Method and related device for solving the polishing parameter interval of aircraft engine blades

Abstract

The present invention relates to a method for solving an interval of polishing parameters for an aero-engine blade and a related device, belonging to the field of polishing processing technology. The method comprises: constructing a multi-objective optimization model of a response surface model of multiple polishing parameters to be solved to obtain an optimal solution for each polishing parameter to be solved; constructing multiple binary functions with any two first polishing parameters to be solved as independent variables and the roughness of the polished surface to be solved as a dependent variable, wherein the remaining second polishing parameters to be solved in the binary function take corresponding optimal solutions, determine the optimal value interval of each second polishing parameter to be solved, and solve the binary function to obtain the optimal value interval of the first polishing parameter to be solved. The present invention can obtain an accurate optimal value interval of the polishing parameter to be solved, facilitates adjustment of the polishing parameters according to actual processing conditions, and improves polishing accuracy and polishing efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of polishing processing, and in particular to a method for solving an interval of polishing parameters for an aero-engine blade and a related device. Background Art

[0002] With the continuous development of science and technology, in some special industries, there are extremely high requirements for the precision and efficiency of polishing processing.

[0003] Many existing optimization methods can provide specific values for optimal polishing process parameters. However, in actual production, due to subtle differences in processing environments and components, a reasonable range of values must be selected for optimal polishing results. Existing technologies often only provide the optimal solution for polishing parameters or an inaccurate range of values. This makes it impossible to precisely adjust polishing parameters based on actual conditions, affecting the accuracy and efficiency of the polishing process.

[0004] It can be seen that the existing technology cannot provide an accurate parameter value range for the polishing process, which affects the accuracy and efficiency of the polishing process. Summary of the Invention

[0005] In view of this, it is necessary to provide a method and related devices for solving the polishing parameter range of aircraft engine blades to solve the problem that the existing technology cannot provide an accurate parameter value range for the polishing process, which affects the accuracy and efficiency of the polishing process.

[0006] In order to solve the above problems, the present invention provides a method for solving the polishing parameter interval of an aero-engine blade, comprising:

[0007] Constructing a response surface model for multiple polishing parameters to be solved, establishing a multi-objective optimization model of the response surface model based on preset polishing requirements, solving the multi-objective optimization model to obtain an optimal solution for each polishing parameter to be solved; the multiple polishing parameters to be solved include two first polishing parameters to be solved and at least one second polishing parameter to be solved;

[0008] Based on the response surface model, multiple binary functions are constructed with any two first polishing parameters to be solved as independent variables and the roughness of the polished surface to be solved as the dependent variable, wherein the corresponding optimal solution is obtained for the remaining second polishing parameters to be solved in the binary function; and the optimal value range of each second polishing parameter to be solved is determined based on the solution threshold area corresponding to each binary function;

[0009] A binary function is solved based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished to obtain the optimal value range of the first polishing parameter to be solved.

[0010] In one possible implementation, a response surface model of multiple polishing parameters to be solved is constructed, and a multi-objective optimization model of the response surface model is established based on preset polishing requirements, including:

[0011] Constructing a functional relationship between the roughness of the surface to be polished and the response surface model of the polishing parameters to be solved;

[0012] A multi-objective optimization model for each polishing parameter to be solved is established by combining the initial range and functional relationship of each polishing parameter to be solved.

[0013] In a possible implementation, determining the optimal value range of each second polishing parameter to be solved based on the solution threshold area corresponding to each binary function includes:

[0014] Draw a contour map of each binary function, determine a target contour line where the roughness of the surface to be polished is less than or equal to a preset roughness threshold based on the contour map, and use the area enclosed by the target contour line and the coordinate axis as the solution threshold area;

[0015] An initial value interval of each second polishing parameter to be solved is determined based on each solution threshold area, and an optimal value interval of each second polishing parameter to be solved is determined based on the intersection of the initial value intervals.

[0016] In a possible implementation, determining the initial value range of each second polishing parameter to be solved based on each solution threshold area includes:

[0017] The binary function corresponding to the solution threshold area smaller than the preset solution threshold area threshold is determined as the first target binary function, and the first target binary function is solved to obtain the initial value intervals of the two second polishing parameters to be solved in the first target binary function.

