A method and system for gas dynamic simulation analysis based on thermodynamic coupling

Abstract

The application discloses a kind of based on thermodynamic coupling's gas power simulation analysis method and system, it is related to simulation analysis technical field, including calculating the sensitive index and uncertain index of each reference parameter, fully consider the characteristics of reference parameter to accurately enhance the robustness of simulation model description.Statistics the geometric characteristics of each region, reference parameter characteristics and the sensitive index of reference parameter to determine the grid density required by the region corresponding, according to the characteristics of region and reference parameter characteristics to set the grid density on the different regions of geometric three-dimensional model, to meet the analysis and calculation requirements of different regions.According to the uncertainty index of reference parameter, the reference parameter in simulation model is given credibility, the simulation model is used to simulate and analyze the marine turbine equipment, and the calculation accuracy of different regions is reasonably distributed to meet the complex and variable working conditions of the equipment.Effectively capture the coupling of multiple physics, and improve the accuracy and adaptability of simulation analysis.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of simulation analysis, in particular to a gas dynamics simulation analysis method and system based on thermodynamic coupling. BACKGROUND

[0002] In the field of marine engine equipment, with the improvement of energy efficiency and environmental protection requirements of the shipping industry, the demand for equipment performance optimization and fault prediction is increasingly urgent. When the marine engine equipment is running, it involves complex thermodynamic processes and gas dynamics phenomena, and there is a close thermodynamic coupling relationship between the components. For example, the combustion of gas in the engine combustion chamber produces high-temperature and high-pressure gas, and its expansion work process is closely related to the thermodynamic state change, and it will affect the temperature field of the surrounding components through heat conduction, convection, etc., and then change the gas flow characteristics. The traditional simulation analysis method often isolates the thermodynamic and gas dynamics processes, and it is difficult to accurately simulate the actual working conditions.

[0003] In the prior art, the analysis and calculation accuracy of different positions on the established simulation model of the marine engine equipment are the same, the calculation accuracy distribution is unreasonable, which leads to the fact that the marine engine equipment cannot be effectively and accurately simulated, and the coupling of thermodynamics, gas dynamics and other physical fields cannot be effectively captured, resulting in poor effect and low adaptability of the simulation analysis of the marine engine equipment.

[0004] Therefore, how to improve the rationality of the calculation accuracy distribution of the simulation model is a technical problem to be solved at present. SUMMARY

[0005] The purpose of the present application is to solve the problem of poor rationality of the calculation accuracy distribution of the simulation model in the prior art, and to provide a gas dynamics simulation analysis method based on thermodynamic coupling, which comprises,

[0006] Collect all reference parameters related to the marine engine equipment, determine the functional relationship and coupling relationship between the reference parameters, and analyze the functional relationship and coupling relationship between the reference parameters to calculate the sensitive index and uncertain index of each reference parameter;

[0007] Establish a three-dimensional geometric model of the marine engine equipment, and divide the three-dimensional geometric model into multiple regions according to the structure and function of the marine engine equipment;

[0008] Determine the required grid density of each region by counting the geometric characteristics, reference parameter characteristics and sensitive index of the reference parameters of each region, perform grid processing on the three-dimensional geometric model based on the grid density, and establish a simulation model of the marine engine equipment based on the functional relationship and coupling relationship between the reference parameters and the three-dimensional geometric model;

[0009] According to the uncertainty index of the reference parameter, the credibility of the reference parameter in the simulation model is given, and the ship marine equipment is simulated and analyzed by the simulation model, so as to realize fault recognition and prediction.

[0010] The reference parameter includes one or more of a device design parameter, a mechanical parameter, a thermodynamic parameter, a fluid mechanics parameter and an electrical parameter.

[0011] In some embodiments of the application, the function relationship and coupling relationship between the reference parameters are determined, including,

[0012] The data samples of the reference parameters are collected, and the simple function relationship and the complex function relationship are distinguished. For the simple function relationship, the simple function relationship is described by physical laws or related theoretical laws. For the complex function relationship, the initialization of the complex function relationship is determined by mathematical modeling, and the initialization of the complex function relationship is optimized by the data samples of the reference parameters.

[0013] The multi-physical field mechanism and the energy and material transfer mechanism involved in the ship marine equipment are analyzed, the coupling model is established, the coupling model is a physical model coupling or a numerical simulation coupling, and the coupling model is optimized according to the data samples of the reference parameters.

[0014] In some embodiments of the application, the function relationship and coupling relationship between the reference parameters are analyzed to calculate the sensitivity index and the uncertainty index of each reference parameter, including,

[0015] The effect parameter describing the performance or running state of the ship marine equipment is screened out from the reference parameters, and a plurality of objective functions between the other parameters in the reference parameters and the effect parameter are established.

