A method, device and equipment for designing a combination of a disk and turbine blade of an engine

Abstract

This invention provides a method, apparatus, and device for designing an engine's turbine blade and impeller assembly. The method includes: acquiring a plurality of turbine blade and impeller assembly parameters; calculating the probability density function value for each assembly parameter under the condition that the blades detach at a given speed and the impeller does not break at a given speed; determining the speed margin corresponding to each assembly parameter based on the probability density function value; calculating the optimal speed for each assembly parameter under its corresponding speed margin; selecting candidate assembly parameters that meet the engine design requirements from the available assembly parameters; calculating the turbine rotor mass for each candidate assembly parameter at its corresponding optimal speed; and selecting the target assembly parameter from the candidate assembly parameters based on the ranking of turbine rotor masses. The engine turbine blade and impeller assembly design method, apparatus, and device provided by this invention can effectively select target assembly parameters, facilitating lightweight turbine rotor design.

Description

Technical Field

[0001] This invention relates to the field of engine design, and more specifically to a method, apparatus, and equipment for designing an engine's disk and turbine blade combination. Background Technology

[0002] In the design of turbines for aero-engines or other gas turbine engines, a shedding section needs to be designed on the turbine blades. Once the engine loses load and the turbine overclocks to a certain speed, the turbine blades will detach prematurely at this section, causing the rotor to lose the power to continue rising and avoiding non-containment damage caused by disk fracture. Therefore, in the design of the shedding section, it is crucial to select appropriate turbine blade shedding speed, disk fracture speed, and the design margin between the disk fracture speed and the turbine blade shedding speed.

[0003] In existing technologies, the maximum turbine blade shedding speed is typically calculated considering the best turbine blade material, and the minimum disk fracture speed is calculated under the most favorable geometry and load conditions. Furthermore, considering multiple extreme cases, a design margin of no less than 10% is maintained between the maximum turbine blade shedding speed and the minimum disk fracture speed. However, this method results in turbine rotors with a relatively large mass and high margin, which is not conducive to lightweight design. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the defects of the large mass of the turbine rotor in the prior art, which is not conducive to lightweight design, and thus provide a design method, device and equipment for the combination of engine disk and turbine blade.

[0005] According to a first aspect, the present invention provides a method for designing a combination of a turbine disk and turbine blades for an engine, the method comprising:

[0006] Obtain combined parameters of several disks and turbine blades, including: the geometric dimensions, loads, and material properties of the disks and turbine blades;

[0007] Calculate the probability density function value for each combination of parameters under the condition that the blade falls off at the speed and the disk does not break.

[0008] The speed margin corresponding to each combination parameter is determined based on the probability density function value corresponding to each combination parameter.

[0009] Calculate the optimal speed for each combination of parameters under its corresponding speed margin;

[0010] Select alternative parameter combinations that meet the engine design requirements from among the various parameter combinations;

[0011] The turbine rotor mass of each candidate combination parameter at its corresponding optimal speed is calculated, and the target combination parameter is selected from the candidate combination parameters based on the ranking result of the turbine rotor mass.

[0012] In one embodiment, calculating the probability density function value for each combination parameter under the condition of blade shedding speed and disk non-fracture speed includes:

[0013] The probability density function value for the current combination parameters, under the condition of blade detachment speed and disk non-fracture speed, is calculated using the following formula:

[0014]

[0015] Where P is the probability density function value of blade detachment without disk breakage, X is the current combination parameters, μ, σ, and σ 2 These are the mean, standard deviation, and variance, respectively.

[0016] In one embodiment, before obtaining the combined parameters of the plurality of disks and turbine blades, the method further includes:

[0017] The maximum rotational speed of the turbine rotor after it loses its load and the minimum rotational speed at which the blades fall off are obtained, and the lower limit of the blade fall-off speed is determined based on the sorting result of the maximum rotational speed and the minimum rotational speed.

