Water turbine runner dynamic characteristic analysis method and vibration monitoring system

Abstract

The invention discloses a water turbine runner dynamic characteristic analysis method and a vibration monitoring system, and belongs to the field of water turbine simulation analysis. The method mainly comprises the steps of data acquisition, model establishment, excitation frequency calculation, inherent frequency analysis, danger frequency range evaluation, vibration monitoring system design and the like. The method comprises the following steps: collecting the design specification and the working environment of the turbine runner, establishing a three-dimensional model, calculating the excitation frequency possibly causing the vibration of the turbine runner, solving the inherent frequency and the vibration mode of the model, and evaluating whether the turbine is in a dangerous frequency range in which relatively large vibration possibly occurs or not. And a vibration monitoring system capable of monitoring vibration in real time and early warning possible problems is designed and realized. According to the analysis method, the dynamic characteristics of the turbine runner can be efficiently and accurately analyzed, the vibration monitoring system can monitor the state of the runner in real time, possible problems can be warned in advance, safe operation of the turbine is guaranteed, and the operation efficiency and the equipment management efficiency are improved.

Description

Technical Field

[0001] The invention belongs to the field of water turbine simulation analysis, and more specifically relates to a water turbine runner dynamic characteristic analysis method and a vibration monitoring system. Background Art

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

[0003] However, traditional methods for analyzing the dynamic characteristics of turbine runners mostly rely on traditional physical modeling and manual calculations, which not only consumes time and manpower, but also the accuracy and efficiency of the results cannot be guaranteed.

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

[0005] In addition, the vibration monitoring of the turbine runner is often carried out manually on a regular basis. This method not only consumes a lot of manpower and material resources, but also fails to monitor the dynamic state of the turbine runner in real time, and fails to detect and handle faults in a timely manner, which can easily lead to equipment damage and may even cause major production accidents.

[0006] Therefore, developing a method and system that can efficiently and accurately analyze the dynamic characteristics of the turbine runner and provide real-time monitoring is of great significance for ensuring the operating status and equipment safety of the turbine, reducing maintenance costs, and improving power generation efficiency. Summary of the invention

[0007] The main technical problem to be solved by the present invention is how to provide an efficient, accurate and real-time method for analyzing the dynamic characteristics of a turbine runner, and to design a system for monitoring the dynamic characteristics of a turbine runner, so as to solve the problems of low efficiency, low accuracy, inability to reflect the working status of the runner in real time and to warn of potential problems during the dynamic characteristics analysis and monitoring of the turbine runner.

[0008] In order to achieve the above object, the present invention is implemented by adopting the following technical scheme: the method comprises:

[0009] Data collection: Collect the design specifications and working environment of the turbine runner, including the influence of eddy currents, 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 eddy current frequency and dynamic-static interference frequency, calculate the excitation frequency that causes the turbine runner vibration, and adjust the exciter strength and position to the optimal state;

[0012] Natural frequency analysis: Use finite element analysis to solve the natural frequency and vibration mode of the model under the set boundary conditions;

[0013] Dangerous frequency range assessment: Compare the actual operating frequency with the excitation frequency to assess whether the turbine is in a dangerous frequency range where large vibrations may occur.

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

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

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

[0017] Eddy current impact analysis: Based on the collected working environment data, the impact of eddy current on the runner is analyzed through physical models;

[0018] Corrosion and equipment aging analysis: Conduct special testing and analysis on existing corrosion or equipment aging factors.

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

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

[0021] Liquid flow field model setting: Set the liquid flow field conditions, and set appropriate initialization conditions and boundary conditions for the model based on the working environment data, eddy velocity, pressure, and temperature parameters obtained in the data acquisition step;

[0022] 3D model establishment: A 3D model of the turbine runner is established based on the collected data. This model covers the runner part and the corresponding fluid area.

