A method and related apparatus for dynamic modeling and modal calibration of hydraulic turbines

Abstract

This invention discloses a method and related apparatus for dynamic modeling and modal calibration of a hydro-turbine, comprising: constructing a multi-degree-of-freedom dynamic model of a hydro-turbine rotor-bearing-foundation system; introducing multi-source coupled excitation into the multi-degree-of-freedom dynamic model; performing numerical simulation calculations on the multi-degree-of-freedom dynamic model to obtain numerical simulation results; and calibrating the key parameters of the multi-degree-of-freedom dynamic model based on actual machine modal test results using a parameter sensitivity correction and iterative calibration algorithm, thereby achieving automatic matching between the numerical simulation results and the actual machine modal test results to obtain a calibrated multi-degree-of-freedom dynamic model. This method and related apparatus can achieve high-precision modeling and rapid convergence.

Description

Technical Field

[0001] This invention belongs to the field of vibration characteristics research and engineering application of hydropower equipment, and relates to a method and related device for dynamic modeling and modal calibration of hydro turbines. Background Technology

[0002] As the core power equipment of a hydropower station, the turbine experiences complex fluid-structure interaction phenomena and various external disturbances during operation, including hydraulic pulse forces, electromagnetic forces, and bearing oil film forces. Under these multi-source excitations, the vibration characteristics of the turbine structure significantly affect the stability and safety of the unit.

[0003] Existing research typically employs the finite element method to establish dynamic models or obtains the natural frequencies and damping ratios of structures through modal tests. However, a single modeling method cannot fully reflect the multi-source coupling effects under actual operating conditions, leading to discrepancies between the critical speeds and modal parameters predicted by the model and the measured results. Furthermore, traditional modal calibration methods mostly rely on manual experience for correction, lacking systematic sensitivity analysis and automated calibration mechanisms, which easily results in low efficiency and unstable convergence.

[0004] Furthermore, in practical engineering, turbine modal testing is often subject to strong interference from the operating environment, such as power grid harmonics, frequency order components, and hydraulic pulsation noise. This further increases the difficulty of comparing and correcting numerical models with experimental results. How to establish a dynamic model that can couple multi-source excitations and combine it with automated modal calibration algorithms to achieve high-precision modeling and rapid convergence is a pressing technical problem to be solved in the field of turbine vibration analysis and optimization design. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and related apparatus for hydro turbine dynamics modeling and modal calibration, which can achieve high-precision modeling and rapid convergence.

[0006] To achieve the above objectives, this invention discloses a method for hydro-turbine dynamics modeling and modal calibration, comprising: Construct a multi-degree-of-freedom dynamic model of the turbine rotor-bearing-foundation system; Introduce multi-source coupled excitation into the multi-degree-of-freedom dynamic model; Numerical simulation calculations were performed on the aforementioned multi-degree-of-freedom dynamic model to obtain numerical simulation results; Based on the results of the actual machine modal test, the key parameters of the multi-degree-of-freedom dynamic model are calibrated using a parameter sensitivity correction and iterative calibration algorithm. This enables automatic matching between the numerical simulation results and the actual machine modal test results, resulting in a calibrated multi-degree-of-freedom dynamic model.

[0007] Furthermore, the multi-source coupled excitation adopts an equivalent stiffness-damping matrix modeling method, which unifies and superimposes the hydraulic pulsating force, electromagnetic force and oil film force into the multi-degree-of-freedom dynamic model.

[0008] Furthermore, the numerical simulation process is as follows: Solve the eigenvalue problem to obtain the natural frequencies and mode shapes; The unbalanced response can be obtained through harmonic response analysis or time-domain integration. Plot Campbell's diagram and stability criterion curves to identify critical speeds and vibration risks.

[0009] Furthermore, modal testing includes shutdown modal testing and in-service modal testing, which are used to obtain structural modal parameters by employing shock / vibration device testing and random vibration output modal analysis.

