Method for quickly identifying individuals with same serial number in grid

Abstract

The invention discloses a method for rapidly identifying individuals with the same number in a grid, and belongs to the technical field of aero-engine optimization. The method comprises the following steps: in an aero-engine overall performance multi-objective optimization model, normalizing each target value of each individual in population design parameters; calculating a grid number of each individual on each target dimension; converting a plurality of grid numbers of each individual on all targets into a comprehensive number; sorting all the individuals in the population according to the comprehensive numbers of the individuals; and traversing the sorted population, and identifying individuals in the same grid according to the same comprehensive number. According to the method, the problems of long time and high complexity of identifying individuals with the same number in the grid during the overall performance optimization of the aero-engine are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of aircraft engine optimization, and in particular relates to a method for quickly identifying individuals with the same number in a grid. Background Art

[0002] The design parameters of various components of aircraft engines have a great impact on the performance of the engine, such as the overall thrust, fuel consumption and stability, and there are many parameters that need to be optimized. The traditional optimization method mainly uses engine performance simulation analysis software to analyze engine performance, and based on existing empirical knowledge, it repeatedly modifies the design parameters to perform numerical simulation to achieve optimization; the manual iteration method is inefficient and cannot fully consider the coupling relationship between disciplines, making it difficult to find the optimal solution to multi-objective problems. The multi-objective optimization algorithm is used to select appropriate design parameters so that multiple objectives can be optimized as much as possible under given conditions. It can perform multi-objective optimization on the comprehensive performance of the engine under different working conditions, thereby obtaining the optimal engine design solution.

[0003] However, for multi-objective optimization algorithms, it is necessary to use a certain strategy multiple times to maintain the uniformity of the population. The grid method is an effective method to maintain the uniformity of the population. This method requires a double-layer loop to traverse and identify individuals with the same number in the grid, so that individuals with a smaller aggregation density can be retained in each grid to enter the new population. For complex engine overall performance optimization problems, a larger population size is usually required to ensure that the optimization algorithm can obtain the global optimal solution. However, as the number of individuals in the population increases, the amount of computation of the double-layer loop of the grid method to identify individuals with the same number increases dramatically. The conventional grid method uses a double-layer loop to identify individuals with the same number in the grid. When the number of individuals in the population is N, its time complexity is O(N 2 ). This makes the multi-objective optimization algorithm based on the grid method less efficient in solving complex optimization problems, thus limiting the scope of application of the grid method.

[0004] Therefore, in order to improve the applicability of the grid method to complex optimization problems, the present invention proposes a method for quickly identifying individuals with the same number in a grid for overall performance optimization of aircraft engines, and improves the process of identifying individuals with the same number in the grid in the grid method, thereby effectively improving the computational efficiency of the grid method. Summary of the invention

[0005] Technical issues to be solved:

[0006] In order to avoid the shortcomings of the prior art, the present invention provides a method for quickly identifying individuals with the same number in a grid. When identifying individuals with the same number in a grid, the numbers of the individuals in each dimension of the grid are placed in different positions of the same comprehensive number, and the numbers of the individuals in different dimensions are represented by the values ​​of different digits of the comprehensive number. The process of identifying individuals with the same number is converted into a sorting problem of the comprehensive number, and the comprehensive number is sorted using a quick sorting method, so that individuals with the same comprehensive number can be quickly gathered into the same comprehensive number area. The present invention solves the problem of long time and high complexity in identifying individuals with the same number in a grid when optimizing the overall performance of an aircraft engine.

[0007] The technical solution of the present invention is: a method for quickly identifying individuals with the same number in a grid, the specific steps are as follows:

[0008] In the multi-objective optimization model of the overall performance of an aircraft engine, each target value of each individual in the population design parameter is normalized;

[0009] Calculate the grid number of each individual on each target dimension;

[0010] Convert multiple grid numbers of each individual on all targets into a single composite number;

[0011] Sort all individuals in the population according to their comprehensive numbers;

[0012] Traverse the sorted population and identify individuals in the same grid based on the same comprehensive number.

[0013] A further technical solution of the present invention is: the population design parameters include N individuals, wherein each individual is a vector including D optimization variables, and the expression is:

[0014] X m =(x m,1 ,x m,2 ,…,x m,n ,…,x m,D ) T

[0015] Where m = 1, 2, ... N, x m,n represents the nth optimization variable of the mth individual.