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

[0024] 1) Rotor frequency: f0 = 93.75 / 60 ​​= 1.56 Hz

[0025] 2) Eddy current frequency: For mixed flow turbine: 0.6*f0 <f1<0.8*f00.9Hz<f1<1.3Hz

[0026] 3) Dynamic and static interference frequency

[0027] The wheel is subjected to a frequency of nZ S Simple harmonic excitation of f0, Z S is the number of guide vanes, f0 is the rotation frequency;

[0028] Theory and experiments have shown that n depends on the number of blades and guide vanes, and there is the following relationship:

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

[0030] M: positive or negative integer; N: simple harmonic excitation order (positive integer); K: positive or negative integer, its absolute value determines the number of nodal diameters of the pressure field; Z R :Number of blades: 15; Z S :The number of guide vanes is 24.

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

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

[0033] Finite element meshing: The finite element method is used to mesh the runner model;

[0034] Frequency solution: After completing the meshing, the frequency solution algorithm is used to perform natural frequency and vibration mode analysis on the model; natural frequency solution involves solving linear algebraic equations and second-order differential equations.

[0035] The Rayleigh-Ritz method is used. Assume that the equation of motion 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 a solution that satisfies {d}=α{d_0}e (iω*t) {d}, that is, the natural frequency ω;

[0038] Vibration shape analysis: Based on the calculation results of the natural frequency, the vibration shapes of each mode are obtained, and the vibration conditions of the wheel at these frequencies are visualized.

[0039] In one embodiment, the critical frequency range assessment includes:

[0040] Obtain working frequency: Obtain the actual working frequency of the turbine by online data collection or retrieving the operation record of the turbine, which is recorded as f_working.

[0041] Get the excitation frequency and natural frequency: The data in this step comes directly from the first two steps, namely the results of the excitation frequency calculation and the natural frequency analysis, recorded as f_excitation and f_natural.

[0042] Compare frequencies: compare the actual working frequency f_working with the excitation frequency f_excitation and the natural frequency f_natural;

[0043] Define the dangerous frequency range: This range is based on experience or theoretical estimation. The dangerous frequency range is: |f_working-f_excitation|<=δ or |f_working-f_natural|<=δ, ​​where δ is the allowable difference;

[0044] In order to more precisely evaluate the possibility of danger, an evaluation index R of the degree of danger is introduced, which has the following expression:

[0045]

[0046] The larger the value of R is, the greater the deviation between the operating state of the equipment and the dangerous state is; if R exceeds a predetermined threshold, the equipment is considered to be in a dangerous state.

[0047] On the other hand, a turbine runner dynamic vibration monitoring system is provided, the system being applicable to the method described, and the system comprising the following modules:

[0048] Data acquisition module: collects the working status information of the turbine runner through sensors, including the speed, vibration, temperature and pressure physical parameters of the runner, and sends the collected data to the data processing module;

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

[0050] Early warning module: Receives information such as excitation frequency and natural frequency sent by the data processing module, and determines whether the turbine runner may be in a dangerous state through the set early warning rules. Once it is determined that the runner may be in a dangerous state, it will issue an early warning signal;

[0051] Display module: receives the turbine runner status information sent by the data processing module and displays it in a visual way;

[0052] Control module: processes and controls the data received from other modules to ensure the normal operation and safety of the entire system.

[0053] Beneficial effects of the present invention:

[0054] 1. Through efficient and accurate analysis of the dynamic characteristics of the turbine runner, the working status and possible problems of the turbine runner can be discovered in time, so that timely adjustments or processing can be made, thereby ensuring the safe operation of the turbine and improving its operating efficiency.

[0055] 2. By establishing a dynamic vibration monitoring system for the turbine runner, the status of the runner can be monitored in real time. Once a problem occurs, it can be discovered first and a warning can be given in time to prevent possible equipment damage or serious accidents, 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 operating status of the equipment can be accurately understood, which is helpful for the maintenance and care of the equipment, prolongs the service life of the equipment, and saves the cost of maintenance and replacement of equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 is a flow chart of the method of the present invention;

[0058] Figure 2 It is a three-dimensional model diagram of the present invention;

[0059] Figure 3 It is the boundary condition diagram of the present invention;

[0060] Figure 4 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0061] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Typical embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in the present invention. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0062] Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used in the present invention in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Typical embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in the present invention. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0063] like Figure 1 The method for analyzing the dynamic characteristics of a hydraulic turbine runner includes:

[0064] S1. Data collection: Collect the design specifications and working environment of the turbine runner, including the influence of eddy currents, possible corrosion or equipment aging, etc.