[0018] In a possible implementation, solving a binary function based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished to obtain the optimal value range of the first polishing parameter to be solved includes:

[0019] Determining an optimal boundary value of the second polishing parameter to be determined based on a correlation between the second polishing parameter to be determined and the roughness of the surface to be polished;

[0020] The optimal boundary value of the second polishing parameter to be solved is substituted into the binary function, and the binary function is solved to obtain the optimal value range of the first polishing parameter to be solved.

[0021] In a possible implementation, substituting the optimal boundary value of the second polishing parameter to be solved into a binary function, and solving the binary function to obtain the optimal value range of the first polishing parameter to be solved includes:

[0022] Substituting the optimal boundary value of the second polishing parameter to be solved into the binary function to obtain a second target binary function;

[0023] A contour map of the second target binary function is drawn, and an optimal value interval of the first polishing parameter to be solved is solved based on the solution threshold area in the contour map of the second target binary function.

[0024] In a possible implementation, solving the optimal value range of the first polishing parameter to be solved based on the solution threshold area in the contour map of the second objective binary function includes:

[0025] When there are multiple solution threshold areas in the contour map of the second objective binary function, the optimal value interval of the first polishing parameter to be solved is solved based on the smaller solution threshold area.

[0026] The present invention also provides a device for solving the polishing parameter interval of an aero-engine blade, which is characterized by comprising:

[0027] a model building module for constructing a response surface model for a plurality of polishing parameters to be solved, establishing a multi-objective optimization model of the response surface model based on preset polishing requirements, solving the multi-objective optimization model, and obtaining an optimal solution for each of the polishing parameters to be solved; the plurality of polishing parameters to be solved include two first polishing parameters to be solved and at least one second polishing parameter to be solved;

[0028] A first solving module is configured to construct, based on a response surface model, a plurality of binary functions with any two first polishing parameters to be solved as independent variables and the roughness of the surface to be polished as a dependent variable, wherein the remaining second polishing parameters to be solved in the binary functions are solved for corresponding optimal solutions; and an optimal value range for each second polishing parameter to be solved is determined based on a solution threshold area corresponding to each binary function;

[0029] The second solving module is used to solve the binary function based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished, so as to obtain the optimal value range of the first polishing parameter to be solved.

[0030] The present invention also provides an electronic device, comprising a memory and a processor, wherein:

[0031] Memory, used to store programs;

[0032] The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the method for solving the polishing parameter interval of an aircraft engine blade in any of the above embodiments.

[0033] The present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction. When the program or instruction is executed by a processor, the steps in the method for solving the polishing parameter interval of an aircraft engine blade in any of the above-mentioned embodiments can be implemented.

[0034] The beneficial effects of the present invention are as follows: the method for solving the polishing parameter interval of an aero-engine blade provided by the present invention constructs a response surface model of the polishing parameters to be solved, and establishes a multi-objective optimization model of the response model based on preset polishing requirements, and solves the optimal solution of each polishing parameter to be solved based on the multi-objective optimization model, and then constructs a binary function with two first polishing parameters to be solved among the polishing parameters to be solved as independent variables and the roughness of the surface to be polished as the dependent variable, and the other second polishing parameters to be solved in the binary function take the corresponding optimal solution, and solves the binary function to obtain the optimal value interval of each second polishing parameter to be solved, and then solves the binary function based on the relationship between the optimal value interval of each second polishing parameter to be solved and the roughness of the surface to be polished, and obtains the optimal value interval of the first polishing parameter to be solved. Through rigorous mathematical calculation, on the basis of solving the optimal solution of the polishing parameter to be solved, the optimal value interval of the polishing parameter to be solved can be accurately obtained, which facilitates adjustment of the polishing parameters according to actual processing conditions and improves polishing accuracy and polishing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 A schematic flow chart of a method for solving an interval of polishing parameters for an aero-engine blade provided by an embodiment of the present invention;

