Flutter suppression sequence optimization method and device for aperiodically arranged blades

Abstract

The invention discloses a flutter suppression sequence optimization method and device for non-periodically arranged blades, and relates to the technical field of blade flutter of turbomachinery. Determining the vibration frequency of each blade in the non-periodically arranged blades; obtaining an ant colony optimization algorithm oriented to aperiodically arranged blade flutter suppression sequence planning; wherein the updating mode of the pheromone concentration of the ant colony optimization algorithm in the ant colony algorithm iteration process is determined according to the aerodynamic damping corresponding to the blade with the minimum aerodynamic damping in each optimization sequence in the last iteration; the aerodynamic damping value of each blade is determined according to aerodynamic force influence on the blade caused by vibration of a plurality of adjacent blades in the optimization sequence where the blade is located; the heuristic information of the ant colony optimization algorithm is determined according to the deviation of the vibration frequencies of the blades and the dispersion of the vibration frequencies of all the blades; and optimizing the non-periodic arrangement sequence of the blades by using an ant colony optimization algorithm. According to the method, the flutter suppression effectiveness of the non-periodically arranged blades is improved.

Description

Technical Field

[0001] This application relates to the field of turbine blade flutter technology, and in particular to a method and apparatus for optimizing flutter suppression sequences for non-periodic blade arrangement. Background Technology

[0002] During the manufacturing and operation of axial-flow turbine blades, factors such as machining errors and wear result in a non-periodic structural distribution across the entire blade ring, leading to differences in vibration frequency and mode among individual blades. This non-periodicity can cause vibration localization, resulting in increased amplitude in specific blades and inducing flutter. Flutter, as a destructive self-excited vibration, severely restricts engine performance and threatens operational safety. Therefore, effective suppression of flutter is crucial for improving the aeroelastic stability of turbine machinery.

[0003] Currently, in order to improve the aeroelastic stability of non-periodic blades, blade sequence optimization technology is usually adopted, which mainly focuses on reducing vibration stress to alleviate stress concentration. However, the sequence optimization method used in the existing technology is not effective in suppressing blade flutter. Summary of the Invention

[0004] Therefore, it is necessary to provide a method and apparatus for optimizing the flutter suppression sequence of non-periodic blades to address the above-mentioned technical problems.

[0005] The following technical solution is adopted in this specification: This specification provides a method for optimizing the flutter suppression sequence of non-periodic blade arrangement, including: Structural dynamics characteristics of the blades were analyzed to determine the vibration frequency of each blade in the non-periodic arrangement. An ant colony optimization algorithm based on sequence planning for flutter suppression of non-periodic leaf arrangement is used to determine the number of ants, pheromone concentration, and maximum number of iterations; heuristic information is calculated based on the deviation and dispersion of vibration frequencies of all leaves. Treat each leaf to be arranged as a node, randomly assign ants to any node, and create a taboo list for each ant to record the nodes visited. Each ant is controlled to select the next unvisited node according to the state transition probability matrix, until all ants have visited all nodes; the state transition probability matrix is ​​calculated based on pheromone concentration and heuristic information; For any given ant, the aerodynamic damping of each blade in the node sequence is calculated based on the node sequence visited by the ant and the vibration frequency of each blade. The aerodynamic damping value of each blade is determined based on the aerodynamic influence caused by the vibration of multiple neighboring blades in the node sequence to which the blade is located. Based on the minimum aerodynamic damping of the blades in all node sequences, update the pheromone concentration and control each ant to re-search all blades using the updated pheromone concentration until the termination condition is met. The termination condition includes the minimum aerodynamic damping of the blades in all node sequences in the current iteration being greater than the minimum aerodynamic damping of the blades in previous consecutive iterations, or reaching the maximum number of iterations. When the termination condition is met, the node sequence corresponding to the maximum value of all minimum aerodynamic damping values ​​in each node sequence is taken as the optimal blade sequence.

