Hydropower station runner pressure pulsation and dynamic stress collaborative analysis method and system

Abstract

The invention relates to a hydropower station runner pressure pulsation and dynamic stress collaborative analysis method, which realizes accurate extraction of actual point group operation conditions of a unit by constructing a water head-output-time coupled operation condition model, accurately calculates the rigidity and strength of a runner through a one-way fluid-solid coupling method, positions a stress concentration area and a maximum stress point, and realizes collaborative analysis of the runner pressure pulsation and dynamic stress. Furthermore, a pressure load curve is generated through the hydrodynamic pressure monitoring data of the positioning area and is fed back to the structure model for transient dynamic calculation, collaborative analysis of flow field pressure pulsation and structure dynamic response is achieved, and the flow field pressure pulsation and structure dynamic response can be effectively improved on the premise of reducing resource consumption. The dynamic stress time sequence data of the key position of the runner under the complex working condition are obtained in a high-fidelity mode, and reliable data support is provided for fatigue life evaluation and structure optimization of the runner.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of hydroelectric power generation, and in particular, to a method and system for analyzing pressure pulsation and dynamic stress of a runner of a hydroelectric power station, a computer device, and a computer readable storage medium. BACKGROUND

[0002] The runner of a hydro-turbine unit is a core power component of a hydroelectric power station, and its operation stability is directly related to the safety and service life of the unit. In actual operation, the runner is subjected to complex hydraulic loads for a long time, and in particular, the alternating stress caused by water flow pressure pulsation is the main reason for the generation of fatigue cracks and even structural failure of the runner.

[0003] In related technologies, the mechanical analysis of the runner of a hydro-turbine unit is usually based on a design working condition point or a few steady-state working conditions. The traditional analysis method often assumes that the flow field is steady, or only a simplified pressure distribution is loaded onto the structure model for statics calculation. However, the actual operation environment of a hydroelectric power station is extremely complex, and the unit often needs to operate under non-design working conditions (for example, low load, overload, or large water head variation), and frequently experiences transition processes such as start-stop and load adjustment. Under these complex working conditions, the pressure pulsation characteristics of different regions of the runner blade are quite different, and have strong unsteadiness and randomness.

[0004] The current method mainly has the following defects: first, the working conditions are not fully covered, and it is difficult to reflect the true stress state of the unit in the full working condition range of “water head-power output”; second, the load is not accurately applied, and the dynamic changes of fluid pressure pulsation in the time dimension are often ignored, resulting in the inability to accurately capture the structural dynamic response caused by hydraulic excitation; third, the key position is not accurately positioned, and there is no step of accurately identifying the stress concentration area through full-flow passage fluid-structure coupling analysis, resulting in lack of pertinence in monitoring and analysis.

[0005] Therefore, there is an urgent need for a method that can consider the full working condition operation characteristics, accurately locate the key area, and perform transient dynamics analysis, to accurately obtain the dynamic stress time series data of the runner in actual operation, and provide accurate data support for crack initiation prediction of the runner. SUMMARY

[0006] Embodiments of the present application provide a method and system for analyzing pressure pulsation and dynamic stress of a runner of a hydroelectric power station, a computer device, and a computer readable storage medium, to at least solve the problem of excessive resource consumption in related art methods for analyzing pressure pulsation and dynamic stress of a runner of a hydroelectric power station.

[0007] In a first aspect, embodiments of the present application provide a method for analyzing pressure pulsation and dynamic stress of a runner of a hydroelectric power station, the method comprising: The flow field simulation data of the turbine runner under point group operation condition is mapped to the runner structural model, and the runner stiffness is calculated by the one-way fluid-structure coupling method to determine the target position of the runner. The target position includes: stress concentration area and the position of maximum stress point. Based on the steady flow field simulation data of the turbine unit under point group operating conditions, pressure pulsation calculation is performed on the turbine unit, and during the pressure pulsation calculation, dynamic water pressure detection data corresponding to the target position is obtained, and pressure load curves under the operating conditions of each point group of water are generated according to the dynamic water pressure detection data. The hydrodynamic pressure load curves of each point group under operating conditions are input into the impeller structure model for transient dynamic calculation to obtain the dynamic stress time series data of the target location.

