Method and system for optimizing revolution and rotation of runner blade of axial flow water turbine

Abstract

The invention relates to an axial flow turbine runner blade revolution and rotation optimization method and system, and relates to optimization design of an axial flow turbine, the method comprises the following steps: establishing a fluid domain model based on a drawing, and carrying out grid discretization to ensure grid independence; formulating a motion rule of the operation frame, and further determining a rotation rule of the paddle; monitoring pressure pulsation and stress conditions of the key points in CFD simulation through a user-defined function (UDF); carrying out nondimensionalization and peak-to-peak value calculation on the unsteady signal obtained by simulation; decomposing a signal mode by using an empirical mode decomposition (EMD) method; weights are set for modal signals of different blade rotation rules, a genetic algorithm is adopted for optimization, the weight is minimized, and finally the optimal blade revolution and rotation composite motion mode is determined. According to the method, vibration and fluctuation of the water turbine during operation are reduced, and the stability of the water turbine is improved.

Description

Technical Field

[0001] The invention relates to an axial flow water turbine runner blade revolution and rotation optimization method and system, belonging to the axial flow water turbine design and control technical field. Background Art

[0002] As the underwater rotating parts of the turbine for energy conversion, turbine blades are one of the parts that are most likely to be damaged in various power station accidents due to improper design or unreasonable operation. With the increasing requirements for stable operation of large axial flow turbines, the increase in specific speed, power and single unit capacity of newly developed power station turbines, and the continuous increase in unit size, the material strength has increased and the stiffness has been relatively reduced. The vibration problem of turbine blades has received widespread attention.

[0003] There are many reasons for turbine blade vibration. It is affected by the quality of unit design, manufacturing, installation, and maintenance, as well as the operating conditions of the unit and the inlet and outlet water flow conditions of the turbine. During normal operation, the blades of axial flow turbines are subjected to large static stress and relatively small dynamic stress. However, when operating under certain unfavorable conditions (such as water flow disturbance, destruction of the synergy state, flow separation on the blade surface, Karman vortex or cavitation at the tail of the blade, etc.), the dynamic stress will increase significantly, and the vibration amplitude of the blade will also increase accordingly, and even cause destructive accidents. When the blade's natural frequency is close to or equal to the frequency of the interference force, the blade will resonate, which is the most unfavorable to the safe operation of the blade.

[0004] On the other hand, during the operation of the axial flow turbine unit, the guide vanes and the blade openings need to be adjusted according to the water level and matched to maximize the use of water energy. However, in the actual adjustment process of the blades and guide vanes, the complex changes in the flow field caused by the transition process and the deformation of the blades are coupled to each other, causing the blades and the entire relay system to be subjected to complex stress changes, especially the mechanical structures such as the operating frame and the crank arm. If the mechanical strength is insufficient, it may break during the adjustment transition process, causing the unit to shut down or even other accidents, resulting in economic losses.

[0005] The patent document with the publication number "CN119167595A" has developed a method for simulating the defect of the runner blade of a hydropower unit based on CFD and FEM. The problem with this method is that it involves the combination of CFD and FEM, and requires multi-physics field coupling calculations, including fluid-solid coupling, wet modal calculations, etc. These calculations require the use of multiple software tools, such as Fluent, Workbench and Acoustic-Modal, and the calculation process is complex and time-consuming. Summary of the invention

[0006] To solve the problems existing in the above-mentioned prior art, the present invention proposes an optimization method and system for the revolution and rotation of the blades of an axial-flow turbine runner.

[0007] The technical solution of the present invention is as follows:

[0008] On the one hand, the present invention provides an optimization method for the revolution and rotation of the blades of an axial-flow turbine runner, including the following steps:

[0009] Use UG NX software or a three-dimensional model to establish a code based on the drawings of the axial-flow turbine to establish a fluid domain model of the axial-flow turbine;

[0010] Perform grid discretization on the fluid domain model to obtain fluid domain grids, and conduct grid independence tests;

[0011] Formulate the motion law of the operating frame, and obtain the blade rotation law according to the motion law of the operating frame;

[0012] Compile a user-defined function UDF for different blade rotation laws, and set monitoring points during the CFD numerical simulation process. The monitoring points include the pressure pulsation P h measurement points in the non-blade area, the pressure pulsation P d measurement points in the draft tube, the runner and the blades;

[0013] Use the CFD numerical simulation method to simulate the unsteady signals of the monitoring points according to the user-defined function UDF. The unsteady signals include the forces and torques on the runner, the forces and torques on the blades, and the pressure pulsation signals;

[0014] Perform dimensionless processing on the unsteady signals, and calculate the peak-to-peak values of the unsteady signals;

[0015] Use the empirical mode decomposition EMD method to perform modal decomposition on the unsteady signals to obtain the modal signals of the unsteady signals;

[0016] Preset weights for the modal signals of different blade rotation laws to calculate the weights, and use the genetic algorithm for several weights with the minimum weight as the optimization goal to obtain the optimal compound motion mode of the blade revolution and rotation.

[0017] As a preferred embodiment, the method of grid discretization is:

[0018] S1: Use the finite volume method grid division code or ANSYS ICEM software to divide the fluid domain model into discrete grid units based on tetrahedral unstructured grids. The grid units include the leading and trailing edges of the guide vane blades and the blade blades of the fluid domain model, the inlet chamber, the guide vane flow passage, the runner flow passage, the draft tube, the clearance between the blade tips of the runner chamber and the outer wall of the runner chamber;

[0019] S2: Set the number of first grid cells N to be less than 3 million, and generate the first fluid domain grid with the minimum grid quality greater than 0.25;

[0020] S3: Set the number of second grid cells N f , where the number of second grid cells N f and the number of first grid cells N satisfy the first grid encryption ratio r1, and generate the second fluid domain grid with the minimum grid quality greater than 0.25;

[0021]

[0022] S4: Set the number of third grid cells N c , where the number of third grid cells N c and the number of first grid cells N satisfy the second grid encryption ratio r2, and generate the third fluid domain grid with the minimum grid quality greater than 0.25;

[0023]

[0024] S5: Perform numerical simulation on the obtained first fluid domain grid, second fluid domain grid, and third fluid domain grid:

[0025] Preset boundary conditions, set the inlet as the average static pressure type inlet, the pressure is set to 0 Pa, the outlet is set as the mass flow type outlet, and the flow value is the designed flow rate;

[0026] Set the root mean square error RMS < 1 * 10 -5 as the termination condition of the numerical simulation, and set the total pressure of the outlet surface as the target variable, and use Richardson extrapolation to verify the grid independence:

[0027] S6. Calculate the first grid convergence index of the first fluid domain grid and the second fluid domain grid;

[0028] S7. Calculate the second grid convergence index of the first fluid domain grid and the third fluid domain grid;

[0029] S8. If the first grid convergence index and the second grid convergence index are less than 0.05, the step ends; otherwise, execute step S1.