[0016] The correlation between each reference parameter and the corresponding effect parameter in each objective function is calculated, the normal value range of each reference parameter is obtained, and the disturbance amount is determined based on the normal value range of the reference parameter and the correlation.

[0017] In the simulation software, the reference parameter is slightly disturbed by the disturbance amount in the bidirectional disturbance of each objective function. The bidirectional disturbance includes positive disturbance and negative disturbance of the reference parameter, and the change rate of the effect parameter and the reference parameter in the objective function is counted to obtain the central difference as the local sensitivity index.

[0018] For the same objective function, the correlation between different reference parameters is calculated, the strong correlation reference parameter corresponding relationship is screened out, the correlation change with different value ranges under the reference parameter corresponding relationship is drawn, and the standard value range of the reference parameter is determined.

[0019] Random sampling is performed on the basis of the standard value range of the reference parameters by using Latin hypercube sampling or Monte Carlo sampling to obtain a plurality of reference parameter combinations, each of which is input into the simulation software to obtain the size of the effect parameter on the objective function;

[0020] The complexity of each objective function is evaluated, and the Sobol index order is selected in combination with the complexity of the objective function and the correlation between different reference parameters under the objective function to determine the global sensitivity index;

[0021] The sensitivity index is determined based on the local sensitivity index and the global sensitivity index of each reference parameter;

[0022] The uncertainty index of each reference parameter is described by a probability distribution.

[0023] In some embodiments of the present application, the uncertainty index of each reference parameter is described by a probability distribution, including,

[0024] A histogram of each reference parameter is drawn, and the statistics of each reference parameter are counted on the histogram. Fitting degree test is performed on each reference parameter to determine the distribution type, establish the original probability distribution of each parameter, and establish the joint probability distribution under the corresponding relationship of the strongly correlated reference parameters. The uncertainty index of each reference parameter is determined according to the original probability distribution and the joint probability distribution.

[0025] In some embodiments of the present application, the three-dimensional geometric model is divided into multiple regions according to the structure and function of the marine engine equipment, including,

[0026] The three-dimensional geometric model is divided into multiple structural regions according to the differences of the structural components of the marine engine equipment, and each structural region is further divided into regions according to the differences in function.

[0027] In some embodiments of the present application, the geometric characteristics, reference parameter characteristics and sensitivity index of each region are counted to determine the required grid density corresponding to the region, including,

[0028] The geometric complexity of each type of geometric feature is evaluated to generate an evaluation index;

[0029] The reference parameter categories involved in each region are confirmed according to the function of the marine engine equipment and a plurality of physical processes, a reference parameter set is constructed, each region corresponds to a reference parameter set, and the physical field characteristics of the reference parameters are counted. The calculation accuracy requirement level is defined based on the evaluation index of the geometric characteristics, the physical field characteristics of the reference parameters and the sensitivity index of the reference parameters, and a grid density is mapped according to the calculation accuracy requirement level.

[0030] In some embodiments of the present application, the reference parameters in the simulation model are given a credibility according to the uncertainty index of the reference parameters, including,

[0031] The maximum value, the minimum value, the mode value and the median value of the uncertainty indexes of all reference parameters are counted, the distances between the mode value and the maximum value and the minimum value are calculated respectively, the minimum distance of the two distances is taken as the adjacent distance, the median value is adjusted to be close to the maximum value or the minimum value through the adjacent distance, and a standard threshold value is obtained;

[0032] The reference parameters are distinguished as strong credible parameters and weak credible parameters through the standard threshold value, and the credibility of the strong credible parameters and the weak credible parameters is determined through two mapping relationships respectively.

[0033] In some embodiments of the application, the ship marine equipment is simulated and analyzed through the simulation model, including,

[0034] The boundary conditions and the initial conditions are set on the simulation model, and the credibility of the strong credible parameters and the weak credible parameters is fused to identify and predict the fault.

[0035] Correspondingly, the application also provides a gas power simulation analysis system based on thermodynamic coupling, including,

[0036] The first module is used for collecting all reference parameters related to the ship marine equipment, determining the function relationship and the coupling relationship between the reference parameters, and analyzing the function relationship and the coupling relationship between the reference parameters to calculate the sensitive index and the uncertainty index of each reference parameter;

[0037] The second module is used for establishing a three-dimensional geometric model of the ship marine equipment, and dividing the three-dimensional geometric model into multiple regions according to the structure and function of the ship marine equipment;

[0038] The third module is used for counting the geometric characteristics of each region, the reference parameter characteristics and the sensitive index of the reference parameters to determine the required grid density of the region, performing grid processing on the three-dimensional geometric model based on the grid density, and establishing a simulation model of the ship marine equipment based on the function relationship and the coupling relationship between the reference parameters and the three-dimensional geometric model;

[0039] The fourth module is used for giving the reference parameters in the simulation model the credibility according to the uncertainty index of the reference parameters, simulating and analyzing the ship marine equipment through the simulation model, so as to realize fault identification and prediction;

[0040] The reference parameters include one or more of the device design parameters, the mechanical parameters, the thermodynamic parameters, the fluid mechanics parameters and the electrical parameters.