[0018] Obtain the structural parameters of the wheel, and determine the upper limit of the wheel's fracture speed based on the structural parameters;

[0019] The turbine disk and blades are designed with the condition that both the blade shedding speed and the disk breakage speed are between the lower limit and the upper limit, resulting in several combination parameters of the turbine disk and blades.

[0020] In one embodiment, determining the speed margin corresponding to each combination parameter based on the probability density function value corresponding to each combination parameter includes:

[0021] The response surface equation is fitted based on the probability density function values ​​corresponding to each combination parameter, and the limit state functions corresponding to the disk breakage speed and blade shedding speed are determined based on the response surface equation.

[0022] Based on the limit state functions corresponding to the disk fracture speed and the blade shedding speed, the minimum limit state function value of the disk fracture speed and the maximum limit state function value of the blade shedding speed are determined.

[0023] The difference between the minimum limit state function value and the maximum limit state function value is determined as the speed margin.

[0024] In one embodiment, calculating the optimal speed for each combination of parameters under its corresponding speed margin includes:

[0025] The optimal speed for each combination of parameters under its corresponding speed margin is calculated iteratively using a sequential quadratic programming optimization algorithm.

[0026] In one embodiment, the step of selecting alternative combination parameters that meet the engine design requirements from the various combination parameters includes:

[0027] Calculate the static strength parameters, vibration parameters, and life parameters of the disk and turbine blades at the design point speeds for each combination of parameters.

[0028] If the static strength parameters, vibration parameters, and life parameters at the design point speed all meet the engine design requirements, then this combination of parameters is determined as the alternative combination of parameters.

[0029] In one embodiment, the method further includes:

[0030] Based on the optimal rotational speed corresponding to the target combination parameters, calculate the static strength parameters, vibration parameters, and life parameters of the disk and turbine blades at the design point rotational speeds.

[0031] Determine whether the static strength parameters, vibration parameters, and life parameters meet the engine design requirements;

[0032] If the static strength parameters, vibration parameters, and life parameters do not meet the engine design requirements, the upper limit value and / or the upper limit value shall be corrected, and the process shall return to the step of obtaining the combined parameters of several disks and turbine blades.

[0033] According to a second aspect, the present invention provides a design apparatus for a combination of a turbine disk and turbine blades for an engine, the apparatus comprising:

[0034] The acquisition module is used to acquire combined parameters of several disks and turbine blades, including: the geometric dimensions, loads, and material properties of the disks and turbine blades;

[0035] The first calculation module is used to calculate the probability density function value of each combination parameter under the condition that the blade falls off at the speed and the disk does not break at the speed.

[0036] The determination module is used to determine the speed margin corresponding to each combination parameter based on the probability density function value corresponding to each combination parameter;

[0037] The second calculation module is used to calculate the optimal speed of each combination of parameters under its corresponding speed margin.

[0038] The first screening module is used to select alternative combination parameters that meet the engine design requirements from various combination parameters;

[0039] The second filtering module is used to calculate the turbine rotor mass of each candidate combination parameter at its corresponding optimal speed, and to filter the target combination parameter from each candidate combination parameter based on the ranking result of the turbine rotor mass.

[0040] According to a third aspect, the present invention provides a computer device including a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the design method for the combination of a disk and turbine blades of an engine according to any one of the first aspects and its alternative embodiments.

[0041] According to a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to perform the design method for the combination of a disk and turbine blades of an engine according to any one of the first aspects and its alternative embodiments.

[0042] The technical solution of this invention has the following advantages:

[0043] This invention provides a design method for the combination of turbine blades and impeller blades in an engine. By calculating the probability density function value corresponding to each combination parameter of turbine blades and impeller blades, and ensuring that the probability density function value satisfies the speed condition of blade detachment without impeller breakage, the safety and reliability of the engine are increased. By calculating the speed margin corresponding to each combination parameter and determining the optimal speed, and by screening the combination parameters that meet the conditions, the lightest combination parameter at the optimal speed is finally determined as the target combination parameter. This method can effectively reduce the mass of the turbine rotor while meeting design requirements, thereby facilitating the lightweight design of the turbine rotor. Attached Figure Description