[0037] Figure 2 A flowchart of a method for constructing a multi-objective optimization model provided by an embodiment of the present invention;

[0038] Figure 3 A schematic flow chart of a method for solving the optimal value range of a second polishing parameter to be solved provided by an embodiment of the present invention;

[0039] Figure 4-a to Figure 4-o Contour plots corresponding to coupling relationships of different parameters to be solved provided by the embodiment of the present invention;

[0040] Figure 5 A schematic flow chart of a method for solving an optimal value range of a first polishing parameter to be solved provided by an embodiment of the present invention;

[0041] Figure 6 A flowchart of a possible implementation of S502 provided in an embodiment of the present invention;

[0042] Figure 7A contour plot of a second objective binary function provided by an embodiment of the present invention;

[0043] Figure 8 A schematic structural diagram of a device for solving the polishing parameter interval of an aero-engine blade provided by an embodiment of the present invention;

[0044] Figure 9 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein the accompanying drawings constitute a part of the present invention and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0046] The terms "first," "second," and so on, used in the embodiments of the present invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, technical features designated as "first" or "second" may explicitly or implicitly include at least one such feature.

[0047] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0048] A specific embodiment of the present invention, as Figure 1 As shown, a method for solving the polishing parameter interval of an aero-engine blade is disclosed, comprising:

[0049] S101, constructing a response surface model for multiple polishing parameters to be solved, and establishing a multi-objective optimization model of the response surface model based on preset polishing requirements, solving the multi-objective optimization model to obtain an optimal solution for each polishing parameter to be solved; the multiple polishing parameters to be solved include two first polishing parameters to be solved and at least one second polishing parameter to be solved;

[0050] S102, constructing multiple binary functions based on a response surface model, with any two first polishing parameters to be solved as independent variables and the roughness of the surface to be polished as a dependent variable, wherein the remaining second polishing parameters to be solved in the binary functions are optimally solved; and determining the optimal value range of each second polishing parameter to be solved based on the solution threshold area corresponding to each binary function;

[0051] S103 , solving a binary function based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished, to obtain the optimal value range of the first polishing parameter to be solved.

[0052] In an embodiment of the present invention, the polishing parameters to be solved refer to parameters that can be adjusted in the polishing process. The adjustment of the polishing parameters to be solved will affect the accuracy and efficiency of the polishing process. Taking the process of polishing aircraft engine blades with a shutter wheel as an example, the polishing parameters to be solved can be the shutter wheel linear speed, the shutter wheel feed speed, the polishing depth, the contact arc length, the normal polishing force, and the elastic modulus of the shutter wheel. In addition, in the polishing process, there are also preset parameters that cannot be fine-tuned, such as the abrasive particle size of the shutter wheel. The response surface model refers to a relationship model between the roughness of the surface to be polished and each polishing parameter. Based on this relationship model and according to the actual processing conditions, a multi-objective optimization model for the polishing parameters to be solved is constructed. The multi-objective optimization model can optimize each polishing parameter to be solved, and then obtain the optimal solution for each polishing parameter to be solved.

[0053] Furthermore, after determining the optimal solution of each polishing parameter to be solved, any two polishing parameters to be solved are selected from all the polishing parameters to be solved as the first polishing parameters to be solved, and the first polishing parameters to be solved are used as independent variables, and the roughness of the surface to be polished is used as the dependent variable. A binary function is established based on the response surface model in the above embodiment, wherein the other polishing parameters to be solved in the response surface model are the second polishing parameters to be solved, and the second polishing parameters to be solved are directly assigned to the optimal solution solved in the above embodiment in the binary function. Optionally, if there are n polishing parameters to be solved, a binary function can be constructed. Two-variable function, the two independent variables in each two-variable function are different from the first polishing parameter to be solved. The solution threshold area of the binary function can be used to obtain the optimal value range of the second polishing parameter to be solved.

[0054] Furthermore, the optimal value range of the second polishing parameter to be solved is substituted into the binary function, and the optimal value range of the first polishing parameter to be solved can be obtained based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished.