[0010] Furthermore, the parameter sensitivity correction and iterative calibration algorithm includes: Calculate the frequency deviation, damping difference, and modal similarity between the numerical mode and the experimental mode; Based on the sensitivity matrix, identify the model parameters that have the greatest impact on the differences; The bearing stiffness and connection boundary conditions are iteratively corrected until the error converges to a preset threshold.

[0011] Furthermore, the convergence criteria for the modal calibration are: modal frequency deviation less than 2%, damping ratio deviation less than 10%, and modal similarity greater than 0.9.

[0012] Furthermore, the method is applied to both the turbine design phase and the turbine operation phase.

[0013] This invention discloses a system for dynamic modeling and modal calibration of a hydro turbine, comprising: The building module is used to construct a multi-degree-of-freedom dynamic model of the turbine rotor-bearing-foundation system; An introduction module is used to introduce multi-source coupled excitation into the multi-degree-of-freedom dynamic model; The calculation module is used to perform numerical simulation calculations on the multi-degree-of-freedom dynamic model and obtain numerical simulation results; The calibration module is used to calibrate the key parameters of the multi-degree-of-freedom dynamic model based on the results of actual machine modal tests, using parameter sensitivity correction and iterative calibration algorithms. This enables automatic matching between numerical simulation results and actual machine modal test results, resulting in a calibrated multi-degree-of-freedom dynamic model.

[0014] This invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the turbine dynamics modeling and modal calibration method.

[0015] The present invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the turbine dynamics modeling and modal calibration method.

[0016] The present invention has the following beneficial effects: The turbine dynamics modeling and modal calibration method and related apparatus described in this invention, in practical operation, unifies the introduction of multi-source excitation into a multi-degree-of-freedom dynamic model, and combines parameter sensitivity analysis and iterative calibration algorithms to achieve high-precision matching between the turbine numerical model and the actual machine modes. Compared with traditional methods that rely on single modeling or manual experience correction, this invention not only significantly improves the accuracy of modal frequency, damping, and mode shape prediction, but also has the advantages of automation and strong convergence. It can provide a basis for structural optimization and critical speed avoidance in the design stage, and provide support for health monitoring and fault early warning in the operation stage, thereby improving the safety and reliability of the turbine throughout its entire life cycle. Attached Figure Description

[0017] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart of the method of the present invention; Figure 2 For Campbell's image; Figure 3 A bar chart comparing the numerical simulation frequencies and measured frequencies of the third-order mode; Figure 4 This is a comparison chart of Modal Assurance Criteria (MAC). Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0020] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0021] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0022] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0023] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0025] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0026] Example 1 refer to Figure 1 The turbine dynamics modeling and modal calibration method of the present invention includes the following steps: 1) Establish a multi-source coupled dynamic model; 11) Construct a multi-degree-of-freedom dynamic model of the turbine rotor-bearing-foundation system and represent it using the lumped parameter method or the finite element method.

[0027] 12) The system dynamic equations are established as follows:

[0028] Where M is the mass matrix, representing the lumped mass or finite element mass of structural units such as rotors, impellers, and foundations; C is the damping matrix, including structural damping, oil film damping, and water-added damping; K is the stiffness matrix, including shaft stiffness, foundation stiffness, and support constraint stiffness; x(t) is the system displacement vector, containing displacement responses of different degrees of freedom; and F(t) is the external excitation vector, representing the dynamic load generated by hydraulic pulsation, electromagnetic force, and oil film force.

[0029] 13) Introduce multi-source coupled excitation into the system equations:

[0030] Among them, F h(t) represents the hydraulic pulse force, including fluid-structure interaction effects such as non-uniform flow in the volute, vortex zone in the draft tube, and blade passing frequency (BPF); F e (t) represents the electromagnetic force, mainly composed of electromagnetic tension and harmonic components caused by the non-uniformity of the stator electromagnetic field; F o (t) represents the oil film force, used to reflect the nonlinear oil film effect generated by water-guided bearings and thrust bearings.