[0044] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram illustrating the design principle of the anti-disc rupture blade proposed in an embodiment of the present invention;

[0046] Figure 2 This is a flowchart of a design method for the combination of engine disk and turbine blades proposed in an embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of the speed margin based on the traditional model proposed in an embodiment of the present invention;

[0048] Figure 4 This is a schematic diagram of the speed margin based on a probability model proposed in an embodiment of the present invention;

[0049] Figure 5 This is a structural block diagram of an engine disk and turbine blade combination design device proposed in an embodiment of the present invention;

[0050] Figure 6 This is a schematic diagram of the hardware structure of a computer device proposed in an embodiment of the present invention. Detailed Implementation

[0051] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] In the design process of turbines for aero engines or other gas turbine engines, such as Figure 1 As shown, the key factors in the design of the shedding section are the turbine blade shedding speed, the impeller disk fracture speed, and the design margin between the impeller disk fracture speed and the turbine blade shedding speed. If the turbine blade shedding speed is designed too low, the stress in the shedding section will be high, which may lead to a shorter blade life under normal operating conditions; if the turbine blade shedding speed is designed too high, the impeller disk fracture speed will be high, resulting in an excessively large engine rotor mass.

[0053] In existing anti-disk fracture blade design technologies, the maximum blade shedding speed V is calculated. blade When considering the optimal blade material, the most favorable geometry, and the most favorable load conditions, the calculation of the minimum rotor disc fracture speed V... dsic At that time, the worst disk material, the most unfavorable geometry, and the most severe load conditions were considered. The maximum blade shedding speed V was obtained by comprehensively considering multiple extreme conditions. blade and minimum disc fracture speed V dsic A 10% design margin is still left between the two. The turbine rotor designed by this method has a large mass and a high reserve, which is not conducive to lightweight design.

[0054] To facilitate lightweight design of the turbine rotor, this embodiment of the invention provides a design for the combination of engine disc and turbine blades, such as... Figure 2 As shown, the method includes the following steps S101 to S106.

[0055] Step S101: Obtain the combined parameters of several disks and turbine blades.

[0056] Among them, the combined parameters include: the geometric dimensions, loads, and material properties of the disk and turbine blades.

[0057] In the embodiment of the present invention, the disk is a key component in an aeroengine. The disk rotates at an extremely high speed, and its reliability directly relates to the safety of the aeroengine. The turbine blade is an important component in the turbine section of the aeroengine. The high-speed rotating blade is responsible for sucking the high-temperature and high-pressure air flow into the combustor to maintain the operation of the engine.

[0058] Several combined parameters of the disk and turbine blades can be obtained. The combined parameters of the disk and turbine blades stored in advance can be obtained, or the combined parameters of the disk and turbine blades can be determined through sensitivity analysis.

[0059] Among them, sensitivity analysis refers to an uncertain analysis technique that studies the degree of influence of a certain change in relevant factors on one or a group of key indicators from the perspective of quantitative analysis. Its essence is to explain the law of the influence of these factors on the key indicators by changing the values of relevant variables one by one. In the embodiment of the present application, the relevant factors include geometric dimensions, loads, and material properties.

[0060] Step S102: Calculate the probability density function values corresponding to the blade shedding speed and the condition that the disk does not rupture for each combined parameter.

[0061] In the embodiment of the present invention, the probability density function value is the likelihood function value of the value of a random variable within a certain region. Let X be a random variable. If there exists a non-negative real function f(x) such that for any real numbers a < b, there is Then X is called a continuous random variable; f(x) is the probability density function of X, that is The method of calculating the probability density function value is a prior art and will not be elaborated here.

[0062] Step S103: Determine the speed margins corresponding to each combined parameter based on the probability density function values corresponding to each combined parameter.

[0063] In the embodiment of the present invention, based on the probability density function values corresponding to each combined parameter, calculate the limit state function g of the disk rupture speed and calculate the limit state function q of the blade shedding speed. Take the minimum limit state function min g of the disk rupture speed and the maximum limit state function max g of the blade shedding speed, and determine the difference between min g and max g as the corresponding speed margin.