[0030] As a preferred implementation, the steps of the empirical mode decomposition EMD method are:

[0031] D1. Find the minimum and maximum points of the unsteady signal, and perform cubic spline interpolation to obtain the upper envelope h u (t) and the lower envelope h d (t);

[0032] D2. According to the upper envelope h u (t) and the lower envelope hd (t) Calculate the mean signal p(t) of the unsteady signal:

[0033]

[0034] D3. Subtract the mean signal p(t) from the unsteady signal to obtain the modal signal f(t);

[0035] D4. Verify the modal signal:

[0036] The absolute value of the difference between the number of extreme points and the number of zero-crossing points of the modal signal does not exceed 1, and at any time t0, the mean of the upper envelope h u (0) and the lower envelope h d (0) is 0. If satisfied, execute step D5; otherwise, execute step D1;

[0037] D5. Calculate the residual signal:

[0038]

[0039] where, represents the unsteady signal, and g(t) represents the residual signal;

[0040] D6. If the number of extreme points of the residual signal is greater than or equal to 3, use the residual signal as the unsteady signal and execute step D1; otherwise, execute step D7;

[0041] D7. Calculate the maximum values of several modal signals, and find the maximum value among the several maximum values as the modal maximum value

[0042] As a preferred implementation manner, the calculation method of the weight value is:

[0043]

[0044] where, HZ represents the weight value, W j represents the jth preset weight, and ∑H represents the total weight value;

[0045] ∑H = W1·ΔF r * +W2·ΔM r * +W3·ΔF b * +W4·ΔM b * +W5·Δp n * +W6·Δp d *

[0046] +W7·F r*A +W8·M r *A +W9·F b *A +W 10 ·M b *A +W 11 ·p n *A +W 12 ·p d *A ;

[0047]

[0048] Among them, represents the peak-to-peak value of the force on the runner, represents the peak-to-peak value of the force on the runner in the x-axis direction, represents the peak-to-peak value of the force on the runner in the y-axis direction, represents the peak-to-peak value of the force on the runner in the z-axis direction, represents the peak-to-peak value of the torque of the runner relative to the rotating shaft, represents the peak-to-peak value of the total force on the blade, represents the peak-to-peak value of the total force on the blade in the x-axis direction, represents the peak-to-peak value of the force on the k-th blade in the x-axis direction, represents the peak-to-peak value of the total force on the blade in the y-axis direction, represents the peak-to-peak value of the force on the k-th blade in the y-axis direction, represents the peak-to-peak value of the total force on the blade in the z-axis direction, represents the peak-to-peak value of the force on the k-th blade in the z-axis direction, represents the peak-to-peak value of the total torque of the blade relative to the rotating shaft, represents the peak-to-peak value of the torque of the k-th blade relative to the rotating shaft, represents the pressure pulsation P in the non-blade area h the peak-to-peak value of the pressure pulsation signal at the measuring point, represents the pressure pulsation P in the draft tube d the peak-to-peak value of the pressure pulsation signal at the measuring point, represents the modal maximum value of the force on the runner, represents the modal maximum value of the torque of the runner relative to the rotating shaft, represents the modal maximum value of the total force on the blade, represents the modal maximum value of the total torque of the blade relative to the rotating shaft, represents the pressure pulsation P in the non-blade area n the modal maximum value of the pressure pulsation signal at the measuring point, represents the pressure pulsation P in the draft tube dThe modal maximum values of the pressure pulsation signals at the measurement points, W1, W2, W3, W4, W5, W6, W7, W8, W9, W 10 、W 11 、W 12 、W x 、W y 、W z represent the preset weights, W k represents the k-th preset weight, and n represents the number of blades.

[0049] As a preferred embodiment, the motion law of the operating frame includes:

[0050] Moving at a constant speed at different speeds;

[0051] Performing a first-acceleration-then-deceleration motion with different accelerations, where the accelerations in the acceleration stage and the deceleration stage are the same;

[0052] Performing a first-acceleration-then-deceleration motion with different accelerations, where the accelerations in the acceleration stage and the deceleration stage are different.

[0053] On the other hand, the present invention also provides an optimized system for the revolution and rotation of the blades of an axial-flow turbine runner, including:

[0054] Fluid domain model module: Using UG NX software or three-dimensional model building code based on the drawings of the axial-flow turbine to establish the fluid domain model of the axial-flow turbine; performing grid discretization on the fluid domain model to obtain the fluid domain grid, and conducting grid independence tests;

[0055] Signal simulation module: Formulating the motion law of the operating frame, and obtaining the blade rotation law according to the motion law of the operating frame; compiling a user-defined function UDF for different blade rotation laws, and setting monitoring points during the CFD numerical simulation process, where the monitoring points include the pressure pulsation P n measurement points in the non-blade area, the pressure pulsation P d measurement points in the draft tube, the runner and the blades; using the CFD numerical simulation method to simulate the unsteady signals of the monitoring points according to the user-defined function UDF, where the unsteady signals include the forces and torques on the runner, the forces and torques on the blades, and the pressure pulsation signals;

[0056] Signal processing module: Performing dimensionless processing on the unsteady signals, and calculating the peak-to-peak values of the unsteady signals; using the empirical mode decomposition EMD method to perform modal decomposition on the unsteady signals to obtain the modal signals of the unsteady signals;

[0057] Optimization module: Presetting weights for the modal signals of different blade rotation laws to calculate the weights, and using the genetic algorithm for several weights with the minimum weight as the optimization goal to obtain the optimal compound motion mode of the blade revolution and rotation.