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

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

[0067] (2) Working environment data collection: Collecting the working environment information of the runner, such as the pressure, temperature, flow rate and other physical parameters of the surrounding fluid. This information can be obtained through on-site monitoring or from operation records.

[0068] For example, suppose that the eddy current velocity is V, the pressure is P, and the temperature is T through monitoring.

[0069] (3) Analysis of eddy current impact: Based on the collected working environment data, the impact of eddy current on the runner is analyzed through relevant physical models.

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

[0071] Re=ρvD / η

[0072] Where ρ is the fluid density, v is the fluid velocity, D is the characteristic length (such as the impeller diameter), and η is the dynamic viscosity.

[0073] (4) Corrosion and equipment aging analysis: Special testing and analysis are required for possible corrosion or equipment aging factors. This may require the use of relevant testing equipment and evaluation methods, such as evaluating the aging degree of the equipment by measuring the chemical stability or physical changes of the wheel material.

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

[0075] V=K·A·p

[0076] Among them, 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 turbine runner part and the fluid domain involved, which improves the authenticity and accuracy of the model. Figure 2 shown.

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

[0079] 2) CFD software selection: Select appropriate CFD software, such as ANSYS, Fluent or OpenFOAM, for model building 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 initialization conditions and boundary conditions for the model based on the working environment data obtained in the data acquisition step, such as eddy current velocity, pressure, temperature and other parameters. For example, set the liquid flow direction, flow rate and even the contact surface between the liquid and the impeller. Figure 3 shown.

[0081] 4) 3D 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 3D model of the turbine runner based on the collected data. This model covers the runner part and the corresponding fluid area.

[0082] Each step in this process needs to be updated and optimized according to the previous steps and results, forming a mold establishment cycle with successive and closely related links. The accuracy and authenticity of the model directly affects the accuracy and effectiveness of subsequent excitation frequency calculation, natural frequency analysis, and dangerous frequency range assessment. Therefore, it plays a vital role in the entire turbine runner dynamic characteristics analysis method.

[0083] S3. Excitation frequency calculation: calculate the eddy current frequency and dynamic-static interference frequency, calculate the excitation frequency that causes the turbine runner vibration, and adjust the exciter strength and position to the optimal state.

[0084] 1) Rotor frequency: f0 = 93.75 / 60 ​​= 1.56 Hz

[0085] 2) Eddy current frequency: For mixed flow turbine: 0.6*f0 <f1<0.8*f00.9Hz<f1<1.3Hz

[0086] 3) Dynamic and static interference frequency

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

[0088] Theory and experiments have shown that n depends on the number of blades and guide vanes, and there is the following relationship:

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

[0090] M: positive or negative integer;

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

[0092] K: a positive or negative integer, whose absolute value determines the number of nodal diameters of the pressure field;

[0093] Z R : Number of blades: 15;

[0094] Z S : Number of guide vanes 24;

[0095] From this, the critical excitation frequency can be calculated

[0096] n m Pitch diameter k Excitation frequency 1 2 6 <![CDATA[f2=37.5Hz]]>

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

[0098]

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

[0100] Mode number Modal frequency [Hz] Modal pitch 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: Use the finite element analysis method to solve the natural frequency and vibration mode of the model under the set boundary conditions.

[0102] 1) Set boundary conditions: Set boundary conditions based on the three-dimensional model, working environment and flow field conditions established in the previous steps. Boundary conditions include fixed boundaries, free boundaries, mixed boundaries, etc. For example, set the contact between the runner and the environment, or set the external forces 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 usually completed directly through the corresponding finite element analysis software.

[0104] 3) Frequency solution: After completing the meshing, use the frequency solution algorithm to perform natural frequency and vibration modal analysis on the model. Natural frequency solution generally involves solving linear algebraic equations and second-order differential equations, such as the Rayleigh-Ritz method. Assume that the system's equation of motion is [M]{a}+[C]{v}+[K]{d}={F}, 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. This can be achieved by finding a condition that satisfies {d}=α{d_0}e (iω*t) {d}, that is, the natural frequency ω is obtained.

[0105] 4) Mode analysis: At the same time, based on the calculation results of the natural frequency, the vibration shape of each mode can be obtained, and the vibration conditions of the wheel at these frequencies can be visualized.