[0064] Among them, the probability density function value P satisfies the following conditions:

[0065] P[g(x i ; y j ; zk )-(x l ;y m ;z n )<0]≤Φ(β),

[0066] Where x, y, and z are the basic random variables of geometric dimensions, load, and material properties, and i, j, k, l, m, and n are the quantities of each basic random variable. The wheel disk failure speed ratio is defined as wheel disk failure speed / design point speed, and the blade detachment speed ratio is defined as blade detachment speed / design point speed. β is the reliability of wheel disk failure, and Φ(·) is the standard normal cumulative probability distribution function. Here, the failure probability of blade detachment without wheel disk failure is less than 10⁻⁸ times / engine flight hour.

[0067] Step S104: Calculate the optimal speed for each combination of parameters under its corresponding speed margin.

[0068] In this embodiment of the invention, the optimal speed under the speed margin can be calculated by an iterative algorithm that reduces the objective function within the feasible region, or by constructing an augmented objective function using the objective function and constraints. The specific calculation process is existing technology and will not be described in detail here.

[0069] Step S105: Select alternative combination parameters that meet the engine design requirements from the various combination parameters.

[0070] In this embodiment of the invention, combined parameters that meet the engine design requirements are listed as candidates, and combined parameters that do not meet the engine design requirements are deleted, so as to reduce the amount of data and thus speed up the processing speed of combined parameters.

[0071] Step S106: Calculate the turbine rotor mass of each candidate combination parameter at its corresponding optimal speed, and select the target combination parameter from each candidate combination parameter based on the ranking result of the turbine rotor mass.

[0072] In this embodiment of the invention, the combination parameters corresponding to the minimum mass in the turbine rotor are determined as the target combination parameters in order to reduce the mass of the entire turbine rotor, so as to facilitate the lightweight design of the turbine rotor.

[0073] Through the above embodiments, the probability density function value corresponding to each set of disk and turbine blade combination parameters is calculated, and the speed condition that the probability density function value satisfies blade detachment without disk breakage is determined to increase the safety and reliability of the engine. By calculating the speed margin corresponding to each combination parameter, the optimal speed is determined, and the combination parameters that meet the conditions are screened. Finally, the lightest mass at the optimal speed is determined as the target combination parameter. Under the premise of meeting the design requirements, the mass of the turbine rotor can be effectively reduced, thus facilitating the lightweight design of the turbine rotor.

[0074] Specifically, in one embodiment, before performing the above step S101, the engine disk and turbine blade combination design method provided in this embodiment further includes the following steps:

[0075] Step S201: Obtain the maximum speed of the turbine rotor after it loses its load and the minimum speed at which the blades fall off, and determine the lower limit of the blade fall-off speed based on the sorting results of the maximum and minimum speeds.

[0076] Step S202: Obtain the structural parameters of the wheel and determine the upper limit of the wheel's breaking speed based on the structural parameters.

[0077] Step S203: Design the disk and blades with the condition that the blade shedding speed and the disk breakage speed are both between the lower and upper limits, and obtain several combination parameters of disk and turbine blades.

[0078] In this embodiment of the invention, the maximum overspeed V1 of the turbine rotor after the engine electronic overspeed protection is triggered and the load is lost is first calculated. The minimum blade shedding speed V2 that can be designed under various constraints such as strength, fatigue life, vibration characteristics, deformation and creep at the blade design point speed is comprehensively evaluated. The larger of V1 and V2 is taken as the lower limit value V of the blade shedding speed. 下 Taking into account the turbine rotor's weight, disk fracture speed requirements, life indicators, and other structural parameters, the upper limit value V of the disk fracture speed is determined. 上 .

[0079] Based on the determined basic random variables, the blade shedding speed distribution and the disk fracture speed distribution are designed separately to ensure that the blade shedding speed distribution and the disk fracture speed distribution satisfy the condition [V]. 下 V 上 ]between.