[0058] As a preferred embodiment, the method of grid discretization is as follows:

[0059] S1: Use the finite volume method grid generation code or ANSYS ICEM software to divide the fluid domain model into discrete grid cells based on tetrahedral unstructured grids. The grid cells include the leading and trailing edges of the guide vane blades and runner blades in the fluid domain model, the inlet chamber, the guide vane flow passage, the runner flow passage, the draft tube, the clearance between the top of the runner blades in the runner chamber, and the outer wall of the runner chamber;

[0060] S2: Set the number of the first grid cells N to be less than 3 million, and generate the first fluid domain grid with the minimum grid quality value greater than 0.25;

[0061] S3: Set the number of the second grid cells N f , and the number of the second grid cells N f satisfies the first grid encryption ratio r1 with the number of the first grid cells N, and generate the second fluid domain grid with the minimum grid quality value greater than 0.25;

[0062]

[0063] S4: Set the number of the third grid cells N c , and the number of the third grid cells N c satisfies the second grid encryption ratio r2 with the number of the first grid cells N, and generate the third fluid domain grid with the minimum grid quality value greater than 0.25;

[0064]

[0065] S5: Conduct numerical simulations on the obtained first fluid domain grid, second fluid domain grid, and third fluid domain grid:

[0066] Preset the boundary conditions. Set the inlet as the average static pressure type inlet with the pressure set to 0 Pa, and set the outlet as the mass flow rate type outlet with the flow rate value set to the designed flow rate;

[0067] Set the root mean square error RMS < 1×10 -5 as the termination condition of the numerical simulation, and use the Richardson extrapolation method to verify the grid independence with the total pressure on the outlet surface as the target variable:

[0068] S6. Calculate the first grid convergence index of the first fluid domain grid and the second fluid domain grid;

[0069] S7. Calculate the second grid convergence index of the first fluid domain grid and the third fluid domain grid;

[0070] S8. If the first grid convergence index and the second grid convergence index are less than 0.05, the step ends; otherwise, execute step S1.

[0071] As a preferred embodiment, the steps of the empirical mode decomposition (EMD) method are as follows:

[0072] D1. Find the minimum and maximum points of the non-steady signal, and perform cubic spline interpolation to obtain the upper envelope h u (t) and the lower envelope h d (t);

[0073] D2. Calculate the mean signal p(t) of the non-steady signal according to the upper envelope h u (t) and the lower envelope h d (t):

[0074]

[0075] D3. Subtract the mean signal p(t) from the non-steady signal to obtain the modal signal f(t);

[0076] D4. Verify the modal signal:

[0077] The absolute value of the difference between the number of extreme points and the number of zero-crossing points of the modal signal does not exceed 1, and at any time t0, the mean of the upper envelope h u (0) and the lower envelope h d (0) is 0. If satisfied, execute step D5; otherwise, execute step D1;

[0078] D5. Calculate the residue signal:

[0079]

[0080] where, represents the non-steady signal, and g(t) represents the residue signal;

[0081] D6. If the number of extreme points of the residue signal is greater than or equal to 3, use the residue signal as the non-steady signal and execute step D1; otherwise, execute step D7;

[0082] D7. Calculate the maximum values of several modal signals, and find the maximum value among the several maximum values as the modal maximum value

[0083] As a preferred embodiment, the calculation method of the weight value is as follows:

[0084]

[0085] where, HZ represents the weight value, W j represents the jth preset weight, and ∑H represents the total weight value; ∑H = W1·ΔF r * + W2·ΔM r* +W3·ΔF b * +W4·ΔM b * +W5·Δp n * +W6·Δp d * +W7·F r *A +W8·M r *A +W9·F b *A +W 10 ·M b *A +W 11 ·p n *A +W 12 ·p d *A ;

[0086]

[0087] wherein, represents the peak-to-peak value of the force on the runner, represents the peak-to-peak value of the force on the runner in the x-axis direction, represents the peak-to-peak value of the force on the runner in the y-axis direction, represents the peak-to-peak value of the force on the runner in the z-axis direction, represents the peak-to-peak value of the torque of the runner relative to the rotating shaft, represents the peak-to-peak value of the total force on the blade, represents the peak-to-peak value of the total force on the blade in the x-axis direction, represents the peak-to-peak value of the force on the k-th blade in the x-axis direction, represents the peak-to-peak value of the total force on the blade in the y-axis direction, represents the peak-to-peak value of the force on the k-th blade in the y-axis direction, represents the peak-to-peak value of the total force on the blade in the z-axis direction, represents the peak-to-peak value of the force on the k-th blade in the z-axis direction, represents the peak-to-peak value of the total torque of the blade relative to the rotating shaft, represents the peak-to-peak value of the torque of the k-th blade relative to the rotating shaft, represents the pressure pulsation P in the non-blade area, n the peak-to-peak value of the pressure pulsation signal at the measuring point, represents the pressure pulsation P in the draft tube, d the peak-to-peak value of the pressure pulsation signal at the measuring point, represents the modal maximum value of the force on the runner, represents the modal maximum value of the torque of the runner relative to the rotating shaft, Represents the modal maximum value of the total force on the blade Represents the modal maximum value of the total torque of the blade with respect to the rotation axis Represents the pressure pulsation P in the bladeless area n The modal maximum value of the pressure pulsation signal at the measuring point Represents the pressure pulsation P in the draft tube d The modal maximum value of the pressure pulsation signal at the measuring point, W1, W2, W3, W4, W5, W6, W7, W8, W9, W 10 、W 11 、W 12 、W x 、W y 、W z Represents the preset weight, W k Represents the k-th preset weight, and n represents the number of blades

[0088] As a preferred embodiment, the motion law of the operating frame includes:

[0089] Perform uniform motion at different speeds;

[0090] Perform accelerated-then-decelerated motion with different accelerations, and the accelerations in the acceleration stage and the deceleration stage are the same;

[0091] Perform accelerated-then-decelerated motion with different accelerations, and the accelerations in the acceleration stage and the deceleration stage are different

[0092] The present invention has the following beneficial effects:

