crystals, based on the real-time average pressure value, the proportion of high-carbon hydrocarbon by-products, and the retrieved heavy hydrocarbon crystallization characteristic data, using a phase equilibrium calculation model as the potential wax crystallization temperature, includes:

[0045] From the heavy hydrocarbon crystallization characteristic data, the solid-liquid phase equilibrium constants of each heavy hydrocarbon component contained in the current high-carbon hydrocarbon component of the fuel gas at different temperatures are extracted;

[0046] The real-time average pressure value, the proportion of high-carbon hydrocarbon by-products, and the initial mole fraction of each heavy hydrocarbon component are input into a phase equilibrium calculation model based on the equation of state. The phase equilibrium calculation model adopts the PR equation or SRK equation applicable to hydrocarbon mixtures.

[0047] An initial temperature value is set, and the distribution coefficients of each heavy hydrocarbon component in the gas phase and the hypothetical solid phase are calculated using the phase equilibrium calculation model under the initial temperature value and the real-time average pressure value.

[0048] For all high-carbon hydrocarbon components in the fuel gas, calculate the sum of their mole fractions in the hypothetical solid phase, and determine whether the sum is greater than the preset crystallization precipitation threshold.

[0049] If the total mole fraction is less than or equal to the crystallization threshold, the initial temperature value is gradually reduced, and the phase equilibrium calculation model is called again for calculation and judgment.

[0050] When the sum of the molar fractions first exceeds the crystallization threshold, the system temperature at this time is determined as the critical temperature at which the high-carbon hydrocarbon components begin to precipitate solid wax crystals, and is used as the potential waxing temperature.

[0051] Furthermore, it also includes a dynamic correction step based on policy execution feedback:

[0052] After implementing the differentiated electric heat tracing control strategy, the temperature gradient distribution data of the outer metal wall of the pipeline is re-acquired and updated;

[0053] The updated temperature gradient distribution data of the outer metal wall of the pipeline is input into the real-time heat exchange model to calculate the updated theoretical temperature decay curve of the gas.

[0054] The updated theoretical gas temperature decay curve is compared again with the theoretical dew point temperature and potential waxing temperature to assess the actual elimination of condensation and waxing risks.

[0055] If the risk is not completely eliminated, the heating power setting value of the corresponding pipeline section shall be increased proportionally;

[0056] If the risk has been eliminated and the temperature of the outer metal wall of the pipeline exceeds the safety margin threshold, the heating power setting value of the corresponding pipeline section shall be reduced proportionally.

[0057] Based on the evaluation results and the adjusted heating power setting, a correction instruction for the electric heat tracing control strategy is generated for the next control cycle.

[0058] Further, the step of inputting the updated temperature gradient distribution data of the pipeline's metal outer wall into the real-time heat exchange model to calculate the updated theoretical gas temperature decay curve includes:

[0059] The updated temperature gradient distribution data of the outer metal wall of the pipeline is used as a new boundary condition to replace the original boundary condition used when constructing the real-time heat exchange model.

[0060] Keep all parameters in the real-time heat exchange model unchanged except for the boundary conditions, including pipeline geometry parameters, material thermal conductivity parameters, and gas flow characteristics parameters;

[0061] The real-time heat exchange model was rerun using the new boundary conditions to recalculate the theoretical outlet temperature of the gas flow through each micro-element pipe segment.

[0062] Starting from the actual gas temperature at the pipeline inlet, the gas temperature changes of all micro-pipe segments are recalculated sequentially to obtain an updated sequence of predicted gas temperatures, which is the updated theoretical gas temperature decay curve.

[0063] Furthermore, it also includes a feedforward compensation step for the heating strategy under variable engine load operation:

[0064] Monitor the real-time power output signal of the engine of the marine gas generator set;

[0065] Based on the changing trend of the engine's real-time power output signal, predict the expected change in gas flow rate;

[0066] Based on the expected change in gas flow rate, the expected change in the overall heat loss of the engine gas delivery pipeline is predicted using a pre-calibrated gas flow rate-heat loss rate relationship model.

[0067] Based on the expected direction and magnitude of the overall heat loss change, the heating power setpoint in the currently executed differentiated electric heat tracing control strategy is synchronously fed forward and adjusted.

[0068] Before the expected increase in gas flow due to the increase in engine power, the heating power setting value is increased in advance according to the predicted proportion.

[0069] When the engine power decreases, leading to a predicted reduction in gas flow, the heating power setting value is reduced in advance according to the predicted proportion.

[0070] Compared with the prior art, the beneficial effects of the present invention are:

[0071] Real-time data on gas composition and pressure fluctuations at the inlet of the engine gas delivery pipeline is collected. The system analyzes and identifies the methane content, high-carbon hydrocarbon byproduct ratio, and pressure pulsation period and amplitude of the current gas. Combined with a pre-set gas property database, the theoretical dew point temperature and potential waxing temperature under the current monitoring pressure conditions are calculated. The dew point temperature and waxing temperature values ​​of the gas are updated synchronously with the real-time status of gas composition and pressure. The judgment parameters are consistent with the actual physical state of the gas in the pipeline, avoiding parameter deviations caused by the mismatch between fixed values ​​and actual operating conditions. The judgment criteria for condensation and waxing risks are closely aligned with the real-time gas delivery status.