[0080] Among them, the lower limit value V of the blade shedding speed 下 And the upper limit of the rotational speed V of the wheel breaking. 上 Adjustments can be made based on specific circumstances such as the engine model and its application scenario; no restrictions are imposed here.

[0081] Specifically, in one embodiment, the calculation of the probability density function value for each combination parameter under the condition of blade shedding speed and disk non-fracture speed includes the following steps:

[0082] The probability density function value for the current combination parameters, under the condition of blade detachment speed and disk non-fracture speed, is calculated using the following formula:

[0083]

[0084] Where P is the probability density function value of blade detachment without disk breakage, X is the current combination parameters, μ, σ, and σ 2 These are the mean, standard deviation, and variance, respectively. The methods for calculating the mean, standard deviation, and variance are existing techniques and will not be elaborated here. The probability density function value for each set of combined parameters is calculated using the above formulas, until the probability density function values ​​for all combined parameters are calculated.

[0085] Specifically, in one embodiment, the step S103 above, which determines the speed margin corresponding to each combination parameter based on the probability density function value corresponding to each combination parameter, specifically includes the following steps:

[0086] Step S1031: Fit the response surface equation based on the probability density function values ​​corresponding to each combination parameter, and determine the limit state functions corresponding to the disk rupture speed and blade shedding speed based on the response surface equation.

[0087] Step S1032: Based on the limit state functions corresponding to the disk fracture speed and the blade shedding speed, determine the minimum limit state function value of the disk fracture speed and the maximum limit state function value of the blade shedding speed.

[0088] Step S1033: Determine the speed margin as the difference between the minimum limit state function value and the maximum limit state function value.

[0089] In this embodiment of the invention, a three-level orthogonal experimental design method is used to select test points, and the disk and blade are modeled and numerically analyzed. The numerical analysis is usually the finite element analysis method, and relevant calculation results are extracted, including stress, strain, etc. The response surface equations of the limit state functions of the disk fracture speed and the blade shedding speed are fitted based on the probability density function values ​​corresponding to each combination parameter.

[0090] The finite element method (FEM) is applicable to any complex mechanical structure. FEM consists of an assembly of several elements, each interconnected at its respective nodes. It replaces the simulation method of a normally continuous entity with infinite degrees of freedom by combining several elements. FEM enables large-scale design and calculation, and can perform flexibility analysis on complex mechanical structures. The specific analysis methods of FEM are existing technologies and will not be elaborated here. The process of establishing the response surface is also existing technology and will not be elaborated here.

[0091] Based on the established response surface equations, the minimum limit state function value for the disk fracture speed and the maximum limit state function value for the blade shedding speed are determined by combining the least squares method and a quadratic polynomial fitting method without cross terms. The minimum and maximum limit state function values ​​satisfy the following conditions:

[0092] min g(x i ;y j ;z k )-max q(x l ;y m ;z n -a≥0,

[0093] Where a is the speed margin, and a is a constant, which is usually not less than 10% in engineering. In the embodiments of this application, the probability density function value is used instead of the speed margin.

[0094] Specifically, in one embodiment, the calculation of the optimal speed of each combination parameter under its corresponding speed margin in step S104 includes the following steps:

[0095] Step S1041: Iteratively calculate the optimal speed of each combination parameter under its corresponding speed margin based on the sequential quadratic programming optimization algorithm.

[0096] In this embodiment of the invention, based on the speed margin, it is determined whether the blade shedding overspeed protection design is satisfied to design the objective function, and the optimal design point is obtained by iterative calculation using a sequential quadratic programming optimization algorithm.

[0097] Sequential quadratic programming (SQP) optimization algorithms construct augmented objective functions using the objective function and constraints, thereby transforming constrained optimization problems into unconstrained optimization problems. Local optima of the new objective function are then indirectly found using methods for solving unconstrained optimization problems. Compared to other algorithms, SQP algorithms exhibit better convergence, higher computational efficiency, and stronger boundary search capabilities.

