Hydropower station powerhouse vibration cause identification method and system based on structural modal inversion

Abstract

Embodiments of the present disclosure provide a method and system for identifying the cause of vibration of a hydropower station based on structural modal inversion. The method comprises: obtaining unit operation parameters, plant vibration monitoring data and tail water side boundary condition data under multiple operating conditions; establishing a structural dynamics model covering the unit foundation, machine pit structure and main body of the plant, and extracting the sensitive mode of the plant in combination with the vibration monitoring data; constructing a candidate excitation set of tail water pulsation including different frequency bands, amplitudes and action areas, and converting the candidate excitation into equivalent dynamic load to map to the structural model; calculating the dynamic response of the plant under the constraint of the sensitive mode, and solving the candidate excitation parameters through inversion analysis; sorting each candidate excitation based on frequency band consistency and response contribution to determine the main cause of the plant vibration and its corresponding dominant frequency band and key transmission path. The structural modal inversion idea is introduced to realize the quantitative identification of the main cause of the tail water pulsation vibration from the response characteristics of the plant structure.

Description

Technical Field

[0001] The embodiments disclosed herein belong to the field of hydropower plant vibration cause identification technology, specifically relating to a hydropower plant vibration cause identification method and system based on structural mode inversion. Background Technology

[0002] During the operation of a hydropower station, the powerhouse and its auxiliary structures may experience significant vibrations under certain operating conditions due to factors such as changes in hydraulic conditions, switching of unit operating conditions, and differences in structural characteristics. Such vibrations not only affect the long-term safety of the powerhouse structure but may also adversely impact the operation of equipment and the working environment of personnel within the plant.

[0003] Existing analytical methods for vibration problems in hydropower plant buildings mainly fall into the following categories: one category analyzes factors such as rotor imbalance and shaft vibration from the perspective of mechanical or electromagnetic vibration of the unit; another category uses hydraulic numerical calculations or fluid-structure interaction calculations to directly simulate and analyze hydraulic factors such as unstable water flow and pressure pulsation; and yet another category relies on a large amount of field test data to qualitatively infer the source of vibration through empirical judgment or comparative analysis.

[0004] However, the above methods still have significant shortcomings in practical engineering applications: First, directly conducting full-scale fluid-structure interaction calculations usually involves large computational scales and complex modeling, requiring high levels of engineering application conditions and computational resources, making it difficult to conduct rapid analysis under multiple operating conditions; Second, when tailrace pulsations, structural modes, and multiple vibration transmission paths act together, relying solely on unidirectional analysis from the hydraulic or structural side makes it difficult to accurately distinguish the contribution relationships of different excitation factors to powerhouse vibration; Third, existing methods generally lack an analytical approach that identifies vibration causes from the perspective of powerhouse response characteristics, making it difficult to quantitatively characterize the "amplification effect" of the powerhouse, which can easily lead to unclear judgments of vibration causes or insufficient targeted remediation measures. Summary of the Invention

[0005] The embodiments disclosed herein aim to at least solve one of the technical problems existing in the prior art, and provide a method and system for identifying the causes of vibration in hydropower plant buildings based on structural modal inversion.

[0006] One aspect of this disclosure provides a method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion, the method comprising: The system acquires operating parameters, powerhouse vibration monitoring data, and tailrace boundary condition data of hydropower station units under multiple operating conditions, and aggregates them according to operating conditions to establish the correspondence between operating conditions and powerhouse vibration response. A structural dynamics model covering the unit foundation, pit structure, main structure of the plant and key connecting components is established. Modal analysis is performed on the structural dynamics model to obtain a candidate mode set. Based on the plant vibration monitoring data, the dominant frequency and response energy distribution of the plant response are extracted to determine the sensitive mode set of the plant. For the aforementioned multiple operating conditions, a set of candidate excitations for tailrace pulsations with different frequency bands, operating regions, and phase characteristics is constructed; Each tailrace pulsation candidate excitation is converted into an equivalent dynamic load that can be applied to the structural dynamics model and mapped to the corresponding action part of the structural dynamics model; For each of the candidate tailwater pulsation excitations, dynamic response calculations are performed on the structural dynamics model to obtain the response of the target monitoring point in the powerhouse; based on the set of sensitive modes of the powerhouse, an inversion objective function is constructed and optimized to obtain the optimal solution of the excitation parameters of each candidate tailwater pulsation excitation under different operating conditions; Based on the inversion solution results, the contribution index of each tailrace pulsation candidate excitation to the response of the target monitoring point in the powerhouse is calculated and sorted. The candidate excitation that meets the preset criteria and has the highest ranking is determined as the main cause of the powerhouse vibration, and the location of action, dominant frequency band and key transmission path information of the main cause are output.