[0072] A real-time heat exchange model for the engine gas delivery pipeline is constructed by integrating temperature gradient distribution data of the pipeline's metal outer wall with cabin ambient temperature change data. Based on the model, the theoretical temperature decay curves of the gas inside the pipeline at different locations are calculated. By comparing the curves with the theoretical dew point temperature and potential waxing temperature, the risk locations and levels of condensation or waxing are determined. The effect of cabin relative humidity change data on condensation on the pipeline wall is combined to generate differentiated electric heat tracing control strategies for different sections of the pipeline. The gas temperature change status at each location of the pipeline is accurately quantified, and the electric heat tracing control parameters are adapted to the actual risk status of different sections of the pipeline. The heating regulation execution method is consistent with the actual operating status of each section of the pipeline. Attached Figure Description

[0073] Figure 1 This is a flowchart illustrating the steps of the heating control method for the engine gas delivery pipeline of the marine gas generator set according to the present invention.

[0074] Figure 2 A flowchart for analyzing and processing data on gas composition and pressure fluctuations;

[0075] Figure 3A flowchart for calculating the theoretical dew point temperature and potential wax deposition temperature;

[0076] Figure 4 The absolute humidity and condensation critical temperature distribution curves along the pipeline for marine gas transmission;

[0077] Figure 5 The curves show the axial gas pressure and pulsation amplitude distribution of the engine's gas delivery pipeline. Detailed Implementation

[0078] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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.

[0079] See Figure 1 This system collects multi-dimensional environmental information on the engine gas delivery pipeline in real time, including gas composition and pressure fluctuation data at the pipeline inlet, temperature gradient distribution data of the pipeline's metal outer wall, and ambient temperature and relative humidity changes in the compartment where the pipeline is located. The gas composition and pressure fluctuation data at the pipeline inlet are analyzed to identify the methane content, proportion of high-carbon hydrocarbon byproducts, and the period and amplitude of pressure pulsations in the current gas. Combined with a pre-set gas property database, the theoretical dew point temperature and potential waxing temperature of the current gas under the monitored pressure conditions are calculated. The temperature gradient distribution data of the pipeline's metal outer wall and the ambient temperature change data of the compartment where the pipeline is located are fused and analyzed to construct a real-time heat exchange model for the engine gas delivery pipeline. Based on this real-time heat exchange model, the theoretical temperature decay curves of the gas inside the pipeline at different locations are calculated. Based on the comparison between the theoretical dew point temperature, potential waxing temperature, and the theoretical temperature decay curves, the risk locations and degree of condensation or waxing of the gas inside the pipeline along the delivery path are predicted. Based on the predicted risk locations and levels of condensation or wax formation, and combined with the promoting effect of relative humidity changes on pipe wall condensation, differentiated electric heat tracing control strategies are generated for different sections of the engine gas delivery pipeline.

[0080] See Figure 2In one embodiment of the present invention, the gas composition and pressure fluctuation data at the pipeline inlet are analyzed to identify the methane main component content, the proportion of high-carbon hydrocarbon by-products, and the period and amplitude of pressure pulsations in the current gas. This analysis process is carried out based on online gas chromatography analysis technology and signal time-domain analysis methods. Online gas chromatography analysis technology is used to perform real-time analysis on gas samples continuously extracted at the pipeline inlet by a micro-sampling pump. The chromatographic column of the online gas chromatograph separates the components in the gas sample, and then the detector performs quantitative analysis on the separated components. The online gas chromatography analysis technology outputs the molar percentage content of methane, ethane, propane, butane, pentane, and hydrocarbons with higher carbon numbers, wherein the molar percentage content of methane is directly recorded as the methane main component content. Based on the quantitative analysis results provided by the online gas chromatography analysis technology, the molar percentage content of ethane, propane, butane, and all the above hydrocarbons is accumulated. The sum of the calculated values ​​is defined as the proportion of high-carbon hydrocarbon by-products, which reflects the overall proportion of heavier components in the gas.

[0081] In this specific implementation, the processing of pressure fluctuation data is independent of component analysis. Pressure sensors acquire gas pressure signals at the pipeline inlet using a high-frequency sampling rate, forming a time series of pressure fluctuation data. Time-domain analysis is performed on the pressure fluctuation data time series, employing autocorrelation function or periodogram analysis to extract significantly periodic fluctuation components. The time interval between the recurring peaks or troughs of these fluctuation components is calculated, and this time interval is determined as the period of the pressure pulsation. After identifying the period of a single complete pressure pulsation, the maximum and minimum values ​​of the pressure fluctuation data are searched within this periodic time window. The algebraic difference between the maximum and minimum values ​​is calculated, and this difference is used as the amplitude of the pressure pulsation. It can be done through the formula:

[0082]

[0083] in: This represents the maximum value of the pressure fluctuation data within the period of a single pressure pulsation. This represents the minimum value of pressure fluctuation data within the same period.

[0084] In some embodiments, after identifying and calculating the methane main component content, the proportion of high-carbon hydrocarbon by-products, the period of pressure pulsation, and the amplitude of pressure pulsation, the system associates and binds these data items with a precise timestamp, which identifies the exact moment the data was generated. The bound dataset, including the methane main component content, the proportion of high-carbon hydrocarbon by-products, the period of pressure pulsation, the amplitude of pressure pulsation, and the timestamp, is structured and stored in a data recording unit named the current gas state record. The current gas state record, as a complete data package, provides input for subsequent property calculation steps. It can be understood that online gas chromatography analysis, pressure signal time-domain analysis, and data binding and storage operations are executed cyclically according to a preset period, thereby ensuring that the current gas state record can continuously reflect the latest changes in the gas inlet state. Throughout the entire analytical processing, it does not rely on any offline, non-real-time laboratory analysis results; all data originates from online analytical instruments and sensors directly installed at the pipeline inlet.