[0098] The optimization process can be performed using the `fmincon` function from the MATLAB Optimization Toolbox. The `fmincon` function is a MATLAB function used to find the minimum value of nonlinear multivariate functions; the Optimization Toolbox provides the `fmincon` function for solving constrained optimization problems. Using `fmincon` to find the optimal solution is an existing technique and will not be elaborated upon here.

[0099] Specifically, in one embodiment, step S105 above, which involves selecting candidate combination parameters from the various combination parameters that meet the engine design requirements, includes the following steps:

[0100] Step S1051: Calculate the static strength parameters, vibration parameters, and life parameters of the disk and turbine blades at the design point speeds corresponding to each combination of parameters.

[0101] Step S1052: If the static strength parameters, vibration parameters and life parameters at the design point speed all meet the engine design requirements, then the combined parameters are determined as the alternative combined parameters.

[0102] In this embodiment of the invention, each engine model has its corresponding static strength parameters, vibration parameters, and lifespan parameter requirements. The static strength parameters, vibration parameters, and lifespan parameter requirements for all engine models can be pre-stored, or a correspondence between engine models and their corresponding static strength parameters, vibration parameters, and lifespan parameter requirements can be established. Engine design requirements can be determined based on the actual conditions of the engine's operation.

[0103] Specifically, in one embodiment, the engine disk and turbine blade combination design method provided by this embodiment further includes the following steps:

[0104] Step S107: Based on the optimal rotational speed corresponding to the target combination parameters, calculate the static strength parameters, vibration parameters, and life parameters of the disk and turbine blades at the design point rotational speed.

[0105] Step S108: Determine whether the static strength parameters, vibration parameters, and life parameters meet the engine design requirements.

[0106] Step S109: If the static strength parameters, vibration parameters, and life parameters do not meet the engine design requirements, then the upper limit values ​​and / or the upper limit values ​​are corrected, and the process returns to the step of obtaining the combined parameters of several disks and turbine blades.

[0107] In this embodiment of the invention, the finally determined target combination parameters are verified to determine the optimal speed corresponding to the target combination parameters, as well as the static strength parameters, vibration parameters, and life parameters of the disk and turbine blades, and to determine whether the parameters meet the engine design requirements. If they do, the process ends. If they do not meet the requirements, it means that there is no solution that satisfies both the speed margin and the engine design requirements. In this case, the process returns to step S101 to revise the lower limit and / or upper limit values, i.e., the lower limit is reduced and the upper limit is increased, until the conditions are met.

[0108] It should be noted that, to verify the effectiveness and accuracy of this method in predicting the anti-disk fracture blades, the design of the anti-disk fracture blades under two different models is analyzed below. For example... Figure 3 and Figure 4 As shown, Figure 3 For the speed margin based on the traditional model, Figure 4 Table 1 shows the speed margin based on the probabilistic model. Comparative analysis indicates that the rotor mass designed based on the probabilistic model is reduced by 7.2%, effectively reducing rotor mass. Furthermore, experimental verification was conducted on the anti-disk fracture blades designed based on the probabilistic model. The experiments proved that all blades effectively detached, and the disk did not fracture.

[0109] Table 1

[0110] Model Wheel fracture ratio Rotor mass Fragmentation ratio weight Traditional model 1.84 4.43 - - Probabilistic Model 1.74 4.11 -5.4％ -7.2％

[0111] Based on the same inventive concept, the present invention also provides a design device for a combination of engine disk and turbine blades.

[0112] Figure 5 This is a structural block diagram of a design device for an engine's disk and turbine blade assembly, based on an exemplary embodiment. Figure 5 As shown, the device includes:

[0113] The acquisition module 101 is used to acquire combined parameters of several disks and turbine blades. These parameters include the geometric dimensions, loads, and material properties of the disks and turbine blades. For details, please refer to the relevant description of step S101 above; it will not be repeated here.

[0114] The first calculation module 102 is used to calculate the probability density function value of each combination parameter under the condition that the blade falls off at the speed and the impeller does not break at the speed. For details, please refer to the relevant description of step S102 above, which will not be repeated here.

[0115] The determination module 103 is used to determine the speed margin corresponding to each combination parameter based on the probability density function value corresponding to each combination parameter. For details, please refer to the relevant description of step S103 above, which will not be repeated here.