[0055] The present invention provides a method for solving the polishing parameter interval of an aero-engine blade. The method constructs a response surface model of the polishing parameters to be solved, establishes a multi-objective optimization model of the response model based on preset polishing requirements, solves the optimal solution of each polishing parameter to be solved based on the multi-objective optimization model, then constructs a binary function with two first polishing parameters to be solved among the polishing parameters to be solved as independent variables and the roughness of the surface to be polished as a dependent variable, takes the corresponding optimal solution of the other second polishing parameters to be solved in the binary function, and solves the binary function to obtain the optimal value interval of each second polishing parameter to be solved. Then, based on the relationship between the optimal value interval of each second polishing parameter to be solved and the roughness of the surface to be polished, the binary function is solved to obtain the optimal value interval of the first polishing parameter to be solved. Through rigorous mathematical calculation, based on the optimal solution of the polishing parameters to be solved, the accurate optimal value interval of the polishing parameters to be solved can be obtained, which facilitates adjustment of the polishing parameters according to actual processing conditions and improves polishing accuracy and polishing efficiency.

[0056] As a possible embodiment of the present invention, in this embodiment, Figure 2 As shown, a response surface model of multiple polishing parameters to be solved is constructed, and a multi-objective optimization model of the response surface model is established based on the preset polishing requirements, including:

[0057] S201, constructing a functional relationship between the roughness of the surface to be polished and the response surface model of the polishing parameters to be solved;

[0058] S202 , establishing a multi-objective optimization model for each polishing parameter to be solved by combining the initial range and the functional relationship of each polishing parameter to be solved.

[0059] In an embodiment of the present invention, when constructing a response surface model, a functional relationship between the roughness of the surface to be polished and the polishing parameters to be solved can be constructed. Taking the process of polishing aircraft engine blades with a louver wheel in the aforementioned embodiment as an example, the functional relationship of the response surface model is as follows:

[0060]

[0061] in, is the roughness of the surface to be polished, is the linear speed of the impeller, is the flap wheel feed speed, is the polishing depth, l is the contact arc length, is the normal polishing force, K is the elastic modulus of the louver wheel, P is the abrasive particle size of the flap wheel.

[0062] Furthermore, a multi-objective optimization model of the functional relationship can be constructed by combining the initial ranges of the polishing parameters to be solved:

[0063]

[0064] in, E For polishing efficiency.

[0065] The embodiment of the present invention facilitates subsequent accurate calculations by constructing a functional relationship between a response model and a multi-objective optimization model.

[0066] Furthermore, a preset optimization algorithm can be used to solve the multi-objective optimization model to obtain the optimal solution for each polishing parameter to be solved.

[0067] In the embodiment of the present invention, when solving the multi-objective optimization model, existing optimization algorithms such as genetic algorithms and gradient descent methods can be used. The optimization algorithm can be used to calculate the optimal solution of each polishing parameter to be solved, as shown in Table 1:

[0068] Table 1:

[0069]

[0070] As a possible embodiment of the present invention, in this embodiment, Figure 3 As shown, the optimal value range of each second polishing parameter to be solved is determined based on the solution threshold area corresponding to each binary function, including:

[0071] S301, drawing a contour map of each binary function, determining a target contour line where the roughness of the surface to be polished is less than or equal to a preset roughness threshold based on the contour map, and taking the area enclosed by the target contour line and the coordinate axis as the threshold area;

[0072] S302 : determining initial value intervals of each second polishing parameter to be solved based on each solution threshold area, and determining optimal value intervals of each second polishing parameter to be solved based on the intersection of the initial value intervals.

