Hydro-generator performance evaluation method and system based on CAE simulation

Abstract

The present invention discloses a method and system for evaluating the performance of a hydro-generator set based on CAE simulation, relating to the technical field of hydro-generators. The method comprises: traversing component parameters of a target hydro-generator set to collect data, obtaining multiple component performance parameters, and formulating multiple component performance optimization targets; constructing a physical dynamic simulation model using CAE simulation technology; setting simulation constraints; performing simulation according to the simulation constraints to obtain a simulation data set; verifying that the simulation data set matches multiple component performance optimization targets, evaluating the component performance of multiple components, and generating multiple component performance evaluation results; generating optimization plans for multiple components based on the multiple component performance evaluation results, and executing the optimization plans to optimize and adjust the target hydro-generator set. This method solves the technical problem of insufficiently comprehensive and accurate evaluation of hydro-generator sets in the prior art, achieving the technical effect of a comprehensive and detailed evaluation of unit performance.

Description

Technical Field

[0001] The present invention relates to the technical field of hydro-generators, and in particular to a method and system for evaluating the performance of a hydro-generator set based on CAE simulation. Background Art

[0002] As global energy demand continues to grow, hydropower, as a clean and renewable form of energy, is playing an increasingly important role in the energy structure. As the core equipment for hydropower generation, the performance of hydroelectric generator sets directly affects the efficiency and stability of the entire power generation system. Therefore, accurately evaluating and optimizing the performance of hydroelectric generator sets is of great significance for improving power generation efficiency, reducing operating costs, and ensuring stable system operation. Traditional performance evaluation methods mainly rely on experimental testing and field observations, which are not only costly and time-consuming, but also limited by environmental conditions and test equipment. They can only provide a rough assessment of the overall performance of the unit, and cannot conduct detailed analysis and optimization of the various components and links within the unit, making it difficult to fully reflect the performance characteristics of the unit. Summary of the Invention

[0003] The embodiments of the present application provide a method and system for evaluating the performance of a hydro-generator set based on CAE simulation, which solves the technical problem in the prior art that the evaluation of a hydro-generator set is not comprehensive and accurate enough.

[0004] In view of the above problems, the embodiments of the present application provide a method and system for evaluating the performance of a hydro-generator set based on CAE simulation.

[0005] A first aspect of an embodiment of the present application provides a method for evaluating the performance of a hydro-generator set based on CAE simulation, the method comprising:

[0006] Traversing component parameters of the target hydro-generator set to collect a plurality of component performance parameters, and formulating a plurality of component performance optimization targets based on the plurality of component performance parameters, wherein the plurality of component performance optimization targets correspond to the plurality of component performance parameters;

[0007] Use CAE simulation technology to build a physical dynamic simulation model of the target hydro-generator unit;

[0008] Setting simulation constraints based on the operating data of the target hydro-generator unit;

[0009] According to the simulation constraints, multiple components in the target hydro-generator set are simulated by using the physical dynamic simulation model to obtain a simulation data set;

[0010] Verifying that the simulation data set matches the multiple component performance optimization objectives, evaluating component performance of the multiple components, and generating multiple component performance evaluation results;

[0011] An optimization scheme for the multiple components is generated according to the performance evaluation results of the multiple components, and the optimization scheme is executed to optimize and adjust the target hydro-generator set.

[0012] A second aspect of an embodiment of the present application provides a hydro-generator performance evaluation system based on CAE simulation, the system comprising:

[0013] a parameter acquisition module, the parameter acquisition module being configured to traverse component parameters of a target hydro-generator set to acquire a plurality of component performance parameters, and to formulate a plurality of component performance optimization targets based on the plurality of component performance parameters, wherein the plurality of component performance optimization targets correspond to the plurality of component performance parameters;

[0014] A model building module, wherein the model building module is used to build a physical dynamic simulation model of the target hydro-generator unit using CAE simulation technology;

[0015] A constraint condition setting module, wherein the constraint condition setting module is used to set simulation constraint conditions based on the operating data of the target hydro-generator set;

[0016] A simulation module, configured to simulate multiple components in a target hydro-generator set using the physical dynamic simulation model according to the simulation constraints to obtain a simulation data set;

[0017] an evaluation module, the evaluation module being configured to verify that the simulation data set matches the plurality of component performance optimization objectives, evaluate component performance of the plurality of components, and generate a plurality of component performance evaluation results;

[0018] An optimization module is used to generate an optimization plan for the multiple components based on the performance evaluation results of the multiple components, and execute the optimization plan to optimize and adjust the target hydro-generator set.