[0016] A further technical solution of the present invention is: the individual X m The target value at target i is f i (X m ), the target value after normalization is The expression is:

[0017]

[0018] Among them, f i,max and f i,min are the maximum and minimum values ​​of target i in the population, respectively, and i represents the sequence number of the target.

[0019] A further technical solution of the present invention is: the method for calculating the grid number of each individual on each target dimension is as follows: the number of grids on target i is G i , for f i * (X m )×G i We can get individual X by rounding m The grid number O in the i-th target dimension i (X m ).

[0020] A further technical solution of the present invention is: the comprehensive number is O C (X m ), the expression is as follows:

[0021]

[0022] Among them, O1(X m ) represents individual X m The grid number in the first target dimension; O i (X m ) represents individual X m The grid number in the i-th target dimension; W j Represents the number of grids G on target j j The number of digits; p represents the total number of targets.

[0023] A further technical solution of the present invention is: the method for sorting all individuals in a population is a quick sorting method.

[0024] A system for quickly identifying individuals with the same number in a grid, comprising a normalization processing module, a grid numbering module, a comprehensive numbering module, a sorting module and an identification module; through the cooperation of the modules, the fast identification of individuals with the same number in a multi-objective model grid for optimizing the overall performance of the engine is achieved;

[0025] The normalization processing module is used to perform normalization processing on each target value of each individual in the population design parameter;

[0026] The grid numbering module is used to calculate the grid number of each individual in each target dimension;

[0027] The integrated numbering module is used to convert multiple grid numbers of each individual on all targets into an integrated number;

[0028] The sorting module is used to sort all individuals in the population;

[0029] The identification module identifies individuals in the same grid according to the same comprehensive number.

[0030] A multi-objective optimization method for overall performance of an aero-engine is disclosed. The multi-objective optimization method adopts a method for quickly identifying individuals with the same number in a grid.

[0031] An electronic device comprises at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for quickly identifying individuals with the same number in a grid.

[0032] A computer-readable digital storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for quickly identifying individuals with the same number in a grid when the instructions are executed.

[0033] Beneficial Effects

[0034] The beneficial effect of the present invention is that in the process of identifying individuals with the same number in a grid of a multi-objective optimization model of overall performance of an aircraft engine, the present invention no longer directly traverses and searches for individuals with the same number in each dimension of the grid through a double-layer loop, but places the numbers of the individuals in each dimension of the grid in different positions of the same comprehensive number, and uses numerical values ​​of different digits of the comprehensive number to represent the numbers of the individuals in different dimensions, and ensures that the individuals in the same grid have the same comprehensive number. The comprehensive numbers of all individuals are sorted using a quick sorting method, so that individuals with the same comprehensive number can be quickly gathered into the same comprehensive number area. The method of quickly identifying individuals with the same number in a grid of the present invention can convert the process of identifying individuals with the same number into a sorting problem, so that an efficient quick sorting method can be introduced to overcome the problem of slow speed when identifying individuals with the same number in a grid.

[0035] By using the method of quickly identifying individuals with the same number in the grid of the present invention, the double-layer cycle process of identifying individuals with the same grid number can be converted into a sorting problem based on the comprehensive number, and a high-efficiency sorting method such as a quick sorting method can be introduced to improve the sorting efficiency, thereby overcoming the problem of large computational complexity of the traditional grid method and solving the problem of poor applicability of the traditional grid method to complex multi-objective optimization problems of aircraft engines. Based on the standard multi-objective optimization algorithm NSGA-||, when optimizing the performance of three typical working conditions of aircraft engines, compared with the conventional grid method, the improved grid method of the present invention can reduce the optimization time by 14.44% to 17.77%. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a flowchart of a method for quickly identifying individuals with the same number in a grid, which can be selected according to an embodiment of the present invention;

[0037] Figure 2 This is a schematic diagram of the individual distribution of the 2D grid method.