[0085] See Figure 3 In one embodiment of the present invention, the process of calculating the theoretical dew point temperature and potential waxing temperature by combining a pre-set fuel gas property database begins with the content of methane main component and the proportion of high-carbon hydrocarbon by-products obtained from the current fuel gas state record. The content of methane main component and the proportion of high-carbon hydrocarbon by-products together constitute a composite query index. The system uses this composite query index to access the pre-set fuel gas property database. The pre-set fuel gas property database stores the property parameters corresponding to different fuel gas components in tabular form. The goal of the retrieval operation is to obtain saturated vapor pressure data and heavy hydrocarbon crystallization characteristic data that match the current fuel gas components. The saturated vapor pressure data describes the relationship between pressure and temperature when water vapor reaches saturation in the fuel gas, while the heavy hydrocarbon crystallization characteristic data describes the phase change information of high-carbon hydrocarbon components at different temperatures and pressures.

[0086] In some embodiments, calculating the theoretical dew point temperature requires consideration of real-time pressure conditions. From the continuously collected gas pressure fluctuation data at the pipeline inlet, all pressure samples within a time window are extracted. These pressure samples are then arithmetically averaged, and the resulting average is defined as the real-time average pressure value. Based on the real-time average pressure value and saturated vapor pressure data retrieved from a pre-set gas property database, the theoretical dew point temperature is determined through iterative calculation. The iterative calculation takes the current water vapor partial pressure of the gas and the real-time average pressure as input, searching for the temperature in the saturated vapor pressure data where the water vapor partial pressure equals the saturated vapor pressure. This temperature is the theoretical dew point temperature at which water vapor in the gas begins to condense into liquid water. The calculation of the potential wax deposition temperature is based on the real-time average pressure value, the proportion of high-carbon hydrocarbon by-products, and heavy hydrocarbon crystallization characteristic data retrieved from a pre-set gas property database. This is accomplished using a specialized phase equilibrium calculation model, which employs the PR equation of state or the SRK equation of state suitable for hydrocarbon mixtures to describe the thermodynamic properties of the system.

[0087] In practice, determining the potential waxing temperature through a phase equilibrium calculation model is a systematic iterative process. From the heavy hydrocarbon crystallization characteristic data, the solid-liquid equilibrium constants of each specific heavy hydrocarbon component in the current fuel gas's high-carbon hydrocarbon component are extracted at different temperatures. These constants characterize the component's distribution tendency between the solid and gas phases. The real-time average pressure, the proportion of high-carbon hydrocarbon by-products, and the initial mole fraction of each heavy hydrocarbon component are input into the phase equilibrium calculation model based on the equation of state. Under the set initial temperature and real-time average pressure values, the model uses the PR or SRK equations to calculate the system's fugacity and enthalpy, thereby deriving the distribution coefficients of each heavy hydrocarbon component in the gas and hypothetical solid phases. For all high-carbon hydrocarbon components in the fuel gas, the sum of their mole fractions in the hypothetical solid phase is calculated. It is then determined whether this sum exceeds a preset crystallization precipitation threshold, a small value close to zero, used to characterize the critical point at which microscopic crystal nuclei begin to form stably.

[0088] Optionally, if the calculated total molar fraction of high-carbon hydrocarbon components in the hypothetical solid phase is less than or equal to the crystallization threshold, it indicates that the high-carbon hydrocarbon components have not yet met the conditions for the precipitation of solid wax crystals at the current temperature. In this case, the system will initiate an iterative cooling process, decreasing the initial temperature value according to the set step size, and using the updated temperature value to recalculate and judge the phase equilibrium calculation model. The iterative cooling process continues, and after each iteration, the total molar fraction in the hypothetical solid phase is recalculated and compared with the crystallization threshold. When the iterative calculation first shows that the total molar fraction of high-carbon hydrocarbon components in the hypothetical solid phase is greater than the crystallization threshold, the iterative process terminates, and the system temperature value used by the phase equilibrium calculation model at this moment is determined as the potential wax crystallization temperature. The judgment condition can be expressed as finding the condition that satisfies The lowest temperature, of which It is a component Mole fraction in the gas phase It is a component The solid-liquid equilibrium constant, This is a preset crystallization threshold. It can be understood that the calculated results of the theoretical dew point temperature and the potential wax deposition temperature are independent of each other, but they share the same real-time average pressure input. After the calculation is complete, the system associates these two numerical results—the theoretical dew point temperature and the potential wax deposition temperature—with the original data that generated them and stores them together in the current gas state record. This ensures that the current gas state record contains complete information on gas composition, pressure characteristics, and key phase change temperatures.

[0089] In one embodiment of the present invention, constructing a real-time heat exchange model of the engine gas delivery pipeline and calculating the theoretical temperature decay curve relies on the fusion processing of temperature gradient distribution data of the pipeline's metal outer wall and ambient temperature change data of the compartment where the pipeline is located. The temperature gradient distribution data of the pipeline's metal outer wall is collected by multiple temperature sensors installed at fixed intervals along the pipeline's axial direction. These raw temperature readings are converted into a series of outer wall temperature measurement points arranged sequentially along the pipeline's axial coordinates. Simultaneously, the ambient temperature change data recorded by ambient temperature sensors arranged in the compartment where the pipeline is located is synchronously processed into an ambient reference temperature corresponding to the location of each outer wall temperature measurement point. The ambient reference temperature reflects the air temperature conditions surrounding the corresponding pipeline segment.