[0106] S5. Assessment of dangerous frequency range: Compare the actual operating frequency with the excitation frequency to assess whether the turbine is in a dangerous frequency range where large vibrations may occur.

[0107] 1) Obtaining the working frequency: Obtain the actual working frequency of the turbine by online data acquisition or retrieving the operation record of the turbine, which is recorded as f_working.

[0108] 2) Obtain the excitation frequency and natural frequency: The data in this step comes directly from the first two steps, namely the results of the excitation frequency calculation and the natural frequency analysis, recorded as f_excitation and f_natural.

[0109] 3) Compare frequencies: Compare the actual working frequency f_working with 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 experience large vibrations.

[0110] 4) Define a dangerous frequency range: Define a "dangerous frequency range", that is, within this range, the operating frequency is close enough to the excitation frequency or natural frequency, and the vibration may be enhanced. This range is based on experience 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 allowable difference.

[0111] 2) In order to more precisely evaluate the possibility of danger, we can also introduce an evaluation index R of the degree of danger, which has the following expression:

[0112]

[0113] The larger the value of R is, the greater the deviation between the operating state of the equipment and the dangerous state is; if R exceeds a predetermined threshold, the equipment is considered to be in a dangerous state.

[0114] 5) Assess vibration hazard: If the operating frequency is in the hazardous frequency range, further vibration analysis and possible machine improvements are required to avoid possible damage to the turbine during long-term operation.

[0115] Embodiment 2:

[0116] like Figure 4 As shown, a turbine runner dynamic vibration monitoring system has the following modules:

[0117] Data acquisition module: This module collects the working status information of the turbine runner through sensors, including physical parameters such as the runner's speed, vibration, temperature and pressure, and sends the collected data to the data processing module;

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

[0119] Early 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 turbine runner may be in a dangerous state through the set early warning rules. Once it is judged that the runner may be in a dangerous state, it will issue an early warning signal;

[0120] Display module: This module is responsible for receiving the turbine runner status information sent by the data processing module and displaying it in a visual way so that the operator can grasp the working status of the turbine runner in time;

[0121] Control module: This module is responsible for the central control of the system, processes and controls the data received from other modules, and ensures 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 embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0123] It should be understood that the detailed description of the technical solutions of the present invention by means of the preferred embodiments is illustrative rather than restrictive. A person skilled in the art may modify the technical solutions described in the embodiments, or replace some of the technical features by equivalents, based on reading the specification of the present invention; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing dynamic characteristics of a turbine runner, characterized in that: The method described above includes: Data collection: Collect the design specifications and working environment of the water turbine runner, including the influence of eddy currents, corrosion or equipment aging factors; Model establishment: Based on the collected data, use computational fluid dynamics software to establish a three-dimensional model; Excitation frequency calculation: Calculate the eddy current frequency and the dynamic-static interference frequency, calculate the excitation frequency that causes the vibration of the water turbine runner, and adjust the intensity and position of the exciter to the optimal state; Natural frequency analysis: Use the finite element analysis method to solve the natural frequency and vibration mode of the model under the set boundary conditions; Dangerous frequency range assessment: Compare the actual working frequency with the excitation frequency to evaluate whether the water turbine is in the dangerous frequency range where large vibrations occur.

2. A method for analyzing dynamic characteristics of a water turbine runner according to claim 1, characterized in that: The data collection described above includes: 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, the physical parameters of the pressure, temperature and flow velocity of the surrounding fluid; Eddy current influence analysis: According to the collected working environment data, analyze the influence of eddy currents on the runner through a physical model; Corrosion and equipment aging analysis: Conduct special inspections and analyses for existing corrosion or equipment aging factors.

3. A method for analyzing dynamic characteristics of a water turbine runner according to claim 1, characterized in that: The model establishment described above includes: Design parameter setting: According to the design specifications obtained in the data collection step, such as the runner diameter, weight and other parameters, set the key dimensions and physical properties of the three-dimensional model of the runner; Liquid flow field model setting: Set the liquid flow field conditions, and according to the working environment data obtained in the data collection step, such as eddy current velocity, pressure, temperature parameters, set appropriate initial conditions and boundary conditions for the model; Three-dimensional model establishment: 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.