[0093] By formulating the motion law of the operating frame and obtaining the blade rotation law, and then combining the CFD numerical simulation and the empirical mode decomposition EMD method, the present invention can accurately analyze the force conditions of the runner and the blade and the pressure pulsation signal under different blade rotation laws. On this basis, using the genetic algorithm with the minimum weight value as the optimization target, the optimal compound motion mode of the blade's revolution and rotation can be obtained, thereby effectively reducing the vibration and fluctuation of the water turbine during operation and improving its operation stability. By establishing the fluid domain model of the axial-flow water turbine and performing grid discretization and grid independence test, the internal flow field of the water turbine can be accurately simulated. After formulating the motion law of the operating frame and obtaining the blade rotation law, and then combining the CFD numerical simulation, the influence of different blade rotation laws on the flow field can be analyzed, thereby optimizing the flow field, reducing energy loss, and improving the efficiency of the water turbine. By setting monitoring points during the CFD numerical simulation, including the pressure pulsation measuring points in the bladeless area and the draft tube pressure pulsation measuring points, and monitoring the runner and the blade simultaneously, the operation state of the water turbine can be monitored in real time. Once an abnormal situation is found, measures can be taken in time to avoid accidents and improve the operation safety of the water turbine Brief Description of the Drawings

[0094] Figure 1 This is the implementation flowchart of the method of the present invention.

[0095] Figure 2 This is the schematic diagram of the monitoring point positions of the present invention.

[0096] Figure 3 This is the schematic diagram of the connection of the operating frame, the swivel arm and the blade rotating shaft of the present invention. Detailed implementation manners

[0097] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part rather than all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0098] It should be understood that the step numbers used herein are only for convenient description and do not limit the order of execution of the steps.

[0099] It should be understood that the terms used 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. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0100] The terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0101] The term " / and / " refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0102] Embodiment 1:

[0103] Refer to Figure 1-2 , the present invention provides an optimized method for the revolution and rotation of the runner blades of an axial-flow water turbine, including the following steps:

[0104] Use UG NX software or 3D model building code to establish a fluid domain model of the axial-flow water turbine according to the drawings of the axial-flow water turbine;

[0105] Perform grid discretization on the fluid domain model to obtain fluid domain grids and conduct grid independence tests;

[0106] Refer to Figure 3, formulate the motion law of the operating frame, and obtain the rotation law of the blade according to the motion law of the operating frame;

[0107] Compile a user-defined function UDF for different blade rotation laws. The user-defined function UDF obtains the change of the blade position with time, and the specific expression can be deduced mathematically according to the mechanical structure constraints. And set monitoring points during the CFD numerical simulation process. The monitoring points include the pressure pulsation P n measurement point, the pressure pulsation P d measurement point of the draft tube; at the same time, monitor the forces F rx in the x, y, and z directions of the runner and the blade, and monitor the runner ry in the x, y, and z directions of the runner and the blade, and monitor the runner rz in the x, y, and z directions of the runner and the blade, and monitor the torque M of the runner relative to the rotating shaft r in the x, y, and z directions of the runner and the blade, and monitor the forces F bxk in the x, y, and z directions of the runner and the blade, and monitor the forces F byk in the x, y, and z directions of the runner and the blade, and monitor the forces F bzk in the x, y, and z directions of the runner and the blade, and monitor the torque M of each blade relative to its own rotation axis bk , (where k is the kth blade);

[0108] Use the CFD numerical simulation method to simulate the unsteady signals of the monitoring points according to the user-defined function UDF. The unsteady signals include the forces and torques of the runner, the forces and torques of the blade, and the pressure pulsation signals;

[0109] Perform dimensionless processing on the unsteady signals and calculate the peak-to-peak values of the unsteady signals;

[0110] Use the empirical mode decomposition EMD method to perform mode decomposition on the unsteady signals to obtain the mode signals of the unsteady signals;

[0111] Preset weight calculation weights for the mode signals of different blade rotation laws, and use the genetic algorithm for several weights with the minimum weight as the optimization goal to obtain the optimal compound motion mode of the blade's revolution and rotation.

[0112] As a preferred implementation method, the method of grid discretization is as follows:

[0113] S1: Use the finite volume method grid division code or ANSYS ICEM software to divide the fluid domain model into discrete grid cells based on tetrahedral unstructured grids. The grid cells include the leading and trailing edges of the guide vane blades and the blade blades of the fluid domain model, the inlet chamber, the guide vane flow channel, the runner flow channel, the draft tube, the clearance between the blade tip of the runner chamber and the outer wall of the runner chamber;

[0114] S2: Set the number of the first grid cells N to be less than 3 million, and generate the first fluid domain grid with the minimum grid quality greater than 0.25;

[0115] S3: Set the number of second grid cells N f , where the number of second grid cells N f and the number of first grid cells N satisfy the first grid encryption ratio r1, and the minimum grid quality is greater than 0.25 to generate the second fluid domain grid;

[0116]

[0117] S4: Set the number of third grid cells N c , where the number of third grid cells N c and the number of first grid cells N satisfy the second grid encryption ratio r2, and the minimum grid quality is greater than 0.25 to generate the third fluid domain grid;

[0118]

[0119] S5: Perform numerical simulation on the obtained first fluid domain grid, second fluid domain grid, and third fluid domain grid:

[0120] Preset boundary conditions, set the inlet as an average static pressure type inlet, the pressure is set to 0 Pa, the outlet is set as a mass flow type outlet, and the flow value is the design flow;

[0121] Set the root mean square error RMS < 1 * 10 -5 as the termination condition of the numerical simulation, and the total pressure of the outlet surface is the target variable, and use Richardson extrapolation to verify the grid independence:

[0122] S6. Calculate the first grid convergence index of the first fluid domain grid and the second fluid domain grid;

[0123] S7. Calculate the second grid convergence index of the first fluid domain grid and the third fluid domain grid;

[0124] S8. If the first grid convergence index and the second grid convergence index are less than 0.05, the step ends; otherwise, execute step S1.

[0125] As a preferred implementation manner, the steps of the empirical mode decomposition EMD method are:

[0126] D1. Find the minimum and maximum points of the unsteady signal, and perform cubic spline interpolation to obtain the upper envelope h u (t) and the lower envelope h d (t);

[0127] D2. Calculate the mean signal p(t) of the unsteady signal according to the upper envelope h u (t) and the lower envelope h d (t):

[0128]

[0129] D3. Subtract the mean signal p(t) from the unsteady signal to obtain the modal signal f(t);

[0130] D4. Verify the modal signal:

[0131] The absolute value of the difference between the number of extreme points and the number of zero-crossing points of the modal signal does not exceed 1, and at any time t0, the mean value of the upper envelope h u (0) and the lower envelope h d (0) is 0. If satisfied, execute step D5; otherwise, execute step D1.