[0041] The application also has the following beneficial effects:

[0042] 1, Determine the function relationship and coupling relationship between the reference parameters, and provide a reliable basis for the subsequent characteristic analysis of the reference parameters and the construction of the simulation model. Calculate the sensitive index and uncertain index of each reference parameter, fully consider the characteristics of the reference parameters to enhance the robustness of the simulation model description. Statistics of the geometric characteristics of each region, the characteristics of the reference parameters and the sensitive index of the reference parameters are used to determine the required grid density of the region. According to the characteristics of the region and the characteristics of the reference parameters, the grid density on different regions of the three-dimensional geometric model is set to meet the analysis and calculation requirements of different regions.

[0043] 2, On the basis of the function relationship and coupling relationship between the reference parameters and the three-dimensional geometric model, the simulation model of the ship's marine equipment is established. According to the uncertainty index of the reference parameters, the reference parameters in the simulation model are given the reliability. Through the simulation analysis of the simulation model on the ship's marine equipment, the calculation accuracy of different regions is reasonably distributed to meet the complex and variable working conditions of the equipment. Effectively capture the multi-physical coupling situation, and improve the accuracy and adaptability of the simulation analysis, identify and predict the fault condition of the ship's marine equipment in time, and ensure the normal operation of the equipment. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 A flowchart of a gas power simulation analysis method based on thermodynamic coupling is proposed in the present application.

[0045] Figure 2 A structure diagram of a gas power simulation analysis system based on thermodynamic coupling is proposed in the present application. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be described clearly and completely in the embodiments of the present application with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all.

[0047] Reference Figure 1 A gas power simulation analysis method based on thermodynamic coupling, comprising the following steps:

[0048] Step S101, collect all reference parameters related to the ship's marine equipment, determine the function relationship and coupling relationship between the reference parameters, analyze the function relationship and coupling relationship between the reference parameters, and calculate the sensitive index and uncertain index of each reference parameter.

[0049] Among them, the reference parameters include one or more of the device design parameters, mechanical parameters, thermodynamic parameters, fluid mechanics parameters and electrical parameters.

[0050] In this embodiment, the equipment design parameters (such as cylinder diameter, stroke, etc.), mechanical parameters (such as speed, torque, etc.), thermodynamic parameters (such as temperature, pressure, etc.), fluid mechanics parameters (such as flow, flow rate, etc.), electrical parameters (such as voltage, current, etc.) related to marine engine equipment are collected. To analyze the characteristics of the reference parameters, the function relationship and the mutual coupling relationship involved in the reference parameters need to be determined. The function relationship refers to the existence of a clear and deterministic correspondence between two or more variables, that is, the value of a variable can be uniquely determined by the values of other variables through a deterministic mathematical expression or rule. In marine engine equipment, the function relationship describes the direct and accurately calculable correlation between parameters. For example, the relationship between power and speed, torque, and the relationship between fuel consumption rate and power. The coupling relationship refers to the mutual influence and interaction between two or more systems, parameters or physical fields. This relationship is often complex and nonlinear, and the change of a parameter will not only affect itself, but also affect other parameters or systems through certain mechanisms, while the change of other parameters or systems will also affect the parameter in turn. In marine engine equipment, the coupling relationship reflects the mutual correlation and constraints between different parts of the equipment and different physical processes. Thermal-mechanical coupling. In marine engines, the high temperature generated by combustion will cause the engine components to expand and change in size and mechanical properties, which will affect the mechanical movement and stress distribution of the engine. In turn, the changes in mechanical movement and stress distribution may affect the combustion process, such as affecting the gas flow and mixture formation in the cylinder, and thus affecting the combustion efficiency and temperature distribution. This mutual influence between heat and force is the thermal-mechanical coupling relationship.

[0051] In some embodiments of the present application, the function relationship and coupling relationship between the reference parameters are determined, including,

[0052] Collecting data samples of the reference parameters, distinguishing simple function relationships and complex function relationships, for simple function relationships, describing the simple function relationships through physical laws or related theoretical laws, for complex function relationships, determining the initialization of the complex function relationship through mathematical modeling, and optimizing the initialization of the complex function relationship through the data samples of the reference parameters;

[0053] Analyzing the multi-physical field mechanism and energy and mass transfer mechanism involved in the marine engine equipment, establishing a coupling model, and optimizing the coupling model according to the data samples of the reference parameters.