[0116] The second calculation module 104 is used to calculate the optimal speed for each combination of parameters under its corresponding speed margin. For details, please refer to the relevant description of step S104 above, which will not be repeated here.

[0117] The first screening module 105 is used to screen candidate combination parameters that meet the engine design requirements from various combination parameters. For details, please refer to the relevant description of step S105 above, which will not be repeated here.

[0118] The second filtering module 106 is used to calculate the turbine rotor mass of each candidate combination parameter at its corresponding optimal speed, and to filter the target combination parameter from the candidate combination parameters based on the ranking result of the turbine rotor mass. For details, please refer to the relevant description of step S106 above, which will not be repeated here.

[0119] The engine disk and turbine blade combination design device provided in this invention calculates the probability density function value corresponding to each set of disk and turbine blade combination parameters. The probability density function value satisfies the speed condition that the blades fall off without the disk breaking, thereby increasing the safety and reliability of the engine. By calculating the speed margin corresponding to each combination parameter and determining the optimal speed, the combination parameters that meet the conditions are screened, and finally the lightest mass at the optimal speed is determined as the target combination parameter. Under the premise of meeting the design requirements, the mass of the turbine rotor can be effectively reduced, thereby facilitating the lightweight design of the turbine rotor.

[0120] The specific limitations and beneficial effects of the aforementioned engine-based disk and turbine blade combination design device can be found in the above description of the limitations of the engine disk and turbine blade combination design method, and will not be repeated here. Each of the above modules 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 in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0121] Figure 6 This is a schematic diagram of the hardware structure of a computer device according to an exemplary embodiment. For example... Figure 6 As shown, the device includes one or more processors 610 and a memory 620, which includes persistent memory, volatile memory, and a hard disk. Figure 6 Taking a processor 610 as an example, the device may also include an input device 630 and an output device 640.

[0122] The processor 610, memory 620, input device 630, and output device 640 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0123] Processor 610 can be a Central Processing Unit (CPU). Processor 610 can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof. The general-purpose processor can be a microprocessor or any conventional processor.

[0124] The memory 620, as a non-transitory computer-readable storage medium, includes persistent memory, volatile memory, and a hard disk. It can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions / modules in the embodiments of this application. The processor 610 executes various functional applications and data processing of the server by running the non-transitory software programs, instructions, and modules stored in the memory 620, thereby implementing any of the above-described engine disk and turbine blade combination design methods.

[0125] The memory 620 may include a program storage area and a data storage area. The program storage area may store application programs required for operating the device and at least one function; the data storage area may store data that is needed and required. Furthermore, the memory 620 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 620 may optionally include memory remotely located relative to the processor 610, and these remote memories can be connected to the data processing device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0126] Input device 630 can receive input digital or character information, and generate key signal inputs related to user settings and function control. Output device 640 may include display devices such as a display screen.

[0127] One or more modules are stored in memory 620, and when executed by one or more processors 610, they perform actions such as... Figure 2 The design method for the combination of the engine disk and turbine blades is shown.

[0128] The above-described product can execute the method provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in this embodiment can be found in [reference 1]. Figure 2 The relevant descriptions in the illustrated embodiments.

[0129] This invention also provides a non-transitory computer storage medium storing computer-executable instructions that can execute the methods described in any of the above method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0130] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A design method for the combination of a turbine disk and turbine blades in an engine, characterized in that, include: Obtain combined parameters of several disks and turbine blades, including: the geometric dimensions, loads, and material properties of the disks and turbine blades; Calculate the probability density function value for each combination of parameters under the condition that the blade falls off at the speed and the disk does not break. The speed margin corresponding to each combination parameter is determined based on the probability density function value corresponding to each combination parameter. Calculate the optimal speed for each combination of parameters under its corresponding speed margin; Select alternative parameter combinations that meet the engine design requirements from among the various parameter combinations; The turbine rotor mass of each candidate combination parameter at its corresponding optimal speed is calculated, and the target combination parameter is selected from the candidate combination parameters based on the ranking result of the turbine rotor mass.