[0090] In some embodiments, establishing a real-time heat exchange model requires spatial discretization of the pipeline. Based on the actual geometric parameters of the engine gas delivery pipeline, including pipeline length, inner diameter, outer diameter, and the flow characteristics of the gas under current operating conditions, the entire engine gas delivery pipeline is logically divided into dozens to hundreds of continuous micro-segments. For each micro-segment, based on the inlet gas temperature flowing into that micro-segment, the temperature of the corresponding outer wall temperature measuring point, the corresponding ambient reference temperature, and the thermal conductivity and wall thickness parameters of the engine gas delivery pipeline material itself, the theoretical outlet temperature of the gas after flowing through this micro-segment is calculated based on the energy conservation equation. This theoretical outlet temperature is the inlet gas temperature of the next downstream adjacent micro-segment. The theoretical outlet temperature of a single micro-segment is then calculated. The relationship can be expressed as:

[0091]

[0092] in: It is the inlet gas temperature of micro-element pipe segment i. It is the temperature of the outer wall measuring point corresponding to micro-element pipe segment i. This is the ambient reference temperature corresponding to micro-element pipe segment i. It is the thermal conductivity coefficient of the pipe wall material. It is the heat exchange area of ​​the inner wall of the micro-tube section. It is the convective heat transfer coefficient between the outer wall of the pipe and the air. It is the heat exchange area of ​​the outer wall of the micro-tube segment. It is the length of the micro-element pipe segment. It is the gas mass flow rate. It is the specific heat capacity of the gas at constant pressure.

[0093] In practice, the generation of the theoretical temperature decay curve is a recursive calculation process from the pipeline inlet to the outlet. The actual gas temperature, directly measured by another temperature sensor at the pipeline inlet, is used as the initial inlet gas temperature and substituted into the calculation model of the first micro-element pipe segment to obtain its theoretical outlet temperature. Next, this theoretical outlet temperature is used as the inlet gas temperature of the second micro-element pipe segment. Combined with the temperature of the corresponding external wall temperature measurement point and the ambient reference temperature, the theoretical outlet temperature of the second micro-element pipe segment is calculated. This process is repeated sequentially according to the direction of gas flow, calculating the gas temperature changes of all micro-element pipe segments. Finally, a sequence containing the predicted gas temperature values ​​at each calculated location along the entire engine gas delivery pipeline axis is obtained. This sequence of predicted gas temperature values ​​constitutes the theoretical temperature decay curve of the gas inside the pipeline. Based on the generated theoretical temperature decay curve, the risk of condensation and wax deposition can be predicted. For each location point recorded along the theoretical temperature decay curve, the theoretical gas temperature value at each location point is compared with the theoretical dew point temperature obtained from the current gas state record. Points where the theoretical gas temperature is lower than the theoretical dew point temperature are marked as condensation risk points. For each condensation risk point, the difference between the theoretical dew point temperature and the theoretical gas temperature is calculated. This difference is defined as the theoretical condensation risk level of the condensation risk point. The larger the difference, the higher the subcooling and the greater the condensation risk.

[0094] Optionally, the prediction process for wax deposition risk is similar to that for condensation risk, but the comparison objects differ. Along the same theoretical temperature decay curve, the theoretical gas temperature value at each location point is compared with the potential wax deposition temperature obtained from the current gas state record. Locations where the theoretical gas temperature value is lower than the potential wax deposition temperature are marked as wax deposition risk points. For each wax deposition risk point, the numerical difference between the potential wax deposition temperature and the theoretical gas temperature value is calculated; this difference is defined as the theoretical wax deposition risk level for the wax deposition risk point. It is understood that the same location point may be marked as both a condensation risk point and a wax deposition risk point, depending on the theoretical dew point temperature, the potential wax deposition temperature, and the relative relative levels of the theoretical gas temperature value at that point. Finally, the system summarizes the location coordinates of all identified condensation risk points and wax deposition risk points, the corresponding risk type (condensation or wax deposition), and the calculated theoretical condensation risk level or theoretical wax deposition risk level into a structured data table. This data table constitutes a pipeline risk prediction map to guide subsequent heating control.

[0095] In one embodiment of the present invention, the process of generating a differentiated electric heat tracing control strategy begins with reading an established pipeline risk prediction map. The core output of the differentiated electric heat tracing control strategy includes the heating power setpoint, heating rate, and heating start-up time for a specified pipeline section in the engine gas delivery pipeline. Based on relative humidity change data collected by humidity sensors located in the compartment where the pipeline is situated, combined with synchronously collected ambient temperature change data, the absolute humidity of the compartment air is calculated. Absolute humidity reflects the actual mass of water vapor per unit volume of air. Using ambient temperature change data and absolute humidity, the critical condition for surface condensation on the pipeline outer wall is estimated through thermodynamic relationships. The critical condition for surface condensation on the pipeline outer wall is directly related to the pipe wall temperature and the dew point temperature of the ambient air. When the pipe wall temperature is lower than the dew point temperature of the ambient air, water vapor will condense on the pipe wall. Estimating the critical condition for surface condensation on the pipeline outer wall involves calculating the current ambient air dew point temperature. :

[0096]

[0097] in: It is a percentage of relative humidity. It refers to the ambient temperature.

[0098] In some embodiments, the estimated critical conditions for surface condensation on the outer wall of the pipeline are overlaid with existing pipeline risk prediction maps for data analysis. For pipeline segments marked in the pipeline risk prediction map that have theoretical condensation or waxing risks, their external environmental conditions are assessed. If the local compartment environmental parameters of the pipeline segment simultaneously meet or approach the critical conditions for surface condensation, the risk level of the pipeline segment is increased by one or more levels based on the original risk level. Using the location of the risk points marked in the updated pipeline risk prediction map after overlay analysis and the final risk level as the core decision-making basis, combined with the pre-divided electric heat tracing zone design on the physical structure of the engine gas delivery pipeline, control parameters including heating power setpoint, heating rate, and heating start time are formulated for each electric heat tracing zone. For pipeline segments rated as high-risk in the updated pipeline risk prediction map, their control parameters are determined by querying the first preset power mapping table and the first preset rate mapping table, and the heating start logic is set to start immediately or start a preset first time threshold based on the high risk level. For pipeline sections assessed as low-risk in the updated pipeline risk prediction map, their control parameters are determined by querying the second preset power mapping table and the third preset rate mapping table. The heating start-up logic is set to either start with a delay of a preset second time threshold or perform intermittent heating according to a preset fixed duty cycle. The reference power value corresponding to the first preset power mapping table is higher than that of the second preset power mapping table, and the reference heating rate corresponding to the first preset rate mapping table is higher than that of the third preset rate mapping table. It can be understood that there may be multiple risk levels, including high, medium, and low. Each risk level is associated with a different preset power mapping table, preset rate mapping table, and heating start-up logic. Refer to Table 1, which shows a parameter mapping table for an electric heat tracing control strategy.