[0031] 14) Each excitation is introduced using the equivalent stiffness-damping form:

[0032] Where ΔK h ΔC h These represent the changes in equivalent stiffness and damping caused by hydraulic pulsation, respectively. ΔK e ΔC e ΔK represents the changes in equivalent stiffness and damping under electromagnetic force, respectively. o ΔC o These represent the changes in equivalent stiffness and damping introduced by the oil film force, respectively.

[0033] This results in the following system equations that include multi-source disturbances:

[0034] 2) Numerical simulation calculation; 21) Solve for the natural frequencies and mode shapes of the system through eigenvalue analysis:

[0035] Where ω is the natural frequency.

[0036] 22) Obtain the system response curve under unbalanced excitation by using harmonic response analysis or time-domain integration method.

[0037] 23) Draw the Campbell diagram, i.e. the speed-frequency relationship curve, identify the critical speed and the crossover point, and generate the stability criterion curve.

[0038] 3) Experiment; 31) Shutdown modal test: Using impact hammer method or electromagnetic exciter, the acceleration response is collected to obtain the inherent modal parameters under shutdown state.

[0039] 32) In-service modal test: Using random vibration output modal analysis (OMA), the operating response signals of the unit under different operating conditions are collected, and the in-service modal parameters are extracted by frequency domain decomposition (FDD) and random subspace identification (SSI-COV).

[0040] 33) Form a modal parameter database, including natural frequencies, damping ratios and mode shape information.

[0041] 4) Parameter sensitivity analysis; 41) Perform sensitivity analysis on the model parameters and calculate the effect of parameter changes on modal frequency and damping:

[0042] Wherein: S ij ω represents the relative sensitivity of the i-th modal frequency to the j-th parameter; i p is the frequency of the i-th mode; j For the j-th parameter of the model, such as bearing stiffness, foundation constraint stiffness, and oil film damping coefficient; ω i The partial derivative of the modal frequency with respect to the parameters reflects the intensity of the influence of parameter changes on the mode.

[0043] 42) Sort relative sensitivity to identify the parameters that have the greatest impact on modal differences, such as bearing stiffness, support boundary conditions and damping coefficient.

[0044] 5) Iterative calibration algorithm; 51) Calculate the deviation between the numerical mode and the experimental mode:

[0045] in, The i-th order frequency is calculated from the numerical model; The i-th frequency obtained from the experiment; Δω i The relative frequency deviation is (%). The damping ratio of the i-th order obtained from the numerical model; Δζ is the i-th order damping ratio obtained from the actual test. i The relative deviation of the damping ratio is (%). The i-th mode shape vector obtained from the numerical model calculation; is the vector of the i-th mode shape obtained from the experiment; MAC is the Modal Assurance Criterion, which takes values ​​of 0–1 and is used to measure the similarity between the numerical and experimental mode shapes.

[0046] 52) Adjust parameter p according to the sensitivity matrix. j for:

[0047] in, For the parameter p in the k-th iteration j The value; These are the parameters updated in the (k+1)th iteration; α is the iteration step size factor, used to control the correction magnitude and avoid divergence; The inverse of the sensitivity matrix is ​​used to calculate the direction of parameter correction; Δω i This represents the deviation between the numerical value and the experimental modal frequency.

[0048] 53) Iterate repeatedly until the convergence condition is met, that is: Frequency deviation less than 2%; Damping ratio deviation is less than 10%; Modal similarity (MAC) > 0.9.

[0049] 6) Model application; 61) Design phase: Use the calibrated model to predict the critical speed and modal changes under different operating conditions to guide structural optimization and risk avoidance.

[0050] 62) Operation phase: The operational modal parameters obtained from online monitoring are compared with the calibration model to achieve operational status assessment and early fault warning.

[0051] Example 2 This embodiment takes a 100MW bulb turbine as an example, with a rotational speed of 125r / min, and is equipped with a water guide bearing, a generator guide bearing, and a thrust bearing.