[0019] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0020] The component parameters of a target hydro-turbine generator set are traversed and collected to obtain multiple component performance parameters. Multiple component performance optimization targets are then formulated based on the multiple component performance parameters, wherein the multiple component performance optimization targets correspond to the multiple component performance parameters. A physical dynamic simulation model of the target hydro-turbine generator set is constructed using CAE simulation technology. Simulation constraints are set based on the operating data of the target hydro-turbine generator set. Based on the simulation constraints, multiple components within the target hydro-turbine generator set are simulated using the physical dynamic simulation model to obtain a simulation dataset. The simulation dataset is verified to match the multiple component performance optimization targets, and the component performance of the multiple components is evaluated to generate multiple component performance evaluation results. Based on the multiple component performance evaluation results, optimization plans for the multiple components are generated, and the optimization plans are executed to optimize and adjust the target hydro-turbine generator set. This method solves the technical problem of insufficiently comprehensive and accurate evaluation of hydro-turbine generator sets in the prior art, achieving a comprehensive and detailed evaluation of unit performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A schematic flow chart of a method for evaluating the performance of a hydro-generator set based on CAE simulation provided in an embodiment of the present application;

[0023] Figure 2 Schematic diagram of the structure of the hydro-generator performance evaluation system based on CAE simulation provided in an embodiment of the present application.

[0024] Explanation of the accompanying drawings: parameter acquisition module 11, model construction module 12, constraint condition setting module 13, simulation module 14, evaluation module 15, optimization module 16. DETAILED DESCRIPTION

[0025] The embodiments of the present application solve the technical problem of insufficient comprehensiveness and accuracy in the evaluation of hydro-generator sets in the prior art by providing a method and system for evaluating the performance of hydro-generator sets based on CAE simulation.

[0026] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0027] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0028] Example 1

[0029] like Figure 1 As shown, the embodiment of the present application provides a method for evaluating the performance of a hydro-generator set based on CAE simulation, wherein the method includes:

[0030] Traversing component parameters of the target hydro-generator set to collect a plurality of component performance parameters, and formulating a plurality of component performance optimization targets based on the plurality of component performance parameters, wherein the plurality of component performance optimization targets correspond to the plurality of component performance parameters;

[0031] The goal of traversing and collecting component parameters of the target hydro-turbine generator set is to obtain key performance parameters, covering each key generator set component. These parameters include turbine speed and torque, generator output power and voltage, bearing friction and wear, and blade flow and profile characteristics. These parameters are crucial to the generator set's operation and performance. Based on the collected component performance parameters, multiple component performance optimization targets can be established, each of which corresponds to the performance parameters of each component. For example, increasing turbine speed can boost generator output power, reducing bearing friction to minimize energy loss, and adjusting blade design to optimize water flow and improve turbine efficiency.

[0032] Furthermore, the component parameters of the target hydro-generator set are traversed and collected to obtain a plurality of component performance parameters, and a plurality of component performance optimization targets are formulated according to the plurality of component performance parameters. The method includes:

[0033] Building a component parameter information library based on the component parameters of the target hydro-generator set;

[0034] Performing performance matching based on the component parameter information library to generate multiple component performance parameters;

[0035] performing a performance efficiency analysis on the plurality of component performance parameters to generate a plurality of performance analysis results;

[0036] Performing a maximum performance optimization evaluation based on the multiple performance analysis results to obtain an optimization improvement index;

[0037] The plurality of component performance parameters are traversed and compared according to the optimization improvement index to determine the plurality of component performance optimization targets.

[0038] Based on the component parameters of the target hydro-turbine generator set, a component parameter information library can be constructed, which contains the key parameters of each component and its performance data. By comparing the performance parameters of different components, the correlations and mutual influences between them can be identified. For example, the matching relationship between the rotor and bearings and their impact on the overall performance of the unit can be analyzed. Through performance matching, multiple component performance parameters can be generated. Performance efficiency analysis of the generated multiple component performance parameters is performed to evaluate the performance of each combination. By comparing and analyzing the performance data of different components, multiple performance analysis results can be generated. Based on the performance analysis, a maximum performance optimization evaluation is performed to obtain the optimization improvement index, which is the maximum efficiency improvement percentage. According to the optimization improvement index, multiple component performance parameters are traversed and compared to determine the performance optimization targets of multiple components.