[0099] Table 1: Parameter Mapping Table for Electric Heat Tracing Control Strategy

[0100]

[0101] In practical implementation, after setting control parameters for each electric heat tracing zone, these scattered parameter commands are integrated. The integration process includes summarizing the zone number, its corresponding heating power setpoint, heating rate, and heating start-up time. The control parameters for all electric heat tracing zones are then compiled according to a unified command format. This compiled command set constitutes a global, differentiated electric heat tracing control strategy that can be distributed to the actuators in each zone. Optionally, when the heating power setpoint is retrieved from a preset power mapping table, the input variables are the risk level of the pipeline section and the length or heat loss coefficient of that section; the output is a specific power value. When the heating rate is retrieved from a preset rate mapping table, the input variable is also the risk level; the output is a temperature change rate value. The heating start-up time may be an absolute time point, a time offset relative to the current moment, or a specific command code representing "immediate" execution.

[0102] See Figure 4 This study focuses on analyzing the relationship between absolute humidity and the critical condensation condition of pipelines, providing key environmental boundary basis for the formulation of differentiated electric heat tracing control strategies. The figure uses pipeline length (meters) as the horizontal axis, absolute humidity (kg / m³) as the left vertical axis, and the critical condensation temperature (°C) as the right vertical axis. The solid line represents the curve of absolute humidity of the cabin air changing with pipeline length, while the dashed line represents the critical temperature at which surface condensation occurs on the pipeline outer wall at the corresponding location. The relative positions and fluctuation trends of the two curves intuitively reflect the condensation risk potential of different pipeline sections. The physical meaning of the critical condensation condition: The critical condensation temperature refers to the critical temperature at which water vapor in the air will condense on the pipeline wall if the temperature of the pipeline outer wall is lower than the current absolute humidity. It is derived from the ambient temperature and absolute humidity through a thermodynamic dew point calculation model and is the core threshold for judging the risk of condensation on the pipeline wall. The coupling relationship between absolute humidity and condensation risk: When absolute humidity increases, the water vapor content in the air increases, and the critical condensation temperature also increases, meaning that the pipeline wall is more likely to reach the condensation condition. Conversely, lower absolute humidity reduces the risk of condensation. The two curves in the figure show simultaneous peaks in multiple pipe sections (e.g., around 20 meters and 70 meters), demonstrating this strong coupling characteristic. Guidance for electric heat tracing control strategies: When generating differentiated electric heat tracing control strategies, it is necessary to overlay the condensation critical conditions in the figure with the pipeline risk prediction map. For pipe sections with existing theoretical condensation or waxing risks, if their external environment simultaneously meets or approaches the condensation critical conditions, their risk level needs to be increased, and higher heating power and heating rate should be selected from the first preset power mapping table to ensure that the pipe wall temperature remains above the condensation critical temperature, effectively suppressing condensation.

[0103] In one embodiment of the invention, the method includes a dynamic correction step based on strategy execution feedback, initiated after the system completes one execution of the differentiated electric heat tracing control strategy. The dynamic correction step first re-acquires temperature sensor data installed on the outer wall of the engine gas delivery pipeline, updating the temperature gradient distribution data of the pipeline's metal outer wall with the newly acquired data. The updated temperature gradient distribution data of the pipeline's metal outer wall is then transmitted as a new input parameter to the computational unit of the real-time heat exchange model, and an updated theoretical gas temperature decay curve is calculated using this updated data. The updated theoretical gas temperature decay curve is then compared again with the theoretical dew point temperature and potential waxing temperature obtained from the current gas state record. Each location in the pipeline is checked to see if the updated theoretical gas temperature is still lower than the theoretical dew point temperature or potential waxing temperature, thereby assessing the actual elimination of condensation and waxing risks. If the comparison reveals that the condensation or waxing risks in certain pipeline sections have not been completely eliminated, the heating power setting value of the corresponding pipeline section in the differentiated electric heat tracing control strategy is increased by a fixed proportional coefficient, which is determined based on the difference between the theoretical temperature and the phase change temperature. If the risk assessment indicates that the risk has been completely eliminated, and the temperature of the outer metal wall of the corresponding pipeline section exceeds a preset safety margin threshold, the heating power setting value of the corresponding pipeline section in the differentiated electric heat tracing control strategy is reduced by a fixed proportional coefficient. Based on the above assessment results and the adjusted heating power setting value, the system generates an instruction containing the corrected set of control parameters. This instruction is defined as the electric heat tracing control strategy correction instruction for the next control cycle.