[0073] In the embodiment of the present invention, when the abrasive grain size of the flap wheel is determined, any two of the six polishing parameters to be solved in the response surface model are used as independent variables, and the remaining four polishing parameters to be solved are set to the optimal values shown in Table 1. The roughness of the surface to be polished is used as the dependent variable. Then, an expression of the roughness of the surface to be polished with respect to any two polishing parameters to be solved can be obtained. This expression is a binary function, and then a contour map can be drawn based on this binary function, as shown in FIG. Figure 4-a value Figure 4-oAs shown, the coupling effect between any two polishing parameters to be solved can be analyzed using contour plots. The roughness threshold is preset to 0.4 μm, so the areas smaller than 0.4 μm in the contour plots are all satisfactory solution domains. Starting from the contour plots with smaller solution areas, the optimal interval can be determined by combining the influence of each polishing process parameter on polishing roughness. Specifically, using the aforementioned embodiment as an example, 15 binary functions can be constructed, and these 15 binary functions can be used to draw 15 contour plots. Among them, the binary functions with smaller solution threshold areas can be solved to obtain a more accurate optimal value interval.

[0074] Specifically, determining the initial value range of each second polishing parameter to be solved based on each solution threshold area includes:

[0075] The binary function corresponding to the solution threshold area smaller than the preset solution threshold area threshold is determined as the first target binary function, and the first target binary function is solved to obtain the initial value intervals of the two second polishing parameters to be solved in the first target binary function.

[0076] In an embodiment of the present invention, Figure 4-c 、 Figure 4-d 、 Figure 4-e 、 Figure 4-m 、 Figure 4-n 、 Figure 4-o The solution threshold area is small, and its corresponding coupled polishing process parameters and corresponding value ranges are shown in Table 2:

[0077] Table 2:

[0078]

[0079] Furthermore, by finding the intersection of the solution thresholds of the four polishing parameters to be solved, the optimal value ranges of the four polishing parameters to be solved can be obtained as shown in Table 3:

[0080] Table 3:

[0081]

[0082] In the embodiment of the present invention, the optimal value range of the second polishing parameter to be solved can be determined by solving the solution threshold area of the binary function.

[0083] As a possible embodiment of the present invention, in this embodiment, Figure 5 As shown, solving a binary function based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished to obtain the optimal value range of the first polishing parameter to be solved includes:

[0084] S501, determining an optimal boundary value of the second polishing parameter to be determined based on a correlation between the second polishing parameter to be determined and the roughness of the surface to be polished;

[0085] S502 , substituting the optimal boundary value of the second polishing parameter to be solved into the binary function, and solving the binary function to obtain the optimal value range of the first polishing parameter to be solved.

[0086] In this embodiment of the present invention, the response surface model relationship established for the roughness of the surface to be polished with respect to the polishing parameters to be solved shows that the roughness of the surface to be polished is inversely correlated with the shutter wheel linear velocity, contact arc length, normal polishing force, and shutter wheel elastic modulus. That is, the roughness of the surface to be polished decreases as these four polishing parameters increase; whereas the roughness of the surface to be polished is positively correlated with the shutter wheel feed speed and polishing depth. Therefore, substituting the lower bounds of the four polishing process parameters in Table 3 into the response surface model relationship yields a binary function of the roughness of the surface to be polished with respect to the shutter wheel feed speed and polishing depth. Then, by plotting the contours of this binary function, the optimal ranges for the shutter wheel feed speed and polishing depth can be determined.

[0087] Specifically, such as Figure 6 As shown, the optimal boundary value of the second polishing parameter to be solved is substituted into the binary function, and the binary function is solved to obtain the optimal value range of the first polishing parameter to be solved, including:

[0088] S601, substituting the optimal boundary value of the second polishing parameter to be solved into the binary function to obtain a second target binary function;

[0089] S602 : Draw a contour map of the second target binary function, and solve the optimal value range of the first polishing parameter to be solved based on the solution threshold area in the contour map of the second target binary function.

[0090] Furthermore, when there are multiple solution threshold areas in the contour map of the second objective binary function, the optimal value interval of the first polishing parameter to be solved is solved based on the smaller solution threshold area.

