A method for analyzing dynamic characteristics of a water turbine runner and a vibration monitoring system

Abstract

The application discloses a kind of water turbine runner dynamic characteristic analysis method and vibration monitoring system, belong to water turbine simulation analysis field.The method mainly includes data acquisition, model establishment, excitation frequency calculation, inherent frequency analysis, dangerous frequency range evaluation and vibration monitoring system design and the like steps.Through collecting the design specification and working environment of water turbine runner, establishing three-dimensional model, calculating the excitation frequency possibly leading to water turbine runner vibration, solving the inherent frequency and vibration mode of model, evaluating whether water turbine is in the dangerous frequency range possibly appearing larger vibration, and designing and realizing a kind of vibration monitoring system capable of real-time monitoring vibration, early warning possible problem.The analysis method can efficiently and accurately analyze the dynamic characteristics of water turbine runner, and the vibration monitoring system can monitor the state of the runner in real time, provide early warning for possible problems, ensure the safe operation of the water turbine, and improve the operation efficiency and equipment management efficiency.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of water turbine simulation analysis, and more particularly relates to a water turbine runner dynamic characteristic analysis method and a vibration monitoring system. BACKGROUND

[0002] The water turbine is one of the important components of a hydropower station, and its core component is the runner. In the operation process of the water turbine, the dynamic characteristics of the runner have an important influence on the output power, vibration, noise, etc. of the water turbine. Therefore, it is of great practical significance to analyze and monitor the dynamic characteristics of the water turbine runner.

[0003] However, the traditional dynamic characteristic analysis method of the water turbine runner mostly relies on traditional physical modeling and manual calculation, which not only consumes time and manpower, but also cannot guarantee the accuracy and efficiency of the results.

[0004] At the same time, due to the nonlinearity and complexity of the working condition of the water turbine runner, the traditional numerical analysis method for dynamic characteristic analysis often leads to low accuracy of the results due to model simplification or unreasonable mathematical model assumptions.

[0005] In addition, for the vibration monitoring of the water turbine runner, the artificial periodic detection method is often used, which not only needs to consume a lot of manpower and material resources, but also cannot monitor the dynamic state of the water turbine runner in real time, and cannot discover and handle faults in time, which is easy to cause equipment damage and even may cause major production accidents.

[0006] Therefore, developing a method and system capable of efficiently and accurately analyzing the dynamic characteristics of the water turbine runner and providing real-time monitoring is of great significance for ensuring the operation state and equipment safety of the water turbine, reducing maintenance costs, and improving power generation efficiency. SUMMARY

[0007] The main technical problem to be solved by the present application is to provide an efficient and accurate real-time water turbine runner dynamic characteristic analysis method, and to design a system for monitoring the dynamic characteristics of the water turbine runner, so as to solve the problems of low efficiency, low accuracy, inability to reflect the working state of the runner in real time, and early warning of potential problems in the process of water turbine runner dynamic characteristic analysis and monitoring.

[0008] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0009] Data acquisition: collect the design specifications and working environment of the water turbine runner, including the influence of eddy current, corrosion or equipment aging factors;

[0010] Model building: Based on the collected data, a three-dimensional model is built using computational fluid dynamics software;

[0011] Excitation frequency calculation: Calculate the vortex frequency and dynamic-static interference frequency, calculate the excitation frequency that causes the runner vibration of the water turbine, and adjust the strength and position of the exciter to the best state;

[0012] Natural frequency analysis: Using finite element analysis method under the set boundary conditions, the natural frequency and vibration mode of the model are solved;

[0013] Dangerous frequency range evaluation: Compare the actual working frequency with the excitation frequency to evaluate whether the water turbine is in the dangerous frequency range of larger vibration.

[0014] In one aspect, the data collection includes:

[0015] Design specification collection: Collect the design specifications of the runner of the water turbine, including the size, shape, weight and material information of the runner;

[0016] Working environment data collection: Collect the working environment information of the runner, the physical parameters of the surrounding fluid such as pressure, temperature and flow rate;

[0017] Vortex effect analysis: According to the collected working environment data, the effect of vortex on the runner is analyzed through physical model;

[0018] Corrosion and equipment aging analysis: For existing corrosion or equipment aging factors, special detection and analysis are carried out.