[0007] Furthermore, the operating parameters include one or more of the following: active power, rotational speed, guide vane opening, upstream water level, and downstream water level; and / or The plant vibration monitoring data includes one or more of the following: acceleration, velocity, and displacement at key points of the unit foundation, pit structure, plant floor slab, and auxiliary buildings.

[0008] Furthermore, the dynamic equations of the structural dynamics model are shown below:

[0009] In the formula, For the quality matrix, Here is the damping matrix. Here is the stiffness matrix. The structural displacement vector. For external excitation load, It is a time variable.

[0010] Furthermore, determining the set of sensitive modes of the factory building includes: When the frequency band matching condition is met Furthermore, if the mode participation coefficient of the corresponding candidate mode at the target monitoring point exceeds a preset threshold, the candidate mode is determined to be a sensitive mode of the factory building; in, To ensure the factory can respond to the main frequency, The natural frequencies of the candidate modes, This represents the maximum permissible frequency error.

[0011] Furthermore, the candidate excitations for each tailrace pulsation are shown in the following equation:

[0012] In the formula, Candidate excitation for tailrace pulsation. The dominant frequency or frequency band range of the pulsation. The amplitude of the pulse. For phase characteristics, This is the region of incentive effect.

[0013] Furthermore, the conversion of each tailrace pulsation candidate excitation into an equivalent dynamic load that can be applied to the structural dynamics model is shown in the following equation:

[0014] In the formula, For equivalent dynamic load, Let be the spatial position variable of any point on the surface of the structure. For the incentive area, For pulsating pressure function, This is the normal vector of the action surface.

[0015] Furthermore, the inversion objective function is shown in the following equation:

[0016] In the formula, Candidate excitation for tailrace pulsation. This is the frequency sampling point number. This represents the total number of frequency sampling points. To calculate the response spectrum, For the measured response spectrum, For the first k The frequency value corresponding to each frequency sampling point.

[0017] Furthermore, the contribution index is shown in the following formula:

[0018] In the formula, As a contribution indicator, For frequency variables, For the sensitive mode frequency band of the factory building, In the first j The structural response spectrum obtained under candidate excitation of tailwater pulsation.

[0019] Another aspect of this disclosure provides a system for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion, the system comprising: The data acquisition module is used to acquire the operating parameters of the hydropower station units under multiple operating conditions, powerhouse vibration monitoring data, and tailrace boundary condition data, and to collect them according to the operating conditions to establish the correspondence between the operating conditions and the powerhouse vibration response. The modal analysis module is used to establish a structural dynamics model covering the unit foundation, pit structure, main structure of the plant and key connecting components, perform modal analysis on the structural dynamics model to obtain a candidate mode set, and extract the plant response dominant frequency and response energy distribution based on the plant vibration monitoring data to determine the plant sensitive mode set. The excitation construction module is used to construct a set of candidate excitations for tailrace pulsations with different frequency bands, operating regions and phase characteristics for the multiple operating conditions. The load mapping module is used to convert each tailrace pulsation candidate excitation into an equivalent dynamic load that can be applied to the structural dynamics model, and map it to the corresponding action part of the structural dynamics model; The inversion solution module is used to perform dynamic response calculations on the structural dynamics model for each of the candidate tailwater pulsation excitations to obtain the response of the target monitoring point in the powerhouse; based on the set of sensitive modes of the powerhouse, an inversion objective function is constructed and optimized to obtain the optimal solution of the excitation parameters of each candidate tailwater pulsation excitation under different operating conditions; The cause determination module is used to calculate and sort the contribution index of each candidate excitation of tailwater pulsation to the response of the target monitoring point in the powerhouse based on the inversion solution results. The candidate excitation that meets the preset criteria and has the highest ranking is determined as the main cause of the powerhouse vibration, and the module outputs the location of action, the dominant frequency band, and the key transmission path information of the main cause.