[0006] Optionally, the information density can be updated as follows: ; ; ; in, For the first In the next iteration, the blade With the blade The pheromone concentration between them; It is the pheromone decay factor; For the first In the next iteration, the blade With the blade The pheromone concentration between them; For the first During the next iteration, the blades... With the blade The pheromone increment between them; The number of ants in the ant colony optimization algorithm; For the first An ant In the next iteration, the leaf remains With the blade The amount of pheromones between them; The pheromone baseline value after path reconstruction is completed; For the first After the nth iteration Find the minimum aerodynamic damping of the entire blade circle in a topological search by an ant.

[0007] Optionally, the heuristic information is: ; ; ; in, For the first Sub-iteration blades With the blade Heuristic information between them; For the leaves The vibration frequency deviation; For the leaves The vibration frequency deviation; The vibration frequency dispersion of all blades; For the leaves The vibration frequency; This is the reference vibration frequency of the blade; For the leaves The vibration frequency.

[0008] Optionally, based on the node sequence visited by the ants and the vibration frequency of each blade, the aerodynamic damping of each blade in the node sequence is calculated, including: For any blade in the node sequence, the influence coefficient of vibration on the blade is determined based on the aerodynamic effects caused by the vibration frequencies of multiple neighboring blades and the blade itself. Calculate the modal force of the blade based on the vibration influence coefficient. The aerodynamic power of the blade is determined based on the relationship between the aerodynamic power and modal force of the blade. The aerodynamic work power of the blade during one vibration cycle is integrated to obtain the aerodynamic work of the blade during the vibration cycle. The aerodynamic work is then normalized by the vibration kinetic energy to obtain the aerodynamic damping of the blade.

[0009] Optionally, the adjacent blades of blade 3 include blades 1, 2, 4, and 5; the vibration influence coefficient of blade 3 is... for: ; in, This indicates the effect of the vibration of blade n on blade 3.

[0010] Optionally, the blade at time modal forces The calculation formula is: ; Where the symbol Re(·) represents the real part extraction operation, and i is the imaginary unit. The coefficient representing the effect of vibration on the blade. It is the angular frequency of vibration; The relationship between the aerodynamic power and modal force of the blade is as follows: ; in, For the blade at time pneumatic power, This is the displacement coefficient.

[0011] This specification provides a flutter suppression sequence optimization device for non-periodic blade arrangement, comprising: The analysis module is used to perform structural dynamics analysis on the blades and determine the vibration frequency of each blade in a non-periodic arrangement. The optimization module is used for an ant colony optimization algorithm based on a sequence planning approach for flutter suppression of non-periodic leaf arrangements. It determines the number of ants, pheromone concentration, and maximum number of iterations; calculates heuristic information based on the deviation and dispersion of vibration frequencies of all leaves; treats each leaf to be arranged as a node, randomly assigns ants to any node, and creates a tabu list for each ant to record visited nodes; controls each ant to select the next unvisited node according to the state transition probability matrix, until all ants have visited all nodes; the state transition probability matrix is ​​calculated based on pheromone concentration and heuristic information; for any ant, it calculates the node... The aerodynamic damping of each blade in the sequence is determined based on the aerodynamic influence caused by the vibration of multiple neighboring blades in the node sequence. The pheromone concentration is updated based on the minimum aerodynamic damping values ​​of all blades in the node sequence, and each ant is controlled to re-search all blades using the updated pheromone concentration until the termination condition is met. The termination condition includes the minimum aerodynamic damping of blades in the current iteration being greater than the minimum aerodynamic damping of blades in previous consecutive iterations, or reaching the maximum number of iterations. When the termination condition is met, the node sequence corresponding to the maximum value of all minimum aerodynamic damping values ​​in each node sequence is taken as the optimal blade sequence.

[0012] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for optimizing the flutter suppression sequence of non-periodic blade arrangement.

[0013] This specification provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method for optimizing the flutter suppression sequence of non-periodic blade arrangement.