[0038] Explanation of reference numerals: f1: objective function 1; f2: objective function 2; A: code for the area in the grid. DETAILED DESCRIPTION

[0039] The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0040] Based on the conventional grid method, a double-layer loop is used to identify individuals with the same number in the grid. When the number of individuals in the population is N, the time complexity is O(N 2 ). This makes the multi-objective optimization algorithm based on the grid method less efficient in solving complex optimization problems, thereby limiting the scope of application of the grid method. The present invention provides a method for quickly identifying individuals with the same number in a grid, and the specific steps are as follows:

[0041] Step 1: In the multi-objective optimization model of the overall performance of an aircraft engine, each target value of each individual in the population design parameter is normalized;

[0042] Step 2: Calculate the grid number of each individual in each target dimension;

[0043] Step 3: Convert multiple grid numbers of each individual on all targets into a comprehensive number;

[0044] Step 4: Sort all individuals in the population according to their comprehensive numbers;

[0045] Step 5: Traverse the sorted population and identify individuals in the same grid based on the same comprehensive number.

[0046] The invention discloses a system for rapidly identifying individuals with the same number in a grid, comprising a normalization processing module, a grid numbering module, a comprehensive numbering module, a sorting module and an identification module; the modules cooperate to realize rapid identification of individuals with the same number in a grid of a multi-objective optimization model of overall performance of an aeroengine; the normalization processing module is used for normalizing each target value of each individual in a population design parameter; the grid numbering module is used for calculating the grid number of each individual in each target dimension; the comprehensive numbering module is used for converting multiple grid numbers of each individual in all targets into one comprehensive number; the sorting module is used for sorting all individuals in the population; and the identification module identifies individuals in the same grid according to the same comprehensive number.

[0047] The invention discloses a multi-objective optimization method for overall performance of an aero-engine. The multi-objective optimization method adopts a method for rapidly identifying individuals with the same number in a grid.

[0048] The present invention provides an electronic device, comprising at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for quickly identifying individuals with the same number in a grid.

[0049] The present invention provides a computer-readable digital storage medium, wherein the computer-readable digital storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for quickly identifying individuals with the same number in a grid when executing the computer instructions.

[0050] The above technical solution is further described below in conjunction with the accompanying drawings and specific experiments:

[0051] Reference Figure 1 As shown, the specific steps of a method for quickly identifying individuals with the same number in a grid in this embodiment are as follows:

[0052] This embodiment takes the two-objective optimization of thrust and fuel consumption rate of an aircraft engine as an example for explanation, and the optimization goal is to maximize thrust and minimize fuel consumption rate. Figure 2 The individual distribution in the 2D grid, objective function f1 and objective function f2 correspond to the objective functions of thrust and fuel consumption rate respectively.

[0053] Step 1: Normalize each target value of each individual in the population.

[0054] For a population of N individuals, each individual can be represented as a vector X consisting of D optimization variables. m =(x m,1 ,x m,2 ,…,x m,n,…,x m,D ) T , where m = 1, 2, ... N, x m,n represents the nth optimization variable of the mth individual. m The target value at target i is f i (X m ), then the normalized target value f i * (X m )for:

[0055]

[0056] Among them, f i,max and f i,min are the maximum and minimum values ​​of target i in the population, respectively. After normalization, the maximum and minimum values ​​of objective function 1 and objective function 2 are 1 and 0, respectively.

[0057] Step 2: Calculate the grid number of each individual in each target dimension.

[0058] The number of grids on target i is G i , for f i * (X m )×G i We can get individual X by rounding m The grid number O in the i-th target dimension i (X m ).by Figure 2 Individual X in region A A For example, f1(X A ) belongs to the interval [0,0.2), f2(X A ) belongs to the interval [0.6,0.8), G1 and G2 are both 5, then f1(X A )×G1 belongs to the interval [0,1), f2(X A )×G2 belongs to the interval [3,4), for f1(X A )×G1 rounded to get O1(X A ) is 0, for f2(X A )×G2 rounded to get O2(X A ) is 3.

[0059] Step 3: Let the total number of targets be p, and convert the multiple grid numbers of each individual on p targets into a comprehensive number O according to the following formula: C (X m ):

[0060]

[0061] Among them, O1(X m ) represents individual X m The grid number in the first target dimension; O i (X m ) represents individual X m The grid number in the i-th target dimension; W j Represents the number of grids G on target j j The number of digits.

[0062] by Figure 2 Individual X in region A A For example, if G1 and G2 are both 5, then W1 and W2 are both 1. Since the target number p is 2, we have:

[0063]

[0064] Among them, O C (X A ) represents the grid number of the first target O1(X A ), the tenth digit represents the grid number O2(X A ).