[0020] Another aspect of this disclosure provides an electronic device, comprising: At least one processor; and, A memory communicatively connected to the at least one processor is used to store one or more programs, which, when executed by the at least one processor, enable the at least one processor to implement the above-described method for identifying the causes of vibration in hydropower plant buildings based on structural mode inversion.

[0021] This disclosure discloses a method and system for identifying the causes of powerhouse vibration based on structural modal inversion. The method accurately identifies the causes of powerhouse vibration by inverting hydraulic excitation through structural modal inversion, and the inversion results have clear physical meaning and engineering interpretability. It avoids dependence on full-scale fluid-structure interaction calculations, can quantitatively distinguish the contribution relationship of various tailrace pulsation factors to powerhouse vibration, and the identification results have clear physical meaning. They can be directly used for subsequent governance decisions and are applicable to the analysis of the causes of powerhouse vibration in hydropower stations with multiple operating conditions and multiple structural forms. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a method for identifying the causes of vibration in a hydropower plant based on structural modal inversion, according to an embodiment of this disclosure. Figure 2 This is a comparison diagram of the acceleration response spectrum at different locations in the factory building according to another embodiment of this disclosure; Figure 3 This is a comparison chart of the tailwater pulsation inversion results and the measured spectrum of another embodiment of this disclosure; Figure 4 This is a schematic diagram of a hydropower plant vibration cause identification system based on structural modal inversion according to another embodiment of the present disclosure; Figure 5 This is a schematic diagram of the structure of an electronic device according to another embodiment of the present disclosure. Detailed Implementation

[0023] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. Based on the embodiments of this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this disclosure.

[0024] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0025] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0026] As used in this disclosure, the term "and / or" includes any one and all combinations of one or more of the associated listed items.

[0027] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of exemplary embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing this disclosure, and therefore cannot be used to limit the scope of protection of this disclosure.

[0028] like Figure 1 As shown, one embodiment of this disclosure provides a method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion. The method includes: Step S1: Obtain the operating parameters of the hydropower station units under multiple operating conditions, powerhouse vibration monitoring data, and tailrace boundary condition data, and collect them according to the operating conditions to establish the correspondence between the operating conditions and the powerhouse vibration response.

[0029] Specifically, firstly, a sensor monitoring system deployed in the hydropower station powerhouse collects real-time or periodic operating data of the generating units under multiple typical operating conditions (such as different power outputs and heads), including but not limited to parameters such as active power, rotational speed, guide vane opening, upstream water level, and downstream water level. Vibration sensors (such as accelerometers, velocity sensors, or displacement sensors) are deployed at key structural locations such as the unit foundation, pit structure (near the spiral casing and bearing rings), powerhouse floors, and auxiliary buildings (such as office areas) to record vibration signals such as acceleration, velocity, or displacement under various operating conditions in real-time or synchronously. The sampling frequency must meet the requirements of subsequent spectrum analysis, such as 200Hz or higher. Simultaneously, parameters related to the hydraulic state of the tailrace are acquired as boundary condition data for the tailrace side, including at least the tailrace level and potentially the geometric parameters of the tailrace channel and flow condition descriptions, providing conditions for the subsequent construction of candidate excitations for tailrace pulsations.

[0030] Subsequently, all the collected data were categorized and aggregated according to a unified timestamp and operating condition identifier, with each operating condition identifier associated with a specific set of operating parameter values. For each operating condition, its corresponding complete dataset was extracted, including the set of operating parameters under that condition, the vibration signal sequence of all vibration monitoring points, and the tailrace boundary condition data, forming an "operating condition-vibration response" correspondence dataset. This dataset clarifies the specific vibration characteristics of the plant structure under different operating conditions, providing a data foundation for subsequent analysis of the correlation between vibration and operating conditions, as well as for causal inversion under specific operating conditions.

[0031] Step S2: Establish a structural dynamics model covering the unit foundation, pit structure, main structure of the plant and key connecting components. Perform modal analysis on the structural dynamics model to obtain a candidate mode set. Based on the plant vibration monitoring data, extract the plant response dominant frequency and response energy distribution to determine the plant sensitive mode set.

[0032] Specifically, a finite element model is established using 3D modeling software (such as ANSYS, ABAQUS, SAP2000, etc.). This finite element model comprehensively covers key structural components affecting vibration transmission, including the unit foundation (foundation slabs, concrete piers, and anchoring structures of the generator floor and turbine floor), the pit structure (a composite model of the spiral casing, seat ring, pit lining, and steel structure and outer concrete casing of the tailrace pipe), and key connecting components (tailrace pipe supports, connections between the pit and the powerhouse, and connecting corridors between the main powerhouse and auxiliary buildings, etc.). Simultaneously, material properties (such as the elastic modulus, density, and Poisson's ratio of concrete and steel) are defined, and reasonable boundary constraints are applied to form equations that describe the structural dynamics.