[0132] D5. Calculate the residual signal:

[0133]

[0134] where, represents the unsteady signal, and g(t) represents the residual signal;

[0135] D6. If the number of extreme points of the residual signal is greater than or equal to 3, use the residual signal as the unsteady signal and execute step D1; otherwise, execute step D7.

[0136] D7. Calculate the maximum values of several modal signals, and find the maximum value among the several maximum values as the modal maximum value

[0137] As a preferred implementation method, the calculation method of the weight value is:

[0138]

[0139] where, HZ represents the weight value, W j represents the jth preset weight, and ∑H represents the total weight value;

[0140] ∑H = W1·ΔF r * +W2·ΔM r * +W3·ΔF b * +W4·ΔM b * +W5·Δp n * +W6·Δp d *

[0141] +W7·F r *A +W8·M r *A +W9·F b*A +W 10 ·M b *A +W 11 ·p n *A +W 12 ·p d *A ;

[0142]

[0143]

[0144] Among them, represents the peak-to-peak value of the force on the runner, represents the peak-to-peak value of the force on the runner in the x-axis direction, represents the peak-to-peak value of the force on the runner in the y-axis direction, represents the peak-to-peak value of the force on the runner in the z-axis direction, represents the peak-to-peak value of the torque of the runner relative to the rotating shaft, represents the peak-to-peak value of the total force on the blade, represents the peak-to-peak value of the total force on the blade in the x-axis direction, represents the peak-to-peak value of the force on the k-th blade in the x-axis direction, represents the peak-to-peak value of the total force on the blade in the y-axis direction, represents the peak-to-peak value of the force on the k-th blade in the y-axis direction, represents the peak-to-peak value of the total force on the blade in the z-axis direction, represents the peak-to-peak value of the force on the k-th blade in the z-axis direction, represents the peak-to-peak value of the total torque of the blade relative to the rotating shaft, represents the peak-to-peak value of the torque of the k-th blade relative to the rotating shaft, represents the pressure pulsation P in the non-blade area, n the peak-to-peak value of the pressure pulsation signal at the measuring point, represents the pressure pulsation P in the draft tube, d the peak-to-peak value of the pressure pulsation signal at the measuring point, represents the modal maximum value of the force on the runner, represents the modal maximum value of the torque of the runner relative to the rotating shaft, represents the modal maximum value of the total force on the blade, represents the modal maximum value of the total torque of the blade relative to the rotating shaft, represents the pressure pulsation P in the non-blade area, n the modal maximum value of the pressure pulsation signal at the measuring point, represents the pressure pulsation P in the draft tube, dThe modal maximum values of the pressure pulsation signals at the measurement points, W1, W2, W3, W4, W5, W6, W7, W8, W9, W 10 , W 11 , W 12 , W x , W y , W z represent preset weights, W k represents the k-th preset weight, and n represents the number of blades.

[0145] As a preferred embodiment, the motion law of the operation frame includes moving at a constant speed at different speeds;

[0146] Performing a first-acceleration-then-deceleration motion with different accelerations, where the accelerations in the acceleration stage and the deceleration stage are the same;

[0147] Performing a first-acceleration-then-deceleration motion with different accelerations, where the accelerations in the acceleration stage and the deceleration stage are different;

[0148] Adopting a quadratic function method.

[0149] Embodiment 2:

[0150] The present invention also provides an optimized system for the revolution and rotation of the blades of an axial-flow water turbine runner, including:

[0151] Fluid domain model module: Using UG NX software or three-dimensional model building code to establish a fluid domain model of the axial-flow water turbine according to the drawings of the axial-flow water turbine; performing grid discretization on the fluid domain model to obtain fluid domain grids, and performing grid independence tests;

[0152] Signal simulation module: Formulating the motion law of the operation frame, and obtaining the blade rotation law according to the motion law of the operation frame; compiling a user-defined function UDF for different blade rotation laws, and setting monitoring points during the CFD numerical simulation process, where the monitoring points include the pressure pulsation P n measurement points, the draft tube pressure pulsation P d measurement points, the runner and the blades; simulating the unsteady signals of the monitoring points by using the CFD numerical simulation method according to the user-defined function UDF, where the unsteady signals include the forces and torques on the runner, the forces and torques on the blades, and the pressure pulsation signals;

[0153] Signal processing module: Performing dimensionless processing on the unsteady signals, and calculating the peak-to-peak values of the unsteady signals; performing modal decomposition on the unsteady signals by using the empirical mode decomposition EMD method to obtain the modal signals of the unsteady signals;

[0154] Optimization module: Preset weight calculation weights for the modal signals of different blade rotation laws, and use the genetic algorithm for several weights with the minimum weight as the optimization goal to obtain the optimal compound motion mode of the blade's revolution and rotation.

[0155] As a preferred implementation manner, the method of grid discretization is as follows:

[0156] S1: Use the finite volume method grid division code or ANSYS ICEM software to divide the fluid domain model into discrete grid cells based on tetrahedral unstructured grids. The grid cells include the leading and trailing edges of the guide vane blades and the blade blades of the fluid domain model, the inlet chamber, the guide vane flow passage, the runner flow passage, the draft tube, the clearance between the blade tip of the runner chamber blade and the outer wall of the runner chamber;

[0157] S2: Set the number of the first grid cells N to be less than 3 million, and generate the first fluid domain grid with the minimum grid quality greater than 0.25;

[0158] S3: Set the number of the second grid cells N f , where the number of the second grid cells N f and the number of the first grid cells N satisfy the first grid encryption ratio r1, and generate the second fluid domain grid with the minimum grid quality greater than 0.25;

[0159]

[0160] S4: Set the number of the third grid cells N c , where the number of the third grid cells N c and the number of the first grid cells N satisfy the second grid encryption ratio r2, and generate the third fluid domain grid with the minimum grid quality greater than 0.25;

[0161]

[0162] S5: Conduct numerical simulations on the obtained first fluid domain grid, second fluid domain grid, and third fluid domain grid:

[0163] Preset boundary conditions, set the inlet as the average static pressure type inlet, the pressure as 0 Pa, the outlet as the mass flow type outlet, and the flow value as the design flow;

[0164] Set the root mean square error RMS < 1 * 10 -5 as the termination condition of the numerical simulation, and use the Richardson extrapolation method to verify the grid independence with the total pressure of the outlet surface as the target variable:

[0165] S6. Calculate the first grid convergence index of the first fluid domain grid and the second fluid domain grid;

[0166] S7. Calculate the second grid convergence index of the first fluid domain grid and the third fluid domain grid;

[0167] S8. If the first grid convergence index and the second grid convergence index are less than 0.05, end the steps; otherwise, execute step S1.

