Method, apparatus, and equipment for monitoring the structure of a pumped-storage hydroelectric power plant unit frame.

Abstract

To provide a frame structure monitoring method, device, apparatus, and medium for comprehensively grasping the state of stress and deformation of a pumped-storage power generation unit frame.SOLUTION: The method includes constructing a frame structure FE model based on structural parameters and operational parameters, performing simulation analysis on a simulation parameter set based on the FE model to obtain first stress and deformation simulation values, obtaining an optimized proxy model based on the parameter set and the first stress and deformation simulation values, inputting a test parameter set into the FE model and the optimized proxy model to obtain second stress and deformation simulation values and stress and deformation prediction values, and monitoring stress and deformation of the frame using the stress and deformation prediction values when the second stress and deformation simulation values and the stress and deformation prediction values meet a preset accuracy condition.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to the technical field of machine learning and the integration of energy equipment, and more specifically to a method, apparatus, and equipment for monitoring the structure of a pumped-storage hydroelectric power plant unit frame. [Background technology]

[0002] Pumped-storage hydroelectric power units play a vital role in peak load adjustment, valley load filling, and fault tolerance in the power grid. The frame of a pumped-storage hydroelectric power unit is one of its crucial force-bearing components. During operation, it is subjected not only to the gravitational force of rotating components such as the pump, turbine, and generator motor, but also to the effects of unbalanced rotor mass forces, unbalanced magnetic attraction forces of the motor, nonlinear oil film forces on the bearings, nonlinear sealing forces of the fluid, and unstable excitation forces of the fluid. Therefore, the safety and reliability of its structure play a critical role in the safe, reliable, and stable operation of the pumped-storage hydroelectric power unit. Consequently, it is necessary to monitor the stress and deformation status of the frame in real time.

[0003] However, existing methods that rely solely on static analysis during the design phase and on condition monitoring techniques during the operation and maintenance phase to monitor local stresses and deformations have the problem of not being able to comprehensively grasp the stress and deformation conditions at each location of the frame, and not being able to grasp the stress and deformation conditions of the frame in real time and intuitively. [Overview of the project] [Problems that the invention aims to solve]

[0004] In view of this, the present invention provides a method, apparatus, and equipment for monitoring the structure of a pumped-storage hydroelectric power plant unit frame to solve the problem of not being able to comprehensively grasp the stress and deformation status of the frame. [Means for solving the problem]

[0005] In the first aspect, the present invention is The steps include obtaining the structural parameters of the pumped-storage hydroelectric power plant unit frame and the operating parameters of multiple operating conditions, The steps include constructing a frame structure finite element model based on structural parameters and operating parameters for multiple operating conditions, extracting characteristic parameters for multiple operating conditions based on the operating parameters for multiple operating conditions, and dividing the characteristic parameters for multiple operating conditions into a test parameter set for multiple operating conditions and a simulation parameter set for multiple operating conditions, The steps include: performing a simulation analysis on a corresponding set of simulation parameters based on a frame structure finite element model under pre-set operating conditions to obtain the first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame; The steps include optimizing a pre-set initial proxy model based on the simulation parameter set for the corresponding operating conditions and the first stress and deformation simulation values ​​for the corresponding operating conditions, thereby obtaining an optimized proxy model, The process involves inputting the corresponding test parameter sets for pre-defined operating conditions into the frame structure finite element model and the optimized proxy model, respectively, to obtain the second stress and deformation simulation values ​​and the corresponding stress and deformation prediction values ​​for the operating conditions. The present invention provides a method for monitoring the structure of a pumped-storage hydroelectric power unit frame, which includes the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​for the corresponding operating conditions, if the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy a preset accuracy condition.

[0006] The structural monitoring method of the pumped-storage power generation unit frame according to the present invention performs a simulation analysis on the simulation parameter set of the corresponding operating conditions by means of a frame structure finite element model, obtains the first stress and deformation simulation values of the corresponding operating conditions of the pumped-storage power generation unit frame, and based on the first stress and deformation simulation values and the extracted simulation parameter set of the corresponding operating conditions, obtains an optimized proxy model. Under the preset operating conditions, the test parameter sets of the corresponding operating conditions are respectively input into the frame structure finite element model and the optimized proxy model, and the second stress and deformation simulation values of the corresponding operating conditions and the stress and deformation prediction values of the corresponding operating conditions are respectively obtained. When the second stress and deformation simulation values of the corresponding operating conditions and the stress and deformation prediction values of the corresponding operating conditions meet the preset accuracy conditions, the stress and deformation of the pumped-storage power generation unit frame are monitored by using the stress and deformation prediction values of the corresponding operating conditions, thereby realizing the purpose of comprehensively and real-time monitoring the stress and deformation conditions of each position of the pumped-storage power generation unit frame under various operating conditions, and solving the problem that the stress and deformation conditions of the frame cannot be comprehensively grasped.

[0007] In one selectable embodiment, the structural parameters of the pumped-storage power generation unit frame include the geometric dimensions, material attributes and structural connection relationships of the pumped-storage power generation unit frame, and the operating parameters of the plurality of operating conditions of the pumped-storage power generation unit frame include the operating loads in the plurality of operating conditions. The step of constructing a frame structure finite element model based on the structural parameters and the operating parameters of the plurality of operating conditions includes: Using a parametric programming language, constructing a frame structure finite element model in a plurality of operating conditions based on the geometric dimensions, material attributes, structural connection relationships of the pumped-storage power generation unit frame and the operating loads in the plurality of operating conditions.

[0008] The present invention provides a structural monitoring method for a pumped-storage hydroelectric power plant unit frame. This method uses a parametric programming language to construct a finite element model of the frame structure under multiple operating conditions, based on the geometric dimensions, material attributes, structural connection relationships, and operating loads of the pumped-storage hydroelectric power plant unit frame. This achieves the objective of constructing a miniaturized finite element model of the frame structure and provides a model basis for subsequent acquisition of first stress and strain simulation values.

[0009] In one selectable embodiment, under preset operating conditions, a simulation analysis is performed on a corresponding set of simulation parameters based on a frame structure finite element model to obtain first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame. The steps include: obtaining input data for the corresponding operating conditions by sampling the simulation parameter set for the corresponding operating conditions using a Latin hypercube sampling algorithm under pre-set operating conditions; The process includes the step of inputting corresponding operating condition data into a frame structure finite element model, performing a static simulation analysis, and obtaining first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame.

[0010] The present invention provides a structural monitoring method for a pumped-storage hydroelectric power unit frame. Under preset operating conditions, a Latin hypercube sampling algorithm is used to sample a set of simulation parameters corresponding to the operating conditions to obtain input data for the corresponding operating conditions. This input data is then input into a frame structure finite element model to perform static simulation analysis, obtaining first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under the corresponding operating conditions. The frame structure finite element model enables static simulation analysis under various operating conditions, further allowing the acquisition of first stress and deformation simulation values ​​under various operating conditions. These first stress and deformation simulation values ​​under various operating conditions allow for the determination of weak points in the pumped-storage hydroelectric power unit frame and provide a data basis for subsequent optimization of the initial proxy model.

[0011] In one selectable embodiment, the step of optimizing a preset initial proxy model based on a set of simulation parameters for the corresponding operating conditions, and first stress and deformation simulation values ​​for the corresponding operating conditions, to obtain an optimized proxy model is: The steps include: obtaining input data for the corresponding operating conditions by sampling characteristic parameters of the simulation parameter set for the corresponding operating conditions using a Latin hypercube sampling algorithm under pre-set operating conditions; The steps include inputting the corresponding operating conditions as input data, and the first stress and deformation simulation values ​​for the corresponding operating conditions as sample data points into a pre-configured initial proxy model, and obtaining the relevant parameters of the initial proxy model, The steps include: calculating the optimal solution for the relevant parameters using the Pelican optimization algorithm, This includes the steps of optimizing the initial proxy model using the optimal solution to obtain the optimized proxy model.

[0012] The present invention provides a structural monitoring method for a pumped-storage hydroelectric power unit frame. Under preset operating conditions, a Latin hypercube sampling algorithm is used to sample characteristic parameters of the simulation parameter set for the corresponding operating conditions to obtain input data for the corresponding operating conditions. This input data, along with the first stress and deformation simulation values ​​for the corresponding operating conditions, are input as sample data points into a preset initial proxy model. Related parameters of the initial proxy model are obtained. An optimal solution for the related parameters is calculated using a Pelican optimization algorithm. The initial proxy model is optimized using this optimal solution to obtain an optimized proxy model. This optimized proxy model then provides a model basis for predicting the stress and deformation conditions of the pumped-storage hydroelectric power unit frame, thereby improving the accuracy of stress and deformation predictions.