[0019] In one aspect, the model building includes:

[0020] Design parameter setting: According to the design specifications obtained in the data collection step, the key size and physical properties of the three-dimensional model of the runner are set according to the runner diameter, weight and other parameters;

[0021] Liquid flow field model setting: Set the liquid flow field conditions, and set the appropriate initial conditions and boundary conditions for the model according to the working environment data obtained in the data collection step, such as vortex speed, pressure and temperature parameters;

[0022] Three-dimensional model building: A three-dimensional model of the runner of the water turbine is built according to the collected data. This model covers the runner part and the corresponding fluid field.

[0023] In one aspect, the excitation frequency calculation includes:

[0024] 1) Runner rotation frequency: f0=93.75 / 60=1.56Hz

[0025] 2) vortex frequency: for Francis turbine: 0.6*f0 < f1 < 0.8*f0 0.9Hz < f1 < 1.3Hz

[0026] 3) dynamic-static interference frequency

[0027] The runner is subjected to a simple harmonic excitation with a frequency of nZ S f0, Z S is the number of guide vanes, and f0 is the rotational frequency;

[0028] The theory and experiments show that n depends on the number of blades and the number of guide vanes, and have the following relationship:

[0029] mZ R f0-nZ S f0=kf0

[0030] M: positive or negative integer; N: simple harmonic excitation order (positive integer); K: positive or negative integer, whose absolute value determines the number of pitch diameters; Z R : number of blades 15; Z S : number of guide vanes 24.

[0031] In one scheme, the natural frequency analysis includes:

[0032] Setting boundary conditions: setting boundary conditions based on the three-dimensional model established in the previous step, working environment and flow field conditions; the boundary conditions include fixed boundary, free boundary and mixed boundary;

[0033] Finite element meshing: the runner model is meshed using the finite element method;

[0034] Frequency solving: after meshing, the model is analyzed for natural frequency and vibration mode using a frequency solving algorithm; natural frequency solving involves solving linear algebraic equations and solving second-order differential equations,

[0035] The Rayleigh-Ritz method is used. Assuming that the motion equation of the system is [M] {a} + [C] {v} + [K] {d} = {F}

[0036] Where [M], [C], [K] are mass, damping and stiffness matrices respectively, {a}, {v}, {d} represent acceleration, velocity and displacement respectively, and {F} represents external force;

[0037] By finding {d} that satisfies {d} = α {d_0} e (iω*t) , the natural frequency ω is obtained;

[0038] Mode shape analysis: according to the calculation results of the natural frequency, the vibration shape of each mode is obtained, and the vibration of the runner at these frequencies is visually displayed.

[0039] In one aspect, the dangerous frequency range assessment comprises:

[0040] Obtaining working frequency: Obtain the actual working frequency of the water turbine through online data collection or by calling the operation record of the water turbine, denoted as f_working.

[0041] Obtaining excitation frequency and natural frequency: The data in this step comes directly from the results of the previous two steps, i.e., excitation frequency calculation and natural frequency analysis, denoted as f_excitation and f_natural.

[0042] Comparing frequencies: Compare the differences between the actual working frequency f_working and the excitation frequency f_excitation and the natural frequency f_natural.

[0043] Defining the dangerous frequency range: This range is estimated based on experience or theory, and the dangerous frequency range is: |f_working-f_excitation|<=δ or |f_working-f_natural|<=δ, where δ is the allowed difference.

[0044] In order to more finely assess the possibility of danger, a risk degree evaluation index R is introduced, which has the following expression:

[0045]

[0046] The larger the value of R, the greater the deviation of the device's operating state from the dangerous state; if R exceeds a predetermined threshold, the device is considered to be in a dangerous state.

[0047] On the other hand, a water turbine runner dynamic vibration monitoring system, said system is suitable for said method, said system comprises the following modules:

[0048] Data acquisition module: Collect the working state information of the water turbine runner through sensors, including the rotational speed, vibration, temperature and pressure physical parameters of the runner, and send the collected data to the data processing module;

[0049] Data processing module: responsible for receiving data sent by the data acquisition module, and processing data through the set analysis algorithm, calculating the excitation frequency and natural frequency information, and then sending these information to the warning module and display module;

[0050] Warning module: receives the excitation frequency, natural frequency and other information sent by the data processing module, and judges whether the water turbine runner is in a dangerous state through the set warning rules, and once it is judged that the runner may be in a dangerous state, it will send a warning signal;

[0051] Display module: receiving the water turbine runner state information sent by the data processing module, and displaying in a visual manner;

[0052] Control module: processing and controlling the data received from other modules, ensuring the normal operation and safety of the whole system.