[0033] In the formula, For the quality matrix, Here is the damping matrix. Here is the stiffness matrix. The structural displacement vector. For external excitation load, for….

[0034] Modal analysis was performed on the above structural dynamics model, and its characteristic equations were determined. The solution is performed to obtain the first few natural frequencies (e.g., the first 20) of the structure in the undamped state. and its corresponding mode shape vector The modes formed by these natural frequencies and mode shapes This serves as a candidate mode set for analyzing the potential dynamic characteristics of the structure.

[0035] For the vibration time-domain signals (acceleration, velocity, or displacement) of different monitoring points (foundation, pit, floor) of the plant under various working conditions obtained in step S1 above, a spectrum analysis is performed. From the spectrum of each monitoring point, the peak frequency with the most concentrated energy amplitude is identified. This frequency is the dominant response frequency at that measuring point under that working condition. Simultaneously, the distribution characteristics of the response energy across the frequency band are analyzed and recorded, i.e., in which frequency bands the structural response is significant.

[0036] The above measured factory response frequency Natural frequencies of candidate modes calculated with structural model Perform a comparison, when the conditions are met At that time, it is assumed that the measured factory building's response frequency is... With the model's first i The first-order modal frequencies are basically the same, among which This refers to the maximum permissible frequency error set based on engineering experience or analytical accuracy requirements.

[0037] For those that meet the above frequency band matching conditions Candidate modes are identified, and their mode participation coefficients (MPCs) at the target monitoring point are calculated. The MPC characterizes the contribution of that mode to the vibration at the target point. When the MPC of a candidate mode at the target monitoring point exceeds a preset threshold, that mode is identified as a sensitive mode that significantly contributes to the current plant vibration. Finally, all sensitive modes selected under multiple operating conditions are summarized to form a set of sensitive plant modes.

[0038] The sensitive mode set of the factory building represents the key dynamic characteristics of the factory building structure that have a significant amplification effect on specific frequency excitations in the measured vibration, and will serve as the core object of constraint and focus in the subsequent inversion analysis.

[0039] Step S3: For the multiple operating conditions, construct a set of candidate excitations for tailrace pulsations with different frequency bands, operating areas and phase characteristics.

[0040] Specifically, candidate excitations for tailrace pulsations can originate from hydraulic numerical calculation results, fitting results of field monitoring data, or hydraulic mechanism models. For example, in hydraulic numerical calculations, hydraulic numerical models (such as CFD models) are established for different operating conditions of the tailrace system (tailrace pipe, tailrace tunnel, diffuser, etc.), and the pressure pulsation function of the inner wall of the flow field is obtained through transient calculations. Candidate excitations include one or more of the following: pressure pulsation excitations in different frequency bands, load excitations in different spatial action regions, and excitations with different phase characteristics.

[0041] The various excitation sources mentioned above are uniformly transformed into parameterized excitation descriptions, forming a set of candidate excitations for tailrace pulsations that can be selected for subsequent calculations and inversions. Each of the tailwater pulsation candidate excitations In parameterized form, it is expressed as:

[0042] In the formula, For frequency band parameters, For amplitude parameters, For phase characteristic parameters, This refers to the parameters of the area of ​​effect.

[0043] Frequency band parameters This represents the dominant frequency or frequency range of the j-th excitation; it can be a single dominant frequency value or a frequency band. Amplitude parameter. This represents the initial or reference pressure fluctuation amplitude of the j-th excitation; it can be a scalar value or an amplitude function that varies with frequency or position. Phase characteristic parameters. When considering the synchronicity of excitation at multiple points or regions, phase relationship information (such as the phase difference of radial pressure distribution) may be included; for initial mode matching, this can be a default value (such as zero phase) or a distribution determined based on the excitation source. Action area parameters. This is used to explicitly specify the physical location of the excitation at the hydraulic boundary, corresponding to the location of the structural geometric model in step S2.

[0044] For each operating condition collected in step S1, repeat the above process to construct a candidate excitation set corresponding to the operating condition, ensuring that the excitation set for each operating condition contains the typical tailrace pulsation mode that may occur under that operating condition.