[0013] In one selectable embodiment, if the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy a preset accuracy condition, the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​for the corresponding operating conditions is: The steps include calculating the first relative error between the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions, A step of determining whether the first relative error satisfies a predetermined accuracy condition, The procedure includes the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using predicted stress and deformation values ​​for the corresponding operating conditions, provided that the first relative error satisfies a preset accuracy condition.

[0014] The method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to the present invention achieves accuracy verification of the first relative error by determining whether the first relative error between the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfies a preset accuracy condition, thereby improving the accuracy of the predicted stress and deformation values ​​for the corresponding operating conditions. If the first relative error satisfies the preset accuracy condition, the method monitors the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​for the corresponding operating conditions, thereby achieving the objective of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame in real time under various operating conditions.

[0015] In one selectable embodiment, if the first relative error satisfies a preset accuracy condition, the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using predicted stress and deformation values ​​for the corresponding operating conditions is: If the first relative error satisfies the preset accuracy conditions, the step is to collect measured stress and deformation values ​​of the pumped-storage hydroelectric power unit frame under the corresponding operating conditions. The steps include calculating a second relative error between the measured stress and deformation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions, The procedure includes the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using predicted stress and deformation values ​​for the corresponding operating conditions, provided that the second relative error satisfies a preset accuracy condition.

[0016] The method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to the present invention involves, when the first relative error satisfies a preset accuracy condition, continuously verifying the accuracy of the second relative error between the measured stress and deformation values ​​under the corresponding operating conditions and the predicted stress and deformation values ​​under the corresponding operating conditions, and when the second relative error satisfies a preset accuracy condition, monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​under the corresponding operating conditions. This improves the accuracy of verifying the predicted stress and deformation values ​​under the corresponding operating conditions, and makes monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​under the corresponding operating conditions more accurate.

[0017] In one selectable embodiment, a method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame is: If the first relative error does not meet the predetermined accuracy conditions, the second stress and deformation simulation values ​​are added as additional data to the sample data points to obtain additional sample data points, and the optimized proxy model is updated based on the additional sample data points. Or, If the second relative error does not meet the pre-set accuracy requirements, the process further includes updating the frame structure finite element model using a pre-set correction coefficient, adding measured stress and deformation values ​​as additional data to the sample data points to obtain additional sample data points, and updating the optimized proxy model based on the additional sample data points.

[0018] The pumped-storage hydroelectric power unit frame structure monitoring method according to the present invention further optimizes the frame structure finite element model, improves the simulation accuracy of the finite element model, further optimizes the proxy model optimized by the additional sample data points, and further improves the prediction accuracy of the optimized proxy model, if the first relative error does not meet the preset accuracy conditions, by adding stress and deformation simulation values ​​as additional data to the sample data points to obtain additional sample data points, and updating the optimized proxy model based on the additional sample data points. Alternatively, if the second relative error does not meet the preset accuracy conditions, the frame structure finite element model is updated using a preset correction coefficient, and the simulation accuracy of the finite element model is further optimized by the additional sample data points, thereby improving the prediction accuracy of the optimized proxy model.

[0019] In a second aspect, the present invention is An acquisition module for obtaining structural parameters of a pumped-storage hydroelectric power plant unit frame and operating parameters for multiple operating conditions, A construction module for constructing a frame structure finite element model based on structural parameters and operating parameters for multiple operating conditions, extracting characteristic parameters for multiple operating conditions based on the operating parameters for multiple operating conditions, and dividing the characteristic parameters for multiple operating conditions into test parameter sets for multiple operating conditions and simulation parameter sets for multiple operating conditions. A simulation module for obtaining the first stress and deformation simulation values ​​for the pumped-storage hydroelectric power plant unit frame under the corresponding operating conditions by performing simulation analysis on the corresponding simulation parameter set based on a frame structure finite element model under pre-set operating conditions, and An optimization module for optimizing a pre-set initial proxy model and obtaining an optimized proxy model based on the characteristic parameters of the simulation parameter set for the corresponding operating conditions, and the first stress and deformation simulation values ​​for the corresponding operating conditions. A test module is provided to input the corresponding test parameter sets for pre-set operating conditions into a frame structure finite element model and an optimized proxy model, respectively, and to obtain the second stress and deformation simulation values ​​and the corresponding stress and deformation prediction values ​​for the operating conditions. The present invention provides a structural monitoring device for a pumped-storage hydroelectric power plant unit frame, which includes a monitoring module for monitoring the stress and deformation of the pumped-storage hydroelectric power plant unit frame using the predicted stress and deformation values ​​for the corresponding operating conditions, provided that the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy the preset accuracy conditions.

[0020] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory and the processor are communicatively connected, computer instructions are stored in the memory, and the processor executes the computer instructions to perform the method for monitoring the structure of a pumped-storage hydroelectric power unit frame described in the first aspect or any corresponding embodiment thereof.

[0021] In a fourth aspect, the present invention provides a computer-readable storage medium that stores computer instructions for causing a computer to execute the method for monitoring the structure of a pumped-storage hydroelectric power unit frame described in the first aspect or any corresponding embodiment thereof.

[0022] To more clearly describe specific embodiments of the present invention or technical solutions of the prior art, the drawings that need to be used to describe specific embodiments or the prior art will be briefly described below. As will be apparent, the drawings described below are some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these without any creative work. [Brief explanation of the drawing]

[0023] [Figure 1] This is a schematic flowchart of a method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame according to an embodiment of the present invention. [Figure 2] This is a schematic flowchart of a method for monitoring the structure of another pumped-storage hydroelectric power plant unit frame according to an embodiment of the present invention. [Figure 3] This is a schematic flowchart of yet another method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame according to an embodiment of the present invention. [Figure 4] This is a schematic flowchart of yet another method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame according to an embodiment of the present invention. [Figure 5] This is a schematic flowchart of yet another method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame according to an embodiment of the present invention. [Figure 6] This is a schematic flowchart of yet another method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame according to an embodiment of the present invention. [Figure 7] This is a structural block diagram of a structural monitoring device for a pumped-storage hydroelectric power unit frame according to an embodiment of the present invention. [Figure 8] This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. [Modes for carrying out the invention]

[0024] To further clarify the object, technical solution, and advantages of the embodiments of the present invention, the technical solution of the embodiments of the present invention will be described clearly and completely below with reference to the drawings of the embodiments of the present invention, and as will be obvious, the embodiments described are some embodiments of the present invention, not all embodiments. All other embodiments that a person skilled in the art could obtain without creative work based on the embodiments of the present invention are within the scope of the protection of the present invention.

[0025] According to embodiments of the present invention, an embodiment of a method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame is provided, and the steps shown in the flowchart of the drawings are executable on a computer system such as a computer executable instruction set, and although the flowchart shows a logical order, it should be noted that in some cases the steps shown or described may be executed in an order different from the order herein.

[0026] This embodiment provides a method for monitoring the structure of a pumped-storage hydroelectric power unit frame that can be applied to the pumped-storage hydroelectric power unit frame. Figure 1 is a flowchart of the method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to an embodiment of the present invention. As shown in Figure 1, the process includes the following steps S101 to S106.

[0027] Step S101: Obtain the structural parameters of the pumped-storage hydroelectric power plant unit frame and the operating parameters of multiple operating conditions.

[0028] Specifically, the structural parameters of the pumped-storage hydroelectric power unit frame may include the geometric dimensions, material attributes, and structural connection relationships of the pumped-storage hydroelectric power unit frame, and the multiple operating conditions of the pumped-storage hydroelectric power unit in actual operation include two steady-state operating conditions, namely pump operating conditions and turbine operating conditions, and three transient operating conditions, namely turbine braking operating conditions and reverse pump operating conditions. The operating parameters include the operating characteristic parameters and operating load parameters of the pumped-storage hydroelectric power unit frame under each operating condition. The structural parameters of the pumped-storage hydroelectric power unit frame can be obtained from the operating manual for the pumped-storage hydroelectric power unit frame, and the frame operating parameters can be collected when the pumped-storage hydroelectric power unit is operating under various operating conditions.

[0029] Step S102: A frame structure finite element model is constructed based on structural parameters and operating parameters for multiple operating conditions. Feature parameters for multiple operating conditions are extracted based on the operating parameters for those conditions. These feature parameters are then divided into a test parameter set for multiple operating conditions and a simulation parameter set for multiple operating conditions.

[0030] Specifically, a finite element model is a model created using finite element analysis methods, and is a collection of combinations of units connected by nodes, transmitting forces through nodes, and constrained by nodes. A frame structure finite element model is a model constructed based on the geometric properties of a pumped-storage hydroelectric power unit frame, and represents abstract mechanical relationships. Based on the operating parameters of multiple operating conditions, characteristic parameters of multiple operating conditions are extracted, including but not limited to parameters such as rotational speed, flow rate, and head of the pumped-storage hydroelectric power unit.