[0014] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects: In the flutter suppression sequence optimization method for non-periodic blades provided in this specification, the aerodynamic response of the blades is considered in light of the influence of surrounding blades vibrating at different frequencies. Based on the principle of linear superposition, the aerodynamic damping distribution of the blades is obtained, improving the calculation accuracy of aerodynamic damping. Furthermore, this invention proposes a blade sequence optimization method for aerodynamic damping, employing an ant colony optimization algorithm to perform topological iteration on the non-periodic blade arrangement sequence to obtain the non-periodic blade sequence that maximizes aerodynamic damping. Compared with traditional methods, this invention can effectively improve the aerodynamic damping level of non-periodic blades, thereby suppressing flutter and reducing the risk of high-cycle fatigue fracture. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0016] Figure 1 This document presents a flowchart illustrating a flutter suppression sequence optimization method for non-periodic blade arrangement. Figure 2 This document provides a flowchart for optimizing aperiodic leaf arrangement sequences based on an optimized ant colony algorithm. Figure 3 This specification provides a schematic diagram for analyzing the flutter of a non-periodic arrangement of blades. Figure 4 This specification provides a schematic diagram of the influence coefficient method for non-periodic blade arrangement. Figure 5 This is a schematic diagram of a computer device used in this specification to implement a flutter suppression sequence optimization method for non-periodic blade arrangement. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this application.

[0018] In the evaluation of flutter suppression effect, aerodynamic damping is an important indicator for measuring the flutter tolerance of the system, and its value is directly related to whether the blade will flutter instability.

[0019] Currently, the flutter analysis of tuned blades in turbomachinery mainly employs the traveling wave method and the influence coefficient method. However, these methods are difficult to apply to blade structures with non-periodic arrangements. Accurately analyzing the unsteady flow field characteristics of non-periodic blades during vibration typically requires establishing a full-circle blade model and conducting long-term numerical simulations, resulting in high computational costs. Furthermore, existing optimization techniques for non-periodic blade sequences primarily focus on reducing vibration stress to alleviate stress concentration, lacking flutter suppression design methods with aerodynamic damping as the optimization objective.

[0020] Therefore, this invention addresses the problems of low numerical calculation efficiency for flutter of non-periodic blades and the lack of blade sequence optimization methods with aerodynamic damping as the optimization target in the existing technology. It is urgent to develop a flutter suppression sequence optimization method for non-periodic blades that can efficiently and accurately obtain the aerodynamic damping of the blades and use it as the optimization target to optimize the blade arrangement sequence, thereby enhancing the aerodynamic damping characteristics of the blades and reducing the risk of high-cycle fatigue failure.

[0021] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0022] Figure 1 This is a flowchart illustrating a flutter suppression sequence optimization method for non-periodic blade arrangement as described in this specification, specifically including the following steps: S101, perform structural dynamics analysis on the blades to determine the vibration frequency of each blade in the non-periodic arrangement.

[0023] Specifically, a dynamic model of the blade structure is constructed, and the structural dynamic characteristics of the blade are analyzed to obtain the mode shape and natural frequency of each blade in the non-periodic arrangement of blades, i.e., the vibration frequency.

[0024] S102, based on the ant colony optimization algorithm for planning the flutter suppression sequence of non-periodic blade arrangement, determines the number of ants, pheromone concentration and maximum number of iterations; and calculates heuristic information based on the deviation of vibration frequency of all blades and the dispersion of vibration frequency.

[0025] S103, treat each leaf to be arranged as a node, randomly assign ants to any node, and create a tabu list for each ant to record the nodes visited.

[0026] S104 controls each ant to select the next unvisited node according to the state transition probability matrix, until all ants have visited all nodes; the state transition probability matrix is ​​calculated based on pheromone concentration and heuristic information.

[0027] S105, For any ant, calculate the aerodynamic damping of each blade in the node sequence based on the node sequence visited by the ant and the vibration frequency of each blade; the aerodynamic damping value of each blade is determined based on the aerodynamic influence caused by the vibration of multiple neighboring blades in the node sequence where the blade is located.

