Aero-engine blade precision electrolytic machining cathode profile design optimization method

Abstract

The present application relates to the field of aero-engine blade manufacturing, and provides a method for optimizing the cathode profile design of aero-engine blade precision electrochemical machining. The method solves the current density distribution in the blade precision electrochemical machining process through a multi-physical field coupling simulation software, and takes the average value and variance of the current density around the blade profile as the optimization target, and gradually optimizes the cathode profile through the differential evolution algorithm until the current density distribution is uniform, so as to improve the precision and surface quality of the blade electrochemical machining. The present application effectively solves the problems of a large number of cathode profile curve control points, slow optimization speed and difficult convergence of optimization, and through the multi-field coupling simulation technology, the distribution of the current density in the blade precision electrochemical machining process can be accurately and quickly solved, and the uniformity of the current density distribution around the blade when the blade precision electrochemical machining process proceeds to the final stage is improved.

Description

Technical Field

[0001] This invention belongs to the field of aero-engine blade manufacturing, specifically relating to a method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades. Background Technology

[0002] Aero-engine blades are typical thin-walled components, often exhibiting significant torsion. Operating under high temperature, high pressure, and high speed conditions, they must withstand enormous centrifugal forces and complex vibrations, and are generally made of difficult-to-machine metal materials such as titanium alloys and nickel-based alloys. To meet the requirements of high-performance engines, blades must possess precise dimensions, accurate shapes, and stringent surface integrity, placing extremely high demands on blade manufacturing processes.

[0003] Compared to traditional machining, electrochemical machining has a wider range of applications. During electrochemical machining, the cathode and workpiece do not contact each other, and there is no macroscopic cutting force. The removal of workpiece blank material is primarily achieved through electrochemical reactions. It is not limited by the mechanical or physical properties of the workpiece material, such as strength, hardness, and toughness. Furthermore, electrochemical machining produces no wear on the tool cathode, significantly reducing processing costs in the mass production of engine blades. Due to its wide range of applicable materials, absence of residual stress and macroscopic cutting forces, and wear-free tool cathode, electrochemical machining has stood out among numerous aero-engine blade manufacturing technologies. Electrochemical machining is gradually becoming the ideal processing technology for the mass production of engine blades.

[0004] The distribution of current density during electrochemical machining directly affects the machining accuracy of the blades. If the uniformity of current density near the blades can be maintained in the final stage of electrochemical machining, the machining accuracy and quality of the blades will be greatly improved. However, due to the relatively twisted shape of the blades, and the fact that the current density distribution depends on the structure of the cathode profile and the combined influence of multiple physical fields such as electric field, flow field, and temperature field during electrochemical machining, the design and optimization of the cathode profile is quite difficult. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by providing a method for optimizing the cathode profile design in the precision electrolytic machining of aero-engine blades. This method uses multiphysics coupled simulation software to solve for the current density distribution during the precision electrolytic machining process of the blade. The average value and variance of the current density around the blade profile are used as optimization targets. A differential evolution algorithm is then used to progressively optimize the cathode profile until the current density distribution is uniform, thereby improving the precision and surface quality of the blade electrolytic machining.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades, characterized by comprising:

[0008] Step 1: Input the initial cathode profile;

[0009] Step 2: Based on the cathode profile, obtain the current density distribution around the blade profile through multiphysics coupling simulation;

[0010] Step 3: Calculate the average and variance of the current density around the blade profile, which will serve as the objective function of the differential evolution algorithm;

[0011] Step 4: Based on the objective function, use the differential evolution algorithm to calculate the offset of the control points of the cathode profile curve, and update the curve control points according to the offset to obtain the cathode profile after differential evolution.

[0012] Step 5: Perform multiphysics coupling simulation on the differentially evolved cathode profile, solve the objective function based on the simulation results, and select the cathode profile with the optimal objective function value as the optimized cathode profile.

[0013] To optimize the above technical solution, the specific measures also include:

[0014] Furthermore, in step one, the cathode profile is a spline curve containing several control points; for the input cathode profile, the coordinate values ​​of each control point of the spline curve are read and stored, and the coordinate values ​​of the control points are converted into a spline curve in Python through the spline curve generation command, and the generated spline curve is converted into a dxf graphic file.