[0054] In this embodiment, for simple function relationships, such as the relationship between power P and rotational speed n and torque T, physical laws can be directly used for description. For complex function relationships, such as the relationship between the fuel consumption rate of an engine and multiple parameters, mathematical modeling is first used for initialization, such as a multivariate linear regression model, and then data samples are used to optimize model parameters. Coupling model establishment: analyze the mechanisms of multiple physical fields (such as thermal-mechanical coupling, fluid-solid coupling, etc.) and energy and mass transfer mechanisms, and establish a physical model coupling or numerical simulation coupling model. For example, the heat transfer and gas flow in the combustion process of an engine are coupled with each other, and a coupled model can be established by using finite element software, and the model is optimized by using data samples.

[0055] In some embodiments of the present application, the sensitivity index and the uncertainty index of each reference parameter are calculated by analyzing the function relationship and the coupling relationship between the reference parameters, including,

[0056] Effect parameters describing the performance or operating state of the marine engine equipment are screened out from the reference parameters, and multiple objective functions are established between the other parameters in the reference parameters and the effect parameters;

[0057] The correlation between each reference parameter and the corresponding effect parameter in each objective function is calculated, the normal value range of each reference parameter is obtained, and the disturbance amount is determined based on the normal value range of the reference parameters and the correlation;

[0058] In the simulation software, the reference parameters are slightly disturbed by the disturbance amount in the bidirectional disturbance of each objective function, the bidirectional disturbance includes positive and negative disturbances of the reference parameters, and the change rates of the effect parameters and the reference parameters of the objective function are counted to obtain the central difference as the local sensitivity index;

[0059] For the same objective function, the correlation between different reference parameters is calculated, the corresponding relationship of the strongly correlated reference parameters is screened out, the correlation change with different value ranges of the reference parameter corresponding relationship is drawn, and thus the standard value range of the reference parameters is determined;

[0060] Latin hypercube sampling or Monte Carlo sampling is used to randomly sample in the standard value range of the reference parameters, a plurality of reference parameter combinations are obtained, each reference parameter combination is input into the simulation software, and the size of the effect parameter on the objective function is obtained;

[0061] The complexity of each objective function is evaluated, the Sobol index order is selected in combination with the complexity of the objective function and the correlation between different reference parameters under the objective function, and the global sensitivity index is determined;

[0062] The sensitivity index is determined based on the local sensitivity index and the global sensitivity index of each reference parameter;

[0063] The uncertainty indicators of each reference parameter are described by a probability distribution.

[0064] In this embodiment, the effect parameters describing the performance or operating state of the marine engine equipment are screened out, such as the power and efficiency of the engine. The objective functions of other parameters and effect parameters are established, such as the objective function of power, and the objective functions of parameters such as speed and torque and power. For sensitivity, the local sensitivity and global sensitivity are integrated to determine the sensitivity indicator. The correlation between the reference parameters and the effect parameters in each objective function is calculated to determine the normal value range of the reference parameters, such as the speed generally in 1000-3000 rpm. Based on the normal value range and the correlation, the perturbation amount is determined, and the stronger the correlation, the greater the proportion, such as taking 5% of the normal range as the perturbation amount. In the simulation software, bidirectional perturbation is performed on each objective function (such as positive perturbation of 5% and negative perturbation of 5%), and the change rate of the effect parameter and the reference parameter is counted to obtain the central difference as the local sensitivity indicator. The reason for the small perturbation is that the local sensitivity analysis is based on the local linear assumption, that is, within a small neighborhood of the parameter, the relationship between the objective function and the parameter can be approximated as a linear relationship. If a large range of perturbation is used, the relationship between the parameter and the objective function may no longer satisfy the linear assumption, resulting in inaccurate calculation results of the local sensitivity. Small perturbation can make the change of the objective function caused by the change of the parameter in the linear or approximately linear region, so that the calculation process is more stable. For example, in the calculation of the sensitivity of the engine fuel efficiency to the fuel injection amount, the small change of the fuel injection amount will not cause the engine to work in a nonlinear region, and the influence of the parameter near the specific working point can be more accurately reflected. Large-scale perturbation may cause the system to enter a nonlinear working region, making the relationship between the objective function and the parameter complex and unstable. For example, if the fuel injection amount of the engine is perturbed in a large range, the combustion process and heat transfer process of the engine may change significantly, causing the change of the objective function (such as fuel efficiency) no longer following a simple linear relationship, thereby making the calculation of local sensitivity meaningless.

[0065] It can be understood that when calculating the change rate of the objective function, a numerical stability algorithm is selected. For example, when calculating the difference, the central difference formula is used instead of the one-sided difference formula because the central difference formula has higher numerical precision and stability.