[0039] Use CAE simulation technology to build a physical dynamic simulation model of the target hydro-generator unit;

[0040] CAE simulation technology is a method for simulating and analyzing product performance and design on a computer. For complex systems like hydro-generators, it provides an effective tool for predicting and optimizing their performance. CAE simulation software can be used to construct a physical dynamic simulation model of a hydro-generator.

[0041] Furthermore, CAE simulation technology is used to construct a physical dynamic simulation model of the target hydro-generator set, and the method includes:

[0042] Retrieve the structural dimension information set of the target hydro-generator unit and construct a three-dimensional model of the unit;

[0043] Meshing the three-dimensional model of the unit based on the component attribute map to generate a plurality of grid space data, wherein each grid space data in the plurality of grid space data includes physical attributes of a corresponding component;

[0044] Based on the historical operating data of the target hydro-generator set, activating the plurality of grid space data in sequence to perform dynamic simulation and obtain a plurality of dynamic simulation results;

[0045] The precision of the plurality of grid space data is adjusted based on the plurality of dynamic simulation results, and a plurality of grid space adjustment results are generated to output the physical dynamic simulation model.

[0046] The target hydro-turbine generator unit's structural dimension information set is retrieved, including the unit's main component dimensions, assembly relationships, and overall structural layout. A 3D model of the unit is constructed using this structural dimension information set. The 3D model reflects the unit's true geometry and the relative positional relationships between its components. The 3D model is meshed based on a component attribute map. A component attribute map is a tool that maps component physical properties onto the 3D model, determining the component physical properties contained in each grid space. Through meshing, the 3D model is divided into multiple grid spaces, each containing the corresponding component's physical properties, such as material characteristics, density, and thermal conductivity. After acquiring these multiple grid spaces, dynamic simulation is performed on these grid spaces using the target hydro-turbine generator unit's historical operating data. This historical operating data includes the unit's operating parameters, load variations, and environmental conditions under different operating conditions. By activating these grid spaces and simulating these historical operating conditions, multiple dynamic simulation results are obtained, reflecting the unit's performance under different operating conditions. Based on these dynamic simulation results, the accuracy of the multiple grid spaces is adjusted. By comparing and analyzing the differences between simulation results and actual operational data, inaccuracies in the simulation model can be identified and the accuracy of the grid space data adjusted accordingly. Through continuous adjustment and optimization, multiple grid space adjustment results can be generated and output to the physical dynamic simulation model.

[0047] Setting simulation constraints based on the operating data of the target hydro-generator unit;

[0048] Simulation constraints refer to simulation boundaries. Setting simulation constraints based on the operating data of the target hydro-generator set can ensure that the simulation model is simulated under real working conditions and improve the accuracy and reliability of the simulation results.

[0049] Furthermore, the simulation constraint conditions are set based on the operating data of the target hydro-generator unit, and the method includes:

[0050] Real-time monitoring of water level changes of target hydro-generator units and preset water flow velocity ranges;

[0051] performing flow analysis based on the water flow velocity interval to determine fluid dynamics constraint information;

[0052] Collect and obtain operating vibration data and operating noise data according to the material properties of the target hydro-generator unit;

[0053] limiting a safe range of structural displacement according to the operating vibration data and the operating noise data, and determining structural mechanics constraint information;

[0054] Extracting operating environment information of the target hydro-generator set, wherein the operating environment information includes operating temperature data, operating humidity data, and operating air pressure data;

[0055] determining operating environment constraint information based on the operating temperature data, the operating humidity data, and the operating air pressure data;

[0056] The simulation constraint conditions are set by integrating the fluid dynamics constraint information, the structural mechanics constraint information, and the operating environment constraint information.