[0052] 1) Modeling: A finite element model of rotor-bearing-foundation is established. The rotor is simplified using beam elements, and the impeller and blades are equivalent in terms of lumped mass and stiffness. Constrained boundary conditions are applied to the frame and foundation. Hydraulic pulsation force (whirlpool frequency of approximately 0.3Hz in the tailrace pipe), electromagnetic force (stator current fundamental frequency of 50Hz and second harmonic), and oil film force (linearized from short bearing theory) are introduced into the dynamic equations to obtain the equivalent stiffness-damping matrix.

[0053] 2) Numerical Calculation: Through eigenvalue analysis, the first three natural frequencies of the model were obtained as 8.6Hz, 15.2Hz, and 28.4Hz, with corresponding damping ratios of 2.1%, 3.5%, and 4.0%. A Campbell's diagram was plotted, as shown below. Figure 2 As shown, the intersection of the frequency order and the second-order mode is identified near 125 r / min.

[0054] 3) Modal testing: Under shutdown conditions, the impact hammer test was used to obtain the first and second natural frequencies of 8.3Hz and 15.5Hz, respectively. Under in-service operation conditions, the modal parameters were obtained through output modal analysis (OMA), confirming that the third frequency is 27.9Hz.

[0055] 4) Sensitivity Analysis and Iterative Correction: The sensitivity matrix was calculated, and the results showed that the second-order frequency is most sensitive to the radial stiffness of the water-conducting bearing. An iterative correction algorithm was used to adjust the bearing radial stiffness from 2.0 × 10⁻⁶. 7 N / m adjusted to 2.3×10 7N / m, updated model calculation. The corrected second-order frequency is 15.4Hz, the frequency deviation is reduced to <1%, and the MAC value is greater than 0.92, meeting the convergence requirements.

[0056] like Figure 3 As shown, the deviations between the numerically calculated and measured modal frequencies for the first to third orders are all less than 0.5 Hz, verifying the effectiveness of the model calibration. Furthermore, as... Figure 4 As shown, the modal guarantee criterion (MAC) for the third mode is greater than 0.9, indicating that the numerical mode shape and the measured mode shape are highly consistent, proving that the method of the present invention is reliable in modal calibration.

[0057] 5) Application effect: The calibrated model can accurately predict critical speed and mode drift, and can be used for unit design optimization and operation status assessment.

[0058] Example 3 The turbine dynamics modeling and modal calibration system of the present invention includes: The building module is used to construct a multi-degree-of-freedom dynamic model of the turbine rotor-bearing-foundation system; An introduction module is used to introduce multi-source coupled excitation into the multi-degree-of-freedom dynamic model; The calculation module is used to perform numerical simulation calculations on the multi-degree-of-freedom dynamic model and obtain numerical simulation results; The calibration module is used to calibrate the key parameters of the multi-degree-of-freedom dynamic model based on the results of actual machine modal tests, using parameter sensitivity correction and iterative calibration algorithms. This enables automatic matching between numerical simulation results and actual machine modal test results, resulting in a calibrated multi-degree-of-freedom dynamic model.

[0059] The module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in each embodiment of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0060] Example 4 A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a hydro-turbine dynamics modeling and modal calibration method. For example, the steps include: constructing a multi-degree-of-freedom dynamic model of the hydro-turbine rotor-bearing-foundation system and introducing multi-source coupled excitations into the multi-degree-of-freedom dynamic model; performing numerical simulation calculations on the multi-degree-of-freedom dynamic model to obtain numerical simulation results; and calibrating the key parameters of the multi-degree-of-freedom dynamic model based on actual machine modal test results using a parameter sensitivity correction and iterative calibration algorithm, thereby achieving automatic matching between the numerical simulation results and the actual machine modal test results to obtain a calibrated multi-degree-of-freedom dynamic model. The memory may include main memory, such as high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus, which can be an industry standard architecture bus, a peripheral component interconnection standard bus, an extended industry standard architecture bus, etc. The bus can be divided into address bus, data bus, control bus, etc. The memory is used to store the program; specifically, the program may include program code, which includes computer operation instructions. Memory can include main memory and non-volatile memory, and provides instructions and data to the processor.