[0045] Step S4: Convert each tailwater pulsation candidate excitation into an equivalent dynamic load that can be applied to the structural dynamics model, and map it to the corresponding action part of the structural dynamics model.

[0046] Specifically, for each tailrace pulsation candidate excitation constructed in step S3, based on its effective region... This is considered as a distributed dynamic surface pressure acting on the inner wall of a hydraulic structure (such as a tailrace pipe or a concrete protective cover for a machine pit). This hydraulic excitation is then converted into a dynamic load acting on the structural dynamics model. The main mapping form is a surface load, and the pulsating pressure integral is equivalent to the force acting on the structural wall.

[0047] First, establish the mapping relationship from excitation to structural units to ensure that the geometric coordinate system of the tailrace pulsation region and the structural dynamics model is consistent, or establish a definite coordinate transformation relationship. For the structural dynamics model located in the excitation region... For the wall elements, a mapping algorithm (such as nearest neighbor projection, distance weighting, or original mesh interpolation) is applied to map the pulsating pressure function of the excitation pressure node to the structural element.

[0048] Then the pressure pulsation function The equivalent dynamic load is applied to the structural elements it maps to. For each desired excitation frequency and time, the equivalent dynamic load... It is obtained by integrating the area of ​​action, as shown in the following formula:

[0049] In the formula, This is the equivalent surface load vector applied to the wall of the structural model. Let be the pulsating pressure function of the wall. For the working surface micro-element The normal vector, the integral over the region of excitation. The above will be carried out.

[0050] Through the above mapping and transformation process, each candidate stimulus This creates an independent dynamic load condition, thereby transforming the parameterized excitation. It is concretized on the structural mesh as a computable excitation vector with a definite amplitude, frequency, phase and spatial distribution, providing a direct structural input for subsequent dynamic response analysis and inversion solution.

[0051] Step S5: Perform dynamic response calculation on the structural dynamics model for each of the candidate tailwater pulsation excitations to obtain the response of the target monitoring point in the powerhouse; based on the set of sensitive modes of the powerhouse, construct the inversion objective function and perform optimization solution to obtain the optimal solution of the excitation parameters of each candidate tailwater pulsation excitation under different operating conditions.

[0052] Specifically, under the conditions of applying each candidate stimulus, the structural response of the target monitoring point of the plant is calculated. And construct the inversion objective function:

[0053] In the formula, Candidate excitation for tailrace pulsation. for…, for…, To calculate the response spectrum, For the measured response spectrum, for….

[0054] Under the conditions of satisfying physical constraints and amplitude constraints, solve for the minimized candidate excitation parameters. Complete the inversion analysis.

[0055] Step S6: Based on the inversion solution results, calculate the contribution index of each of the tailrace pulsation candidate excitations to the response of the target monitoring point in the powerhouse and sort them. The candidate excitation that meets the preset criteria and has the highest ranking is determined as the main cause of the powerhouse vibration, and the location of action, dominant frequency band and key transmission path information of the main cause are output.

[0056] Specifically, the proportion of response energy of the candidate excitation in the sensitive mode band is calculated as shown in the following formula:

[0057] In the formula, As a contribution indicator, for…, For the sensitive mode frequency band of the factory building, for….

[0058] When a candidate stimulus satisfies the frequency band consistency condition under multiple operating conditions, and its contribution index When the ranking is consistently at the top, the candidate excitation is determined to be the main cause of plant vibration, and its dominant frequency band, area of ​​action, and key transmission path are output.

[0059] The following uses a mixed-flow hydropower unit as an example to illustrate the specific application process of the hydropower plant vibration cause identification method based on structural mode inversion as described in this disclosure.

[0060] A mixed-flow hydroelectric power station has a single unit capacity of 300MW, a rated speed of 150r / min, and 13 turbine blades. The powerhouse is a reinforced concrete frame-shear wall structure, with the unit foundation and main powerhouse structure integrally cast. An auxiliary office area is located on one side of the powerhouse, connected to the main powerhouse via a structural corridor. During unit operation, significant vibrations were observed in the powerhouse and office area when the unit was operating under partial load, particularly noticeable vibrations felt on the office floor slabs.

[0061] First, three typical operating conditions were selected as the analysis objects, as shown in Table 1 below.