[0008] In some embodiments, before mapping the flow field simulation data of the impeller under point group operation conditions to the impeller structure model, the method further includes: Based on the historical operating data of the turbine unit, a turbine unit operating condition model coupled with head, output and time is constructed, and point group operating conditions are extracted from the turbine unit operating condition model. A three-dimensional model of the entire flow channel of the turbine unit is constructed. Based on the three-dimensional model of the entire flow channel and the operating conditions of the point group, a steady flow field simulation calculation of the entire flow channel is performed to obtain the flow field simulation data.

[0009] In some embodiments, constructing a head-output-time coupled turbine unit operating condition model includes: Based on the distribution characteristics of the historical operating data, the normal operating head interval and the abnormal operating head interval are divided, and the normal operating head interval is further subdivided into segments. Based on the division of the head interval, the output interval of the turbine unit is divided simultaneously; Based on the division results of the head interval, the division results of the output interval, and the running time corresponding to each division result, the operating condition model of the turbine unit is constructed.

[0010] In some embodiments, extracting point group operating conditions from the turbine unit operating condition model includes: Based on the turbine unit operating condition model, the data distribution characteristics of each operating condition interval are extracted; Based on the data distribution characteristics, the data-intensive core area is obtained; Within the data-intensive core area, typical operating points for each operating condition range are selected, and these typical operating points are integrated to obtain the point group operating conditions.

[0011] In some embodiments, calculating the runner stiffness to determine the target position of the runner using a one-way fluid-structure interaction method includes: Obtain the fluid pressure load in the flow field simulation data under the operating conditions of each point group; The fluid pressure load is transferred to the impeller structure model through the coupling interface. After applying the centrifugal force and gravity load corresponding to the point group operation condition to the impeller structure model, the statics are solved by the structural mechanics solver to obtain the stress cloud diagram and displacement distribution diagram of the impeller. Based on the stress cloud map and displacement distribution map, the region with the largest change in stress gradient is identified as the stress concentration region, and the node with the highest equivalent stress value is identified as the location of maximum stress. The stress concentration region and the location of maximum stress are taken as the target location.

[0012] In some embodiments, obtaining the dynamic hydraulic pressure detection data corresponding to the target location includes: Based on the target location, a virtual monitoring probe is set at the corresponding spatial coordinates of the full flow channel model of the rotor; Using the flow field simulation data under the operating conditions of the point group as the initial value, an unsteady flow field calculation is performed using a transient turbulence model, and the data sequence of pressure fluctuations at the virtual monitoring probe over time is recorded in real time. The data sequence is processed to generate hydrodynamic pressure load curves containing time-domain pulsation characteristics under the operating conditions of each point group.

[0013] In some embodiments, inputting the hydrodynamic pressure load curves under the various point group operating conditions into the runner structure model for transient dynamic calculations includes: The dynamic water pressure load curves under the operating conditions of each point group are applied to the impeller structure model, and the centrifugal force load and static load at the corresponding speed are superimposed to establish the impeller dynamic stress calculation model. The transient dynamic structure algorithm is used to calculate the dynamic stress model of the impeller, and the dynamic stress time series data of the target position under the point group operation condition is obtained.

[0014] In some embodiments, the method further includes: Based on the switching and start-up / shutdown conditions of the turbine runner, and according to the time constraints of the condition transition and the standard time procedures for unit start-up and shutdown, a dynamic load time series is constructed. A dynamic stress calculation model for the turbine runner during the transition process is established by using the dynamic load time series, the transient hydraulic loads under the switching and start-up / shutdown conditions, and the structural inertial loads generated by the speed change. The transient dynamic structure algorithm is used to calculate the dynamic stress of the impeller during the transition process, and the dynamic stress time series data of the target position during the transition process are obtained.