[0057] Water level sensors and flow rate monitoring equipment are used to collect real-time water level and flow rate data from the target hydro-turbine generator unit. Water level sensors accurately measure water level changes, while flow rate monitoring equipment provides dynamic information on water flow rate. Based on this collected flow rate data, a reasonable flow rate range is preset. This range must take into account factors such as the hydro-turbine generator unit's design requirements, operating conditions, and safety constraints. By comparing and analyzing historical data, industry standards, and unit performance curves, a flow rate range that meets the unit's operational requirements while ensuring safety can be determined. After determining the flow rate range, flow analysis is performed to obtain information on fluid dynamic constraints. Flow analysis primarily evaluates the impact of water flow on unit performance by calculating and analyzing parameters such as the flow state, velocity distribution, and pressure variations within the unit. By analyzing flow data, the optimal operating conditions for the unit at different flow rates can be determined, as well as potential fluid dynamic issues such as vortices and scour. Simultaneously, based on the material properties of the target hydro-turbine generator unit, operational vibration and noise data are collected. These data reflect the unit's dynamic performance and structural condition during operation. By analyzing vibration and noise data, it is possible to assess the unit's structural stability, operational smoothness, and potential faults or hidden dangers. Furthermore, it is necessary to extract the target hydro-turbine generator unit's operating environment information, including operating temperature, humidity, and air pressure data. By analyzing this operating environment data, it is possible to understand the unit's performance under different environmental conditions and potential environmental adaptability issues, thereby determining operating environment constraints. By integrating the fluid dynamics constraint information, structural mechanics constraint information, and operating environment constraint information, comprehensive simulation constraint conditions are set. These constraints will guide the construction and operation of the simulation model, ensuring that the simulation results truly reflect the actual operating conditions and performance characteristics of the target hydro-turbine generator unit.

[0058] According to the simulation constraints, multiple components in the target hydro-generator set are simulated by using the physical dynamic simulation model to obtain a simulation data set;

[0059] According to the simulation constraints, multiple components in the target hydro-generator set are simulated through the physical dynamic simulation model, and the simulation data set is obtained.

[0060] Furthermore, according to the simulation constraints, multiple components in the target hydro-generator set are simulated by the physical dynamic simulation model to obtain a simulation data set, and the method includes:

[0061] Setting a simulation time step based on the simulation constraint conditions and obtaining initial simulation parameters;

[0062] Calculating mutual influence coefficients among the plurality of components in the target hydro-generator set;

[0063] Based on the mutual influence coefficient, the physical dynamic simulation model is started to simulate the initial simulation parameters according to the simulation time step, and the simulation operation data is recorded in real time to obtain the simulation parameter change trend;

[0064] The simulation data of the plurality of components are determined based on the simulation parameter change trends to generate the simulation data set.

[0065] Based on the simulation constraints, the actual operating characteristics of the target hydro-turbine generator unit, and the required simulation accuracy, a reasonable simulation time step is set. The time step should be selected to capture important dynamic changes during unit operation without losing critical information due to excessively large step sizes. Initial simulation parameters, including the unit's initial speed, flow rate, water level, and temperature, are determined based on the simulation constraints, the unit's design parameters, and historical operating data. Complex interactions and influences exist between multiple components within the target hydro-turbine generator unit. To more accurately simulate these influences, the mutual influence coefficients between components can be calculated by analyzing the unit's structure, operating principle, and historical operating data. These coefficients quantify the inter-component relationships. Based on the set simulation time step and initial simulation parameters, the physical dynamic simulation model is started and run. During the simulation, simulation data, including the operating status and performance parameters of each component, is recorded in real time. Simulation parameter trends are recorded as the simulation time progresses. Based on these trends, simulation data for multiple components, including the operating status and performance parameters of each component at different time steps, is determined and organized into simulation datasets.

[0066] Verifying that the simulation data set matches the multiple component performance optimization objectives, evaluating component performance of the multiple components, and generating multiple component performance evaluation results;

[0067] The optimization goal is achieved by verifying whether the simulation dataset matches the performance optimization targets of multiple components. The performance of multiple components of the target hydro-generator unit is evaluated, including analyzing key indicators such as the operating status, efficiency, and stability of each component, and generating multiple component performance evaluation results.