[0031] Subsequently, a simulation analysis of the frame structure finite element model is performed to optimize the initial proxy model. Furthermore, to simulate and predict stress and deformation conditions using the frame structure finite element model and the optimized initial proxy model, the characteristic parameters of multiple operating conditions are divided into multiple test parameter sets and multiple simulation parameter sets. The multiple simulation parameter sets are used for the simulation analysis of the finite element model and the optimization of the initial proxy model. The multiple test parameter sets are used to simulate and predict stress and deformation conditions using the frame structure finite element model and the optimized initial proxy model.

[0032] In step S103, under pre-set operating conditions, a simulation analysis is performed on the corresponding simulation parameter set for the operating conditions based on the frame structure finite element model to obtain the first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under the corresponding operating conditions.

[0033] Specifically, the pre-set operating conditions are one of two types of steady-state operating conditions: pump operating conditions and turbine operating conditions, and one of three transient operating conditions: pump braking operating conditions, turbine braking operating conditions, and reverse pump operating conditions.

[0034] Under pre-set operating conditions, a simulation analysis is performed on the corresponding simulation parameter set based on the frame structure finite element model to obtain the first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under the corresponding operating conditions. Based on these first stress and deformation simulation values, weak points of the pumped-storage hydroelectric power unit frame are roughly determined.

[0035] In step S104, the pre-set initial proxy model is optimized based on the simulation parameter set for the corresponding operating conditions and the first stress and deformation simulation values ​​for the corresponding operating conditions to obtain an optimized proxy model.

[0036] Specifically, the initial proxy model can be the Kriging model, which is an unbiased estimation model that minimizes the estimated variance and possesses the characteristics of local estimation.

[0037] The simulation parameter set for the corresponding operating conditions, the first stress and deformation simulation values ​​for the corresponding operating conditions are input into a pre-configured initial proxy model, the pre-configured initial proxy model is optimized, and an optimized proxy model is obtained.

[0038] In step S105, under pre-set operating conditions, the corresponding test parameter sets for the operating conditions are input into the frame structure finite element model and the optimized proxy model, respectively, to obtain the second stress and deformation simulation values ​​and the corresponding stress and deformation prediction values ​​for the operating conditions.

[0039] Specifically, under pre-set operating conditions, the corresponding test parameter set is input into a frame structure finite element model to obtain the second stress and deformation simulation values ​​for the corresponding operating conditions. Then, the corresponding test parameter set is input into an optimized proxy model to obtain the stress and deformation prediction values ​​for the corresponding operating conditions.

[0040] In step S106, if the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy the preset accuracy conditions, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the predicted stress and deformation values ​​for the corresponding operating conditions.

[0041] Specifically, the pre-set accuracy conditions are set according to the actual situation and may be within the range of pre-set accuracy values, and are not specifically limited thereto. The pre-set accuracy conditions are used to verify the accuracy of the second stress and deformation simulation values ​​and the predicted stress and deformation values ​​for the corresponding operating conditions. If the second stress and deformation simulation values ​​and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy the pre-set accuracy conditions, it means that the predicted stress and deformation values ​​for the corresponding operating conditions predicted using the optimized proxy model are closest to the second stress and deformation simulation values, and the stress and deformation of the pumped-storage hydroelectric power plant unit frame can be monitored using the predicted stress and deformation values ​​for the corresponding operating conditions.

[0042] The method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to this embodiment involves performing a simulation analysis on a simulation parameter set for the corresponding operating conditions using a frame structure finite element model to obtain first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under the corresponding operating conditions, obtaining an optimized proxy model based on the first stress and deformation simulation values ​​and the extracted simulation parameter set for the corresponding operating conditions, inputting the test parameter set for the corresponding operating conditions into the frame structure finite element model and the optimized proxy model, respectively, to obtain second stress and deformation simulation values ​​and predicted stress and deformation values ​​for the corresponding operating conditions, respectively, and if the second stress and deformation simulation values ​​and predicted stress and deformation values ​​for the corresponding operating conditions satisfy the preset accuracy conditions, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the predicted stress and deformation values ​​for the corresponding operating conditions. This achieves the objective of comprehensively and in real time monitoring the stress and deformation status of each position of the pumped-storage hydroelectric power unit frame under various operating conditions, thereby solving the problem of not being able to comprehensively grasp the stress and deformation status of the frame.

[0043] This embodiment provides a method for monitoring the structure of a pumped-storage hydroelectric power unit frame that can be applied to pumped-storage hydroelectric power units. Figure 2 is a flowchart of the method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to an embodiment of the present invention. As shown in Figure 2, the process includes the following steps S201 to S206.

[0044] In step S201, the structural parameters of the pumped-storage hydroelectric power plant unit frame and the operating parameters of multiple operating conditions are obtained. For details, refer to step S101 of the embodiment shown in Figure 1, and will not be repeated here.

[0045] Step S202: A frame structure finite element model is constructed based on structural parameters and operating parameters for multiple operating conditions. Feature parameters for multiple operating conditions are extracted based on the operating parameters for those conditions. These feature parameters are then divided into test parameter sets and simulation parameter sets for the multiple operating conditions.

[0046] Specifically, the structural parameters of the pumped-storage hydroelectric power unit frame include the geometric dimensions, material attributes, and structural connection relationships of the pumped-storage hydroelectric power unit frame, and the operating parameters for multiple operating conditions of the pumped-storage hydroelectric power unit frame include the operating loads under multiple operating conditions. In step S20 above, a finite element model of the frame structure is constructed based on the structural parameters and the operating parameters for multiple operating conditions. The process includes the step of constructing a finite element model of the frame structure under multiple operating conditions, based on the geometric dimensions, material attributes, structural connection relationships, and operating loads of the pumped-storage hydroelectric power plant unit frame, using a parametric programming language.

[0047] Specifically, based on the design data or 3D scanning technology of the pumped-storage hydroelectric power unit, a 3D geometric solid model of the pumped-storage hydroelectric power unit frame is created using CAD software, and material attributes of the pumped-storage hydroelectric power unit frame, including density, elastic modulus, and Poisson's ratio, are set. The pumped-storage hydroelectric power unit frame is then discretized using the SOLID187 unit to obtain a finite element mesh model, where the SOLID187 unit is a high-order 3D 10-node solid structure unit.

[0048] After analyzing the load conditions during the actual operation of the pumped-storage hydroelectric power plant unit frame, loads are applied to the frame. The frame is primarily subjected to the gravity of its own structure and auxiliary equipment, and axial water thrust. Gravity includes the weight of the frame itself, the weight of rotating members such as runners, and the gravity of accessories such as thrust bearings and oil tanks. Axial water thrust includes the combined force of the water impact force and water buoyancy acting on the runners. Approximate values ​​can be obtained based on the empirical formula for the axial water thrust of a Francis turbine, or accurate values ​​can be obtained through numerical simulation calculations using CFD (Computational Fluid Dynamics).

[0049] The empirical formula is, The filename is JPEG0007900119000001.jpg15170. Here, λ is a correction coefficient, and according to experimental data in related technologies, it has been found that under normal operating conditions, it increases with increasing output and flow rate of the pumped-storage power generation unit, with a range of 0.7 to 0.8. It is recommended to set the value to 0.75 ± 0.01 at rated output, to 0.77 ± 0.01 when exceeding rated output, and to set the value to a fixed value of 1 ± 0.01 under load dump operating conditions. ω Q is the rotational speed of the pumped-storage hydroelectric power unit, in units of rpm, and Q is the flow rate of the unit, in units of m 3 / s, H is the working head of the extraction unit frame, in units of m, and D1 is the nominal diameter of the runner, in units of m.

[0050] The parametric programming language, also known as APDL (ANSYS Parametric Design Language), is used to analyze the geometric dimensions, material attributes, structural connection relationships divided by a finite element mesh model, and operating loads under multiple operating conditions of a pumped-storage hydroelectric power plant unit frame, and to create a miniaturized frame structure finite element model.

[0051] In step S203, under pre-set operating conditions, a simulation analysis is performed on the corresponding simulation parameter set for the operating conditions based on the frame structure finite element model to obtain the first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under the corresponding operating conditions.

[0052] Specifically, step S203 above includes steps S2031 and S2032 below.

[0053] In step S2031, under pre-set operating conditions, the Latin hypercube sampling algorithm is used to sample the simulation parameter set for the corresponding operating conditions and obtain the corresponding input data for the operating conditions.

[0054] Specifically, the Latin Hypercube Sampling (LHS) algorithm is an algorithm that approximately randomly samples from a multivariate parameter distribution. Under pre-defined operating conditions, the Latin Hypercube Sampling algorithm is used to sample the simulation parameter set corresponding to those operating conditions to obtain input data for those operating conditions; that is, the obtained input data for the corresponding operating conditions is a portion of the data in the simulation parameter set for those operating conditions. Specifically, the type of input data obtained by sampling is predetermined according to the actual situation and is not specifically limited here.

[0055] In step S2032, input data for the corresponding operating conditions is entered into the frame structure finite element model, and a static simulation analysis is performed to obtain the first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power plant unit frame.