4. A method for analyzing dynamic characteristics of a water turbine runner according to claim 1, characterized in that: The excitation frequency calculation described above includes: 1) Runner rotation frequency: f0 = 93.75 / 60 = 1.56Hz 2) Eddy current frequency: For a mixed-flow water turbine: 0.6*f0 < f1 < 0.8*f0 0.9Hz < f1 < 1.3Hz 3) Dynamic-static interference frequency The wheel is subjected to a frequency of nZ S Simple harmonic excitation of f0, Z S is the number of guide vanes, f0 is the rotation frequency; Theory and experiments prove that n depends on the number of blades and guide vanes, and there is the following relationship: mZ R f0-nZ S f0=kf0 M: positive or negative integer; N: simple harmonic excitation order (positive integer); K: positive or negative integer, its absolute value determines the number of nodal diameters of the pressure field; Z R :Number of blades: 15; Z S :The number of guide vanes is 24.

5. A method for analyzing dynamic characteristics of a water turbine runner according to claim 1, characterized in that: The natural frequency analysis described above includes: Set boundary conditions: Set boundary conditions based on the three-dimensional model, working environment and flow field conditions established in the previous steps; The boundary conditions include fixed boundaries, free boundaries, and mixed boundaries; Finite element mesh generation: Use the finite element method to divide the mesh of the runner model; Frequency solution: After completing the mesh generation, use the frequency solution algorithm to analyze the natural frequency and vibration mode of the model; The solution of the natural frequency involves the solution of linear algebraic equations and the solution of second-order differential equations, Adopt the Rayleigh-Ritz method. Assume that the motion equation of the system is [M]{a} + [C]{v} + [K]{d} = {F} Where [M], [C], [K] are the mass, damping, and stiffness matrices respectively, {a}, {v}, {d} represent acceleration, velocity, and displacement respectively, and {F} represents the external force; By finding a solution that satisfies {d}=α{d_0}e (iω*t) {d}, that is, the natural frequency ω; Vibration shape analysis: Based on the calculation results of the natural frequency, the vibration shapes of each mode are obtained, and the vibration conditions of the wheel at these frequencies are visualized.

6. A method for analyzing dynamic characteristics of a water turbine runner according to claim 1, characterized in that: The hazardous frequency range assessment described includes: Obtain working frequency: Obtain the actual working frequency of the turbine by online data collection or retrieving the operation record of the turbine, which is recorded as f_working. Get the excitation frequency and natural frequency: The data in this step comes directly from the first two steps, namely the results of the excitation frequency calculation and the natural frequency analysis, recorded as f_excitation and f_natural. Compare frequencies: compare the actual working frequency f_working with the excitation frequency f_excitation and the natural frequency f_natural; Define the dangerous frequency range: This range is based on experience or theoretical estimation. The dangerous frequency range is: |f_working-f_excitation|<=δ or |f_working-f_natural|<=δ, ​​where δ is the allowable difference; In order to more precisely evaluate the possibility of danger, an evaluation index R of the degree of danger is introduced, which has the following expression: The larger the value of R is, the greater the deviation between the operating state of the equipment and the dangerous state is; if R exceeds a predetermined threshold, the equipment is considered to be in a dangerous state.

7. A turbine runner dynamic vibration monitoring system, the system being applicable to the method according to any one of claims 1 to 6, characterized in that: The system comprises the following modules: Data acquisition module: collects the working status information of the turbine runner through sensors, including the speed, vibration, temperature and pressure physical parameters of the runner, and sends the collected data to the data processing module; Data processing module: responsible for receiving the data sent by the data acquisition module, and processing the data through the set analysis algorithm, calculating the excitation frequency and natural frequency information, and then sending this information to the early warning module and display module; Early warning module: Receives information such as excitation frequency and natural frequency sent by the data processing module, and determines whether the turbine runner may be in a dangerous state through the set early warning rules. Once it is determined that the runner may be in a dangerous state, it will issue an early warning signal; Display module: receives the turbine runner status information sent by the data processing module and displays it in a visual way; Control module: processes and controls the data received from other modules to ensure the normal operation and safety of the entire system.

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