[0015] Secondly, embodiments of this application provide a collaborative analysis system for pressure pulsation of a hydropower station runner. The system includes: a determination module, an analysis module, and a calculation module, wherein... The determining module is used to map the flow field simulation data of the turbine runner under point group operation conditions to the runner structural model, and calculate the runner stiffness and strength through a one-way fluid-structure coupling method to determine the target position of the runner, wherein the target position includes: stress concentration area and the position of maximum stress point; The analysis module is used to perform pressure pulsation calculation on the turbine unit based on the steady flow field simulation data of the turbine unit under point group operating conditions, and to obtain the dynamic water pressure detection data corresponding to the target position during the pressure pulsation calculation process, and to generate pressure load curves under the operating conditions of each point group of water based on the dynamic water pressure detection data. The calculation module is used to input the hydrodynamic pressure load curves of each point group under the operating conditions into the impeller structure model for transient dynamic calculation, and obtain the dynamic stress time series data of the target position.

[0016] Thirdly, embodiments of this application provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect above.

[0017] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect above.

[0018] Compared to related technologies, the hydropower station runner pressure pulsation collaborative analysis method provided in this application embodiment achieves accurate extraction of the actual point group operation conditions of the unit by constructing a head-output-time coupled operating condition model. It also accurately calculates the runner stiffness and strength, locates stress concentration areas and maximum stress points through a one-way fluid-structure interaction method. Furthermore, by generating pressure load curves from the dynamic water pressure monitoring data of the located areas and feeding them back to the structural model for transient dynamic calculation, it achieves collaborative analysis of flow field pressure pulsation and structural dynamic response. This method can obtain high-fidelity dynamic stress time series data of key locations of the runner under complex operating conditions while reducing resource consumption, providing reliable data support for the fatigue life assessment and structural optimization of the runner. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of the hydropower station turbine pressure pulsation collaborative analysis method according to an embodiment of this application; Figure 2 This is a schematic diagram of the unit operation condition zoning system constructed in the embodiments of this application; Figure 3 This is a schematic diagram of the streamlines from the numerical simulation calculation of the entire flow channel of the turbine unit in the embodiments of this application; Figure 4 This is a stress cloud diagram and displacement distribution diagram of the wheel stiffness calculation in the embodiments of this application; Figure 5 This is a schematic diagram of the hydrodynamic pressure load curve generated in the embodiments of this application; Figure 6 This is a structural block diagram of a hydropower station turbine runner pressure pulsation collaborative analysis system according to an embodiment of this application; Figure 7 This is a schematic diagram of the internal structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0021] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0022] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0023] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0024] This embodiment provides a collaborative analysis method for pressure pulsation in hydropower station runners. This method aims to address the problems of incomplete coverage of runner stress analysis conditions and insufficient consideration of dynamic characteristics in existing technologies. By combining fluid-structure interaction and transient dynamics, it achieves accurate calculation of dynamic stress data for key parts of the runner.

[0025] Figure 1 This is a flowchart of a hydropower station turbine pressure pulsation collaborative analysis method according to an embodiment of this application. Figure 1 As shown, the method includes the following steps: S101, based on the historical operating data of the turbine unit, constructs a turbine unit operating condition model that couples head, output, and time, and extracts point group operating conditions from the turbine unit operating condition model.

[0026] Specifically, constructing a head-output-time coupled turbine unit operating condition model includes the following sub-steps: Data Acquisition and Cleaning: Historical operating parameters of the generating units over long periods are collected through the power plant's Supervisory Control and Data Acquisition (SCADA) system or online monitoring devices. These parameters primarily include head parameters (upstream water level minus downstream water level, considering head loss), output parameters (generator active power), and flow parameters. The collected data is cleaned to remove outliers caused by sensor malfunctions or transmission errors (e.g., negative output values ​​or noise exceeding 120% of the rated value).

[0027] This step effectively removes abnormal interference caused by sensor malfunctions by denoising and standardizing historical data, ensuring the authenticity and high fidelity of the input data for subsequent modeling.

[0028] Furthermore, by combining the distribution characteristics of historical data (such as frequency histograms and probability density curves), the "normal operating head interval" and the "unusual operating head interval" are first divided.

[0029] For regularly operating head ranges (e.g., areas with data concentration exceeding 80%), the data is further subdivided (e.g., every 2 meters of head is a sub-range); for non-operating ranges, the segmentation step size can be appropriately relaxed. Based on the head range division results, the unit output range is simultaneously divided (e.g., segmented with a step size of 10% of rated output). By distinguishing between regularly operating and non-operating ranges and performing differentiated subdivisions, this step ensures both extremely high resolution for high-frequency operating conditions and coverage for low-frequency operating conditions, achieving an optimal balance between computational accuracy and computational cost.