[0091] In the embodiment of the present invention, Figure 7 As shown in the figure, the optimal solution threshold of the second objective binary function has two parts, the upper left corner area and the lower area enclosed by the 0.4um contour line and the coordinate axis. The strict expression of this area should be a group of inequalities consisting of binary quadratic inequalities and the range of horizontal and vertical coordinate values. The area of the solution domain in the upper left corner is small, and the polishing depth cannot be directly controlled, so this area is discarded and a part of the lower area is selected as the optimal solution domain. As shown in the figure, the greater the feed speed, the denser the polishing roughness contour lines, and the more sensitive the polishing roughness is to the polishing depth. In actual processing, the polishing depth cannot be directly controlled, but is indirectly controlled by other polishing process parameters. Therefore, the parameter area where the polishing roughness is not sensitive to the polishing depth should be selected. Therefore, the feed speed cannot be too large, and the optimal interval selection Figure 7The grid area in . In order to ensure that the polishing process is flexible polishing, the normal polishing force should be limited to within 10 N. The above interval optimization process also limits the normal polishing force to no more than 10 N, and the normal polishing force has an important influence on it. If the normal polishing force is limited to no more than 10 N, then the elastic modulus of the flap wheel should also be limited to a smaller range accordingly. According to the test results, when the flap wheel abrasive grit is 600 and 800, the normal polishing force is not greater than 10 N, and the flap wheel elastic modulus is in the range of [0.8472, 4.1]. Therefore, the optimal range of the flap wheel elastic modulus is [0.8472, 4.1]. In summary, the optimal range of polishing process parameters when the flap wheel abrasive grit is 600 is shown in Table 4:

[0092] Table 4:

[0093]

[0094] Similarly, the optimal range of polishing process parameters when the flap wheel abrasive grit size is 800 can be obtained as shown in Table 5:

[0095] Table 5:

[0096]

[0097] Based on this, the optimal value range of each polishing parameter to be solved under different flap wheel abrasive grain sizes can be accurately calculated.

[0098] In order to better implement the method for solving the polishing parameter interval of an aero-engine blade in the embodiment of the present invention, based on the method for solving the polishing parameter interval of an aero-engine blade, correspondingly, Figure 8 As shown, an embodiment of the present invention further provides an apparatus for solving the polishing parameter interval of an aero-engine blade. The apparatus 800 for solving the polishing parameter interval of an aero-engine blade includes:

[0099] A model building module 801 is configured to construct a response surface model for multiple polishing parameters to be solved, establish a multi-objective optimization model of the response surface model based on preset polishing requirements, solve the multi-objective optimization model, and obtain an optimal solution for each polishing parameter to be solved; the multiple polishing parameters to be solved include two first polishing parameters to be solved and at least one second polishing parameter to be solved;

[0100] The first solving module 802 is configured to construct, based on a response surface model, a plurality of binary functions with any two first polishing parameters to be solved as independent variables and the roughness of the surface to be polished as a dependent variable, wherein the remaining second polishing parameters to be solved in the binary functions are solved for corresponding optimal solutions; and determine the optimal value range of each second polishing parameter to be solved based on the solution threshold area corresponding to each binary function;

[0101] The second solving module 803 is used to solve a binary function based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished, so as to obtain the optimal value range of the first polishing parameter to be solved.

[0102] The aircraft engine blade polishing parameter interval solving device 800 provided in the above embodiment can implement the technical solution described in the above embodiment of the aircraft engine blade polishing parameter interval solving method. The specific implementation principles of the above modules or units can be found in the corresponding contents in the above embodiment of the aircraft engine blade polishing parameter interval solving method, which will not be repeated here.

[0103] The present invention provides a device for solving polishing parameter intervals for an aero-engine blade. The device constructs a response surface model of the polishing parameters to be solved, establishes a multi-objective optimization model of the response model based on preset polishing requirements, solves the optimal solution of each polishing parameter to be solved based on the multi-objective optimization model, then constructs a binary function with two first polishing parameters to be solved among the polishing parameters to be solved as independent variables and the roughness of the surface to be polished as a dependent variable, takes corresponding optimal solutions for other second polishing parameters to be solved in the binary function, and solves the binary function to obtain the optimal value interval of each second polishing parameter to be solved. Then, the binary function is solved based on the relationship between the optimal value interval of each second polishing parameter to be solved and the roughness of the surface to be polished to obtain the optimal value interval of the first polishing parameter to be solved. Through rigorous mathematical calculations, based on the optimal solution of the polishing parameters to be solved, an accurate optimal value interval of the polishing parameters to be solved can be obtained, which facilitates adjustment of the polishing parameters according to actual processing conditions and improves polishing accuracy and polishing efficiency.