[0028] S106, based on the minimum aerodynamic damping of the blades in all node sequences, update the pheromone concentration, and control each ant to re-search all blades using the updated pheromone concentration until the termination condition is met; the termination condition includes the minimum aerodynamic damping of the blades in all node sequences in the current iteration being greater than the minimum aerodynamic damping of the blades in previous consecutive iterations, or reaching the maximum number of iterations; when the termination condition is met, among the minimum aerodynamic damping of each node sequence, the node sequence corresponding to the maximum value of all minimum aerodynamic damping is taken as the optimal blade sequence.

[0029] This invention optimizes the blade arrangement sequence based on the aerodynamic damping of the blades throughout the circumference, aiming to improve the aeroelastic stability of the entire circumference, thereby constructing an ant colony optimization algorithm for planning the flutter suppression sequence of non-periodic blade arrangement.

[0030] Specifically, for aperiodic blade arrangement, the aeroelastic stability of the entire circumference of aperiodic blades depends on the blade with the lowest aerodynamic damping. Therefore, the aerodynamic damping value of the blade with the lowest aerodynamic damping in the entire circumference is used as the objective function variable for optimization. By using the blade sequence as a design variable, the aeroelastic stability of the blade stage can be improved. The optimization problem can be expressed as:

[0031] (1) in, It is the minimum aerodynamic damping of non-periodic blade arrangement. It is a sequence of non-periodic leaf arrangements. This method constructs a non-periodic leaf arrangement vector based on the ant colony optimization algorithm. Aerodynamic damping optimization is achieved through the following process: First, the blade number sequence in the rotation direction is defined to establish an initial arrangement topology; then, the ant colony agent is initialized, and baseline aerodynamic damping parameters are obtained through influence coefficient analysis. During the iteration phase, the pheromone concentration between blades is dynamically updated. With heuristic factors Based on the state transition probability matrix The ant colony is driven to complete a subtopology migration, generating candidate layout schemes; then, the minimum aerodynamic damping value of each scheme is extracted. An elite strategy is used to update the global pheromone. The iteration termination condition is set as follows: the minimum aerodynamic damping of the blades in the current iteration's node sequence is greater than the minimum aerodynamic damping of the blades in previous consecutive iterations, or the maximum number of iterations T is reached. The final output satisfies the convergence requirement. Layout configuration. The optimization process is as follows: Figure 2 As shown. For example, the first t The minimum aerodynamic damping of the blades in all node sequences of the next iteration. Greater than the previous consecutive Minimum aerodynamic damping of the blade in the next iteration This means that the termination condition has been met.

[0032] Optionally, if there are 3 ants, the node sequence corresponding to the termination condition includes node sequence 1, node sequence 2, and node sequence 3, where the minimum aerodynamic damping of node sequence 1 is... The minimum aerodynamic damping of node sequence 2 is The minimum aerodynamic damping of node sequence 3 is , Then the maximum value will be The corresponding node sequence 2 is taken as the optimal leaf sequence.

[0033] The information density is updated as follows: (2) (3) (4) in, For the first In the next iteration, the blade With the blade The pheromone concentration between them; The pheromone decay factor characterizes the strength of path memory. For the first In the next iteration, the blade With the blade The pheromone concentration between them; For the first During the next iteration, the blades... With the blade The pheromone increment between them; The number of ants in the ant colony optimization algorithm; For the first An ant In the next iteration, the leaf remains With the blade The pheromone content between them; C is the pheromone baseline value after path reconstruction. ; For the first After the nth iteration Find the minimum aerodynamic damping of the entire blade circle in a topological search by an ant.

[0034] The heuristic information is: (5) (6) (7) in, For the first Sub-iteration blades With the blade Heuristic information between them; For the leaves The vibration frequency deviation; For the leaves The vibration frequency deviation; The vibration frequency dispersion of all blades, , μ This is the average vibration frequency of all blades; N Number of leaves; For the leaves The vibration frequency; This is the reference vibration frequency of the blade; For the leaves The vibration frequency.

[0035] The state transition probability matrix is: (8) in, For pheromone weights; For heuristic factor weights; For the first A set of candidate nodes in an ant topology search; For the first In the next iteration, the blade With the candidate blades The pheromone concentration between them; For the first Sub-iteration blades With the candidate blades Heuristic information between them.