[0056] Specifically, as shown in Figure 4, static simulation analysis is a static simulation analysis of the structure using a frame finite element model with corresponding operating condition input data. The pumped-storage hydroelectric power unit frame deforms under the action of preset operating conditions and operating loads, and the internal material of the pumped-storage hydroelectric power unit frame is in a complex force-bearing state. Static simulation analysis explains the relationship between stress and deformation of the pumped-storage hydroelectric power unit frame, and finally obtains first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame. Using these first stress and deformation simulation values, a stress and deformation cloud map of the entire frame is generated by finite element software, and weak points of the frame can be identified from the stress and deformation cloud map.

[0057] The method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to this embodiment involves sampling a set of simulation parameters for corresponding operating conditions using a Latin hypercube sampling algorithm under pre-set operating conditions to obtain input data for the corresponding operating conditions, inputting this input data into a frame structure finite element model to perform static simulation analysis, obtaining first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under corresponding operating conditions, enabling static simulation analysis under various operating conditions using the frame structure finite element model, obtaining first stress and deformation simulation values ​​under various operating conditions, determining weak points in the pumped-storage hydroelectric power unit frame based on the first stress and deformation simulation values ​​under various operating conditions, and providing a data basis for subsequent optimization of the initial proxy model.

[0058] In step S204, the pre-set initial proxy model is optimized based on the simulation parameter set for the corresponding operating conditions and the first stress and deformation simulation values ​​for the corresponding operating conditions to obtain an optimized proxy model.

[0059] Specifically, step S204 above includes steps S2041 to S2044 below.

[0060] In step S2041, under pre-set operating conditions, the characteristic parameters of the simulation parameter set for the corresponding operating conditions are sampled using the Latin hypercube sampling algorithm to obtain input data for the corresponding operating conditions.

[0061] Specifically, this step is the same as the process in step S2031, and under pre-set operating conditions, the characteristic parameters of the simulation parameter set for the corresponding operating conditions are sampled using the Latin hypercube sampling algorithm to obtain input data for the corresponding operating conditions, and the obtained input data for the corresponding operating conditions is the same as the input data for the corresponding operating conditions obtained in step S2031.

[0062] In step S2042, the input data for the corresponding operating conditions, the first stress and deformation simulation values ​​for the corresponding operating conditions are input as sample data points into a pre-configured initial proxy model, and the relevant parameters of the initial proxy model are obtained.

[0063] Specifically, the pre-configured initial proxy model uses the Kriging model. The input data for the corresponding operating conditions, along with the first stress and deformation simulation values ​​for the corresponding operating conditions, are input into the pre-configured initial proxy model as sample data points.

[0064] In the Kriging model, the response value and the independent variable satisfy the relationship given by equation (2). JPEG0007900119000002.jpg14170Here, \(x=(x_1,x_2,\ldots,x n ) T is the input data for any corresponding operating condition, that is, a sample data point, \(n\) is the dimension of the sample data point, \(y(x)\) is the predicted response value of the corresponding sample data point, \(\beta i (i = 1,2,\ldots,n)\) are the estimated regression coefficients, \(f i (x)(i = 1,2,\ldots,n)\) is the polynomial basis function vector, \(z(x)\) is a Gaussian random function following \(N(0,\sigma 2 )\), and the covariance between any two sample data points \(x i and \(x j is added by Equation (3), JPEG0007900119000003.jpg10170Here, Cov is the covariance operation, \(R(\theta,xEQUATION (3) i ,x j )\) is the correlation function characterizing the spatial correlation between the sample data points \(x i and \(x j \), \(\theta=[\theta_1,\theta_2,\ldots,\theta n T is the related parameter vector.

[0065] The correlation function may be a linear function, an exponential function, or a Gaussian function. The Gaussian function is generally calculated by Equation (4), JPEG0007900119000004.jpg28170Here, \(N\) is the dimension of \(x\), \(\theta n is the unknown related parameter of the Kriging model, \(d n represents the distance between the sample data points \(x_i\) and \(x_j\), as shown in Equation (5).

[0066] Step S2043, calculate the optimal solution of the related parameters using the pelican optimization algorithm.

[0067] Specifically, after determining the correlation function, the prediction of the Kriging model can be further explained as follows, JPEG0007900119000005.jpg31170r T (x * ) can be expressed as follows: According to the Kriging model, unknown data point x * The mean squared error or standard deviation s in 2 To predict, that is, JPEG0007900119000007.jpg11170 Here, s 2 θ is the mean squared error or standard deviation, representing the predicted deviation between the Kriging model and the actual response value. n By solving this problem, an optimized Kriging model can be obtained.

[0068] Related parameter θ n The mathematical model for optimization is as follows: JPEG0007900119000008.jpg84170

[0069] Solve equation (11) using the Pelican optimization algorithm.

[0070] The Pelican Optimization Algorithm (POA) is a probabilistic metaheuristic algorithm that simulates the hunting behavior of pelicans. It possesses relatively good global search capabilities and optimal local identification capabilities. Its process is divided into two stages: a search phase in which the pelican approaches its prey, and an utilization phase in which it flies over the water's surface.

[0071] (1) Initialization: The pelican population is initialized as follows: JPEG0007900119000009.jpg28170

[0072] Pelican populations can be represented as follows: JPEG0007900119000010.jpg48170

[0073] The objective function value vector for a pelican population can be expressed as follows: JPEG0007900119000011.jpg26170

[0074] (2) Search phase, approaching prey: The exploration phase refers to the stage after a pelican has determined the location of its prey and is moving to the hunting area. The mathematical model of the approach strategy to prey is as follows: JPEG0007900119000012.jpg45170

[0075] Objective function value F P Once the position is improved, the new position of the pelican is accepted and, at this time, is effectively updated as follows: JPEG0007900119000013.jpg32170

[0076] (3) Usage stage, water surface flight: The utilization stage refers to the phase in which the pelican reaches the water's surface, spreads its wings above the water, and, after guiding the fish upwards, collects the prey with its throat pouch. The mathematical model of the surface flight strategy is as follows: JPEG0007900119000014.jpg26170

[0077] At this time, the pelican's position is effectively updated as follows: JPEG0007900119000015.jpg38170

[0078] According to the Pelican algorithm described above, the related parameter θ n Obtain the optimal solution.

[0079] Step S2044: Optimize the initial proxy model using the optimal solution to obtain the optimized proxy model.

[0080] Specifically, the θ of the proxy model n Using a mathematical model of optimization, combined with the Pelican algorithm, θ nWe obtain the optimal solution for θ n The initial proxy model is optimized using the optimal solution, and an optimized Kriging proxy model is formed.

[0081] In step S205, under pre-set operating conditions, the corresponding test parameter sets are input into the frame structure finite element model and the optimized proxy model, respectively, to obtain the second stress and deformation simulation values ​​and the corresponding stress and deformation prediction values ​​for the operating conditions. For details, please refer to step S105 of the embodiment shown in Figure 1, which will not be repeated here.

[0082] In step S206, if the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy the preset accuracy conditions, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the predicted stress and deformation values ​​for the corresponding operating conditions. For details, refer to step S106 of the embodiment shown in Figure 1, which will not be repeated here.

[0083] The method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame according to this embodiment involves sampling characteristic parameters of the simulation parameter set for the corresponding operating conditions using a Latin hypercube sampling algorithm under preset operating conditions to obtain input data for the corresponding operating conditions, inputting the input data for the corresponding operating conditions, the first stress and deformation simulation values ​​for the corresponding operating conditions as sample data points into a preset initial proxy model, obtaining the relevant parameters of the initial proxy model, calculating the optimal solution for the relevant parameters using a Pelican optimization algorithm, optimizing the initial proxy model using the optimal solution, obtaining an optimized proxy model, and using the optimized proxy model to provide a model basis for subsequently predicting the stress and deformation conditions of the pumped-storage hydroelectric power plant unit frame, thereby improving the accuracy of stress and deformation predictions.

[0084] This embodiment provides a method for monitoring the structure of a pumped-storage hydroelectric power unit frame that can be applied to pumped-storage hydroelectric power units. Figure 3 is a flowchart of the method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to an embodiment of the present invention. As shown in Figure 3, the process includes the following steps S301 to S308.

[0085] In step S301, the structural parameters of the pumped-storage hydroelectric power plant unit frame and the operating parameters of multiple operating conditions are obtained. For details, refer to step S201 of the embodiment shown in Figure 2, and will not be repeated here.

[0086] In step S302, a frame structure finite element model is constructed based on the structural parameters and the operating parameters of multiple operating conditions. Feature parameters for multiple operating conditions are extracted based on the operating parameters of multiple operating conditions, and these feature parameters are divided into test parameter sets and simulation parameter sets for multiple operating conditions. For details, please refer to step S202 of the embodiment shown in Figure 2; a detailed explanation will not be repeated here.