[0030] The historical data on the runtime within each "head-output" two-dimensional grid is statistically analyzed, and a model containing three-dimensional information (head, output, and cumulative duration) is constructed. Based on this model, the operating conditions of the point group can be quickly obtained.

[0031] This step discretizes the continuous and complex operation process into a highly representative set of point-based operating conditions. By extracting the data centroid, it ensures that the calculated operating conditions cover the vast majority of the actual operating time. This modeling approach accurately captures the temporal distribution characteristics of the unit, avoiding the omission of key stress scenarios.

[0032] Step S101 overcomes the limitations of traditional methods that rely solely on design or theoretical operating conditions by constructing a three-dimensional coupled model of "head-output-time". Utilizing data mining techniques, it recreates the actual operating pattern of the turbine unit throughout its entire lifecycle, achieving high-precision coverage of the frequently operating area. Furthermore, point cluster extraction technology transforms infinite continuous operating conditions into finite computable operating conditions, improving the relevance and computational efficiency of subsequent simulation analyses and ensuring the analysis results have extremely high engineering practical value.

[0033] In one exemplary instance, the unit operating condition model (interval system) involved is as follows: Figure 2 As shown. Figure 2 This is a schematic diagram of the unit operating condition zoning system constructed in the embodiments of this application. For example... Figure 2 As shown, the model displays multiple head ranges and corresponding output percentage ranges based on historical data statistical analysis. This model allows for the intuitive identification of the unit's frequently operating areas (such as the 59-63m head and 90-100% output range, accounting for 26.46%), thus guiding the selection of subsequent unit group operating conditions and ensuring that simulation computing resources are concentrated on these high-frequency, high-weight core operating conditions.

[0034] S102 maps the flow field simulation data of the turbine runner under point group operation conditions to the runner structural model, and calculates the runner stiffness and strength through the unidirectional fluid-structure interaction method to determine the target position of the runner. The target position includes the stress concentration area and the position of the maximum stress point.

[0035] In this embodiment, after determining the working conditions of the point group, it is necessary to locate the position on the rotating wheel that is most prone to damage.

[0036] Specifically, a three-dimensional geometric model of the entire flow channel of the turbine unit, including the volute, guide vanes, runner, and draft tube, is constructed.

[0037] For each point group operating condition extracted from S101, corresponding boundary conditions (inlet total pressure, outlet static pressure, impeller speed, etc.) were set, and steady flow field calculations were performed using CFD (Computational Fluid Dynamics) software. The pressure distribution, velocity vector, and streamline distribution within the flow field were obtained.

[0038] This step involves obtaining detailed flow regime information of the fluid under point group operation conditions through full-channel 3D CFD simulation, providing accurate fluid dynamic boundary conditions for subsequent structural analysis and ensuring the homogeneity and consistency of physical field transmission.

[0039] In this step, the flow field simulation results involved are as follows: Figure 3 As shown, Figure 3 This is a schematic diagram of the streamlines from the numerical simulation calculation of the entire flow channel of the turbine unit in the embodiments of this application. Figure 3 This diagram illustrates the velocity streamline distribution of water flowing through the volute, guide vanes, runner, and tailrace under typical point group operating conditions. This streamline diagram allows for a direct analysis of the flow stability within the hydraulic components, identification of undesirable flow regimes such as flow separation and vortices, verification of the rationality of CFD simulation parameter settings, and ensures that the flow field calculation results accurately reflect the hydraulic characteristics within the unit.

[0040] Furthermore, a finite element model (FEM) of the runner's solid structure was established. Through the fluid-structure interaction interface, the fluid surface pressure loads under various point group operating conditions obtained from CFD calculations were mapped onto the corresponding surface meshes of the runner's structural model. Specifically, unidirectional fluid-structure interaction technology was used to achieve a lossless mapping of fluid pressure loads from the fluid domain to the solid domain, significantly improving the boundary accuracy of structural stress calculations.