[0104] In some embodiments, the updated temperature gradient distribution data of the pipeline's outer metal wall is input into the real-time heat exchange model to calculate the updated theoretical gas temperature decay curve. This process involves updating the model's boundary conditions. The updated temperature gradient distribution data of the pipeline's outer metal wall, as the new thermal boundary conditions reflecting the current instantaneous state, completely replaces the original temperature gradient distribution data boundary conditions used when constructing the real-time heat exchange model. All other internal parameters in the real-time heat exchange model, except for the boundary conditions, remain unchanged. These internal parameters include the geometric parameters of the engine gas delivery pipeline, the thermal conductivity parameters of the pipeline material, and the gas flow characteristics parameters determined by the current operating conditions. The computational core of the real-time heat exchange model is rerun using the new boundary conditions, and the theoretical outlet temperature of the gas after flowing through each micro-element pipe segment is recalculated based on the principle of energy conservation. Starting from the actual gas temperature sensor reading at the inlet of the engine gas delivery pipeline, as the new initial temperature, the gas temperature changes of all micro-element pipe segments are recalculated sequentially according to the gas flow direction, ultimately yielding a new sequence of predicted gas temperatures reflecting the current thermal state. This new sequence is the updated theoretical gas temperature decay curve.

[0105] In its implementation, the method also includes a feedforward compensation step for the heating strategy under variable engine load operation. This step can run in parallel or independently with the dynamic correction step. The feedforward compensation step continuously monitors the real-time power output signal of the marine gas generator set, which reflects the engine's instantaneous load. Based on the changing trend of the real-time power output signal, a pre-set engine power-gas flow rate relationship model is used to predict the expected change in gas flow rate over a short period. Based on the predicted expected change in gas flow rate, a pre-calibrated gas flow rate-heat loss rate relationship model is used to predict the expected change in the overall heat loss of the engine's gas delivery pipeline. This model describes the quantitative relationship of heat dissipation intensity in the pipeline under different flow rates. Based on the predicted direction and magnitude of the overall heat loss change, the heating power setpoint in the currently implemented differentiated electric heat tracing control strategy is synchronously fedforward adjusted. The feedforward adjustment amount... The calculation formula is:

[0106]

[0107] in: It is the feedforward compensation coefficient. It is the predicted overall heat loss rate. This is the overall heat loss rate currently calculated.

[0108] Optionally, when the engine's real-time power output signal indicates that the engine power is increasing, it suggests that the gas flow is expected to increase. In this case, before the actual increase in gas flow, the heating power setting value for the corresponding pipeline section is increased in advance according to the predicted ratio to compensate for the upcoming increase in pipeline heat loss. Conversely, when the engine's real-time power output signal indicates that the engine power is decreasing, it suggests that the gas flow is expected to decrease. In this case, before the actual decrease in gas flow, the heating power setting value for the corresponding pipeline section is decreased in advance according to the predicted ratio to avoid unnecessary overheating and energy waste. It can be understood that the feedforward compensation step and the feedback-based dynamic correction step in the heating strategy under variable engine load operation work in tandem. The feedforward compensation step acts in advance based on the trend of engine power changes to offset the main disturbances caused by load changes, while the dynamic correction step finely corrects the final effect after the feedforward compensation and other factors. The combination of the two achieves more precise pipeline temperature control.

[0109] See Figure 5In the core data acquisition and analysis phase of the gas transmission pipeline for marine gas generator sets, the axial gas pressure and pulsation amplitude distribution in the pipeline exhibited significant dynamic characteristics. As shown in the figure, the gas pressure (MPa) (solid line) fluctuated generally within the range of 1.50-2.10 MPa in the axial direction of the pipeline from 0 to 100 m, exhibiting a non-stationary change with multiple peaks and valleys. The peak values ​​repeatedly approached 2.10 MPa, while the valley values ​​were distributed within the range of 1.25-1.60 MPa. This reflects the pressure response caused by changes in flow conditions, composition, or system disturbances during gas transmission. Meanwhile, the pressure pulsation amplitude (MPa) (dashed line) remained within a narrow range of 0.10-0.25 MPa, demonstrating high stability and indicating that the intensity of pressure fluctuations within the pipeline was controlled and possessed a clear periodicity. This coordinated distribution of pressure and pulsation amplitude is a key input for constructing a real-time heat exchange model and predicting the risks of condensation and waxing: on the one hand, the dynamic changes in gas pressure directly affect the calculation accuracy of theoretical dew point temperature and potential waxing temperature; on the other hand, the stable characteristics of pressure pulsation amplitude provide a quantitative basis for identifying pressure fluctuation cycles and assessing pipeline dynamic loads, providing core data support for the generation of subsequent differentiated electric heat tracing control strategies.

[0110] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for controlling the heating of the engine gas delivery pipeline in a marine gas generator set, characterized in that, include: Real-time acquisition of multi-dimensional environmental status information of the engine gas delivery pipeline, including gas composition and pressure fluctuation data at the pipeline inlet, temperature gradient distribution data of the pipeline's metal outer wall, and ambient temperature and relative humidity changes in the compartment where the pipeline is located; The gas composition and pressure fluctuation data at the pipeline inlet are analyzed and processed to identify the methane main component content, the proportion of high carbon hydrocarbon by-products, and the period and amplitude of pressure pulsation of the current gas. Combined with a pre-set gas property database, the theoretical dew point temperature and potential waxing temperature of the current gas under the monitored pressure conditions are calculated. The temperature gradient distribution data of the outer metal wall of the pipeline is fused and analyzed with the ambient temperature change data of the compartment where the pipeline is located to construct a real-time heat exchange model of the engine gas delivery pipeline. Based on the real-time heat exchange model, the theoretical temperature decay curve of the gas inside the pipeline at different locations is calculated. Based on the comparison between the theoretical dew point temperature, the potential waxing temperature and the theoretical temperature decay curve, the risk location and risk level of condensation or waxing of gas inside the pipeline along the transportation path are predicted. Based on the risk location and degree of condensation or waxing, and combined with the effect of relative humidity change data on condensation on the pipe wall, a differentiated electric heat tracing control strategy is generated for different sections of the engine gas delivery pipeline.