[0087] In step S303, under pre-set operating conditions, a simulation analysis is performed on the corresponding simulation parameter set for the operating conditions based on the frame structure finite element model to obtain the first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under the corresponding operating conditions. For details, please refer to step S203 of the embodiment shown in Figure 2, and will not be repeated here.

[0088] In step S304, the pre-configured initial proxy model is optimized based on the simulation parameter set for the corresponding operating conditions and the first stress and deformation simulation values ​​for the corresponding operating conditions to obtain the optimized proxy model. For details, please refer to step S204 of the embodiment shown in Figure 2, which will not be repeated here.

[0089] In step S305, under pre-set operating conditions, the corresponding test parameter sets for the operating conditions are input into the frame structure finite element model and the optimized proxy model, respectively, to obtain the second stress and deformation simulation values ​​and the corresponding stress and deformation prediction values ​​for the operating conditions. For details, please refer to step S205 of the embodiment shown in Figure 2, which will not be repeated here.

[0090] In step S306, if the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy the preset accuracy conditions, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the predicted stress and deformation values ​​for the corresponding operating conditions.

[0091] Specifically, step S306 above includes steps S3061 to S3063 below.

[0092] Step S3061: Calculate the first relative error between the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions.

[0093] Specifically, the absolute error between the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions is calculated. Then, the ratio of the absolute error to the second stress and deformation simulation values ​​is calculated, and this is multiplied by 100% to obtain the first relative error.

[0094] In step S3062, it is determined whether the first relative error satisfies the preset accuracy conditions.

[0095] Specifically, the pre-set accuracy conditions can be set according to the actual situation and are not specifically limited here. For example, in this embodiment, the accuracy conditions are set to be 10% or less, less than 10%, or equal to 10%. It is determined whether the first relative error is 10% or less.

[0096] The accuracy detection metric for the model is the coefficient of determination (R). 2Select the following, which is given by equation (19). JPEG0007900119000016.jpg54170R 2 The closer this value is to 1, the higher the prediction accuracy of the optimized proxy model.

[0097] In step S3063, if the first relative error satisfies the preset accuracy conditions, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the stress and deformation prediction values ​​for the corresponding operating conditions.

[0098] Specifically, when the first relative error is 10% or less, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored in real time using predicted stress and deformation values ​​for the corresponding operating conditions.

[0099] In selectable embodiments, step S3063 includes the following steps a1 to a3.

[0100] Step a1: If the first relative error satisfies the preset accuracy conditions, measured stress and deformation values ​​of the pumped-storage hydroelectric power plant unit frame under the corresponding operating conditions are collected.

[0101] Specifically, as shown in Figure 4, in order to more accurately verify the accuracy of the predicted stress and deformation values ​​for the corresponding operating conditions, if the first relative error is 10% or less, the measured stress and deformation values ​​of the pumped-storage power generation unit frame for the corresponding operating conditions are collected when the pumped-storage power generation unit is operating under those conditions.

[0102] Step a2: Calculate the second relative error between the measured stress and deformation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions.

[0103] Specifically, the measured stress and deformation values ​​are obtained from real-time monitoring data collected by sensors attached to the frame of the pumped-storage hydroelectric power unit in situ. The absolute error between the measured stress and deformation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions is calculated, then the ratio of the absolute error to the measured stress and deformation values ​​is calculated, and this is further multiplied by 100% to obtain the second relative error.

[0104] Step a3: If the second relative error satisfies the preset accuracy conditions, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the corresponding stress and deformation prediction values ​​for the operating conditions.

[0105] Specifically, if the second relative error also meets the set accuracy condition, i.e., 10% or less, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored in real time using the stress and deformation prediction values ​​for the corresponding operating conditions.

[0106] In the pumped-storage hydroelectric power unit frame structure monitoring method according to this embodiment, if the first relative error satisfies the preset accuracy conditions, the accuracy verification of the second relative error between the measured stress and deformation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions is continued. If the second relative error satisfies the preset accuracy conditions, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the predicted stress and deformation values ​​for the corresponding operating conditions. This improves the accuracy of the verification of the predicted stress and deformation values ​​for the corresponding operating conditions, and makes the monitoring of the pumped-storage hydroelectric power unit frame structure using the predicted stress and deformation values ​​for the corresponding operating conditions more accurate.

[0107] In step S307, if the first relative error does not meet the preset accuracy conditions, the second stress and deformation simulation values ​​are added as additional data to the sample data points to obtain additional sample data points, and the optimized proxy model is updated based on the additional sample data points.

[0108] Specifically, as shown in Figure 4, if the first relative error does not meet the preset accuracy conditions, stress and deformation simulation values ​​are added as additional data to the sample data points to obtain additional sample data points in order to further optimize the optimized model. The optimized proxy model is then updated based on these additional sample data points.

[0109] In step S308, if the second relative error does not meet the preset accuracy conditions, the frame structure finite element model is updated using a preset correction coefficient, and the measured stress and deformation values ​​are added as additional data to the sample data points to obtain additional sample data points. The optimized proxy model is then updated based on these additional sample data points.

[0110] Specifically, if the second relative error does not meet the preset accuracy conditions, it means that there is a large error between the predicted stress and deformation values ​​and the measured stress and deformation values. This reflects the inaccuracy of the obtained predicted stress and deformation values, and further reflects the inaccuracy of the first stress and deformation simulation values ​​obtained from the frame structure finite element model. When the first simulation values ​​are input into a preset initialization model and optimized, the resulting optimized proxy model also becomes inaccurate. To improve the accuracy of both the frame structure finite element model and the optimized proxy model, as shown in Figure 5, the frame structure finite element model is updated using a preset correction coefficient, the measured stress and deformation values ​​are added as additional data to the sample data points to obtain additional sample data points, and the optimized proxy model is updated based on the additional sample data points, further improving the simulation accuracy of the frame structure finite element model and the prediction accuracy of the optimized proxy model.

[0111] The method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to this embodiment further optimizes the frame structure finite element model, improves the simulation accuracy of the finite element model, further optimizes the proxy model optimized by the additional sample data points, and further improves the prediction accuracy of the optimized proxy model, if the first relative error does not meet the preset accuracy conditions, by adding the stress and deformation simulation values ​​as additional data to the sample data points to obtain additional sample data points, and updating the optimized proxy model based on the additional sample data points. Alternatively, if the second relative error does not meet the preset accuracy conditions, the frame structure finite element model is updated using a preset correction coefficient, and the simulation accuracy of the finite element model is further optimized by the additional sample data points, further improving the prediction accuracy of the optimized proxy model.

[0112] As one or more specific application examples of the present invention, a method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame will be further described with reference to Figures 4, 5, and 6, and is specifically as follows.

[0113] Specific process of a preferred embodiment shown in Figure 4: 1. Acquisition of structural parameters of the pumped-storage hydroelectric power plant unit frame and operating parameters under multiple operating conditions: Step S1: Based on the higher-level scheduling command, identify the operating characteristics of the pumped-storage power unit under each operating condition. Step S2: Collect monitoring history data of the pumped-storage power generation unit's status. Step S3: Statistically analyze and clarify the characteristic parameters of the operating load of the pumped-storage hydroelectric power plant unit frame. Step S4: Based on Steps S1 to S3, determine the range of stress and deformation of the pumped-storage hydroelectric power unit frame, determine the hazardous operating conditions of the pumped-storage hydroelectric power unit frame, and determine the characteristic parameters of the proxy model. The characteristic parameters include, but are not limited to, parameters such as rotational speed, flow rate, and working head. Divide the characteristic parameters into a simulation parameter set and a test parameter set.

[0114] 2. Process of static simulation analysis based on the finite element method: Step S1: Creation of a finite element simulation model for frame miniaturization: Based on rules such as geometric dimensions, material attributes, and contact connection relationships, a finite element simulation model of the frame structure, including the frame and its ancillary members, is created using the APDL parametric programming language. The process for creating the frame structure finite element simulation model is as follows: Step S11: Based on the design data of the pumped-storage hydroelectric power unit or 3D scanning technology, create a 3D geometric solid model of the frame using CAD software. Step S12: Set the material attributes of the pumped-storage hydroelectric power unit frame, including density, elastic modulus, and Poisson's ratio. Step S13: Discretize the three-dimensional geometric solid model of the pumped-storage hydroelectric power plant unit frame using the SOLID187 unit to obtain a finite element mesh model, and create a refined frame structure finite element simulation model including the geometric dimensions of the frame, material attributes and its attached components using the APDL parametric programming language. Step S14: After analyzing the load conditions during actual operation of the pumped-storage hydroelectric power unit frame, loads are applied. The pumped-storage hydroelectric power unit frame is mainly subjected to the gravity of its own structure and accessories and axial water thrust. Gravity includes the weight of the frame itself, the weight of rotating members such as runners, and the gravity of accessories such as thrust bearings and oil tanks. Axial water thrust includes the combined force of the water impact force and water buoyancy acting on the runners. Approximate values ​​can be obtained based on the empirical formula for the axial water thrust of a Francis turbine, or accurate values ​​can be obtained by numerical simulation calculations using CFD. The empirical formula is, The filename is JPEG0007900119000017.jpg16170. Here, λ is a correction coefficient, and according to experimental data in related technologies, it has been found that under normal operating conditions, it increases with increasing output and flow rate of the pumped-storage power generation unit, with a range of 0.7 to 0.8. It is recommended to set the value to 0.75 ± 0.01 at rated output, to 0.77 ± 0.01 when exceeding rated output, and to set the value to a fixed value of 1 ± 0.01 under load dump operating conditions. ω Q is the rotational speed of the pumped-storage hydroelectric power unit, in units of rpm, and Q is the flow rate of the unit, in units of m 3 / s, H is the working head of the extraction unit frame, in units of m, and D1 is the nominal diameter of the runner, in units of m.