[0041] Finally, after mapping onto the corresponding surface mesh of the runner structure model, centrifugal force (determined by rotational speed) and gravity load under the corresponding point group operating conditions are applied to the runner structure model, and correct displacement constraints are set. Static solutions are then performed using a structural mechanics solver to obtain the stress contour map and displacement distribution map of the runner.

[0042] Finally, the calculation results are iterated to identify the region with the largest change in stress gradient as the "stress concentration region"; at the same time, the node with the highest equivalent stress value is marked as the "maximum stress point location". In this embodiment, these two types of locations are collectively referred to as "target locations".

[0043] This step uses statics to accurately identify the weak points of the impeller under the combined action of centrifugal force and water pressure, and quantifies the stress distribution gradient, thereby narrowing the focus of subsequent monitoring from blind search to key targets and significantly reducing the amount of data processing.

[0044] In this step, the calculation results of the wheel stiffness are as follows: Figure 4 As shown, Figure 4 This is a stress cloud diagram and displacement distribution diagram for calculating the rigidity of the impeller in an embodiment of this application. For example... Figure 4 As shown, the stress cloud diagram on the left clearly shows the high stress distribution at the connection between the runner blade and the upper crown and lower ring (T-joint), and marks the maximum stress point (Max); the displacement cloud diagram on the right shows the deformation trend of the runner under the action of centrifugal force and water thrust. Figure 4 This is the direct basis for determining the target location, and the subsequent pressure pulsation monitoring probes will be precisely positioned based on the coordinates of the high-stress area in this figure.

[0045] Step S102 introduces a unidirectional fluid-structure interaction method for targeted localization. Compared to traditional empirical selection of monitoring points, this step directly calculates the stiffness distribution of the runner through physical field simulation, identifying stress concentration areas and points of maximum stress. This process not only eliminates uncertainties introduced by human experience but also provides clear spatial coordinates for subsequent high-frequency pressure pulsation monitoring, ensuring that all dynamic analysis resources are concentrated on the critical parts of the runner most susceptible to fatigue failure.

[0046] S103, based on the steady flow field simulation data of the turbine unit under point group operating conditions, performs pressure pulsation calculation on the turbine unit, and during the pressure pulsation calculation process, acquires the dynamic pressure detection data corresponding to the target location, and generates pressure load curves for each point group operating condition based on the dynamic pressure detection data.

[0047] Based on the target location determined in S102, a virtual monitoring probe is set at the corresponding spatial coordinates of the CFD full-channel model.

[0048] Using the steady-state calculation results in S102 as the initial flow field, a transient turbulence model adapted to large separation flows (such as the SSTk-ω or DES model) is adopted, and an appropriate time step is set to perform unsteady flow field calculations. By embedding a virtual probe into the numerical model and performing transient turbulence calculations, this step can capture millisecond-level unsteady flow details in the flow field, successfully simulating the complex flow state inside the impeller that is difficult for actual sensors to reach, and obtaining high-time-resolution raw data.

[0049] During the calculation process, the pressure fluctuation data sequence at the virtual monitoring probe is recorded in real time over time. The calculation is performed for a sufficient time period (e.g., 5-10 rotations of the impeller). Time-domain analysis is performed on the recorded data sequence to remove data from the initial stage of numerical oscillation, generating hydrodynamic pressure-load curves containing time-domain pulsation characteristics for each point group's operating conditions.

[0050] Step S103 overcomes the limitation of steady-state calculations in reflecting fluid dynamics by utilizing unsteady-state calculation techniques to acquire high-frequency data specifically for identified key locations. By generating hydrodynamic pressure-load curves containing fine time-domain characteristics, the hydraulic excitation in fluid dynamics is quantified into a dynamic load recognizable by structural dynamics, providing loading conditions closest to the real physical environment for accurately evaluating the dynamic response and fatigue life of the runner under complex flow conditions.