[0062] Table 1:

[0063] Accelerometers were installed at the center of the factory foundation, the machine pit structure, and the second floor of the office area, with a sampling frequency of 200Hz. Spectrum analysis is as follows: Figure 2 As shown, under partial load operation, the acceleration response spectra of the plant foundation, the pit structure, and the second-floor slab of the office area all exhibit a distinct main peak at approximately 2.4 Hz, indicating that the plant vibration has a consistent dominant frequency characteristic. Among these, the response amplitude of this frequency component at the office floor slab is significantly higher than that at the plant foundation and the pit structure, indicating that the vibration energy is amplified step-by-step along the structural transmission path, producing a significant amplification effect at the corresponding structural mode of the office floor slab. The results show that under operating conditions A and B, the dominant vibration frequency of the office floor slab is concentrated between 2.3 Hz and 2.6 Hz; under operating condition C, the vibration in this frequency band is significantly reduced.

[0064] A three-dimensional structural dynamics model covering the unit foundation, pit structure, main plant structure, and connecting corridor structure was established. The elastic modulus of concrete was taken as 3.25 × 10¹⁰ Pa, and the density was taken as 2500 kg / m³. 3 Modal analysis was performed on the model, and the first 20 intrinsic modes were obtained. The main modes related to the response of the office floor are shown in Table 2 below.

[0065] Table 2:

[0066] Since the natural frequency of mode 3, 2.41Hz, is highly consistent with the measured dominant frequency, and the mode participation coefficient is the largest at the office floor slab, mode 3 is identified as a sensitive mode of the factory building.

[0067] For partial load conditions, three sets of candidate excitations for tailrace pulsation are constructed: 1. Incentives Tailwater vortex pulsation clock speed =2.4Hz, operating area: inner wall of the tailwater diffuser section.

[0068] 2. Incentives Guide vane-rotor interference pulsation clock speed ≈32.5Hz.

[0069] 3. Incentives Low-frequency random hydraulic disturbances Frequency band: 0.5Hz~1.5Hz.

[0070] The initial estimated range for the amplitude of the pulsating pressure is 5 kPa to 25 kPa.

[0071] Further equivalent load mapping and response calculations are performed to excite... For example, the pulsating pressure on the inner wall of the tailrace diffuser section is expressed as:

[0072] in This represents the amplitude of the pulsating pressure.

[0073] The equivalent dynamic load is calculated using the following formula:

[0074] Among them, the area of ​​action =18.6m 2 .

[0075] when At a pressure of 18 kPa, the equivalent excitation peak value is approximately: =18000×18.6≈3.35×10 5 N The equivalent load is applied to the corresponding nodes of the tailrace pipe support and the machine pit structure.

[0076] Next, response calculations are performed on the three sets of candidate excitations, and the objective function is constructed using the acceleration spectrum of the office floor slab as the inversion objective:

[0077] Inversion results as follows Figure 3 As shown, the details are as follows: 1. Incentives exist Objective function at 17.6 kPa Minimum; 2. Incentives , Within the target frequency band, the response contribution is less than 10% of the total energy.

[0078] Further calculation of incentive contribution indicators: =68%, =14% =18%.

[0079] Among incentives It maintained the highest contribution ranking under both operating conditions A and B.

[0080] Based on the above implementation process, it is determined that: 1. Low-frequency pressure pulsations (approximately 2.4 Hz) caused by tailrace vortices are the main cause of plant vibration; 2. The vibration is transmitted through the tailrace pipe - pit structure - factory foundation - connecting corridor, and is significantly amplified at mode 3 of the office area floor slab; 3. Under rated load conditions (condition C), the amplitude of tailwater pulsation is significantly reduced, and the vibration phenomenon is weakened accordingly.

[0081] This disclosure discloses a method for identifying the causes of powerhouse vibration based on structural modal inversion. The method accurately identifies the causes of powerhouse vibration by inverting hydraulic excitation through structural modal inversion, and the inversion results have clear physical meaning and engineering interpretability. It avoids dependence on full-scale fluid-structure interaction calculations, can quantitatively distinguish the contribution relationship of various tailrace pulsation factors to powerhouse vibration, and the identification results have clear physical meaning. They can be directly used for subsequent governance decisions and are applicable to the analysis of the causes of powerhouse vibration in hydropower stations with multiple operating conditions and multiple structural forms.