[0053] The present application has the following advantages:

[0054] 1. Through efficient and accurate analysis of the dynamic characteristics of the water turbine runner, the working state and possible problems of the water turbine runner can be found in time, so as to adjust or process in time, thereby ensuring the safe operation of the water turbine and improving its operation efficiency.

[0055] 2. By establishing the dynamic vibration monitoring system of the water turbine runner, the state of the runner can be monitored in real time, and once the condition occurs, it can be found first and timely warned, preventing possible equipment damage or serious accidents, and greatly enhancing the safety of the hydropower station.

[0056] 3. Through real-time analysis and early warning of the dynamic characteristics of the runner, the running condition of the equipment can be accurately understood, which is helpful for the maintenance and maintenance of the equipment, prolongs the service life of the equipment, and saves the cost of maintenance and replacement of the equipment. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 The method flowchart of the present application;

[0058] Figure 2 The three-dimensional model diagram of the present application;

[0059] Figure 3 The boundary condition diagram of the present application;

[0060] Figure 4 The system block diagram of the present application. DETAILED DESCRIPTION

[0061] In order to facilitate the understanding of the present application, the present application will be described more fully below with reference to the related drawings. The drawings show typical embodiments of the present application. However, the present application can be realized in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present application more thorough and comprehensive.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. In order to fully understand the application, reference is made to the appended drawings. The drawings show typical embodiments of the application. However, the application can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.

[0063] As shown in Figure 1 The water turbine runner dynamic characteristic analysis method comprises:

[0064] S1, data collection: collect the design specifications and working environment of the water turbine runner, including the influence of vortex, possible corrosion or equipment aging, etc.

[0065] (1) Design specification collection: Collect the design specifications of the water turbine runner, which may include information such as the size, shape, weight, and material of the runner. These information can be obtained from design drawings or relevant production specifications.

[0066] For example, assuming that in the design drawing, the diameter of the runner is D, and the weight is W, such data can be used for model design.

[0067] (2) Working environment data collection: Collect the working environment information of the runner, such as the pressure, temperature, and flow rate of the surrounding fluid, etc. These information can be obtained by monitoring in the field or from operation records.

[0068] For example, suppose through monitoring that the vortex speed is V, the pressure is P, and the temperature is T.

[0069] (3) Vortex effect analysis: According to the collected working environment data, analyze the influence of vortex on the runner through relevant physical models.

[0070] This process will involve relevant formulas of fluid mechanics, such as the Reynolds number Re formula used to describe vortex:

[0071] Re = ρvD / η

[0072] Where ρ is the fluid density, v is the fluid velocity, D is the characteristic length (e.g. runner diameter), and η is the dynamic viscosity.

[0073] (4) Corrosion and equipment aging analysis: For the possible existence of corrosion or equipment aging factors, special detection and analysis are required. This may require the use of relevant detection equipment and evaluation methods, such as measuring the chemical stability or physical changes of the runner material to assess the degree of equipment aging.

[0074] In addition, a common method for evaluating equipment corrosion is electrochemical corrosion testing, sometimes using the change relationship formula of resistivity p or corrosion rate V:

[0075] V = K · A · p

[0076] Where K is the corrosion coefficient, and A is the contact area.

[0077] S2, Model establishment: Based on the collected data, a three-dimensional model is established using computational fluid dynamics software. This model takes into account the water turbine runner part and the involved fluid domain, improving the authenticity and accuracy of the model. The established model is shown in Figure 2 .

[0078] 1) Design parameter setting: According to the design specifications obtained in the data collection step, such as runner diameter, weight, and other parameters, the three-dimensional model of the runner is designed and set. For example, set the key dimensions and physical properties of the model.