[0068] Furthermore, verifying that the simulation data set matches the multiple component performance optimization targets, evaluating the component performance of the multiple components, and generating multiple component performance evaluation results, the method includes:

[0069] extracting first component simulation data based on the simulation data set, and matching the first component simulation data with the plurality of component performance optimization targets to obtain a first component performance optimization target;

[0070] Verifying whether the first component simulation data meets the first component performance optimization goal;

[0071] If the verification is satisfied, performing a fluid mechanics evaluation on the component performance of the first component to generate a first component fluid evaluation result, performing a mechanical strength evaluation on the component performance of the first component to generate a first component mechanical strength evaluation result, and performing an operating environment evaluation on the component performance of the first component to generate a first component operating environment evaluation result;

[0072] The first component fluid evaluation result, the first component mechanical strength evaluation result, and the first component operating environment evaluation result are added to the plurality of component performance evaluation results.

[0073] Simulation data for a first component, such as a runner, guide vane, or other key component, is extracted from the simulation dataset. The extracted simulation data for the first component is matched against multiple pre-defined component performance optimization targets to obtain the first component performance optimization targets. The extracted simulation data is compared with actual operating data, industry standards, or design requirements to verify whether the extracted simulation data for the first component meets the first component performance optimization targets. If the performance optimization targets are met, the performance of the first component is further evaluated in multiple dimensions. A fluid dynamics assessment analyzes the performance of the first component under fluid loads, such as flow field distribution, pressure loss, and energy conversion efficiency, generating a first component fluid dynamics assessment result. A mechanical strength assessment evaluates the strength and stability of the first component under mechanical loads, including stress analysis and fatigue life prediction. For key mechanical components such as bearings, gears, and rotors, finite element analysis (FEA) or other structural mechanics analysis tools can be used to assess stress, strain, and fatigue life, generating a first component mechanical strength assessment result. An operating environment assessment evaluates the adaptability of the first component to the operating environment, such as the impact of factors such as temperature, humidity, and corrosion on component performance, generating a first component operating environment assessment result. The fluid evaluation result, mechanical strength evaluation result, and operating environment evaluation result of the first component are added to the multiple component performance evaluation result sets to form a complete data set including the multiple component performance evaluation results.

[0074] Furthermore, the method further comprises:

[0075] If it is verified that the simulation data of the first component does not meet the performance optimization target of the first component, an abnormal label is generated to identify the first component and an identification result is generated;

[0076] performing a numerical addition operation on the execution priority of the first component according to the identification result;

[0077] Sorting the plurality of components in descending order according to their execution priorities to determine an execution sequence;

[0078] Performing performance screening on the multiple components of the target hydro-generator set based on the execution sequence to obtain multiple performance screening results;

[0079] The plurality of performance screening results are added to the plurality of component performance evaluation results.

[0080] If verification reveals that the simulation data for the first component does not meet the performance optimization target for the first component, an exception tag is generated to indicate that the performance of the first component does not meet expectations, i.e., the identification result. Based on the identification result, a numerical value is added to the execution priority of the first component. The execution priority indicates that since the performance of the first component no longer meets the target, it should be prioritized for optimization in subsequent operations. Therefore, the higher the priority, the higher the execution priority. Increasing the execution priority ensures that the first component occupies a higher position in the processing sequence. The execution priorities of multiple components are sorted in descending order to determine a clear execution sequence. Based on the determined execution sequence, performance screening is performed on multiple components of the target hydro-turbine generator set to determine whether their performance is consistent with the simulation data in the simulation dataset. If consistent, the simulation data is accurate and the component performance requires optimization. If inconsistent, the actual performance is screened to determine if it is sufficient. If so, the simulation dataset should be updated and the priority should be lowered. The performance screening results of the multiple components are added to the existing component performance evaluation results.

[0081] An optimization scheme for the multiple components is generated according to the performance evaluation results of the multiple components, and the optimization scheme is executed to optimize and adjust the target hydro-generator set.

[0082] Based on the performance evaluation results of multiple components, optimization schemes for these components can be further generated, and actual optimization adjustments can be made to the target hydro-generator set accordingly.