[0066] In global sensitivity analysis, the value range of the sampled parameters should generally be determined based on the physical meaning of the parameters and the actual working conditions, but can also be adjusted to some extent according to the correlation between different reference parameters in the objective function. The correlation between different reference parameters is calculated, and the corresponding relationship of the strongly correlated reference parameters is screened out, such as the strong correlation between the speed and the torque under certain conditions. The correlation curve with different value ranges is drawn to determine the standard value range of the reference parameters. If there is a strong correlation between some parameters (such as the positive correlation between fuel injection amount and intake pressure), the value range can be adjusted appropriately during sampling to avoid sampling unreasonable parameter combinations. The correlation can be maintained during sampling to improve the rationality of sampling. For strongly correlated parameters, a conditional sampling method can be used, that is, after the value of a certain parameter is determined, the value range of another parameter is determined according to its correlation. Sobol index method calculates the sensitivity of parameters by decomposing the variance of the objective function. The order is usually determined by the complexity of the objective function and the interaction between parameters. The complexity of the objective function is calculated by one-time two-time, first-order two-order, etc. The Sobol index order is selected in combination with the complexity of the objective function and the correlation between different reference parameters under the objective function. The Sobol index order is selected: according to the complexity of the objective function and the interaction between parameters, a reasonable Sobol index order is selected. Generally, start from the first order, and gradually increase the order. Determine the sensitivity index based on the local sensitivity index and the global sensitivity index of each reference parameter, and calculate the sensitivity index considering both directions.

[0067] In some embodiments of the present application, the uncertainty index of each reference parameter is described by a probability distribution, including,

[0068] Draw a histogram of each reference parameter, count the statistics of each reference parameter on the histogram, perform a goodness-of-fit test on each reference parameter, determine the distribution type, establish the original probability distribution of each parameter, and establish the joint probability distribution under the corresponding relationship of the strongly correlated reference parameters. Determine the uncertainty index of each reference parameter according to the original probability distribution and the joint probability distribution.

[0069] In this embodiment, a data analysis tool (such as Python's Matplotlib, Seaborn library or R language's ggplot2 package) is used to draw a histogram. The statistics include kurtosis, skewness, etc. to reflect the distribution, and the possible distribution type is initially guessed according to the shape of the histogram and the domain knowledge, such as normal distribution, uniform distribution, exponential distribution, etc. The goodness-of-fit test method is:

[0070] Kolmogorov-Smirnov test (K-S test): used to test whether the data conforms to a certain specific distribution.

[0071] Shapiro-Wilk test: A normality test suitable for small sample data.

[0072] Chi-square test: Used to test whether the distribution of data is consistent with the theoretical distribution.

[0073] Original probability distribution: Determine the most appropriate distribution type, such as normal distribution N, based on the goodness-of-fit test results.

[0074] Joint probability distribution: Establish joint probability distribution for strongly correlated reference parameters, such as speed and torque. Methods such as Copula function or multivariate normal distribution can be used.

[0075] Uncertainty indicator: Calculate the uncertainty of the parameters based on the original probability distribution and joint probability distribution. Common uncertainty indicators include:

[0076] Confidence interval: Such as 95% confidence interval, indicating that the parameter has a 95% probability of falling within this interval.

[0077] Coefficient of Variation (CV): The ratio of standard deviation to mean, reflecting the relative dispersion of data.

[0078] Step S102, a three-dimensional geometric model of the marine engine equipment is established, and the three-dimensional geometric model is divided into multiple regions according to the structure and function of the marine engine equipment.

[0079] In this embodiment, the three-dimensional geometric model is divided into multiple structural regions according to the structural components of the marine engine equipment (such as the cylinder, crankshaft, etc. of the engine). Within each structural region, the region is further divided according to the functional differences (such as the combustion chamber, cooling channel, etc. of the cylinder).

[0080] In some embodiments of the present application, the three-dimensional geometric model is divided into multiple regions according to the structure and function of the marine engine equipment, including,

[0081] The three-dimensional geometric model is divided into multiple structural regions according to the different structural components of the marine engine equipment, and the region is further divided according to the functional differences within each structural region.

[0082] Step S103, the geometric characteristics, reference parameter characteristics and sensitive indicators of the reference parameters of each region are counted to determine the required grid density of the region, the three-dimensional geometric model is meshed based on the grid density, and the simulation model of the marine engine equipment is established based on the functional relationship and coupling relationship between the reference parameters and the three-dimensional geometric model.

[0083] In some embodiments of this application, the required mesh density for each region is determined by statistically analyzing the geometric features, reference parameter features, and sensitivity indices of the reference parameters.

[0084] For each type of geometric feature, evaluate the geometric complexity and generate evaluation indicators;

[0085] Based on the functions of ship engine equipment and multiple physical processes, the categories of reference parameters involved in each region are identified, a set of reference parameters is constructed, and each region corresponds to a set of reference parameters. The physical field characteristics of the reference parameters are statistically analyzed. Based on the evaluation index of geometric features, the physical field characteristics of the reference parameters, and the sensitivity index of the reference parameters, the required level of computational accuracy is defined, and a grid density is mapped according to the required level of computational accuracy.