[0036] This invention introduces an ant colony optimization algorithm and utilizes pheromone feedback iteration to output the minimum aerodynamic damping value. Maximum optimal The blade arrangement configuration, i.e. the optimal blade sequence, is a non-periodic blade arrangement scheme that can improve the minimum damping characteristics of the entire loop.

[0037] Based on the node sequence visited by the ants and the vibration frequency of each blade, an unsteady computational fluid domain containing five flow channels is established for each blade, with the middle blade serving as the vibration source. By solving the unsteady flow field of the oscillating blade, the aerodynamic influence of the blade's vibration on surrounding blades is obtained and expressed in the form of modal forces. Then, the aerodynamic power is calculated using the modal forces, and the aerodynamic damping is determined based on the aerodynamic power. Specifically, in one embodiment, the aerodynamic damping of each blade in the node sequence is calculated based on the node sequence visited by the ants and the vibration frequency of each blade, including the following steps:

[0038] S201, for any blade in the node sequence, determine the vibration influence coefficient of the blade based on the aerodynamic influence caused by the vibration frequencies of multiple neighboring blades and the blade itself.

[0039] Existing technologies, based on the traveling wave assumption, linearly superimpose the influence of surrounding blades on the affected blade, further converting modal forces into aerodynamic work that can be used to evaluate aerodynamically damped blades. For aperiodic blades, there are differences in vibration frequency and vibration mode. Therefore, aperiodic blades do not satisfy the traveling wave assumption, and existing technologies lack a method to convert the modal forces of aperiodic blades into aerodynamic work. Therefore, an improved influence coefficient method model suitable for aperiodic blades is constructed to obtain the aerodynamic work of aperiodic blades.

[0040] like Figure 3 As shown, a group of adjacent, non-periodic blades, numbered 1, 2, 3, 4, and 5, have vibration frequencies of f1, f2, f3, f4, and f5, respectively. Under these conditions, the unsteady aerodynamic force on any blade surface can be expressed as a linear superposition of the aerodynamic influences caused by the vibrations of several neighboring blades. Based on this, an improved aerodynamic influence coefficient model is established. Therefore, to solve the aeroelastic stability of the middle blade 3, it is necessary to consider the influence of the vibrations of blades 1, 2, 3, 4, and 5, including blade 3 itself. The neighboring blades of blade 3 include blades 1, 2, 4, and 5; therefore, the vibration influence coefficient of blade 3 is... It can be represented as:

[0041] (9) in, This indicates the effect of the vibration of blade n on blade 3.

[0042] For non-periodic blade arrangement, the following should be adopted: Figure 4 The computational domain is shown. An aerodynamic computational domain is established for an unsteady oscillating blade with intermediate blade vibration frequencies of f1, f2, f3, f4, and f5. For ease of distinction, Figure 4The middle blade in the computational domain is labeled "M", and the two side blades are labeled "L2", "L1", "R1", and "R2" respectively. Figure 4 The calculation in (a) monitors the effect of the middle blade "M" within the blue box on the blade "R2", denoted as The subscript 1 indicates that the vibration frequency of the middle blade is f1. For other calculations, the blade vibration influence coefficient within the blue box is also monitored and compared. Figure 3 We can obtain:

[0043] (10) (11) (12) (13) (14) Substituting formulas (10) to (14) into formula (9), we get: (15) The influence coefficient of vibration on blade No. 3 is calculated based on the vibration frequency of each blade using formula (15). .

[0044] Thus, the influence coefficient method was used to analyze... Figure 3 The calculation of the surface unsteady aerodynamic forces on blade 3 is now complete. For the remaining blades, the same method is used to calculate the unsteady aerodynamic effects of the vibrations of the five surrounding blades (including this blade) on adjacent blades. These effects are then linearly superimposed to obtain the total influence coefficient. Using this influence coefficient, the total aerodynamic work performed on this blade is further calculated.