[0079] 2) Computational fluid dynamics software selection: Select appropriate computational fluid dynamics (CFD) software, such as ANSYS, Fluent, or OpenFOAM, for model establishment and simulation analysis.

[0080] 3) Liquid flow field model setting: In the CFD software selected in the previous step, set the liquid flow field conditions. This requires setting appropriate initial conditions and boundary conditions for the model based on the working environment data obtained in the data collection step, such as vortex speed, pressure, temperature, and other parameters. For example, set the liquid flow direction, flow rate, and even the contact surface between the liquid and the runner. As shown in Figure 3 .

[0081] 4) Three-dimensional model establishment: After setting the design parameters and fluid conditions, the next step is to use the relevant tools of the software to establish a three-dimensional model of the water turbine runner based on the collected data. This model covers the runner part and the corresponding fluid domain.

[0082] In this process, each step, according to the previous steps and results are updated and optimized, forming a mold to establish a period of successive, closely linked to each link. Model accuracy and authenticity directly affect the accuracy and effectiveness of subsequent excitation frequency calculation, natural frequency analysis and risk frequency range assessment steps, so it has a vital position in the entire water turbine runner dynamic characteristics analysis method.

[0083] S3, excitation frequency calculation: calculation of vortex frequency and dynamic and static interference frequency, calculation of the excitation frequency leading to the water turbine runner vibration, and adjust the exciter strength and position to the best state.

[0084] 1) runner rotation frequency: f0=93.75 / 60=1.56Hz

[0085] 2) vortex frequency: for the mixed flow turbine: 0.6*f0<f1<0.8*f00.9Hz<f1<1.3Hz

[0086] 3) dynamic and static interference frequency

[0087] The runner is subjected to a simple harmonic excitation with a frequency of nZ S f0, Z S The number of guide vanes, f0 is the rotation frequency.

[0088] Theory and experimental results show that n depends on the number of blades and guide vanes, as follows:

[0089] mZ R f0-nZ S f0=kf0

[0090] M: positive or negative integer;

[0091] N: harmonic excitation order (positive integer);

[0092] K: positive or negative integer, whose absolute value determines the number of pitch diameters;

[0093] Z R : the number of blades 15;

[0094] Z S : the number of guide vanes 24;

[0095] From which the key excitation frequency

[0096] n m Node number k Excitation frequency 1 2 6 f2 = 37.5 Hz

[0097] According to experience, avoid the ±15% of the excitation frequency, so the frequency range to be avoided is:

[0098]

[0099] According to the calculation results, there are two order modes in the range

[0100] Mode number Mode frequency [Hz] Mode node number Excitation frequency [Hz] Excitation node number 12 39.051 2 37.5 6 13 39.056 2 37.5 6

[0101] S4, Natural frequency analysis: Using finite element analysis method, the natural frequency and vibration mode of the model are solved under the set boundary conditions.

[0102] 1) Set boundary conditions: Set boundary conditions based on the three-dimensional model established in the previous step, working environment and flow field conditions. Boundary conditions include fixed boundary, free boundary, mixed boundary, etc. For example, set the contact conditions of the runner with the environment, or set the external force that the runner may be subjected to during operation.

[0103] 2) Finite element meshing: The runner model is meshed using the finite element method. This step is generally completed directly through the corresponding finite element analysis software.

[0104] 3) Frequency solving: After meshing, the model is analyzed for natural frequency and vibration mode using a frequency solving algorithm. Natural frequency solving generally involves solving linear algebraic equations and second-order differential equations, such as the Rayleigh-Ritz method. Assuming the motion equation of the system is [M] {a} + [C] {v} + [K] {d} = {F}, where [M], [C], [K] are mass, damping, and stiffness matrices, {a}, {v}, {d} represent acceleration, velocity, and displacement, respectively, and {F} represents external force. The natural frequency ω can be obtained by finding {d} that satisfies {d} = α {d_0} e (iω*t)

[0105] 4) Vibration mode analysis: Based on the natural frequency calculation results, the vibration shape of each order mode can be obtained, and the vibration of the runner at these frequencies can be visualized.

[0106] S5, Hazardous frequency range evaluation: Compare the actual working frequency with the excitation frequency to evaluate whether the water turbine is in a dangerous frequency range where large vibrations may occur.