[0051] The results of the hydrodynamic pressure treatment involved in this step are as follows: Figure 5 As shown. Figure 5 This is a schematic diagram of the hydrodynamic pressure load curve generated in an embodiment of this application. Figure 5 As shown, the curve illustrates the fluctuation of pressure collected by the virtual monitoring probe over time (vertical axis represents pressure amplitude, horizontal axis represents time). The waveform clearly reflects the periodicity and randomness of the hydrodynamic pressure. This curve will be directly used as the load boundary condition for transient dynamic calculations, applied to the corresponding position of the runner structure model to simulate the real hydraulic excitation effect.

[0052] S104 outputs the hydrodynamic pressure load curves of each point group under the operating conditions to the runner structure model for transient dynamic calculation, and obtains the dynamic stress time series data of the target position.

[0053] For each point group operating condition, the runner structure model is invoked. The hydrodynamic pressure load curve generated in S103 is applied to the runner surface as a time-varying load boundary condition. Simultaneously, the constant centrifugal force load and gravity static load at the corresponding rotational speed for that point group operating condition are superimposed. This step constructs a full-element dynamic stress calculation model including hydrodynamic pressure, centrifugal force, and gravity, ensuring the completeness of the mechanical model and realistically reproducing the complex stress state of the runner during operation.

[0054] Furthermore, a transient dynamic structural algorithm (such as the Newmark-β method) is employed to solve the model using time-domain integration. The time step is matched to the sampling frequency of the pressure pulsation curve. After calculation, stress variation data at the target location throughout the entire time history is extracted, i.e., dynamic stress time-series data. This step utilizes the transient dynamic algorithm to solve the structure's response to dynamic loads, directly outputting the stress-time history of key components. This not only obtains the peak stress but also captures the cyclical characteristics of stress alternation, providing the most direct and accurate data source for subsequent fatigue analysis based on rainflow counting.

[0055] Step S104 completes the final conversion from fluid pulsation to structural stress fluctuation. Through transient dynamic calculations, it can accurately capture the dynamic stress response of key components of the runner under hydraulic excitation, including high-amplitude stresses caused by resonance or transient impacts. Compared to traditional static analysis or simplified quasi-static analysis, the dynamic stress time-series data obtained in this step contains complete amplitude, frequency, and phase information, which can greatly improve the accuracy of fatigue crack initiation prediction and solve the industry problem of traditional methods being unable to assess unsteady load damage.

[0056] Finally, it should be noted that, for the switching and start-up / shutdown conditions of the turbine runner, the existing unit operating condition interval system and point group operating condition research results can be used to first conduct systematic statistics on the unit switching conditions (such as interval transitions caused by load adjustment and head fluctuations) and start-up / shutdown conditions, and clarify the time distribution characteristics and triggering conditions of the two types of conditions. For switching operating conditions, based on the parameter correlation and interval correspondence of the point group operating conditions, the actual switching process is replaced step by step according to the path from the starting point group operating condition to the target point group operating condition, ensuring that the statistical logic of the switching operating conditions is consistent with the point group operating condition system. On this basis, the annual operating data is integrated to calculate the average number of start-ups and shutdowns and the total number of switching operating conditions throughout the year. At the same time, the frequency of occurrence of each typical switching path (such as "low head - low output point group → rated head - rated output point group") is statistically analyzed to provide data support for subsequent analysis of the impact of operating condition switching on the initiation of unit cracks.

[0057] Furthermore, in the analysis and processing stage, a dynamic load time series is constructed by combining the time constraints of operating condition transitions and the standard time procedures for unit start-up and shutdown. The dynamic load time series, the transient hydraulic loads under switching and start-up / shutdown conditions, and the structural inertial loads generated by speed changes are used to establish a dynamic stress calculation model for the runner during the transition process. The transient dynamic structural algorithm is used to calculate the dynamic stress of the runner during the transition process to obtain the dynamic stress time series data of the target position during the transition process.

[0058] Through the steps described above, this method achieves accurate extraction of the actual operating conditions of the unit's components by constructing a head-output-time coupled operating condition model. It then uses unidirectional fluid-structure interaction (FSI) calculations to precisely determine the stress concentration region and maximum stress point of the turbine runner. Next, the hydrodynamic pressure monitoring data of this located region is used as a load and fed back to the structural model for transient dynamic calculations, achieving coordinated analysis of flow field pressure fluctuations and structural dynamic response. This method can acquire high-fidelity dynamic stress time-series data at key locations with less resource consumption, providing reliable data support for turbine runner fatigue life assessment and structural optimization.