[0168] As a preferred embodiment, the steps of the empirical mode decomposition (EMD) method are as follows:

[0169] D1. Find the minimum and maximum points of the unsteady signal, and perform cubic spline interpolation to obtain the upper envelope h u (t) and the lower envelope h d (t);

[0170] D2. Calculate the mean signal p(t) of the unsteady signal according to the upper envelope h u (t) and the lower envelope h d (t):

[0171]

[0172] D3. Subtract the mean signal p(t) from the unsteady signal to obtain the modal signal f(t);

[0173] D4. Verify the modal signal:

[0174] The absolute value of the difference between the number of extreme points and the number of zero-crossing points of the modal signal does not exceed 1, and at any time t0, the mean of the upper envelope h u (0) and the lower envelope h d (0) is 0. If satisfied, execute step D5; otherwise, execute step D1;

[0175] D5. Calculate the residual signal:

[0176]

[0177] where represents the unsteady signal, and g(t) represents the residual signal;

[0178] D6. If the number of extreme points of the residual signal is greater than or equal to 3, use the residual signal as the unsteady signal and execute step D1; otherwise, execute step D7;

[0179] D7. Calculate the maximum values of several modal signals, and find the maximum value among the several maximum values as the modal maximum value

[0180] As a preferred embodiment, the calculation method of the weight value is as follows:

[0181]

[0182] Among them, HZ represents the weight value, and W j represents the j-th preset weight, and ∑H represents the total weight value;

[0183] ∑H = W1·ΔF r * + W2·ΔM r * + W3·ΔF b * + W4·ΔM b * + W5·Δp n * + W6·Δp d *

[0184] + W7·F r *A + W8·M r *A + W9·F b *A + W 10 ·M b *A + W 11 ·p n *A + W 12 ·p d *A ;

[0185]

[0186]

[0187] Among them, represents the peak-to-peak value of the force on the runner, represents the peak-to-peak value of the force on the runner in the x-axis direction, represents the peak-to-peak value of the force on the runner in the y-axis direction, represents the peak-to-peak value of the force on the runner in the z-axis direction, represents the peak-to-peak value of the torque of the runner relative to the rotating shaft, represents the peak-to-peak value of the total force on the blade, represents the peak-to-peak value of the total force on the blade in the x-axis direction, represents the peak-to-peak value of the force on the k-th blade in the x-axis direction, represents the peak-to-peak value of the total force on the blade in the y-axis direction, represents the peak-to-peak value of the force on the k-th blade in the y-axis direction, represents the peak-to-peak value of the total force on the blade in the z-axis direction, represents the peak-to-peak value of the force on the k-th blade in the z-axis direction, Indicates the peak-to-peak value of the total torque of the blade with respect to the rotation axis, Indicates the peak-to-peak value of the torque of the k-th blade with respect to the rotation axis, Indicates the pressure pulsation P in the non-blade area n The peak-to-peak value of the pressure pulsation signal at the measurement point, Indicates the pressure pulsation P in the draft tube d The peak-to-peak value of the pressure pulsation signal at the measurement point, Indicates the modal maximum value of the force on the runner, Indicates the modal maximum value of the torque of the runner with respect to the rotating shaft, Indicates the modal maximum value of the total force on the blade, Indicates the modal maximum value of the total torque of the blade with respect to the rotation axis, Indicates the pressure pulsation P in the non-blade area n The modal maximum value of the pressure pulsation signal at the measurement point, Indicates the pressure pulsation P in the draft tube d The modal maximum value of the pressure pulsation signal at the measurement point, W1, W2, W3, W4, W5, W6, W7, W8, W9, W 10 、W 11 、W 12 、W x 、W y 、W z Indicates the preset weight, W k Indicates the k-th preset weight, and n indicates the number of blades.

[0188] As a preferred embodiment, the movement law of the operating frame includes moving at a constant speed at different speeds;

[0189] Accelerate first and then decelerate with different accelerations, and the accelerations in the acceleration stage and the deceleration stage are the same;

[0190] Accelerate first and then decelerate with different accelerations, and the accelerations in the acceleration stage and the deceleration stage are different;

[0191] Adopt the quadratic function method.

[0192] In the embodiments of the present application, "at least one" means one or more, and "a plurality of" means two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent the cases of A existing alone, A and B existing simultaneously, and B existing alone. Where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" and its similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0193] Those of ordinary skill in the art can realize that the various units and algorithm steps described in the embodiments disclosed herein can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0194] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0195] In several embodiments provided by the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (hereinafter referred to as ROM), random access memories (hereinafter referred to as RAM), magnetic disks, or optical discs that can store program codes.

[0196] The above are only the embodiments of the present invention, and thus do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A method for optimizing the revolution and rotation of an axial flow turbine runner blade, characterized in that: The following steps are involved: Establish the fluid domain model of the axial flow turbine according to the drawings of the axial flow turbine; Discretizing the fluid domain model into a grid to obtain a fluid domain grid, and performing a grid independence test; Formulate the motion law of the operating frame, and obtain the rotation law of the blades based on the motion law of the operating frame; According to different blade rotation laws, a user-defined function (UDF) is compiled, and monitoring points are set during the CFD numerical simulation process. The monitoring points include the pressure pulsation P in the bladeless area. n Measuring point, tailwater pipe pressure pulsation P d Measuring points, rotors and blades; Using a CFD numerical simulation method according to a user-defined function UDF to simulate the unsteady signals of the monitoring point, the unsteady signals include the force and torque of the runner, the force and torque of the blade, and the pressure pulsation signal; Performing dimensionless processing on the unsteady signal and calculating the peak-to-peak value of the unsteady signal; Using an empirical mode decomposition (EMD) method to perform modal decomposition on the unsteady signal to obtain a modal signal of the unsteady signal; The weights are calculated by presetting weights for modal signals of different blade rotation laws, and a genetic algorithm is used for several weights with the minimum weight as the optimization target to obtain the optimal blade revolution and rotation compound motion mode.