[0045] S202. Based on the influence coefficient of the vibration on the blade, calculate the modal force of the blade. Based on the relationship between the aerodynamic power of the blade and the modal force, determine the aerodynamic power of the blade. Integrate the aerodynamic power of the blade in one vibration cycle to obtain the aerodynamic work of the blade in the vibration cycle. Normalize the aerodynamic work by the vibration kinetic energy to obtain the aerodynamic damping of the blade.

[0046] The above steps yielded the aerodynamic effects of blade vibration on surrounding blades, which are manifested in the form of modal forces.

[0047] Specifically, when the blade vibrates, the vibration displacement of the blade surface is: (16) in, For vibration displacement, For displacement coefficient, For modal vibration modes, The angular frequency of vibration is given by rad·s. t Indicates time. And the vibration displacement coefficient... It is a numerical calculation of the maximum displacement of vibration. and the maximum displacement in the mode shape The ratio:

[0048] (17) Vibration velocity vector for: (18) The surface pressure of the blade during vibration can be expressed as: Instantaneous aerodynamic power during blade vibration for: (19) in, For surface micro-elements, Let be the normal vector of the blade surface.

[0049] For ease of calculation, a time-varying modal force is additionally defined. This variable is the surface integral of the projection of the aerodynamic force onto the mode shape, and the blade at time [time missing]. modal forces The calculation formula is as follows: (20) Here, the symbol Re(·) represents the real part operation, and i is the imaginary unit.

[0050] The modal force of the blade can be calculated based on formula (20) and the influence coefficient of the blade.

[0051] Substituting equation (18) into equation (19) and simplifying, we obtain the relationship between the aerodynamic power and modal force of the blade as follows: (twenty one) The above equation establishes the relationship between the work power of the fluid on the blade and the modal force. In unsteady fluid-structure interaction aerodynamic analysis, the aerodynamic work power can be obtained by monitoring the modal force of the blade during its motion (according to formula (21)). Then, by integrating the aerodynamic work power over one vibration cycle of the blade, the aerodynamic work of the blade during that vibration cycle can be obtained. :

[0052] (twenty two) The total aerodynamic work performed on each blade of a non-periodic blade arrangement was obtained. To convert this aerodynamic work into aerodynamic damping suitable for stability assessment, a vibration kinetic energy normalization method is required. This method normalizes the aerodynamic work with the vibration kinetic energy of the blade in the corresponding mode, thereby eliminating the influence of amplitude dimensions and obtaining the aerodynamic damping. Further normalization of the aerodynamic work using vibration kinetic energy yields the aerodynamic damping. :

[0053] (twenty three) in, Vibrational kinetic energy is defined as follows: (twenty four) in, It's the density of the leaves. Represents the angular frequency of vibration. This refers to the amplitude of the local unit. When aerodynamic damping is greater than 0, it indicates that the fluid dampes the blade vibration, preventing flutter instability. Furthermore, the greater the aerodynamic damping, the stronger the damping effect, and the higher the aeroelastic stability of the blade. Conversely, when aerodynamic damping is less than 0, flutter instability will occur. Through the above processing, the aerodynamic damping distribution of different blades in a non-periodic blade arrangement can be obtained, providing a basis for blade sequence optimization.

[0054] This invention constructs an improved influence coefficient method model suitable for aperiodic blade arrangements, considering the aerodynamic response of the blades under the influence of vibrations at different frequencies around them, and obtains the aerodynamic damping distribution of the blades based on the principle of linear superposition. This method improves the solution efficiency of aerodynamic damping while ensuring computational accuracy. Furthermore, this invention proposes a blade sequence optimization method for aerodynamic damping, employing an ant colony algorithm to perform topological iteration on the aperiodic blade arrangement sequence to obtain the aperiodic blade sequence that maximizes aerodynamic damping. Compared with traditional methods, this invention can effectively improve the aerodynamic damping level of aperiodic blades, thereby suppressing flutter and reducing the risk of high-cycle fatigue fracture. This method provides a complete technical solution for flutter suppression of aperiodic blade arrangements, from efficient numerical calculation to sequence optimization, and has significant engineering application value in the aeroelastic stability design of turbomachinery.

[0055] The execution subject of the method provided by this invention can be a server, which can be a server set up on a business platform, or a device such as a desktop computer or laptop computer that can execute the solution in this specification.