[0104] like Figure 9 As shown, the present invention also provides an electronic device 900. The electronic device 900 includes a processor 901, a memory 902 and a display 903. Figure 9 Only some of the components of the electronic device 900 are shown, but it should be understood that implementation of all of the shown components is not required, and more or fewer components may be implemented instead.

[0105] In some embodiments, the processor 901 may be a central processing unit (CPU), a microprocessor, or other data processing chip, configured to execute program codes or process data stored in the memory 902, such as the method for determining the polishing parameter interval of an aero-engine blade in the present invention.

[0106] In some embodiments, the processor 901 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processor 901 may be local or remote. In some embodiments, the processor 901 may be implemented on a cloud platform. In some embodiments, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, multiple clouds, or any combination thereof.

[0107] In some embodiments, the memory 902 may be an internal storage unit of the electronic device 900, such as a hard disk or memory of the electronic device 900. In other embodiments, the memory 902 may also be an external storage device of the electronic device 900, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 900.

[0108] Furthermore, the memory 902 may include both an internal storage unit of the electronic device 900 and an external storage device. The memory 902 is used to store application software installed in the electronic device 900 and various data.

[0109] In some embodiments, the display 903 can be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display 903 is used to display information about the electronic device 900 and to display a visual user interface. Components 901-903 of the electronic device 900 communicate with each other via a system bus.

[0110] In some embodiments, when the processor 901 executes the polishing parameter interval solving program in the memory 902, the following steps may be implemented:

[0111] Constructing a response surface model for multiple polishing parameters to be solved, and establishing a multi-objective optimization model of the response surface model based on preset polishing requirements, solving the multi-objective optimization model to obtain an optimal solution for each polishing parameter to be solved; the multiple polishing parameters to be solved include two first polishing parameters to be solved and at least one second polishing parameter to be solved;

[0112] Based on the response surface model, multiple binary functions are constructed with any two first polishing parameters to be solved as independent variables and the roughness of the polished surface to be solved as the dependent variable, wherein the corresponding optimal solution is obtained for the remaining second polishing parameters to be solved in the binary function; and the optimal value range of each second polishing parameter to be solved is determined based on the solution threshold area corresponding to each binary function;

[0113] A binary function is solved based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished to obtain the optimal value range of the first polishing parameter to be solved.

[0114] It should be understood that, when the processor 901 executes the polishing parameter interval solving program in the memory 902 , in addition to the above functions, it can also implement other functions. For details, please refer to the description of the corresponding method embodiment above.

[0115] Furthermore, the embodiment of the present invention does not specifically limit the type of the electronic device 900 mentioned. The electronic device 900 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, or a laptop computer. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft or other operating systems. The above-mentioned portable electronic devices may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 900 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0116] Accordingly, an embodiment of the present invention also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by a processor, it can implement the steps or functions in the method for solving the polishing parameter interval of aircraft engine blades provided by the above-mentioned method embodiments.

[0117] Those skilled in the art will appreciate that all or part of the process steps of the above-described embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, such as a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0118] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed by the present invention should be covered by the scope of protection of the present invention.