2. The method for optimizing the revolution and rotation of the axial flow turbine runner blades according to claim 1, characterized in that: The grid discretization method is: S1: using a finite volume method meshing code to divide the fluid domain model into discrete grid units based on tetrahedral unstructured grids, wherein the grid units include the leading and trailing edges of the guide vane blades and the blades of the fluid domain model, the water inlet chamber, the guide vane flow channel, the runner flow channel, the draft tube, the blade top of the runner chamber, and the gap of the outer wall of the runner chamber; S2: Set the number of first grid cells N to less than 3 million and the minimum value of grid quality to greater than 0.25 to generate the first fluid domain grid; S3: Set the second grid unit number N f , the second grid unit number N f The second fluid domain grid is generated when the number of first grid cells N satisfies the first grid encryption ratio r1 and the minimum grid quality value is greater than 0.25; S4: Set the third grid unit number N c , the third grid unit number N c The third fluid domain grid is generated when the number of first grid cells N satisfies the second grid density ratio r2 and the minimum grid quality value is greater than 0.25; S5: Perform numerical simulation on the obtained first fluid domain grid, second fluid domain grid and third fluid domain grid: Preset boundary conditions, the inlet is set to the average static pressure type inlet, the pressure is set to 0Pa, the outlet is set to the mass flow type outlet, and the flow value is the design flow; Set the root mean square error RMS < 1*10 -5 As the termination condition of the numerical simulation, the total pressure at the outlet is taken as the target variable, and the Richardson extrapolation method is used to verify the grid independence: S6, calculating a first grid convergence index of the first fluid domain grid and the second fluid domain grid; S7, calculating a second grid convergence index of the first fluid domain grid and the third fluid domain grid; S8. If the first grid convergence index and the second grid convergence index are less than 0.05, the step ends; otherwise, execute step S1.

3. The method for optimizing the revolution and rotation of the axial flow turbine runner blades according to claim 2, characterized in that: The steps of the EMD method are: D1. Find the minimum and maximum points of the non-steady signal, and perform cubic spline interpolation to obtain the upper envelope h u (t) and the lower envelope h d (t); D2, according to the upper envelope h u (t) and the lower envelope h d (t) Calculate the mean signal p(t) of the unsteady signal: D3. Subtract the mean signal p(t) from the unsteady signal to obtain the modal signal f(t); D4. Verify the modal signal: The absolute value of the difference between the number of extreme points and the number of zero crossing points of the modal signal does not exceed 1, and at any time t0, the upper envelope h u (t0) and the lower envelope h d The mean value of (t0) is 0. If it is satisfied, execute step D5, otherwise execute step D1; D5. Calculate the residual signal: in, represents the unsteady signal, g(t) represents the residual signal; D6. If the number of extreme value points of the residual signal is greater than or equal to 3, the residual signal is regarded as an unsteady signal and step D1 is executed; otherwise, step D7 is executed; D7. Calculate the maximum values ​​of several modal signals and find the maximum value among several maximum values ​​as the modal maximum value 4. The method for optimizing the revolution and rotation of the axial flow turbine runner blades according to claim 3, characterized in that: The weight is calculated as: Among them, HZ represents the weight, W j represents the jth preset weight, ∑H represents the total weight; in, It represents the peak-to-peak value of the force on the runner. It represents the peak-to-peak value of the force on the wheel in the x-axis direction. It represents the peak-to-peak value of the force on the wheel in the y-axis direction. It represents the peak-to-peak value of the force on the wheel in the z-axis direction. It represents the peak-to-peak torque of the wheel relative to the shaft. represents the peak-to-peak value of the total force on the blade, It represents the peak-to-peak value of the total force on the blade in the x-axis direction. represents the peak-to-peak value of the force on the kth blade in the x-axis direction, It represents the peak-to-peak value of the total force on the blade in the y-axis direction. represents the peak-to-peak value of the force on the kth blade in the y-axis direction, It represents the peak-to-peak value of the total force on the blade in the z-axis direction. represents the peak-to-peak value of the force on the kth blade in the z-axis direction, It represents the total peak-to-peak torque of the blade on the rotating shaft, represents the peak-to-peak torque of the kth blade on the rotating shaft, Indicates the pressure pulsation in the bladeless area P n Peak-to-peak value of the pressure pulsation signal at the measuring point, Indicates the tailwater pressure pulsation P d Peak-to-peak value of the pressure pulsation signal at the measuring point, represents the maximum modal value of the wheel force, represents the modal maximum value of the torque of the wheel relative to the shaft, represents the modal maximum value of the total force on the blade, represents the modal maximum value of the total torque of the blade on the rotating shaft, Indicates the pressure pulsation in the bladeless area P n The modal maximum value of the pressure pulsation signal at the measuring point, Indicates the tailwater pressure pulsation P d The modal maximum values ​​of the pressure pulsation signal at the measuring point, W1, W2, W3, W4, W5, W6, W7, W8, W9, W 10 , W 11 , W 12 , W x , W y , W z Represents the preset weight, W k represents the kth preset weight, and n represents the number of blades.

5. The method for optimizing the revolution and rotation of the axial flow turbine runner blades according to claim 1, characterized in that: The motion rules of the operating frame include: Uniform motion at different speeds; Use different accelerations to perform acceleration followed by deceleration, with the accelerations being the same in the acceleration and deceleration stages; Use different accelerations to perform acceleration followed by deceleration, with different accelerations in the acceleration phase and deceleration phase.