[0107] 1) Obtain working frequency: Obtain the actual working frequency of the water turbine, denoted as f_working, through online data acquisition or retrieval of the water turbine's operation records.

[0108] 2) Obtain excitation frequency and natural frequency: The data for this step comes directly from the results of the previous two steps, i.e. excitation frequency calculation and natural frequency analysis, denoted as f_excitation and f_natural.

[0109] ​3) Compare frequency: compare the difference between the actual working frequency f_working and the excitation frequency f_excitation and the natural frequency f_natural. If the working frequency is close to or equal to the excitation frequency or the natural frequency, the system may have a larger vibration.

[0110] 4) Define the dangerous frequency range: define a "dangerous frequency range", that is, in this range, the working frequency is close enough to the excitation frequency or the natural frequency, and the vibration may be enhanced. This range is based on empirical or theoretical estimates, and may be adjusted for specific machines or conditions. For example, the dangerous frequency range may be: |f_working-f_excitation|<=δ or |f_working-f_natural|<=δ, where δ is the allowed difference.

[0111] 2) In order to more finely assess the possibility of danger, we can also introduce a risk assessment index R, which has the following expression:

[0112]

[0113] The larger the value of R, the greater the deviation of the device's operating state from the dangerous state; if R exceeds a predetermined threshold, the device is considered to be in a dangerous state.

[0114] 5) Evaluate the risk of vibration: if the working frequency is in the dangerous frequency range, further vibration analysis and possible machine improvement are needed to avoid damage to the water turbine in the long-term operation.

[0115] Example two:

[0116] As shown in Figure 4 , a water turbine runner dynamic vibration monitoring system includes the following modules:

[0117] Data acquisition module: this module collects the working state information of the water turbine runner through sensors, including the rotational speed, vibration, temperature and pressure of the runner, and sends the collected data to the data processing module;

[0118] Data processing module: this module is responsible for receiving data sent by the data acquisition module, and processing data through the set analysis algorithm to calculate the excitation frequency, natural frequency and other information, and then sends these information to the warning module and display module;

[0119] Warning module: this module is responsible for receiving the excitation frequency, natural frequency and other information sent by the data processing module, and judging whether the water turbine runner may be in a dangerous state through the set warning rules. Once it is judged that the runner may be in a dangerous state, a warning signal will be sent out;

[0120] Display module: this module is responsible for receiving the water turbine runner state information sent by the data processing module, and displaying it in a visual manner, so that the operating personnel can timely master the working state of the water turbine runner;

[0121] Control module: this module is responsible for the central control of the system, and processes and controls the data received from other modules to ensure the normal operation and safety of the entire system.

[0122] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing relevant hardware, and the program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments of each method. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM) or a random access memory (RAM), etc.