2. The method for controlling the heating of the engine gas delivery pipeline of a marine gas generator set according to claim 1, characterized in that, The gas composition and pressure fluctuation data at the pipeline inlet are analyzed to identify the methane main component content, the proportion of high-carbon hydrocarbon by-products, and the period and amplitude of pressure pulsations in the current gas, including: The gas samples continuously extracted from the pipeline inlet were subjected to component separation and quantitative analysis using online gas chromatography analysis technology to obtain the molar percentage content of methane as the main methane component content; In the quantitative analysis results, the total molar percentage content of ethane, propane, butane, and hydrocarbons with 5 or more carbon atoms is calculated as the proportion of the high-carbon hydrocarbon by-components. Time-domain analysis is performed on the pressure fluctuation data to extract the periodic fluctuation components in the pressure signal, and the repetition time interval of the fluctuation components is calculated as the period of the pressure pulsation. The difference between the maximum and minimum values ​​of the pressure fluctuation data within a single period of the pressure pulsation is calculated as the amplitude of the pressure pulsation. The methane main component content, the proportion of high-carbon hydrocarbon by-products, and the period and amplitude of pressure pulsation are associated with timestamps and stored in the current gas state record.

3. The method for controlling the heating of the engine gas delivery pipeline of a marine gas generator set according to claim 2, characterized in that, The calculation, based on a pre-set gas property database, yields the theoretical dew point temperature and potential wax deposition temperature of the current gas under the monitored pressure conditions, including: Using the methane main component content and the proportion of high carbon hydrocarbon by-components as the query index, the saturated vapor pressure data and heavy hydrocarbon crystallization characteristic data of the corresponding component gas under different pressures are retrieved from the preset gas physical property database. Extract the real-time average pressure value from the gas pressure fluctuation data at the pipeline inlet; Based on the real-time average pressure value and the retrieved saturated vapor pressure data, the temperature at which water vapor in the gas reaches saturation is determined through iterative calculation and used as the theoretical dew point temperature. Based on the real-time average pressure value, the proportion of high-carbon hydrocarbon by-products, and the retrieved heavy hydrocarbon crystallization characteristic data, the temperature at which the high-carbon hydrocarbon components in the fuel gas begin to precipitate solid wax crystals is determined by a phase equilibrium calculation model, and is taken as the potential waxing temperature. The calculated theoretical dew point temperature and potential wax deposition temperature are correlated with the current gas state record.

4. The method for heating and controlling the engine gas delivery pipeline of a marine gas generator set according to claim 3, characterized in that, Construct a real-time heat exchange model for the engine gas delivery pipeline, and calculate the theoretical temperature decay curves of the gas inside the pipeline at different locations based on the real-time heat exchange model, including: The temperature gradient distribution data of the outer metal wall of the pipeline is converted into the temperature of a series of outer wall temperature measuring points distributed along the pipeline axis. The ambient temperature change data of the compartment where the pipeline is located is converted into an ambient reference temperature corresponding to the series of external wall temperature measurement points; Based on the gas flow characteristics and pipeline geometric parameters, the engine gas delivery pipeline is divided into multiple continuous micro-element pipe segments; For each micro-pipe segment, based on its inlet gas temperature, the temperature of the outer wall temperature measuring point, the ambient reference temperature, and the thermal conductivity parameters of the pipe material, the theoretical outlet temperature of the gas after flowing through the micro-pipe segment is calculated based on the energy conservation equation. The theoretical outlet temperature is then used as the inlet gas temperature of the next adjacent micro-pipe segment. Starting from the known actual gas temperature at the pipeline inlet, the gas temperature change of all micro-pipe segments is calculated sequentially according to the gas flow direction, and finally a sequence of predicted gas temperature values ​​distributed along the entire pipeline axis is obtained. The sequence of predicted gas temperature values ​​constitutes the theoretical temperature decay curve.

5. The method for heating and controlling the engine gas delivery pipeline of a marine gas generator set according to claim 4, characterized in that, Based on the comparison between the theoretical dew point temperature, the potential wax deposition temperature, and the theoretical temperature decay curve, the risk locations and degree of condensation or wax deposition of gas inside the pipeline along the transportation path are predicted, including: Along the theoretical temperature decay curve, the theoretical gas temperature value at each location is compared with the theoretical dew point temperature. The location where the theoretical gas temperature is lower than the theoretical dew point temperature is marked as a condensation risk point. The difference between the theoretical dew point temperature and the theoretical gas temperature is calculated as the theoretical condensation risk level of the condensation risk point. Along the theoretical temperature decay curve, the theoretical gas temperature value at each location is compared with the potential wax deposition temperature. The locations where the theoretical gas temperature is lower than the potential waxing temperature are marked as waxing risk points. The difference between the potential waxing temperature and the theoretical gas temperature is calculated as the theoretical waxing risk level of the waxing risk point. The location coordinates, risk types, and theoretical risk levels of condensation risk points and wax deposition risk points are summarized to generate a pipeline risk prediction map.