[0086] In this embodiment, the geometric complexity of each type of geometric feature is evaluated. For example, the shape complexity of a cylinder can be evaluated by calculating its surface area to volume ratio. Based on the equipment function and physical process, the categories of reference parameters involved in each region are identified, and a set of reference parameters is constructed. The physical field characteristics of the reference parameters are statistically analyzed, such as the magnitude of the temperature gradient. Based on the geometric feature evaluation indicators, physical field characteristics, and sensitivity indicators, a computational accuracy requirement level is defined, mapping to the mesh density. For example, regions with large temperature gradients require higher mesh densities. The specific formula for the computational accuracy requirement level is as follows: ;

[0087] in, For the first The required computational accuracy level for each region is determined by normalizing the geometric features and reference parameter features. , These are the conversion coefficients for geometric features and reference parameters, respectively. , The first The number of geometric features and the number of reference parameters for each region For the first The combined weights of geometric features, For the first The first region Evaluation metrics for geometric features For the first The combined weights of the reference parameters, For the first The first region Each reference parameter is an evaluation metric that integrates the characteristics of all reference parameters (describing complexity). For the first The first region Sensitive indicators of a reference parameter, For the first a first constant of the reference parameter, a second constant of the i-th region, [] is a rounding symbol, a second constant of the i-th region, [] is a rounding symbol, represents the correction of the sensitive index to the reference parameter evaluation index, the first constant is used to balance the size of the correction function, and the second constant is used to balance the size of the calculation accuracy requirement level. According to the determined grid density, the three-dimensional geometric model is meshed, and software such as ANSYS Meshing can be used.

[0088] In step S104, the reference parameter in the simulation model is given a confidence level according to the uncertainty index of the reference parameter, and the ship machinery equipment is simulated and analyzed through the simulation model, so as to realize fault recognition and prediction.

[0089] In some embodiments of the present application, the reference parameter in the simulation model is given a confidence level according to the uncertainty index of the reference parameter, including,

[0090] The maximum value, the minimum value, the mode value and the median value of the uncertainty index of all reference parameters are counted, the distances between the mode value and the maximum value and the minimum value are calculated respectively, the minimum distance of the two distances is taken as the adjacent distance, the median value is adjusted to be close to the maximum value or the minimum value through the adjacent distance, and a standard threshold is obtained;

[0091] The reference parameters are distinguished as strong confidence parameters and weak confidence parameters through the standard threshold, and two mapping relationships are used to determine the confidence levels of the strong confidence parameters and the weak confidence parameters respectively.

[0092] In this embodiment, the maximum value, the minimum value, the mode value and the median value of the uncertainty index of all reference parameters are counted, so that the distribution of the uncertainty index can be comprehensively understood. The maximum value and the minimum value can reflect the extreme range of the uncertainty index, the mode value reflects the most common value of the uncertainty index, and the median value is in the middle position of the data and is not affected by the extreme value. By comprehensively considering these statistics, the overall characteristics of the uncertainty index can be more accurately grasped. The distances between the mode value and the maximum value and the minimum value are calculated, and the minimum distance is taken as the adjacent distance. This step is to find a reasonable limit for subsequent adjustment of the median value. The adjacent distance reflects the relative closeness between the mode value and the extreme value. Different adjacent distances correspond to different adjustment coefficients, which are modified in the form of the product of the adjustment coefficient and the median value. The mapping relationships corresponding to the strong confidence parameters and the weak confidence parameters are different, the strong confidence parameters and the weak confidence parameters are distinguished through the standard threshold, and the reference parameters of the ship machinery equipment can be classified and managed. The strong confidence parameter means that the uncertainty index is low and the data reliability is high; the weak confidence parameter is the opposite, the uncertainty index is high and the data reliability is low.

[0093] In some embodiments of the present application, the ship machinery equipment is simulated and analyzed through the simulation model, including,

[0094] Boundary conditions and initial conditions are set on the simulation model, and the reliability of strong and weak credible parameters is fused to identify and predict faults.

[0095] In this embodiment, boundary conditions (such as intake pressure, exhaust pressure, etc.) and initial conditions (such as initial temperature, speed, etc.) are set on the simulation model. The reliability of strong and weak credible parameters is fused, such as assigning different weights to different reliability parameters in simulation calculation. Run the simulation model, analyze the simulation results, such as abnormal changes in temperature, pressure and other parameters, and identify and predict faults in combination with sensitive indicators and uncertain indicators. For example, when the cylinder temperature exceeds the normal range and the sensitive indicator is high and the uncertain indicator is low, it may indicate a cylinder failure.

[0096] Correspondingly, the application also provides a gas power simulation analysis system based on thermodynamic coupling, as shown in Figure 2 , comprising,

[0097] The first module is used to collect all reference parameters related to the ship's marine equipment, determine the functional relationship and coupling relationship between the reference parameters, and analyze the functional relationship and coupling relationship between the reference parameters to calculate the sensitive indicators and uncertain indicators of each reference parameter.