[0123] It should be understood that the above detailed description of the technical solutions of the present application by means of preferred embodiments is illustrative rather than limiting. Those skilled in the art can modify the technical solutions recorded in each embodiment or make equivalent substitutions for part of the technical features on the basis of the present application; and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. A method for analyzing dynamic characteristics of a water turbine runner, characterized by: The method comprises: Data collection: Collect the design specifications and working environment of the water turbine runner, including the influence of vortex, corrosion or equipment aging factors; Model establishment: According to the collected data, a three-dimensional model is established by using computational fluid dynamics software; Excitation frequency calculation: Calculate the vortex frequency and dynamic-static interference frequency, calculate the excitation frequency that causes the water turbine runner to vibrate, and adjust the strength and position of the exciter to the optimal state; Natural frequency analysis: Under the set boundary conditions, the natural frequency and vibration mode of the model are solved by using the finite element analysis method; Dangerous frequency range evaluation: Compare the actual working frequency with the excitation frequency to evaluate whether the water turbine is in a dangerous frequency range where large vibrations may occur; The model establishment comprises: Design parameter setting: According to the design specifications obtained in the data collection step, the runner diameter, weight parameters, the key size and physical properties of the runner three-dimensional model are set; Liquid flow field model setting: Set the liquid flow field conditions, according to the working environment data obtained in the data collection step, vortex velocity, pressure, temperature parameters, set appropriate initial conditions and boundary conditions for the model; Three-dimensional model establishment: A three-dimensional model of the water turbine runner is established according to the collected data; this model covers the runner part and the corresponding fluid field; The excitation frequency calculation comprises: 1) Runner rotation frequency: f0=93.75 / 60=1.56Hz 2) Vortex frequency: For a Francis turbine: 0.6*f0<f1<0.8*f00.9Hz<f1<1.3Hz 3) Dynamic-static interference frequency The runner is subjected to a simple harmonic excitation of frequency nZ S f0, Z S is the number of vanes, and f0is the rotational frequency; Theoretical and experimental results show that n depends on the number of blades and guide vanes, and has the following relationship: mZ R f0- nZ S f0=kf0 m: positive or negative integer; n: number of simple harmonic excitations, positive integer; k: positive or negative integer, whose absolute value determines the number of pitch diameters; Z R : number of vanes 15; Z S : number of guide vanes 24; The natural frequency analysis comprises: Boundary condition setting: Set the boundary conditions based on the three-dimensional model, working environment and flow field conditions established in the previous steps; the boundary conditions include fixed boundary, free boundary and mixed boundary; Finite element meshing: The runner model is meshed using the finite element method; Frequency solving: After meshing, the natural frequency and vibration mode of the model are analyzed by using the frequency solving algorithm; the natural frequency solving involves solving linear algebraic equations and second-order differential equations, Using Rayleigh-Ritz method; assuming the motion equation of the system is ; Where [M], [C] and [K] are mass, damping and stiffness matrices, respectively, {a}, {v} and {d} represent acceleration, velocity and displacement, respectively, and {F} represents external force; By looking for a {d} that satisfies i.e. gives the natural frequency ω; Mode shape analysis: According to the natural frequency calculation results, the vibration shape of each mode is obtained, and the vibration of the runner at these frequencies is visually displayed.

2. The method of claim 1, wherein: The data collection comprises: Design specification collection: Collect the design specifications of the water turbine runner, including the size, shape, weight and material information of the runner; Working environment data collection: Collect the working environment information of the runner, including the pressure, temperature and flow rate physical parameters of the surrounding fluid; Vortex influence analysis: According to the collected working environment data, analyze the influence of vortex on the runner through a physical model; Corrosion and equipment aging analysis: For existing corrosion or equipment aging factors, special detection and analysis are performed.

3. The method of claim 1, wherein: The dangerous frequency range evaluation comprises: Obtain working frequency: Obtain the actual working frequency of the water turbine through online data collection or by calling the operation record of the water turbine, denoted as f_working; Obtain excitation frequency and natural frequency: The data for this step comes directly from the results of the previous two steps, i.e., excitation frequency calculation and natural frequency analysis, denoted as f_excitation and f_natural; Compare frequencies: Compare the differences between the actual working frequency f_working and the excitation frequency f_excitation and the natural frequency f_natural; Define the dangerous frequency range: This range is estimated based on experience or theory, and the dangerous frequency range is: |f_working - f_excitation| <= δ or |f_working - f_natural| <= δ, where δ is the allowed difference; To more finely assess the possibility of danger, introduce a risk degree evaluation index R, which has the following expression: ; The larger the value of R, the greater the deviation of the device's operating state from the dangerous state; if R exceeds the predetermined threshold, the device is considered to be in a dangerous state.

4. A system for monitoring the dynamic vibrations of a hydraulic turbine runner, said system being suitable for use in the method according to any one of claims 1 to 3, characterized in that: The system includes the following modules: Data acquisition module: Collect the working state information of the water turbine runner through sensors, including the runner speed, vibration, temperature, and pressure physical parameters, and send the collected data to the data processing module; Data processing module: responsible for receiving data sent by the data acquisition module, and processing data through the set analysis algorithm, calculating the excitation frequency and natural frequency information, and then sending these information to the warning module and display module; Warning module: Receive excitation frequency and natural frequency information sent by the data processing module, and determine whether the water turbine runner may be in a dangerous state through the set warning rules. Once it is determined that the runner may be in a dangerous state, a warning signal will be issued; Display module: Receive water turbine runner state information sent by the data processing module and display it in a visual way; Control module: handle and control the data received from other modules to ensure the normal operation and safety of the entire system.

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