[0115] According to the frame structure finite element model, the finite element model is subjected to different loads under different operating conditions during the finite element analysis process, and the magnitude of the operating load needs to be determined according to the operating conditions.

[0116] Step S2: Based on the frame structure finite element model, static simulation analysis is performed on sample data points under major operating conditions. The simulation output data is the first stress-deformation simulation data, which is used to optimize a pre-set initial proxy model. The sample data points are obtained from initial sample input data determined by sampling from simulation parameter sets for multiple operating conditions using the Latin hypercube sampling algorithm.

[0117] Step S3: Based on the first stress-deformation simulation data output by the static analysis, a stress-deformation cloud map of the entire frame is obtained using the finite element method, and weak points in the frame can be identified from the stress-deformation cloud map.

[0118] 3. Real-time monitoring process based on an optimized proxy model: Step S1: Within the range of the simulation parameter set, initial sample input data is obtained by sampling using the Latin hypercube sampling algorithm. This data is then combined with the first stress-deformation simulation values ​​output by the finite element simulation results to create sample data points for the input data and the corresponding first stress-deformation simulation values.

[0119] Step S2: Optimize the initial proxy model (i.e., the Kriging model) pre-configured with sample data points to obtain the optimized proxy model. The specific process is as follows:

[0120] Step S21: Input the corresponding operating condition input data, the first stress and deformation simulation values ​​for the corresponding operating conditions as sample data points into the pre-set initial proxy model, obtain the relevant parameters of the initial proxy model, In the Kriging model, the response value and the independent variable satisfy the relationship given by equation (2). JPEG0007900119000018.jpg14170 Here, x = (x1, x2, ..., x n ) T is the input data for any corresponding operating conditions, n is the number of sample data points, y(x) is the corresponding predicted response value, and β is the input data for any corresponding operating conditions. i (i=1,2,…,n) are the estimated regression coefficients, and f i (x)(i=1,2,…,n) is a basis function vector of a polynomial, and z(x) is N(0,σ 2 A Gaussian random function that follows the rule, where any two sample data points x in a sample data point i and x j The covariances are added using equation (3), JPEG0007900119000019.jpg9170 Here, Cov is the covariance operation, and R(θ,x i , x j ) is sample data point x i and x j This is a correlation function that characterizes the spatial correlation, where θ = [θ1, θ2, ..., θ n ] T This is the related parameter vector, The correlation function may be a linear function, an exponential function, or a Gaussian function. The Gaussian function is generally calculated using equation (4): JPEG0007900119000020.jpg28170 Here, N is the dimension of x, and θ n is an unknown related parameter of the Kriging model, and d n xj represents the distance between sample data points xi and xj, and is shown in equation (5).

[0121] Step S22: Calculate the optimal solution for the relevant parameters using the Pelican optimization algorithm. Specifically, after determining the correlation function, the predictions of the Kriging model can be further explained as follows: JPEG0007900119000021.jpg31170r T (x * ) can be expressed as follows: According to the Kriging model, unknown data point x * The mean squared error or standard deviation s in 2 To predict, that is, JPEG0007900119000023.jpg11170 Here, s 2 θ is the mean squared error or standard deviation, representing the predicted deviation between the Kriging model and the actual response value, and is calculated using the Pelican optimization algorithm. n By solving this, we can obtain an optimized Kriging model. Related parameter θ n The mathematical model for optimization is as follows: JPEG0007900119000024.jpg86170 Solve equation (11) using the Pelican optimization algorithm.

[0122] Step S3: Optimize the initial proxy model using the optimal solution to obtain the optimized proxy model.

[0123] In other words, by using a mathematical model for optimizing the θn of the proxy model and combining it with the Pelican optimization algorithm, the optimal solution for θn is obtained, forming an optimized Kriging proxy model.

[0124] Step S4: As shown in Figure 4, under pre-set operating conditions, the test parameter sets are input into the frame structure finite element model for simulation analysis, input into the optimized proxy model for stress and deformation prediction, and the second stress and deformation simulation values ​​and stress and deformation prediction values ​​are obtained. The accuracy of the second stress and deformation simulation values ​​and stress and deformation prediction values ​​is verified using equation (19) to determine whether the accuracy requirements are met. If the accuracy requirements are not met, S5 is executed. If the accuracy requirements are met, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the stress and deformation prediction values ​​for the corresponding operating conditions. The accuracy detection metric for the model is the coefficient of determination (R). 2 Select the following, which is given by equation (19). JPEG0007900119000025.jpg65170

[0125] Step S5: Stress and deformation simulation values ​​are added as additional data to the sample data points to obtain additional sample data points, and the optimized proxy model is updated based on the additional sample data points to further improve the prediction accuracy of the optimized proxy model.

[0126] In another preferred embodiment, as shown in Figure 5, the remaining process is the same as in the preferred embodiment shown in Figure 4, in which the accuracy verification is set up in two stages: the first stage is the verification of the second stress and deformation simulation values ​​against the stress and deformation prediction values, and the second stage is the verification of the measured stress and deformation values ​​against the stress and deformation prediction values. The measured stress and deformation values ​​are obtained from real-time monitoring data collected by sensors attached to the in-situ frame of the pumped-storage hydroelectric power unit.

[0127] S4: Under pre-set operating conditions, the test parameter sets are input into the frame structure finite element model for simulation analysis, then input into the optimized proxy model for stress and deformation prediction, obtaining the second stress and deformation simulation values ​​and stress and deformation prediction values, and performing a relative error analysis between the second stress and deformation simulation values ​​and the stress and deformation prediction values ​​to determine whether the accuracy requirements are met.

[0128] S41: First stage accuracy verification: This is the accuracy verification of the second stress and deformation simulation values ​​and the stress and deformation prediction values. If the accuracy requirements are not met, S5 is executed; if the accuracy requirements are met, S42 is executed.

[0129] S42: Second stage accuracy verification: This involves verifying the accuracy of the measured stress and deformation values ​​against the predicted stress and deformation values. If the accuracy requirements are not met, the frame structure finite element model is updated using a pre-set correction factor, and the finite element simulation analysis process is rerun.

[0130] S5: Stress and deformation simulation values ​​are added as additional data to the sample data points to obtain additional sample data points, and the optimized proxy model is updated based on the additional sample data points to further improve the prediction accuracy of the optimized proxy model.

[0131] In yet another preferred embodiment, as shown in Figure 6, the remaining process is the same as in the preferred embodiment shown in Figure 4, and accuracy verification is set up in two stages: the first stage is verification of the second stress and deformation simulation values ​​against the stress and deformation prediction values, and the second stage is verification of the stress and deformation measured values ​​against the stress and deformation prediction values. The stress and deformation measured values ​​are obtained from real-time monitoring data collected by sensors attached to the in-situ frame of the pumped-storage hydroelectric power unit.

[0132] The differences are explained below.

[0133] S4: Under pre-set operating conditions, the test parameter sets are input into the frame structure finite element model for simulation analysis, then input into the optimized proxy model for stress and deformation prediction, obtaining the second stress and deformation simulation values ​​and stress and deformation prediction values, and performing a relative error analysis between the second stress and deformation simulation values ​​and the stress and deformation prediction values ​​to determine whether the accuracy requirements are met.

[0134] S41: First stage accuracy verification: This is the accuracy verification of the second stress and deformation simulation values ​​and the stress and deformation prediction values. If the accuracy requirements are not met, S5 is executed; if the accuracy requirements are met, S42 is executed.

[0135] S42: Second stage accuracy verification: This involves verifying the accuracy of the measured stress and deformation values ​​against the predicted stress and deformation values. If the accuracy requirements are not met, S6 is executed.

[0136] S5: Stress and deformation simulation values ​​are added as additional data to the sample data points to obtain additional sample data points, and the optimized proxy model is updated based on the additional sample data points to further improve the prediction accuracy of the optimized proxy model.