[0056] When applying the flutter suppression sequence optimization method for non-periodic blade arrangement provided in this manual, it is not necessary to consider... Figure 1 The steps shown are executed in sequence. The specific execution order of each step can be determined as needed, and this manual does not impose any restrictions on it.

[0057] The above describes one or more embodiments of the flutter suppression sequence optimization method for non-periodic blade arrangement provided in this specification. Based on the same idea, this specification also provides a corresponding flutter suppression sequence optimization device for non-periodic blade arrangement, which includes: The analysis module is used to perform structural dynamics analysis on the blades and determine the vibration frequency of each blade in a non-periodic arrangement. The optimization module is used for an ant colony optimization algorithm based on a sequence planning approach for flutter suppression of non-periodic leaf arrangements. It determines the number of ants, pheromone concentration, and maximum number of iterations; calculates heuristic information based on the deviation and dispersion of vibration frequencies of all leaves; treats each leaf to be arranged as a node, randomly assigns ants to any node, and creates a tabu list for each ant to record visited nodes; controls each ant to select the next unvisited node according to the state transition probability matrix, until all ants have visited all nodes; the state transition probability matrix is ​​calculated based on pheromone concentration and heuristic information; for any ant, it calculates the node... The aerodynamic damping of each blade in the sequence is determined based on the aerodynamic influence caused by the vibration of multiple neighboring blades in the node sequence. The pheromone concentration is updated based on the minimum aerodynamic damping values ​​of all blades in the node sequence, and each ant is controlled to re-search all blades using the updated pheromone concentration until the termination condition is met. The termination condition includes the minimum aerodynamic damping of blades in the current iteration being greater than the minimum aerodynamic damping of blades in previous consecutive iterations, or reaching the maximum number of iterations. When the termination condition is met, the node sequence corresponding to the maximum value of all minimum aerodynamic damping values ​​in each node sequence is taken as the optimal blade sequence.

[0058] Specific limitations regarding the flutter suppression sequence optimization device for aperiodic blade arrangement can be found in the limitations of the flutter suppression sequence optimization method for aperiodic blade arrangement described above, and will not be repeated here. Each module in the aforementioned flutter suppression sequence optimization device for aperiodic blade arrangement can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0059] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 The provided method optimizes the flutter suppression sequence for non-periodic blade arrangement.

[0060] This instruction manual also provides Figure 5 The schematic diagram of the computer device shown is as follows: Figure 5 At the hardware level, the computer device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above-mentioned functions. Figure 1 The provided method optimizes the flutter suppression sequence for non-periodic blade arrangement.

[0061] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0062] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A method for optimizing the flutter suppression sequence of non-periodic blades, characterized in that, include: Structural dynamics characteristics of the blades were analyzed to determine the vibration frequency of each blade in the non-periodic arrangement. An ant colony optimization algorithm based on sequence planning for flutter suppression of non-periodic leaf arrangement is used to determine the number of ants, pheromone concentration, and maximum number of iterations. Heuristic information is calculated based on the deviation of all blade vibration frequencies and the dispersion of vibration frequencies; Treat each leaf to be arranged as a node, randomly assign ants to any node, and create a taboo list for each ant to record the nodes visited. Each ant is controlled to select the next unvisited node according to the state transition probability matrix, until all ants have visited all nodes; the state transition probability matrix is ​​calculated based on pheromone concentration and heuristic information; For any given ant, the aerodynamic damping of each blade in the node sequence is calculated based on the node sequence visited by the ant and the vibration frequency of each blade. The aerodynamic damping value of each blade is determined based on the aerodynamic influence caused by the vibration of multiple neighboring blades in the node sequence to which the blade is located. Based on the minimum aerodynamic damping of the blades in all node sequences, update the pheromone concentration and control each ant to re-search all blades with the updated pheromone concentration until the termination condition is met. The termination conditions include the minimum aerodynamic damping of the blades in the current iteration's sequence of all nodes being greater than the minimum aerodynamic damping of the blades in previous consecutive iterations, or reaching the maximum number of iterations. When the termination condition is met, the node sequence corresponding to the maximum value of all minimum aerodynamic damping values ​​in each node sequence is taken as the optimal blade sequence.