[0059] Secondly, embodiments of this application also provide a collaborative analysis system for pressure pulsation in hydropower station runners. Figure 6 This is a structural block diagram of a hydropower station turbine runner pressure pulsation collaborative analysis system according to an embodiment of this application, as shown below. Figure 6 As shown, the system includes: a determination module 60, an analysis module 61, and a calculation module 62, wherein, The determination module 60 is used to map the flow field simulation data of the turbine runner under point group operation conditions to the runner structural model, and calculate the runner stiffness and strength through a one-way fluid-structure interaction method to determine the target position of the runner. The target position includes: the stress concentration area and the location of the maximum stress point. The analysis module 61 is used to perform pressure pulsation calculation on the turbine unit based on the steady flow field simulation data of the turbine unit under point group operating conditions, and to obtain the dynamic water pressure detection data corresponding to the target position during the pressure pulsation calculation process, and to generate pressure load curves under the operating conditions of each point group of water based on the dynamic water pressure detection data. The calculation module 62 is used to input the hydrodynamic pressure load curves of each point group under the operating conditions into the impeller structure model for transient dynamic calculation, and to obtain the dynamic stress time series number at the target position.

[0060] This system constructs a head-output-time coupled operating condition model to accurately extract the actual operating conditions of the unit's components. It then uses unidirectional fluid-structure interaction (FSI) calculations to precisely determine the stress concentration areas and maximum stress points of the turbine runner. Next, the hydrodynamic pressure monitoring data of this located area is used as a load and fed back to the structural model for transient dynamic calculations, achieving a coordinated analysis of flow field pressure fluctuations and structural dynamic response. This method can acquire high-fidelity dynamic stress time-series data at key locations with less resource consumption, providing reliable data support for turbine runner fatigue life assessment and structural optimization.

[0061] In one embodiment, Figure 7 This is a schematic diagram of the internal structure of an electronic device according to an embodiment of this application, such as... Figure 7 As shown, an electronic device is provided, which can be a server, and its internal structure diagram can be as follows. Figure 7 As shown, the electronic device includes a processor, a network interface, internal memory, and non-volatile memory connected via an internal bus. The non-volatile memory stores the operating system, computer programs, and a database. The processor provides computing and control capabilities, the network interface communicates with external terminals via a network, the internal memory provides the environment for the operating system, the computer program is executed by the processor to implement a collaborative analysis method for pressure pulsation in a hydropower station runner, and the database stores data.

[0062] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0063] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0064] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0065] The embodiments described above are merely examples of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for the joint analysis of pressure pulsation and dynamic stress in a hydropower station runner, characterized in that, The method includes: The flow field simulation data of the turbine runner under point group operation condition is mapped to the runner structural model, and the runner stiffness is calculated by the one-way fluid-structure coupling method to determine the target position of the runner. The target position includes: stress concentration area and the position of maximum stress point. Based on the steady flow field simulation data of the turbine unit under point group operating conditions, pressure pulsation calculation is performed on the turbine unit, and during the pressure pulsation calculation, dynamic water pressure detection data corresponding to the target position is obtained, and pressure load curves under the operating conditions of each point group of water are generated according to the dynamic water pressure detection data. The hydrodynamic pressure load curves of each point group under operating conditions are input into the impeller structure model for transient dynamic calculation to obtain the dynamic stress time series data of the target location.

2. The method according to claim 1, characterized in that, Before mapping the flow field simulation data of the impeller under point group operation conditions to the impeller structural model, the method further includes: Based on the historical operating data of the turbine unit, a turbine unit operating condition model coupled with head, output and time is constructed, and point group operating conditions are extracted from the turbine unit operating condition model. A three-dimensional model of the entire flow channel of the turbine unit is constructed. Based on the three-dimensional model of the entire flow channel and the operating conditions of the point group, a steady flow field simulation calculation of the entire flow channel is performed to obtain the flow field simulation data.