[0137] S6: Additional sample data points are obtained by adding measured stress and deformation values ​​as additional data to the sample data points. The optimized proxy model is then updated based on these additional sample data points to further improve the prediction accuracy of the optimized proxy model.

[0138] The method for monitoring the structure of a pumped-storage hydroelectric power unit frame according to this embodiment involves performing a simulation analysis on a simulation parameter set for the corresponding operating conditions using a frame structure finite element model to obtain first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame. An optimized proxy model is obtained based on the first stress and deformation simulation values ​​and the extracted simulation parameter set for the corresponding operating conditions. Under preset operating conditions, the test parameter set for the corresponding operating conditions is input into the frame structure finite element model and the optimized proxy model, respectively, to obtain second stress and deformation simulation values ​​and predicted stress and deformation values ​​for the corresponding operating conditions. If the second stress and deformation simulation values ​​and predicted stress and deformation values ​​for the corresponding operating conditions satisfy preset accuracy conditions, the stress and deformation of the pumped-storage hydroelectric power unit frame are monitored using the predicted stress and deformation values ​​for the corresponding operating conditions. This achieves the objective of comprehensively and in real time monitoring the stress and deformation status at each position of the pumped-storage hydroelectric power unit frame under various operating conditions. The set accuracy verification further improves the prediction accuracy of the frame structure finite element model and the optimized proxy model, providing an accurate model foundation for subsequent monitoring of the stress and deformation of the pumped-storage hydroelectric power unit frame.

[0139] This embodiment further provides a structural monitoring device for a pumped-storage hydroelectric power plant unit frame, which is used to implement the above embodiment and preferred embodiments, and will not be repeated what has already been described. Hereafter, the term "module" refers to a combination of software and / or hardware that can implement a predetermined function. While the devices described in the following embodiments are preferably implemented in software, they can also be implemented in hardware, or a combination of software and hardware, and are conceived accordingly.

[0140] This embodiment provides a structural monitoring device for a pumped-storage hydroelectric power unit frame, and as shown in Figure 7, includes an acquisition module 701 for acquiring structural parameters and operating parameters for multiple operating conditions of the pumped-storage hydroelectric power unit frame, an acquisition module 701 for constructing a frame structure finite element model based on the structural parameters and operating parameters for multiple operating conditions, extracting characteristic parameters for multiple operating conditions based on the operating parameters for multiple operating conditions, and dividing the characteristic parameters for multiple operating conditions into a test parameter set for multiple operating conditions and a simulation parameter set for multiple operating conditions, and a simulation module for performing simulation analysis on the corresponding simulation parameter set for the operating conditions based on the frame structure finite element model under pre-set operating conditions, and obtaining the first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame. The system includes a module 703, an optimization module 704 for optimizing a pre-set initial proxy model based on characteristic parameters of the simulation parameter set for the corresponding operating conditions and the first stress and deformation simulation values ​​for the corresponding operating conditions to obtain an optimized proxy model, a test module 705 for inputting the test parameter set for the corresponding operating conditions into the frame structure finite element model and the optimized proxy model, respectively, under pre-set operating conditions to obtain the second stress and deformation simulation values ​​and the predicted stress and deformation values ​​for the corresponding operating conditions, respectively, and a monitoring module 706 for monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​for the corresponding operating conditions if the second stress and deformation simulation values ​​and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy pre-set accuracy conditions.

[0141] The structural parameters of the pumped-storage hydroelectric power unit frame include the geometric dimensions, material attributes, and structural connection relationships of the pumped-storage hydroelectric power unit frame, and the operating parameters for multiple operating conditions of the pumped-storage hydroelectric power unit frame include the operating loads under multiple operating conditions. Construction module 702 is further used to construct a finite element model of the frame structure under multiple operating conditions, based on the geometric dimensions, material attributes, structural connection relationships, and operating loads under multiple operating conditions of the pumped-storage hydroelectric power unit frame, using a parametric programming language.

[0142] In some selectable embodiments, the simulation module 703 includes a first sampling unit for obtaining input data for the corresponding operating conditions by sampling a set of simulation parameters for the corresponding operating conditions using a Latin hypercube sampling algorithm under preset operating conditions, and a simulation unit for inputting the input data for the corresponding operating conditions into a frame structure finite element model to perform static simulation analysis and obtain first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame.

[0143] In some selectable embodiments, the optimization module 704 includes: a second sampling unit for obtaining input data for corresponding operating conditions by sampling characteristic parameters of the simulation parameter set for corresponding operating conditions using a Latin hypercube sampling algorithm under preset operating conditions; an input unit for inputting the input data for corresponding operating conditions, the first stress and deformation simulation values ​​for corresponding operating conditions as sample data points into a preset initial proxy model to obtain relevant parameters of the initial proxy model; a first calculation unit for calculating the optimal solution of the relevant parameters using a Pelican optimization algorithm; and an optimization unit for optimizing the initial proxy model using the optimal solution to obtain an optimized proxy model.

[0144] In some selectable embodiments, the monitoring module 706 includes a second calculation unit for calculating a first relative error between a second stress and deformation simulation value for a corresponding operating condition and a predicted stress and deformation value for a corresponding operating condition; a determination unit for determining whether the first relative error satisfies a preset accuracy condition; and, if the first relative error satisfies the preset accuracy condition, a monitoring unit for monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation value for a corresponding operating condition.

[0145] In some selectable embodiments, the monitoring unit includes a collection subunit for collecting measured stress and deformation values ​​of the pumped-storage hydroelectric power unit frame under corresponding operating conditions, provided that a first relative error satisfies a preset accuracy condition; a calculation subunit for calculating a second relative error between the measured stress and deformation values ​​and the predicted stress and deformation values ​​under corresponding operating conditions; and a monitoring subunit for monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​under corresponding operating conditions, provided that the second relative error satisfies a preset accuracy condition.

[0146] The structure monitoring device for the pumped-storage hydroelectric power unit frame further includes a first update module for updating an optimized proxy model based on the additional sample data points by adding stress and deformation simulation values ​​as additional data to the sample data points if the first relative error does not meet the preset accuracy conditions, and a second update module for updating the frame structure finite element model using a preset correction coefficient, adding measured stress and deformation values ​​as additional data to the sample data points to obtain additional sample data points, and updating an optimized proxy model based on the additional sample data points if the second relative error does not meet the preset accuracy conditions.

[0147] Further functional descriptions of each of the above modules and units are the same as those in the corresponding embodiments described above, so we will omit any redundant explanations here.

[0148] In this embodiment, the structure monitoring device for the pumped-storage hydroelectric power plant unit frame is presented in the form of a functional unit, where a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices capable of providing the above functions.

[0149] An embodiment of the present invention further provides a computer device having a structural monitoring device for the pumped-storage hydroelectric power plant unit frame shown in Figure 7.

[0150] As shown in Figure 8, which is a schematic diagram of the structure of a computer device according to an optional embodiment of the present invention, the computer device includes one or more processors 10, memory 20, and interfaces for connecting each component, including a high-speed interface and a low-speed interface. Each component communicates with each other via different buses and may be mounted on a common motherboard or otherwise mounted as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory for displaying GUI graphic information to an external input / output device (e.g., a display device coupled to the interface). In some optional embodiments, multiple processors and / or multiple buses may be used together with multiple memories as needed. Similarly, multiple computer devices may be connected, each providing a portion of the required operations (e.g., functioning as a server array, a set of blade servers, or a multiprocessor system). Figure 8 takes one processor 10 as an example.

[0151] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include hardware chips. The hardware chips may be application-specific integrated circuits, programmable logic devices, or a combination thereof. The programmable logic devices may be complex programmable logic devices, field programmable logic gate arrays, generic array logic, or any combination thereof.

[0152] In this configuration, the memory 20 stores instructions that can be executed by at least one processor 10, thereby causing the at least one processor 10 to execute and implement the method shown in the above embodiment.

[0153] Memory 20 may include an operating system, a program storage area capable of storing application programs required for at least one function, and a data storage area capable of storing data created in accordance with the use of the computer equipment. Memory 20 may also include high-speed random-access memory and may further include non-temporary memory such as at least one disk storage device, flash memory device, or other non-temporary solid-state storage device. In some optional embodiments, memory 20 may optionally include memory remotely installed relative to the processor 10, and these remote memories may be connected to the computer equipment via a network. Examples of such networks include, but are not limited to, the Internet, a corporate intranet, a local area network, a mobile communication network, and combinations thereof.

[0154] Memory 20 may include volatile memory such as random access memory, or non-volatile memory such as flash memory, hard disk, or solid-state drive, and memory 20 may include a combination of the above types of memory.

[0155] The computer equipment further includes an input device 30 and an output device 40. The processor 10, memory 20, input device 30 and output device 40 can be connected by a bus or other means, with Figure 8 showing a bus connection as an example.