[0083] In summary, the embodiments of the present application have at least the following technical effects:

[0084] The component parameters of a target hydro-turbine generator set are traversed and collected to obtain multiple component performance parameters. Multiple component performance optimization targets are then formulated based on the multiple component performance parameters, wherein the multiple component performance optimization targets correspond to the multiple component performance parameters. A physical dynamic simulation model of the target hydro-turbine generator set is constructed using CAE simulation technology. Simulation constraints are set based on the operating data of the target hydro-turbine generator set. Based on the simulation constraints, multiple components within the target hydro-turbine generator set are simulated using the physical dynamic simulation model to obtain a simulation dataset. The simulation dataset is verified to match the multiple component performance optimization targets, and the component performance of the multiple components is evaluated to generate multiple component performance evaluation results. Based on the multiple component performance evaluation results, optimization plans for the multiple components are generated, and the optimization plans are executed to optimize and adjust the target hydro-turbine generator set. This method solves the technical problem of insufficiently comprehensive and accurate evaluation of hydro-turbine generator sets in the prior art, achieving a comprehensive and detailed evaluation of unit performance.

[0085] Example 2

[0086] Based on the same inventive concept as the hydro-generator performance evaluation method based on CAE simulation in the above embodiment, Figure 2 As shown, the present application provides a hydro-generator performance evaluation system based on CAE simulation. The system and method embodiments in the present application are based on the same inventive concept. The system includes:

[0087] A parameter acquisition module 11 is configured to traverse component parameters of a target hydro-generator set to acquire a plurality of component performance parameters, and formulate a plurality of component performance optimization targets based on the plurality of component performance parameters, wherein the plurality of component performance optimization targets correspond to the plurality of component performance parameters;

[0088] A model building module 12, wherein the model building module 12 is used to build a physical dynamic simulation model of the target hydro-generator set using CAE simulation technology;

[0089] A constraint condition setting module 13, wherein the constraint condition setting module 13 is used to set simulation constraint conditions based on the operating data of the target hydro-generator set;

[0090] A simulation module 14 is configured to simulate multiple components in a target hydro-generator set using the physical dynamic simulation model according to the simulation constraints to obtain a simulation data set;

[0091] An evaluation module 15 is configured to verify that the simulation data set matches the plurality of component performance optimization objectives, evaluate component performance of the plurality of components, and generate a plurality of component performance evaluation results;

[0092] The optimization module 16 is used to generate an optimization scheme for the multiple components according to the performance evaluation results of the multiple components, and execute the optimization scheme to optimize and adjust the target hydro-generator set.

[0093] Furthermore, the parameter acquisition module 11 is used to perform the following method:

[0094] Building a component parameter information library based on the component parameters of the target hydro-generator set;

[0095] Performing performance matching based on the component parameter information library to generate multiple component performance parameters;

[0096] performing a performance efficiency analysis on the plurality of component performance parameters to generate a plurality of performance analysis results;

[0097] Performing a maximum performance optimization evaluation based on the multiple performance analysis results to obtain an optimization improvement index;

[0098] The plurality of component performance parameters are traversed and compared according to the optimization improvement index to determine the plurality of component performance optimization targets.

[0099] Furthermore, the model building module 12 is used to perform the following method:

[0100] Retrieve the structural dimension information set of the target hydro-generator unit and construct a three-dimensional model of the unit;

[0101] Meshing the three-dimensional model of the unit based on the component attribute map to generate a plurality of grid space data, wherein each grid space data in the plurality of grid space data includes physical attributes of a corresponding component;

[0102] Based on the historical operating data of the target hydro-generator set, activating the plurality of grid space data in sequence to perform dynamic simulation and obtain a plurality of dynamic simulation results;

[0103] The precision of the plurality of grid space data is adjusted based on the plurality of dynamic simulation results, and a plurality of grid space adjustment results are generated to output the physical dynamic simulation model.

[0104] Furthermore, the constraint condition setting module 13 is used to execute the following method:

[0105] Real-time monitoring of water level changes of target hydro-generator units and preset water flow velocity ranges;

[0106] performing flow analysis based on the water flow velocity interval to determine fluid dynamics constraint information;

[0107] Collect and obtain operating vibration data and operating noise data according to the material properties of the target hydro-generator unit;

[0108] limiting a safe range of structural displacement according to the operating vibration data and the operating noise data, and determining structural mechanics constraint information;

[0109] Extracting operating environment information of the target hydro-generator set, wherein the operating environment information includes operating temperature data, operating humidity data, and operating air pressure data;

[0110] determining operating environment constraint information based on the operating temperature data, the operating humidity data, and the operating air pressure data;

[0111] The simulation constraint conditions are set by integrating the fluid dynamics constraint information, the structural mechanics constraint information, and the operating environment constraint information.