Claims

1. A method for solving the polishing parameter interval of an aero-engine blade, characterized in that: include: Constructing a response surface model for multiple polishing parameters to be solved, establishing a multi-objective optimization model of the response surface model based on preset polishing requirements, and solving the multi-objective optimization model to obtain an optimal solution for each of the polishing parameters to be solved; the multiple polishing parameters to be solved include two first polishing parameters to be solved and at least one second polishing parameter to be solved; Based on the response surface model, a plurality of binary functions are constructed, each with two arbitrary first polishing parameters to be solved as independent variables and the roughness of the surface to be polished as a dependent variable, wherein the remaining second polishing parameters to be solved in the binary functions are obtained with corresponding optimal solutions; and an optimal value range of each second polishing parameter to be solved is determined based on a solution threshold area corresponding to each binary function; Solving the binary function based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished to obtain the optimal value range of the first polishing parameter to be solved; The step of constructing a response surface model of multiple polishing parameters to be solved and establishing a multi-objective optimization model of the response surface model based on preset polishing requirements includes: Constructing a functional relationship between the roughness of the surface to be polished and the response surface model of the polishing parameters to be solved; Establishing a multi-objective optimization model for each of the polishing parameters to be solved in combination with the initial range of each of the polishing parameters to be solved and the functional relationship; The determining the optimal value range of each second polishing parameter to be solved based on the solution threshold area corresponding to each binary function includes: Drawing a contour map of each of the binary functions, determining a target contour line where the roughness of the surface to be polished is less than or equal to a preset roughness threshold based on the contour map, and using the area of a region enclosed by the target contour line and the coordinate axis as a solution threshold area; determining an initial value interval of each second polishing parameter to be solved based on each of the solution threshold areas, and determining an optimal value interval of each second polishing parameter to be solved based on an intersection of the initial value intervals; The determining of the initial value range of each second polishing parameter to be solved based on each solution threshold area includes: Determining a binary function corresponding to the solution threshold area smaller than a preset solution threshold area threshold as a first target binary function, solving the first target binary function to obtain initial value intervals of two second polishing parameters to be solved in the first target binary function; Solving the binary function based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished to obtain the optimal value range of the first polishing parameter to be solved includes: determining an optimal boundary value of the second polishing parameter to be solved based on a correlation between the second polishing parameter to be solved and the roughness of the surface to be polished; Substituting the optimal boundary value of the second polishing parameter to be solved into the binary function, solving the binary function to obtain the optimal value range of the first polishing parameter to be solved; Substituting the optimal boundary value of the second polishing parameter to be solved into the binary function, and solving the binary function to obtain the optimal value range of the first polishing parameter to be solved, includes: Substituting the optimal boundary value of the second polishing parameter to be solved into the binary function to obtain a second target binary function; A contour map of the second target binary function is drawn, and an optimal value interval of the first polishing parameter to be solved is solved based on a solution threshold area in the contour map of the second target binary function.

2. The method for solving the polishing parameter interval of an aero-engine blade according to claim 1, characterized in that: The step of solving the optimal value range of the first polishing parameter to be solved based on the solution threshold area in the contour map of the second target binary function includes: When there are multiple solution threshold areas in the contour map of the second target binary function, the optimal value interval of the first polishing parameter to be solved is solved based on the smaller solution threshold area.

3. A device for solving the polishing parameter interval of an aero-engine blade, applicable to the method for solving the polishing parameter interval of an aero-engine blade according to claim 1 or 2, characterized in that: include: a model building module, configured to construct a response surface model for a plurality of polishing parameters to be solved, establish a multi-objective optimization model of the response surface model based on preset polishing requirements, and solve the multi-objective optimization model to obtain an optimal solution for each of the polishing parameters to be solved; the plurality of polishing parameters to be solved include two first polishing parameters to be solved and at least one second polishing parameter to be solved; a first solving module, configured to construct, based on the response surface model, a plurality of binary functions with any two first polishing parameters to be solved as independent variables and the roughness of the surface to be polished as a dependent variable, wherein the remaining second polishing parameters to be solved in the binary functions are solved with corresponding optimal solutions; and determine the optimal value range of each second polishing parameter to be solved based on the solution threshold area corresponding to each binary function; The second solving module is used to solve the binary function based on the relationship between the optimal value range of the second polishing parameter to be solved and the roughness of the surface to be polished, so as to obtain the optimal value range of the first polishing parameter to be solved.

4. An electronic device, characterized in that: comprising a memory and a processor, wherein, The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the method for solving the polishing parameter interval of an aircraft engine blade according to claim 1 or 2.

5. A computer-readable storage medium, characterized in that Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the method for solving the polishing parameter interval of an aircraft engine blade as described in claim 1 or 2.

Images