2. The method according to claim 1, characterized in that, The calculation of the probability density function value for each combination of parameters under the condition of blade shedding speed and disk non-breakage speed includes: The probability density function value for the current combination parameters, under the condition of blade detachment speed and disk non-fracture speed, is calculated using the following formula: Where P is the probability density function value of blade detachment without disk breakage, X is the current combination parameters, μ, σ, and σ 2 These are the mean, standard deviation, and variance, respectively.

3. The method according to claim 1, characterized in that, Before obtaining the combined parameters of several disks and turbine blades, the method further includes: The maximum rotational speed of the turbine rotor after it loses its load and the minimum rotational speed at which the blades fall off are obtained, and the lower limit of the blade fall-off speed is determined based on the sorting result of the maximum rotational speed and the minimum rotational speed. Obtain the structural parameters of the wheel, and determine the upper limit of the wheel's fracture speed based on the structural parameters; The turbine disk and blades are designed with the condition that both the blade shedding speed and the disk breakage speed are between the lower limit and the upper limit, resulting in several combination parameters of the turbine disk and blades.

4. The method according to claim 1, characterized in that, The determination of the speed margin corresponding to each combination parameter based on the probability density function value corresponding to each combination parameter includes: The response surface equation is fitted based on the probability density function values ​​corresponding to each combination parameter, and the limit state functions corresponding to the disk breakage speed and blade shedding speed are determined based on the response surface equation. Based on the limit state functions corresponding to the disk fracture speed and the blade shedding speed, the minimum limit state function value of the disk fracture speed and the maximum limit state function value of the blade shedding speed are determined. The difference between the minimum limit state function value and the maximum limit state function value is determined as the speed margin.

5. The method according to claim 1, characterized in that, The calculation of the optimal speed for each combination of parameters under its corresponding speed margin includes: The optimal speed for each combination of parameters under its corresponding speed margin is calculated iteratively using a sequential quadratic programming optimization algorithm.

6. The method according to claim 1, characterized in that, The process of selecting alternative parameter combinations that meet the engine design requirements from various parameter combinations includes: Calculate the static strength parameters, vibration parameters, and life parameters of the disk and turbine blades at the design point speeds for each combination of parameters. If the static strength parameters, vibration parameters, and life parameters at the design point speed all meet the engine design requirements, then this combination of parameters is determined as the alternative combination of parameters.

7. The method according to claim 3, characterized in that, The method further includes: Based on the optimal rotational speed corresponding to the target combination parameters, calculate the static strength parameters, vibration parameters, and life parameters of the disk and turbine blades at the design point rotational speeds. Determine whether the static strength parameters, vibration parameters, and life parameters meet the engine design requirements; If the static strength parameters, vibration parameters, and life parameters do not meet the engine design requirements, the upper limit value and / or the upper limit value shall be corrected, and the process shall return to the step of obtaining the combined parameters of several disks and turbine blades.

8. A design device for a combination of a turbine disk and turbine blades for an engine, characterized in that, The device includes: The acquisition module is used to acquire combined parameters of several disks and turbine blades, including: the geometric dimensions, loads, and material properties of the disks and turbine blades; The first calculation module is used to calculate the probability density function value of each combination parameter under the condition that the blade falls off at the speed and the disk does not break at the speed. The determination module is used to determine the speed margin corresponding to each combination parameter based on the probability density function value corresponding to each combination parameter; The second calculation module is used to calculate the optimal speed of each combination of parameters under its corresponding speed margin. The first screening module is used to select alternative combination parameters that meet the engine design requirements from various combination parameters; The second filtering module is used to calculate the turbine rotor mass of each candidate combination parameter at its corresponding optimal speed, and to filter the target combination parameter from each candidate combination parameter based on the ranking result of the turbine rotor mass.

9. A computer device, characterized in that, The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the design method for the combination of the engine disk and turbine blades as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the design method for the combination of the engine disk and turbine blades of any one of claims 1-7.

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