[0112] Furthermore, the simulation module 14 is used to perform the following method:

[0113] Setting a simulation time step based on the simulation constraint conditions and obtaining initial simulation parameters;

[0114] Calculating mutual influence coefficients among the plurality of components in the target hydro-generator set;

[0115] Based on the mutual influence coefficient, the physical dynamic simulation model is started to simulate the initial simulation parameters according to the simulation time step, and the simulation operation data is recorded in real time to obtain the simulation parameter change trend;

[0116] The simulation data of the plurality of components are determined based on the simulation parameter change trends to generate the simulation data set.

[0117] Furthermore, the evaluation module 15 is configured to perform the following method:

[0118] extracting first component simulation data based on the simulation data set, and matching the first component simulation data with the plurality of component performance optimization targets to obtain a first component performance optimization target;

[0119] Verifying whether the first component simulation data meets the first component performance optimization goal;

[0120] If the verification is satisfied, performing a fluid mechanics evaluation on the component performance of the first component to generate a first component fluid evaluation result, performing a mechanical strength evaluation on the component performance of the first component to generate a first component mechanical strength evaluation result, and performing an operating environment evaluation on the component performance of the first component to generate a first component operating environment evaluation result;

[0121] The first component fluid evaluation result, the first component mechanical strength evaluation result, and the first component operating environment evaluation result are added to the plurality of component performance evaluation results.

[0122] Furthermore, the evaluation module 15 is configured to perform the following method:

[0123] If it is verified that the simulation data of the first component does not meet the performance optimization target of the first component, an abnormal label is generated to identify the first component and an identification result is generated;

[0124] performing a numerical addition operation on the execution priority of the first component according to the identification result;

[0125] Sorting the plurality of components in descending order according to their execution priorities to determine an execution sequence;

[0126] Performing performance screening on the multiple components of the target hydro-generator set based on the execution sequence to obtain multiple performance screening results;

[0127] The plurality of performance screening results are added to the plurality of component performance evaluation results.

[0128] It should be noted that the above-mentioned order of the embodiments of the present application is for descriptive purposes only and does not represent the superiority or inferiority of the embodiments. The above description is of specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0129] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0130] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A hydro-generator performance evaluation method based on CAE simulation is characterized by: The method comprises: Traversing component parameters of the target hydro-generator set to collect a plurality of component performance parameters, and formulating a plurality of component performance optimization targets based on the plurality of component performance parameters, wherein the plurality of component performance optimization targets correspond to the plurality of component performance parameters; Use CAE simulation technology to build a physical dynamic simulation model of the target hydro-generator unit; Setting simulation constraints based on the operating data of the target hydro-generator unit; According to the simulation constraints, multiple components in the target hydro-generator set are simulated by using the physical dynamic simulation model to obtain a simulation data set; Verifying that the simulation data set matches the multiple component performance optimization objectives, evaluating component performance of the multiple components, and generating multiple component performance evaluation results; generating an optimization scheme for the plurality of components according to the performance evaluation results of the plurality of components, and executing the optimization scheme to optimize and adjust the target hydro-generator set; According to the simulation constraints, multiple components in the target hydro-generator set are simulated using the physical dynamic simulation model to obtain a simulation data set, the method comprising: Setting a simulation time step based on the simulation constraint conditions and obtaining initial simulation parameters; Calculating mutual influence coefficients among the plurality of components in the target hydro-generator set; Based on the mutual influence coefficient, the physical dynamic simulation model is started to simulate the initial simulation parameters according to the simulation time step, and the simulation operation data is recorded in real time to obtain the simulation parameter change trend; Determining simulation data of the plurality of components based on the simulation parameter change trend, and generating the simulation data set; The method comprises: traversing component parameters of the target hydro-generator set to collect a plurality of component performance parameters, and formulating a plurality of component performance optimization targets according to the plurality of component performance parameters. Building a component parameter information library based on the component parameters of the target hydro-generator set; Performing performance matching based on the component parameter information library to generate multiple component performance parameters; performing a performance efficiency analysis on the plurality of component performance parameters to generate a plurality of performance analysis results; Performing a maximum performance optimization evaluation based on the multiple performance analysis results to obtain an optimization improvement index; Traversing and comparing the performance parameters of the multiple components according to the optimization improvement index to determine the performance optimization targets of the multiple components; The method of using CAE simulation technology to construct a physical dynamic simulation model of the target hydro-generator set includes: Retrieve the structural dimension information set of the target hydro-generator unit and construct a three-dimensional model of the unit; Meshing the three-dimensional model of the unit based on the component attribute map to generate a plurality of grid space data, wherein each grid space data in the plurality of grid space data includes physical attributes of a corresponding component; Based on the historical operating data of the target hydro-generator set, activating the plurality of grid space data in sequence to perform dynamic simulation and obtain a plurality of dynamic simulation results; Adjusting the precision of the plurality of grid space data based on the plurality of dynamic simulation results, generating a plurality of grid space adjustment results and outputting the physical dynamic simulation model; The method for setting simulation constraints based on the operating data of the target hydro-generator set includes: Real-time monitoring of water level changes of target hydro-generator units and preset water flow velocity ranges; performing flow analysis based on the water flow velocity interval to determine fluid dynamics constraint information; Collect and obtain operating vibration data and operating noise data according to the material properties of the target hydro-generator unit; limiting a safe range of structural displacement according to the operating vibration data and the operating noise data, and determining structural mechanics constraint information; Extracting operating environment information of the target hydro-generator set, wherein the operating environment information includes operating temperature data, operating humidity data, and operating air pressure data; determining operating environment constraint information based on the operating temperature data, the operating humidity data, and the operating air pressure data; The simulation constraint conditions are set by integrating the fluid dynamics constraint information, the structural mechanics constraint information, and the operating environment constraint information.