[0065] Step 4: Use the quick sort method to sort all individuals in the population according to their comprehensive numbers.

[0066] Step 5: traverse the sorted population and identify individuals in the same grid according to the same comprehensive number. Figure 2 The comprehensive numbers of the individuals in area A are all 30. The three consecutive appearances of individuals with the comprehensive number 30 indicate that the above three individuals are all in area A.

[0067] In order to verify the effectiveness of the present invention, based on the standard multi-objective optimization algorithm NSGA-II, the performance of the conventional grid method and the improved grid method of the present invention in optimizing the performance of aircraft engines under different working conditions is compared. The type of aircraft engine selected is a mixed exhaust turbofan engine; the working conditions are selected as ground takeoff, supersonic cruise and subsonic cruise; the optimization goal is maximum thrust and minimum fuel consumption. The time for optimizing the engine performance under different working conditions by the conventional grid method and the improved grid method of the present invention is shown in the following table. It can be seen that compared with the conventional grid method, the improved grid method of the present invention can reduce the optimization time by 14.44% to 17.77%.

[0068] Table 1 Time (s) of different grid methods in optimizing aircraft engine performance

[0069]

[0070] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and purpose of the present invention.

Claims

1. A method for quickly identifying individuals with the same number in a grid, characterized in that The specific steps are as follows: In the multi-objective optimization model of the overall performance of an aircraft engine, each target value of each individual in the population design parameter is normalized; Calculate the grid number of each individual on each target dimension; Convert multiple grid numbers of each individual on all targets into a single composite number; Sort all individuals in the population according to their comprehensive numbers; Traverse the sorted population and identify individuals in the same grid based on the same comprehensive number.

2. A method for quickly identifying individuals with the same number in a grid according to claim 1, characterized in that: The population design parameters include N individuals, where each individual is a vector including D optimization variables, and the expression is: X m =(x m,1 ,x m,2 ,…,x m,n ,…,x m,D ) T Where m = 1, 2, ... N, x m,n represents the nth optimization variable of the mth individual.

3. A method for quickly identifying individuals with the same number in a grid according to claim 2, characterized in that: The individual X m The target value at target i is f i (X m ), the target value after normalization is f i * (X m ), the expression is: Among them, f i,max and f i,min are the maximum and minimum values ​​of target i in the population, respectively, and i represents the sequence number of the target.

4. A method for quickly identifying individuals with the same number in a grid according to claim 3, characterized in that: The method for calculating the grid number of each individual on each target dimension is as follows: the number of grids on target i is G i , for f i * (X m )×G i We can get individual X by rounding m The grid number O in the i-th target dimension i (X m ).

5. A method for quickly identifying individuals with the same number in a grid according to claim 4, characterized in that: The comprehensive number is O C (X m ), the expression is as follows: Among them, O1(X m ) represents individual X m The grid number in the first target dimension; O i (X m ) represents individual X m The grid number in the i-th target dimension; W j Represents the number of grids G on target j j The number of digits; p represents the total number of targets.

6. A method for quickly identifying individuals with the same number in a grid according to claim 5, characterized in that: The method for sorting all individuals in a population is a quick sorting method.

7. A system for quickly identifying individuals with the same number in a grid, characterized by: A method for rapidly identifying individuals with the same number in a grid as described in any one of claims 1 to 6; comprising a normalization processing module, a grid numbering module, a comprehensive numbering module, a sorting module and an identification module; and realizing rapid identification of individuals with the same number in a grid of a multi-objective optimization model for overall performance of an aircraft engine through the cooperation of the modules; The normalization processing module is used to perform normalization processing on each target value of each individual in the population design parameter; The grid numbering module is used to calculate the grid number of each individual in each target dimension; The integrated numbering module is used to convert multiple grid numbers of each individual on all targets into an integrated number; The sorting module is used to sort all individuals in the population; The identification module identifies individuals in the same grid according to the same comprehensive number.

8. A multi-objective optimization method for overall performance of an aircraft engine, characterized by: The multi-objective optimization method adopts the method for quickly identifying individuals with the same number in a grid as described in any one of claims 1 to 6.

9. An electronic device, characterized in that: It includes at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for quickly identifying individuals with the same number in a grid as described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for quickly identifying individuals with the same number in a grid as described in any one of claims 1 to 6 when executed.

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