[0156] The input device 30 can receive input numerical or character information and generate input key signals relating to user settings and function control of the computer equipment, such as a touchscreen, keypad, mouse, trackpad, pointing stick, one or more mouse buttons, trackball, joystick, etc. The output device 40 may include a display device, auxiliary lighting device (e.g., LEDs), and haptic feedback device (e.g., vibration motor), etc. The display device includes, but is not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some optional embodiments, the display device may be a touchscreen.

[0157] Embodiments of the present invention further provide a computer-readable storage medium, and the methods according to the embodiments of the present invention may be implemented in hardware and firmware, or may be implemented in a recordable manner on a storage medium, or may be implemented as computer code downloaded over a network, originally stored on a remote storage medium or a non-temporary machine-readable storage medium but stored on a local storage medium, thereby the methods described herein may be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Here, the storage medium may be a magnetic disk, an optical disk, read-only memory, random access memory, flash memory, a hard disk, or a solid-state drive, and furthermore, the storage medium may include a combination of the above types of memory. Understandably, the computer, processor, microprocessor controller, or programmable hardware includes a storage component capable of storing or receiving software or computer code, and when the software or computer code is accessed and executed by the computer, processor, or hardware, the methods described in the embodiments are implemented.

[0158] While embodiments of the present invention have been described with reference to the drawings, those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention, and any such changes and modifications will fall within the scope defined in the attached claims.

Claims

1. A method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame, The steps include obtaining the structural parameters of the pumped-storage hydroelectric power plant unit frame and the operating parameters of multiple operating conditions, A step of constructing a frame structure finite element model based on the structural parameters and operating parameters of multiple operating conditions, extracting feature parameters of multiple operating conditions based on the operating parameters of multiple operating conditions, and dividing the feature parameters of multiple operating conditions into a test parameter set and a simulation parameter set of multiple operating conditions, wherein the structural parameters of the pumped-storage hydroelectric power unit frame include the geometric dimensions, material attributes and structural connection relationships of the pumped-storage hydroelectric power unit frame, and the operating parameters of the pumped-storage hydroelectric power unit frame for multiple operating conditions include the operating loads under multiple operating conditions. The steps include: performing a simulation analysis on a frame structure finite element model based on pre-set operating conditions to obtain the first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under the corresponding operating conditions; The steps include optimizing a pre-set initial proxy model based on the simulation parameter set for the corresponding operating conditions, the first stress and deformation simulation values ​​for the corresponding operating conditions, and obtaining an optimized proxy model, The process involves inputting the corresponding test parameter sets for pre-set operating conditions into the frame structure finite element model and the optimized proxy model, respectively, to obtain the second stress and deformation simulation values ​​and the corresponding stress and deformation prediction values ​​for the operating conditions. The step includes monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​for the corresponding operating conditions, provided that the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy the preset accuracy conditions. The step of constructing a frame structure finite element model based on the aforementioned structural parameters and the operating parameters of multiple operating conditions is: A method for monitoring the structure of a pumped-storage hydroelectric power unit frame, characterized by including the step of constructing a finite element model of the frame structure under multiple operating conditions based on the geometric dimensions, material attributes, structural connection relationships, and operating loads of the pumped-storage hydroelectric power unit frame, using a parametric programming language.

2. The step of performing a simulation analysis on a corresponding set of simulation parameters based on a frame structure finite element model under pre-set operating conditions to obtain the first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame is as follows: The steps include: obtaining input data for the corresponding operating conditions by sampling the simulation parameter set for the corresponding operating conditions using a Latin hypercube sampling algorithm under pre-set operating conditions; The method according to claim 1, characterized by comprising the step of inputting the corresponding operating condition input data into a frame structure finite element model and performing a static simulation analysis to obtain first stress and deformation simulation values ​​for the corresponding operating conditions of the pumped-storage hydroelectric power unit frame.

3. The step of optimizing a preset initial proxy model based on the corresponding simulation parameter set for the operating conditions, the first stress and deformation simulation values ​​for the corresponding operating conditions, and obtaining an optimized proxy model is as follows: The steps include: obtaining input data for the corresponding operating conditions by sampling characteristic parameters of the simulation parameter set for the corresponding operating conditions using a Latin hypercube sampling algorithm under pre-set operating conditions; The steps include inputting the corresponding operating conditions as input data, the first stress and deformation simulation values ​​for the corresponding operating conditions as sample data points into a pre-configured initial proxy model, and obtaining the relevant parameters of the initial proxy model, The steps include: calculating the optimal solution for the relevant parameters using the Pelican optimization algorithm, The method according to claim 1, further comprising the steps of optimizing the initial proxy model using the optimal solution to obtain an optimized proxy model.

4. If the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy the preset accuracy conditions, the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​for the corresponding operating conditions is as follows: The steps include calculating a first relative error between the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions, A step of determining whether the first relative error satisfies a predetermined accuracy condition, The method according to claim 3, further comprising the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using stress and deformation prediction values ​​for the corresponding operating conditions, provided that the first relative error satisfies a preset accuracy condition.

5. If the first relative error satisfies the preset accuracy conditions, the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the stress and deformation prediction values ​​for the corresponding operating conditions is as follows: If the first relative error satisfies the preset accuracy conditions, the step is to collect measured stress and deformation values ​​of the pumped-storage hydroelectric power unit frame under the corresponding operating conditions. The steps include calculating a second relative error between the measured stress and deformation values ​​under the corresponding operating conditions and the predicted stress and deformation values ​​under the corresponding operating conditions, The method according to claim 4, further comprising the step of monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using stress and deformation prediction values ​​for the corresponding operating conditions, provided that the second relative error satisfies a preset accuracy condition.

6. If the first relative error does not satisfy the preset accuracy conditions, the second stress and deformation simulation values ​​are added as additional data to the sample data points to obtain additional sample data points, and the optimized proxy model is updated based on the additional sample data points. Or, The method according to claim 5, further comprising the step of updating the frame structure finite element model using a preset correction coefficient if the second relative error does not satisfy a preset accuracy condition, and adding the measured stress and deformation values ​​as additional data to the sample data points to obtain additional sample data points, and updating the optimized proxy model based on the additional sample data points.

7. A structural monitoring device for a pumped-storage hydroelectric power plant unit frame, An acquisition module for obtaining structural parameters of a pumped-storage hydroelectric power plant unit frame and operating parameters for multiple operating conditions, A construction module for constructing a frame structure finite element model based on the structural parameters and operating parameters for multiple operating conditions, extracting feature parameters for multiple operating conditions based on the operating parameters for multiple operating conditions, and dividing the feature parameters for multiple operating conditions into a test parameter set for multiple operating conditions and a simulation parameter set for multiple operating conditions, wherein the structural parameters of the pumped-storage hydroelectric power unit frame include the geometric dimensions, material attributes, and structural connection relationships of the pumped-storage hydroelectric power unit frame, and the operating parameters for multiple operating conditions of the pumped-storage hydroelectric power unit frame include the operating loads under multiple operating conditions, A simulation module for obtaining first stress and deformation simulation values ​​for the pumped-storage hydroelectric power unit frame under corresponding operating conditions by performing simulation analysis on a frame structure finite element model based on pre-set operating conditions and corresponding simulation parameter sets. An optimization module for optimizing a pre-set initial proxy model and obtaining an optimized proxy model based on the characteristic parameters of the simulation parameter set for the corresponding operating conditions, the first stress and deformation simulation values ​​for the corresponding operating conditions, and the optimization of the initial proxy model. A test module is provided to input the corresponding test parameter sets for pre-set operating conditions into a frame structure finite element model and an optimized proxy model, respectively, and to obtain the second stress and deformation simulation values ​​and the corresponding stress and deformation prediction values ​​for the operating conditions. The system includes a monitoring module for monitoring the stress and deformation of the pumped-storage hydroelectric power unit frame using the predicted stress and deformation values ​​for the corresponding operating conditions, provided that the second stress and deformation simulation values ​​for the corresponding operating conditions and the predicted stress and deformation values ​​for the corresponding operating conditions satisfy the preset accuracy conditions. The step of constructing a frame structure finite element model based on the aforementioned structural parameters and the operating parameters of multiple operating conditions is: A structural monitoring device for a pumped-storage hydroelectric power plant unit frame, characterized by including the step of constructing a finite element model of the frame structure under multiple operating conditions based on the geometric dimensions, material attributes, structural connection relationships, and operating loads of the pumped-storage hydroelectric power plant unit frame, using a parametric programming language.

8. Computer equipment, A computer device comprising memory and a processor, wherein the memory and the processor are communicateable, computer instructions are stored in the memory, and the processor executes the computer instructions to perform the method for monitoring the structure of a pumped-storage hydroelectric power plant unit frame according to any one of claims 1 to 6.

9. A computer-readable storage medium characterized in that it stores computer instructions for causing a computer to execute the method for monitoring the structure of a pumped-storage hydroelectric power unit frame described in any one of claims 1 to 6.

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