2. The method according to claim 1, characterized in that, The information density is updated as follows: ； ； ； in, For the first In the next iteration, the blade With the blade The pheromone concentration between them; It is the pheromone decay factor; For the first In the next iteration, the blade With the blade The pheromone concentration between them; For the first During the next iteration, the blades... With the blade The pheromone increment between them; The number of ants in the ant colony optimization algorithm; For the first An ant In the next iteration, the leaf remains With the blade The amount of pheromones between them; The pheromone baseline value after path reconstruction is completed; For the first After the nth iteration Find the minimum aerodynamic damping of the entire blade circle in a topological search by an ant.

3. The method according to claim 2, characterized in that, The heuristic information is: ； ； ； in, For the first Sub-iteration blades With the blade Heuristic information between them; For the leaves The vibration frequency deviation; For the leaves The vibration frequency deviation; The vibration frequency dispersion of all blades; For the leaves The vibration frequency; This is the reference vibration frequency of the blade; For the leaves The vibration frequency.

4. The method according to claim 1, characterized in that, Based on the node sequence visited by the ants and the vibration frequency of each blade, calculate the aerodynamic damping of each blade in the node sequence, including: For any blade in the node sequence, the influence coefficient of vibration on the blade is determined based on the aerodynamic effects caused by the vibration frequencies of multiple neighboring blades and the blade itself. Calculate the modal force of the blade based on the vibration influence coefficient. The aerodynamic power of the blade is determined based on the relationship between the aerodynamic power and modal force of the blade. The aerodynamic work power of the blade during one vibration cycle is integrated to obtain the aerodynamic work of the blade during the vibration cycle. The aerodynamic work is then normalized by the vibration kinetic energy to obtain the aerodynamic damping of the blade.

5. The method according to claim 4, characterized in that, The adjacent blades of blade #3 include blades #1, #2, #4, and #5; the vibration influence coefficient of blade #3. for: ； in, This indicates the effect of the vibration of blade n on blade 3.

6. The method according to claim 4, characterized in that, The leaves at all times modal forces The calculation formula is: ； Where the symbol Re(·) represents the real part extraction operation, and i is the imaginary unit. The coefficient representing the effect of vibration on the blade. It is the angular frequency of vibration; The relationship between the aerodynamic power and modal force of the blade is as follows: ； in, For the blade at time pneumatic power, This is the displacement coefficient.

7. A flutter suppression sequence optimization device for non-periodic blade arrangement, characterized in that, The device includes: The analysis module is used to perform structural dynamics analysis on the blades and determine the vibration frequency of each blade in a non-periodic arrangement. The optimization module is used for an ant colony optimization algorithm based on a sequence planning approach for flutter suppression of non-periodic leaf arrangements. It determines the number of ants, pheromone concentration, and maximum number of iterations; calculates heuristic information based on the deviation and dispersion of vibration frequencies of all leaves; treats each leaf to be arranged as a node, randomly assigns ants to any node, and creates a tabu list for each ant to record visited nodes; controls each ant to select the next unvisited node according to the state transition probability matrix, until all ants have visited all nodes; the state transition probability matrix is ​​calculated based on pheromone concentration and heuristic information; for any ant, it calculates the node... The aerodynamic damping of each blade in the sequence is determined based on the aerodynamic influence caused by the vibration of multiple neighboring blades in the node sequence. The pheromone concentration is updated based on the minimum aerodynamic damping values ​​of all blades in the node sequence, and each ant is controlled to re-search all blades using the updated pheromone concentration until the termination condition is met. The termination condition includes the minimum aerodynamic damping of blades in the current iteration being greater than the minimum aerodynamic damping of blades in previous consecutive iterations, or reaching the maximum number of iterations. When the termination condition is met, the node sequence corresponding to the maximum value of all minimum aerodynamic damping values ​​in each node sequence is taken as the optimal blade sequence.

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