[0098] The second module is used to establish a three-dimensional geometric model of the ship's marine equipment, and divide the three-dimensional geometric model into multiple regions according to the structure and function of the ship's marine equipment.

[0099] The third module is used to determine the required grid density of each region by counting the geometric characteristics, reference parameter characteristics and sensitive indicators of the reference parameters of each region, and to perform grid processing on the three-dimensional geometric model based on the grid density. On the basis of the functional relationship and coupling relationship between the reference parameters and the three-dimensional geometric model, a simulation model of the ship's marine equipment is established.

[0100] The fourth module is used to assign a reliability to the reference parameters in the simulation model according to the uncertain indicators of the reference parameters, and to perform simulation analysis on the ship's marine equipment through the simulation model, so as to realize fault identification and prediction.

[0101] The reference parameters include one or more of the device design parameters, mechanical parameters, thermodynamic parameters, fluid mechanics parameters, and electrical parameters.

[0102] The application also has the following beneficial effects:

[0103] 1. Determine the functional and coupling relationships between the reference parameters to provide a reliable foundation for subsequent characteristic analysis and simulation model construction. Calculate the sensitivity and uncertainty indices of each reference parameter, fully considering their characteristics to enhance the robustness and accuracy of the simulation model. Statistically analyze the geometric features, reference parameter characteristics, and sensitivity indices of each region to determine the required mesh density for that region. Based on the different characteristics of each region and the properties of the reference parameters, specifically set the mesh density for different regions of the geometric 3D model to meet the analysis and computational needs of different regions.

[0104] 2. Based on the functional and coupling relationships between reference parameters and the three-dimensional geometric model, a simulation model of the ship's marine machinery equipment is established. The reliability of the reference parameters in the simulation model is assigned according to their uncertainty indices. The simulation model is used to perform simulation analysis on the ship's marine machinery equipment, reasonably allocating computational precision for different regions to meet the complex and variable operating conditions of the equipment. This effectively captures multi-physics coupling and improves the accuracy and adaptability of the simulation analysis, enabling timely identification and prediction of faults in the ship's marine machinery equipment and ensuring its normal operation.

[0105] Through the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented in hardware or by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0106] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention.

[0107] Those skilled in the art will understand that the modules in the system of the implementation scenario can be distributed throughout the system of the implementation scenario as described, or they can be modified to reside in one or more systems different from this implementation scenario. The modules of the above-mentioned implementation scenario can be merged into one module, or they can be further divided into multiple sub-modules.

[0108] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for thermodynamic coupling-based gas dynamic simulation analysis, characterized in that, The application relates to a method for realizing fault identification and prediction of marine engine equipment. The method comprises the following steps: Collecting all reference parameters related to marine engine equipment, determining the functional relationship and coupling relationship between the reference parameters, and analyzing the functional relationship and coupling relationship between the reference parameters to calculate the sensitive index and uncertain index of each reference parameter; A three-dimensional geometric model of the marine engine equipment is established, and the three-dimensional geometric model is divided into multiple regions according to the structure and function of the marine engine equipment; The geometric characteristics, reference parameter characteristics and sensitive index of each region are counted to determine the required grid density of the region, and the three-dimensional geometric model is subjected to grid processing based on the grid density; on the basis of the functional relationship and coupling relationship between the reference parameters and the three-dimensional geometric model, a simulation model of the marine engine equipment is established; According to the uncertain index of the reference parameters, the reference parameters in the simulation model are given a credibility, and the marine engine equipment is simulated and analyzed through the simulation model, so as to realize fault identification and prediction.