[0082] like Figure 4 As shown, another embodiment of this disclosure provides a hydropower station powerhouse vibration cause identification system based on structural modal inversion, the system comprising: The data acquisition module 410 is used to acquire the operating parameters of the hydropower station unit under multiple operating conditions, powerhouse vibration monitoring data and tailrace side boundary condition data, and to collect them according to the operating conditions to establish the correspondence between the operating conditions and the powerhouse vibration response. Modal analysis module 420 is used to establish a structural dynamics model covering the unit foundation, pit structure, main structure of the plant and key connecting components, perform modal analysis on the structural dynamics model to obtain a candidate mode set, and extract the plant response dominant frequency and response energy distribution based on the plant vibration monitoring data to determine the plant sensitive mode set; The excitation construction module 430 is used to construct a set of candidate excitations for tailwater pulsations with different frequency bands, operating areas and phase characteristics for the multiple operating conditions. The load mapping module 440 is used to convert each tailwater pulsation candidate excitation into an equivalent dynamic load that can be applied to the structural dynamics model, and map it to the corresponding action part of the structural dynamics model. The inversion solution module 450 is used to perform dynamic response calculation on the structural dynamics model for each of the tailwater pulsation candidate excitations to obtain the response of the target monitoring point of the powerhouse; based on the set of sensitive modes of the powerhouse, an inversion objective function is constructed and optimized to obtain the optimal solution of the excitation parameters of each of the tailwater pulsation candidate excitations under different operating conditions. The cause determination module 460 is used to calculate and sort the contribution index of each candidate excitation of tailwater pulsation to the response of the target monitoring point of the powerhouse based on the inversion solution results. The candidate excitation that meets the preset criteria and has the highest ranking is determined as the main cause of the powerhouse vibration, and the location of action, dominant frequency band and key transmission path information of the main cause are output.

[0083] Specifically, the hydropower plant vibration cause identification system based on structural mode inversion in this embodiment is used to implement the hydropower plant vibration cause identification method based on structural mode inversion described in the above embodiments. The specific implementation process has been described in detail in the above embodiments and will not be repeated here.

[0084] like Figure 5 As shown, another embodiment of this disclosure provides an electronic device, including: At least one processor 501; and a memory 502 communicatively connected to the at least one processor 501 for storing one or more programs that, when executed by the at least one processor 501, enable the at least one processor 501 to implement the above-described method for identifying the causes of vibration in hydropower plant buildings based on structural mode inversion.

[0085] The memory 502 and processor 501 are connected via a bus, which can include any number of interconnecting buses and bridges. The bus connects various circuits of one or more processors 501 and memory 502 together. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by processor 501 is transmitted over a wireless medium via an antenna, which further receives data and transmits it to processor 501.

[0086] Processor 501 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory 502 can be used to store data used by processor 501 during operation.

[0087] It is understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of this disclosure, and this disclosure is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this disclosure, and these modifications and improvements are also considered to be within the scope of protection of this disclosure.

Claims

1. A method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion, characterized in that, The method includes: The system acquires operating parameters, powerhouse vibration monitoring data, and tailrace boundary condition data of hydropower station units under multiple operating conditions, and aggregates them according to operating conditions to establish the correspondence between operating conditions and powerhouse vibration response. A structural dynamics model covering the unit foundation, pit structure, main structure of the plant and key connecting components is established. Modal analysis is performed on the structural dynamics model to obtain a candidate mode set. Based on the plant vibration monitoring data, the dominant frequency and response energy distribution of the plant response are extracted to determine the sensitive mode set of the plant. For the aforementioned multiple operating conditions, a set of candidate excitations for tailrace pulsations with different frequency bands, operating regions, and phase characteristics is constructed; Each tailrace pulsation candidate excitation is converted into an equivalent dynamic load that can be applied to the structural dynamics model and mapped to the corresponding action part of the structural dynamics model; For each of the candidate tailwater pulsation excitations, dynamic response calculations are performed on the structural dynamics model to obtain the response of the target monitoring point in the powerhouse; based on the set of sensitive modes of the powerhouse, an inversion objective function is constructed and optimized to obtain the optimal solution of the excitation parameters of each candidate tailwater pulsation excitation under different operating conditions; Based on the inversion solution results, the contribution index of each tailrace pulsation candidate excitation to the response of the target monitoring point in the powerhouse is calculated and sorted. The candidate excitation that meets the preset criteria and has the highest ranking is determined as the main cause of the powerhouse vibration, and the location of action, dominant frequency band and key transmission path information of the main cause are output.