6. An axial flow turbine runner blade revolution and rotation optimization system, characterized in that: include: Fluid domain model module: establish a fluid domain model of an axial flow turbine according to the drawings of the axial flow turbine; discretize the fluid domain model to obtain a fluid domain grid, and perform a grid independence test; Signal simulation module: formulate the motion law of the operating frame, and obtain the blade rotation law according to the motion law of the operating frame; compile user-defined functions (UDF) according to different blade rotation laws, and set monitoring points during CFD numerical simulation, including the pressure pulsation P in the bladeless area. n Measuring point, tailwater pipe pressure pulsation P d Measuring point, rotor and blade; using CFD numerical simulation method according to user-defined function UDF to simulate the unsteady signal of the monitoring point, the unsteady signal includes rotor force and torque, blade force and torque and pressure pulsation signal; Signal processing module: performing dimensionless processing on the unsteady signal and calculating the peak-to-peak value of the unsteady signal; performing modal decomposition on the unsteady signal using the empirical mode decomposition (EMD) method to obtain a modal signal of the unsteady signal; Optimization module: preset weights for modal signals of different blade rotation laws to calculate weights, and use genetic algorithm for several weights with the minimum weight as the optimization target to obtain the optimal blade revolution and rotation composite motion mode.

7. The axial flow turbine runner blade revolution and rotation optimization system according to claim 6, characterized in that: The grid discretization method is: S1: using a finite volume method meshing code to divide the fluid domain model into discrete grid units based on tetrahedral unstructured grids, wherein the grid units include the leading and trailing edges of the guide vane blades and the blades of the fluid domain model, the water inlet chamber, the guide vane flow channel, the runner flow channel, the draft tube, the blade top of the runner chamber, and the gap of the outer wall of the runner chamber; S2: Set the number of first grid cells N to less than 3 million and the minimum value of grid quality to greater than 0.25 to generate the first fluid domain grid; S3: Set the second grid unit number N f , the second grid unit number N f The second fluid domain grid is generated when the number of first grid cells N satisfies the first grid encryption ratio r1 and the minimum grid quality value is greater than 0.25; S4: Set the third grid unit number N c , the third grid unit number N c The third fluid domain grid is generated when the number of first grid cells N satisfies the second grid density ratio r2 and the minimum grid quality value is greater than 0.25; S5: Perform numerical simulation on the obtained first fluid domain grid, second fluid domain grid and third fluid domain grid: Preset boundary conditions, the inlet is set to the average static pressure type inlet, the pressure is set to 0Pa, the outlet is set to the mass flow type outlet, and the flow value is the design flow; Set the root mean square error RMS < 1*10 -5 As the termination condition of the numerical simulation, the total pressure at the outlet is taken as the target variable, and the Richardson extrapolation method is used to verify the grid independence: S6, calculating a first grid convergence index of the first fluid domain grid and the second fluid domain grid; S7, calculating a second grid convergence index of the first fluid domain grid and the third fluid domain grid; S8. If the first grid convergence index and the second grid convergence index are less than 0.05, the step ends; otherwise, execute step S1.

8. The axial flow turbine runner blade revolution and rotation optimization system according to claim 7, characterized in that: The steps of the EMD method are: D1. Find the minimum and maximum points of the non-steady signal, and perform cubic spline interpolation to obtain the upper envelope h u (t) and the lower envelope h d (t); D2, according to the upper envelope h u (t) and the lower envelope h d (t) Calculate the mean signal p(t) of the unsteady signal: D3. Subtract the mean signal p(t) from the unsteady signal to obtain the modal signal f(t); D4. Verify the modal signal: The absolute value of the difference between the number of extreme points and the number of zero crossing points of the modal signal does not exceed 1, and at any time t0, the upper envelope h u (t0) and the lower envelope h d The mean value of (t0) is 0. If it is satisfied, execute step D5, otherwise execute step D1; D5. Calculate the residual signal: in, represents the unsteady signal, g(t) represents the residual signal; D6. If the number of extreme value points of the residual signal is greater than or equal to 3, the residual signal is regarded as an unsteady signal and step D1 is executed; otherwise, step D7 is executed; D7. Calculate the maximum values ​​of several modal signals and find the maximum value among several maximum values ​​as the modal maximum value 9. The axial flow turbine runner blade revolution and rotation optimization system according to claim 8, characterized in that: The weight is calculated as: Among them, HZ represents the weight, W j represents the jth preset weight, ∑H represents the total weight; in, It represents the peak-to-peak value of the force on the runner. It represents the peak-to-peak value of the force on the wheel in the x-axis direction. It represents the peak-to-peak value of the force on the wheel in the y-axis direction. It represents the peak-to-peak value of the force on the wheel in the z-axis direction. It represents the peak-to-peak torque of the wheel relative to the shaft. represents the peak-to-peak value of the total force on the blade, It represents the peak-to-peak value of the total force on the blade in the x-axis direction. represents the peak-to-peak value of the force on the kth blade in the x-axis direction, It represents the peak-to-peak value of the total force on the blade in the y-axis direction. represents the peak-to-peak value of the force on the kth blade in the y-axis direction, It represents the peak-to-peak value of the total force on the blade in the z-axis direction. represents the peak-to-peak value of the force on the kth blade in the z-axis direction, It represents the total peak-to-peak torque of the blade on the rotating shaft, represents the peak-to-peak torque of the kth blade on the rotating shaft, Indicates the pressure pulsation in the bladeless area P h Peak-to-peak value of the pressure pulsation signal at the measuring point, Indicates the tailwater pressure pulsation P d Peak-to-peak value of the pressure pulsation signal at the measuring point, represents the maximum modal value of the wheel force, represents the modal maximum value of the torque of the wheel relative to the shaft, represents the modal maximum value of the total force on the blade, represents the modal maximum value of the total torque of the blade on the rotating shaft, Indicates the pressure pulsation in the bladeless area P n The modal maximum value of the pressure pulsation signal at the measuring point, Indicates the tailwater pressure pulsation P d The modal maximum values ​​of the pressure pulsation signal at the measuring point, W1, W2, W3, W4, W5, W6, W7, W8, W9, W 10 , W 11 , W 12 , W x , W y , W z Represents the preset weight, W k represents the kth preset weight, and n represents the number of blades.

10. The axial flow turbine runner blade revolution and rotation optimization system according to claim 6, characterized in that: The motion rules of the operating frame include: Uniform motion at different speeds; Use different accelerations to perform acceleration followed by deceleration, with the accelerations being the same in the acceleration and deceleration stages; Use different accelerations to perform acceleration followed by deceleration, with different accelerations in the acceleration phase and deceleration phase.

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