2. The method of claim 1, wherein, The reference parameters include one or more of the following: equipment design parameters, mechanical parameters, thermodynamic parameters, fluid mechanics parameters and electrical parameters. The functional relationship and coupling relationship between the reference parameters are determined, which comprises the following steps: Data samples of the reference parameters are collected, simple functional relationships and complex functional relationships are distinguished, for the simple functional relationships, the simple functional relationships are described through physical laws or related theoretical laws, for the complex functional relationships, the initialization of the complex functional relationships is determined through mathematical modeling, and the initialization of the complex functional relationships is optimized through the data samples of the reference parameters; 3. The method of claim 1, wherein, The multi-physical field mechanism and energy and material transfer mechanism related to the marine engine equipment are analyzed, a coupling model is established, the coupling model is a physical model coupling or a numerical simulation coupling, and the coupling model is optimized according to the data samples of the reference parameters. The functional relationship and coupling relationship between the reference parameters are analyzed to calculate the sensitive index and uncertain index of each reference parameter, which comprises the following steps: Effect parameters describing the performance or running state of the marine engine equipment are screened out from the reference parameters, and multiple objective functions between other parameters in the reference parameters and the effect parameters are established; The correlation between each reference parameter and the corresponding effect parameter in each objective function is calculated, the normal value range of each reference parameter is obtained, and the perturbation amount is determined based on the normal value range of the reference parameters and the correlation; In the simulation software, the reference parameters are slightly disturbed in the two-way disturbance through the perturbation amount, the two-way disturbance includes positive disturbance and negative disturbance of the reference parameters, the change rate of the effect parameters and the reference parameters in the objective function is counted, the central difference is obtained as the local sensitive index; For the same objective function, the correlation between different reference parameters is calculated, the corresponding relationship of the strongly correlated reference parameters is screened out, the correlation change with different value ranges in the corresponding relationship of the reference parameters is drawn, and the standard value range of the reference parameters is determined; Latin hypercube sampling or Monte Carlo sampling is adopted to randomly sample in the standard value range of the reference parameters, a plurality of reference parameter combinations are obtained, each reference parameter combination is input into the simulation software, and the size of the effect parameters on the objective function is obtained. The complexity of each objective function is evaluated, the Sobol index order is selected in combination with the complexity of the objective function and the correlation between different reference parameters under the objective function, and the global sensitivity index is determined; The sensitivity index is determined based on the local sensitivity index and the global sensitivity index of each reference parameter; The uncertainty index of each reference parameter is described by a probability distribution.

4. The method of claim 3, wherein, The uncertainty index of each reference parameter is described by a probability distribution, including, A histogram of each reference parameter is drawn, the statistics of each reference parameter are counted on the histogram, the fitting degree test is performed on each reference parameter, the distribution type is determined, the original probability distribution of each parameter is established, and the joint probability distribution under the corresponding relationship of the strongly correlated reference parameters is established, and the uncertainty index of each reference parameter is determined according to the original probability distribution and the joint probability distribution.

5. The method of claim 1, wherein, The three-dimensional geometric model is divided into multiple regions according to the structure and function of the marine engine equipment, including, The three-dimensional geometric model is divided into multiple structural regions according to the different structural components of the marine engine equipment, and each structural region is further divided into regions according to the difference in function.

6. The method of claim 1, wherein, The geometric characteristics of each region, the reference parameter characteristics, and the sensitivity index of the reference parameter are counted to determine the required grid density corresponding to the region, including, The geometric complexity of each type of geometric feature is evaluated, and an evaluation index is generated; The reference parameter categories involved in each region are confirmed according to the function of the marine engine equipment and multiple physical processes, a reference parameter set is constructed, each region corresponds to a reference parameter set, and the physical field characteristics of the reference parameters are counted, the calculation accuracy requirement level is defined based on the evaluation index of the geometric characteristics, the physical field characteristics of the reference parameters, and the sensitivity index of the reference parameters, and a grid density is mapped according to the calculation accuracy requirement level.

7. The method of claim 1, wherein, The reference parameters in the simulation model are given a confidence level according to the uncertainty index of the reference parameters, including, The maximum value, the minimum value, the mode value, and the median value of the uncertainty index of all reference parameters are counted, the distance between the mode value and the maximum value and the minimum value is calculated respectively, the minimum distance of the two distances is taken as the adjacent distance, the median value is adjusted to be close to the maximum value or the minimum value through the adjacent distance, and a standard threshold is obtained; The reference parameters are distinguished as strong confidence parameters and weak confidence parameters through the standard threshold, and two mapping relationships are used respectively to determine the confidence level of the strong confidence parameters and the weak confidence parameters.

8. The method of claim 7, wherein, The simulation model is used to simulate and analyze the marine engine equipment, including, Boundary conditions and initial conditions are set on the simulation model, and the confidence levels of the strong confidence parameters and the weak confidence parameters are fused to identify and predict faults.

9. A thermodynamic coupling-based gas dynamic simulation analysis system, characterized by, including, The first module is used to collect all reference parameters involved in the marine engine equipment, determine the function relationship and coupling relationship between the reference parameters, analyze the function relationship and coupling relationship between the reference parameters, calculate the sensitivity index and uncertainty index of each reference parameter; The second module is used to establish a three-dimensional geometric model of the marine engine equipment, and divide the three-dimensional geometric model into multiple regions according to the structure and function of the marine engine equipment; The third module is configured to count the geometric features, the reference parameter features and the sensitive indexes of the reference parameters of each region to determine the grid density required by the region, perform grid processing on the three-dimensional geometric model based on the grid density, and establish a simulation model of the marine engine equipment based on the function relationship and coupling relationship between the reference parameters and the three-dimensional geometric model; The fourth module is configured to give the reference parameters in the simulation model a credibility according to the uncertainty indexes of the reference parameters, and perform simulation analysis on the marine engine equipment through the simulation model to achieve fault identification and prediction. The reference parameters include one or more of a design parameter of the equipment, a mechanical parameter, a thermodynamic parameter, a fluid mechanics parameter and an electrical parameter.

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