6. The method for controlling the heating of the engine gas delivery pipeline of a marine gas generator set according to claim 5, characterized in that, Based on the effect of relative humidity variation data on condensation on pipe walls, differentiated electric heat tracing control strategies are generated for different sections of the engine gas delivery pipeline, including: The differentiated electric heat tracing control strategy includes the heating power setting, heating rate, and heating start-up time for a specified pipeline section; Based on the relative humidity change data of the compartment where the pipeline is located, the absolute humidity of the air in the compartment is calculated, and combined with the ambient temperature change data, the critical conditions for condensation to occur on the outer wall of the pipeline are estimated. The estimated critical conditions for surface condensation on the outer wall of the pipeline are superimposed on the pipeline risk prediction map. For pipeline sections with theoretical condensation risk or waxing risk, if their external environment simultaneously meets or approaches the critical conditions for surface condensation, the risk level of the pipeline section is increased. Based on the risk points and risk levels marked in the pipeline risk prediction map, and combined with the electric heat tracing zoning design of the gas transmission pipeline, control parameters are formulated for each electric heat tracing zone. For pipeline sections with high risk levels, a heating power setting value determined based on a first preset power mapping table and a heating rate determined based on a first preset rate mapping table are set, and heating is set to start immediately or start heating based on a first time threshold preset in advance based on the risk level. For pipeline sections with low risk levels, set the heating power setting value based on the second preset power mapping table and the heating rate based on the second preset rate mapping table, and set the heating to start with a preset second time threshold or to perform intermittent heating according to a preset duty cycle. Wherein, the reference power value corresponding to the first preset power mapping table is higher than that of the second preset power mapping table, and the reference heating rate corresponding to the first preset rate mapping table is higher than that of the second preset rate mapping table. The heating power settings, heating rate, and heating start-up time of all electric heat tracing zones are integrated to form a global differentiated electric heat tracing control strategy.

7. The method for controlling the heating of the engine gas delivery pipeline of a marine gas generator set according to claim 6, characterized in that, The process of determining the temperature at which high-carbon hydrocarbon byproducts begin to precipitate solid wax crystals in the fuel gas, based on the real-time average pressure value, the proportion of high-carbon hydrocarbon byproducts, and the retrieved heavy hydrocarbon crystallization characteristic data, using a phase equilibrium calculation model, as the potential wax crystallization temperature, includes: From the heavy hydrocarbon crystallization characteristic data, the solid-liquid phase equilibrium constants of each heavy hydrocarbon component contained in the current high-carbon hydrocarbon component of the fuel gas at different temperatures are extracted; The real-time average pressure value, the proportion of high-carbon hydrocarbon by-products, and the initial mole fraction of each heavy hydrocarbon component are input into a phase equilibrium calculation model based on the equation of state. The phase equilibrium calculation model adopts the PR equation or SRK equation applicable to hydrocarbon mixtures. An initial temperature value is set, and the distribution coefficients of each heavy hydrocarbon component in the gas phase and the hypothetical solid phase are calculated using the phase equilibrium calculation model under the initial temperature value and the real-time average pressure value. For all high-carbon hydrocarbon components in the fuel gas, calculate the sum of their mole fractions in the hypothetical solid phase, and determine whether the sum is greater than the preset crystallization precipitation threshold. If the total mole fraction is less than or equal to the crystallization threshold, the initial temperature value is gradually reduced, and the phase equilibrium calculation model is called again for calculation and judgment. When the sum of the molar fractions first exceeds the crystallization threshold, the system temperature at this time is determined as the critical temperature at which the high-carbon hydrocarbon components begin to precipitate solid wax crystals, and is used as the potential waxing temperature.

8. The method for controlling the heating of the engine gas delivery pipeline of a marine gas generator set according to claim 7, characterized in that, It also includes a dynamic correction step based on policy execution feedback: After implementing the differentiated electric heat tracing control strategy, the temperature gradient distribution data of the outer metal wall of the pipeline is re-acquired and updated; The updated temperature gradient distribution data of the outer metal wall of the pipeline is input into the real-time heat exchange model to calculate the updated theoretical temperature decay curve of the gas. The updated theoretical gas temperature decay curve is compared again with the theoretical dew point temperature and potential waxing temperature to assess the actual elimination of condensation and waxing risks. If the risk is not completely eliminated, the heating power setting value of the corresponding pipeline section shall be increased proportionally; If the risk has been eliminated and the temperature of the outer metal wall of the pipeline exceeds the safety margin threshold, the heating power setting value of the corresponding pipeline section shall be reduced proportionally. Based on the evaluation results and the adjusted heating power setting, a correction instruction for the electric heat tracing control strategy is generated for the next control cycle.

9. The method for controlling the heating of the engine gas delivery pipeline of a marine gas generator set according to claim 8, characterized in that, The updated temperature gradient distribution data of the pipeline's metal outer wall is input into the real-time heat exchange model to calculate the updated theoretical gas temperature decay curve, including: The updated temperature gradient distribution data of the outer metal wall of the pipeline is used as a new boundary condition to replace the original boundary condition used when constructing the real-time heat exchange model. Keep all parameters in the real-time heat exchange model unchanged except for the boundary conditions, including pipeline geometry parameters, material thermal conductivity parameters, and gas flow characteristics parameters; The real-time heat exchange model was rerun using the new boundary conditions to recalculate the theoretical outlet temperature of the gas flow through each micro-element pipe segment. Starting from the actual gas temperature at the pipeline inlet, the gas temperature changes of all micro-pipe segments are recalculated sequentially to obtain an updated sequence of predicted gas temperatures, which is the updated theoretical gas temperature decay curve.

10. The method for controlling the heating of the engine gas delivery pipeline of a marine gas generator set according to claim 9, characterized in that, It also includes the feedforward compensation step for the heating strategy under variable engine load operation: Monitor the real-time power output signal of the engine of the marine gas generator set; Based on the changing trend of the engine's real-time power output signal, predict the expected change in gas flow rate; Based on the expected change in gas flow rate, the expected change in the overall heat loss of the engine gas delivery pipeline is predicted using a pre-calibrated gas flow rate-heat loss rate relationship model. Based on the expected direction and magnitude of the overall heat loss change, the heating power setpoint in the currently executed differentiated electric heat tracing control strategy is synchronously fed forward and adjusted. Before the expected increase in gas flow due to the increase in engine power, the heating power setting value is increased in advance according to the predicted proportion. When the engine power decreases, leading to a predicted reduction in gas flow, the heating power setting value is reduced in advance according to the predicted proportion.

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