2. The method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion according to claim 1, characterized in that, The operating parameters include one or more of the following: active power, rotational speed, guide vane opening, upstream water level, and downstream water level; and / or The plant vibration monitoring data includes one or more of the following: acceleration, velocity, and displacement at key points of the unit foundation, pit structure, plant floor slab, and auxiliary buildings.

3. The method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion according to claim 1, characterized in that, The dynamic equations of the structural dynamics model are shown below: In the formula, For the quality matrix, Here is the damping matrix. Here is the stiffness matrix. The structural displacement vector. For external excitation load, It is a time variable.

4. The method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion according to claim 1, characterized in that, The determination of the sensitive mode set of the factory building includes: When the frequency band matching condition is met Furthermore, if the mode participation coefficient of the corresponding candidate mode at the target monitoring point exceeds a preset threshold, the candidate mode is determined to be a sensitive mode of the factory building; in, To ensure the factory can respond to the main frequency, The natural frequencies of the candidate modes, This represents the maximum permissible frequency error.

5. The method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion according to claim 1, characterized in that, The candidate excitations for each tailrace pulsation are shown in the following equations: In the formula, Candidate excitation for tailrace pulsation. The dominant frequency or frequency band range of the pulsation. The amplitude of the pulse. For phase characteristics, This is the region where the incentive effect occurs.

6. The method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion according to claim 1, characterized in that, The process of converting each tailrace pulsation candidate excitation into an equivalent dynamic load that can be applied to the structural dynamics model is shown in the following equation: In the formula, For equivalent dynamic load, Let be the spatial position variable of any point on the surface of the structure. For the incentive area, For pulsating pressure function, This is the normal vector of the action surface.

7. The method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion according to claim 1, characterized in that, The inversion objective function is shown in the following equation: In the formula, Candidate excitation for tailrace pulsation. This is the frequency sampling point number. This represents the total number of frequency sampling points. To calculate the response spectrum, For the measured response spectrum, For the first k The frequency value corresponding to each frequency sampling point.

8. The method for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion according to claim 1, characterized in that, The contribution index is shown in the following formula: In the formula, As a contribution indicator, For frequency variables, For the sensitive mode frequency band of the factory building, In the first j The structural response spectrum obtained under candidate excitation of tailwater pulsation.

9. A system for identifying the causes of vibration in a hydropower station powerhouse based on structural modal inversion, characterized in that, The system includes: The data acquisition module is used to acquire the operating parameters of the hydropower station units under multiple operating conditions, powerhouse vibration monitoring data, and tailrace boundary condition data, and to collect them according to the operating conditions to establish the correspondence between the operating conditions and the powerhouse vibration response. The modal analysis module is used to establish a structural dynamics model covering the unit foundation, pit structure, main structure of the plant and key connecting components, perform modal analysis on the structural dynamics model to obtain a candidate mode set, and extract the plant response dominant frequency and response energy distribution based on the plant vibration monitoring data to determine the plant sensitive mode set. The excitation construction module is used to construct a set of candidate excitations for tailrace pulsations with different frequency bands, operating regions and phase characteristics for the multiple operating conditions. The load mapping module is used to convert each tailrace pulsation candidate excitation into an equivalent dynamic load that can be applied to the structural dynamics model, and map it to the corresponding action part of the structural dynamics model; The inversion solution module is used to perform dynamic response calculations on the structural dynamics model for each of the candidate tailwater pulsation excitations to obtain the response of the target monitoring point in the powerhouse; based on the set of sensitive modes of the powerhouse, an inversion objective function is constructed and optimized to obtain the optimal solution of the excitation parameters of each candidate tailwater pulsation excitation under different operating conditions; The cause determination module is used to calculate and sort the contribution index of each candidate excitation of tailwater pulsation to the response of the target monitoring point in the powerhouse based on the inversion solution results. The candidate excitation that meets the preset criteria and has the highest ranking is determined as the main cause of the powerhouse vibration, and the module outputs the location of action, the dominant frequency band, and the key transmission path information of the main cause.

10. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor is used to store one or more programs, which, when executed by the at least one processor, enable the at least one processor to implement the hydropower plant vibration cause identification method based on structural mode inversion as described in any one of claims 1 to 8.

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