2. The method according to claim 1, wherein Verifying that the simulation data set matches the multiple component performance optimization targets, evaluating component performance of the multiple components, and generating multiple component performance evaluation results, the method includes: extracting first component simulation data based on the simulation data set, and matching the first component simulation data with the plurality of component performance optimization targets to obtain a first component performance optimization target; Verifying whether the first component simulation data meets the first component performance optimization goal; If the verification is satisfied, performing a fluid mechanics evaluation on the component performance of the first component to generate a first component fluid evaluation result, performing a mechanical strength evaluation on the component performance of the first component to generate a first component mechanical strength evaluation result, and performing an operating environment evaluation on the component performance of the first component to generate a first component operating environment evaluation result; The first component fluid evaluation result, the first component mechanical strength evaluation result, and the first component operating environment evaluation result are added to the plurality of component performance evaluation results.

3. The method according to claim 2, wherein Methods include: If it is verified that the simulation data of the first component does not meet the performance optimization target of the first component, an abnormal label is generated to identify the first component and an identification result is generated; performing a numerical addition operation on the execution priority of the first component according to the identification result; Sorting the plurality of components in descending order according to their execution priorities to determine an execution sequence; Performing performance screening on the multiple components of the target hydro-generator set based on the execution sequence to obtain multiple performance screening results; The plurality of performance screening results are added to the plurality of component performance evaluation results.

4. The hydro-generator performance evaluation system based on CAE simulation is characterized by: A system for implementing the CAE simulation-based hydro-generator performance evaluation method according to any one of claims 1 to 3, comprising: a parameter acquisition module, the parameter acquisition module being configured to traverse component parameters of a target hydro-generator set to acquire a plurality of component performance parameters, and to formulate a plurality of component performance optimization targets based on the plurality of component performance parameters, wherein the plurality of component performance optimization targets correspond to the plurality of component performance parameters; A model building module, wherein the model building module is used to build a physical dynamic simulation model of the target hydro-generator unit using CAE simulation technology; A constraint condition setting module, wherein the constraint condition setting module is used to set simulation constraint conditions based on the operating data of the target hydro-generator set; A simulation module, configured to simulate multiple components in a target hydro-generator set using the physical dynamic simulation model according to the simulation constraints to obtain a simulation data set; an evaluation module, the evaluation module being configured to verify that the simulation data set matches the plurality of component performance optimization objectives, evaluate component performance of the plurality of components, and generate a plurality of component performance evaluation results; An optimization module is used to generate an optimization plan for the multiple components based on the performance evaluation results of the multiple components, and execute the optimization plan to optimize and adjust the target hydro-generator set.

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