3. The method according to claim 2, characterized in that, The construction of a head-output-time coupled turbine unit operating condition model includes: Based on the distribution characteristics of the historical operating data, the normal operating head interval and the abnormal operating head interval are divided, and the normal operating head interval is further subdivided into segments. Based on the division of the head interval, the output interval of the turbine unit is divided simultaneously; Based on the division results of the head interval, the division results of the output interval, and the running time corresponding to each division result, the operating condition model of the turbine unit is constructed.

4. The method according to claim 3, characterized in that, The point group operating conditions extracted from the turbine unit operating condition model include: Based on the turbine unit operating condition model, the data distribution characteristics of each operating condition interval are extracted; Based on the data distribution characteristics, the data-intensive core area is obtained; Within the data-intensive core area, typical operating points for each operating condition range are selected, and these typical operating points are integrated to obtain the point group operating conditions.

5. The method according to claim 1, characterized in that, Calculating the runner's stiffness and strength using a one-way fluid-structure interaction method to determine the runner's target position includes: Obtain the fluid pressure load in the flow field simulation data under the operating conditions of each point group; The fluid pressure load is transferred to the impeller structure model through the coupling interface. After applying the centrifugal force and gravity load corresponding to the point group operation condition to the impeller structure model, the statics are solved by the structural mechanics solver to obtain the stress cloud diagram and displacement distribution diagram of the impeller. Based on the stress cloud map and displacement distribution map, the region with the largest change in stress gradient is identified as the stress concentration region, and the node with the highest equivalent stress value is identified as the location of maximum stress. The stress concentration region and the location of maximum stress are taken as the target location.

6. The method according to claim 5, characterized in that, Obtaining the dynamic hydraulic pressure detection data corresponding to the target location includes: Based on the target location, a virtual monitoring probe is set at the corresponding spatial coordinates of the full flow channel model of the rotor; Using the flow field simulation data under the operating conditions of the point group as the initial value, an unsteady flow field calculation is performed using a transient turbulence model, and the data sequence of pressure fluctuations at the virtual monitoring probe over time is recorded in real time. The data sequence is processed to generate hydrodynamic pressure load curves containing time-domain pulsation characteristics under the operating conditions of each point group.

7. The method according to claim 1, characterized in that, The hydrodynamic pressure load curves under various point group operating conditions are input into the turbine runner structure model for transient dynamic calculations, including: The dynamic water pressure load curves under the operating conditions of each point group are applied to the impeller structure model, and the centrifugal force load and static load at the corresponding speed are superimposed to establish the impeller dynamic stress calculation model. The transient dynamic structure algorithm is used to calculate the dynamic stress model of the impeller, and the dynamic stress time series data of the target position under the point group operation condition is obtained.

8. The method according to claim 1, characterized in that, The method further includes: Based on the switching and start-up / shutdown conditions of the turbine runner, and according to the time constraints of the condition transition and the standard time procedures for unit start-up and shutdown, a dynamic load time series is constructed. A dynamic stress calculation model for the turbine runner during the transition process is established by using the dynamic load time series, the transient hydraulic loads under the switching and start-up / shutdown conditions, and the structural inertial loads generated by the speed change. The transient dynamic structure algorithm is used to calculate the dynamic stress of the impeller during the transition process, and the dynamic stress time series data of the target position under switching and start-stop conditions are obtained.

9. A collaborative analysis system for pressure pulsation in a hydropower station runner, characterized in that, The system includes: a determination module, an analysis module, and a calculation module, wherein, The determining module is used to map the flow field simulation data of the turbine runner under point group operation conditions to the runner structural model, and calculate the runner stiffness and strength through a one-way fluid-structure coupling method to determine the target position of the runner, wherein the target position includes: stress concentration area and the position of maximum stress point; The analysis module is used to perform pressure pulsation calculation on the turbine unit based on the steady flow field simulation data of the turbine unit under point group operating conditions, and to obtain the dynamic water pressure detection data corresponding to the target position during the pressure pulsation calculation process, and to generate pressure load curves under the operating conditions of each point group of water based on the dynamic water pressure detection data. The calculation module is used to input the hydrodynamic pressure load curves of each point group under the operating conditions into the impeller structure model for transient dynamic calculation, and obtain the dynamic stress time series data of the target position.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 7.

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