[0061] Example 5 A computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the turbine dynamics modeling and modal calibration method. For example, the method includes: constructing a multi-degree-of-freedom dynamic model of the turbine rotor-bearing-foundation system and introducing multi-source coupled excitations into the multi-degree-of-freedom dynamic model; performing numerical simulation calculations on the multi-degree-of-freedom dynamic model to obtain numerical simulation results; and calibrating the key parameters of the multi-degree-of-freedom dynamic model based on actual machine modal test results using a parameter sensitivity correction and iterative calibration algorithm, thereby achieving automatic matching between the numerical simulation results and the actual machine modal test results to obtain a calibrated multi-degree-of-freedom dynamic model. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0062] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0063] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0064] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0065] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0066] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0067] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

[0068] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for dynamic modeling and modal calibration of a hydraulic turbine, characterized in that, include: Construct a multi-degree-of-freedom dynamic model of the turbine rotor-bearing-foundation system; Introduce multi-source coupled excitation into the multi-degree-of-freedom dynamic model; Numerical simulation calculations were performed on the aforementioned multi-degree-of-freedom dynamic model to obtain numerical simulation results; Based on the results of the actual machine modal test, the key parameters of the multi-degree-of-freedom dynamic model are calibrated using a parameter sensitivity correction and iterative calibration algorithm. This enables automatic matching between the numerical simulation results and the actual machine modal test results, resulting in a calibrated multi-degree-of-freedom dynamic model.

2. The method for hydro-turbine dynamics modeling and modal calibration according to claim 1, characterized in that, The multi-source coupled excitation adopts the equivalent stiffness-damping matrix modeling method, which unifies and superimposes the hydraulic pulsation force, electromagnetic force and oil film force into the multi-degree-of-freedom dynamic model.

3. The method for turbine dynamics modeling and modal calibration according to claim 1, characterized in that, The numerical simulation process is as follows: Solve the eigenvalue problem to obtain the natural frequencies and mode shapes; The unbalanced response can be obtained through harmonic response analysis or time-domain integration. Plot Campbell's diagram and stability criterion curves to identify critical speeds and vibration risks.

4. The method for hydro-turbine dynamics modeling and modal calibration according to claim 1, characterized in that, Modal testing includes shutdown modal testing and in-service modal testing, which are used to obtain structural modal parameters by using shock / vibration device testing and random vibration output modal analysis.

5. The method for hydro-turbine dynamics modeling and modal calibration according to claim 1, characterized in that, The parameter sensitivity correction and iterative calibration algorithm includes: Calculate the frequency deviation, damping difference, and modal similarity between the numerical mode and the experimental mode; Based on the sensitivity matrix, identify the model parameters that have the greatest impact on the differences; The bearing stiffness and connection boundary conditions are iteratively corrected until the error converges to a preset threshold.

6. The method for hydro-turbine dynamics modeling and modal calibration according to claim 1, characterized in that, The convergence criteria for the modal calibration are: modal frequency deviation less than 2%, damping ratio deviation less than 10%, and modal similarity greater than 0.

9.

7. The method for hydro-turbine dynamics modeling and modal calibration according to claim 1, characterized in that, The method is applied to both the design and operation phases of the water turbine.

8. A system for dynamic modeling and modal calibration of a hydro-turbine, characterized in that, include: The building module is used to construct a multi-degree-of-freedom dynamic model of the turbine rotor-bearing-foundation system; An introduction module is used to introduce multi-source coupled excitation into the multi-degree-of-freedom dynamic model; The calculation module is used to perform numerical simulation calculations on the multi-degree-of-freedom dynamic model and obtain numerical simulation results; The calibration module is used to calibrate the key parameters of the multi-degree-of-freedom dynamic model based on the results of actual machine modal tests, using parameter sensitivity correction and iterative calibration algorithms. This enables automatic matching between numerical simulation results and actual machine modal test results, resulting in a calibrated multi-degree-of-freedom dynamic model.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the turbine dynamics modeling and modal calibration method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the turbine dynamics modeling and modal calibration method as described in any one of claims 1-7.

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