[0015] Furthermore, in step two, the solution for the distribution of current density around the blade profile is performed in the multiphysics coupling simulation software COMSOL. The dxf graphic file of the cathode profile spline curve is imported into COMSOL using Python, and then the simulation is started and post-processed. The current density around the blade profile obtained from the simulation is read into the Python program and stored.

[0016] Furthermore, in step four, the differential evolution algorithm is executed in Python.

[0017] Furthermore, in step four, the specific process of obtaining the differentially evolved cathode profile is as follows:

[0018] S1: Generate n initial random matrices composed of m-dimensional random numbers, where m is the number of control points of the cathode profile curve, and the random number in each initial random matrix is ​​the offset of the control point of the cathode profile curve.

[0019] S2: For each initial random matrix, a new random matrix is ​​generated through a mutation operation, resulting in n mutated random matrices;

[0020] S3: Perform a cross operation between the mutated random matrix and the initial random matrix to generate n cross-multiplied random matrices;

[0021] S4: Calculate the objective function value for each initial random matrix, each mutated random matrix, and each crossover random matrix;

[0022] S5: For each initial random matrix, compare its objective function value with the corresponding generated mutated random matrix and the crossover random matrix, and select the random matrix with the better objective function value from the three. Finally, n random matrices with better objective function values ​​are obtained as the initial population of the next generation.

[0023] S6: Repeat S2-S5 until the iteration termination condition is met, and output n random matrices. Each output random matrix and the coordinate values ​​of the control points of the input cathode profile curve together constitute the cathode profile after differential evolution.

[0024] Furthermore, in S6, the iteration termination condition is a termination condition that satisfies the number of iterations or reaches the average value and variance of the current density around the blade profile.

[0025] Furthermore, the present invention also proposes a computer-readable storage medium storing a computer program, characterized in that the computer program enables a computer to execute the above-described method for optimizing the cathode profile design of precision electrolytic machining of aero-engine blades.

[0026] Furthermore, the present invention also proposes an electronic device, characterized in that it includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the above-described method for optimizing the cathode profile design of precision electrolytic machining of aero-engine blades.

[0027] The beneficial effects of this invention are as follows: The cathode profile design optimization method proposed in this invention can effectively solve the problems of a large number of control points for the cathode profile curve, slow optimization speed, and difficulty in convergence. Through multi-field coupling simulation technology, the distribution of current density during the precision electrolytic machining of blades can be accurately and quickly solved, which can improve the uniformity of the current density distribution around the blade when the precision electrolytic machining process reaches the final stage. This is of great significance for improving the precision of blade electrolytic machining and the surface quality of the blade. Attached Figure Description

[0028] Figure 1 This is a flowchart of the main process for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades.

[0029] Figure 2 This is a schematic diagram of the updated profile curves of aero-engine blades and cathodes.

[0030] The attached figures are labeled as follows: 1. Initial profile of the blade back cathode, 2. Initial profile of the blade base cathode, 3. Curve control point, 4. Curve control point offset, 5. Updated profile of the blade back cathode, 6. Updated profile of the blade base cathode, 7. Blade profile. Detailed Implementation

[0031] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0032] In one embodiment, the present invention proposes a method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades, such as... Figure 1 As shown, the main processes include initial cathode profile design, current density solution, objective function solution, differential evolution, and cathode profile optimization evaluation.

[0033] The initial cathode profile design can be an existing cathode profile or a cathode profile designed based on the principle of equal gaps. During the cathode profile design optimization process, the cathode profile is a spline curve containing several control points. The offset of the curve control points is the input and output value of the differential evolution algorithm.

[0034] Specifically, in the initial cathode profile design, the cathode profile is a spline curve containing several control points. At the beginning of the cathode profile design optimization process, the coordinate values ​​of each control point of the initial cathode profile spline curve are read and stored. In Python, the coordinate values ​​of the control points are converted into spline curves through the spline curve generation command, and the generated spline curves are converted into dxf graphic files for use by subsequent multi-field coupling simulation software.

[0035] The current density is calculated in a multiphysics coupling simulation software. The workpiece profile in the simulation model is the blade profile corresponding to the cathode profile, and the tool profile is the initial / updated cathode profile.

[0036] Specifically, the current density calculation process is carried out in the multiphysics coupling simulation software COMSOL. During the cathode profile design optimization process, Python is used to control COMSOL to import the cathode profile spline curve dxf graphic file, and then the simulation is started and post-processed. The current density around the blade profile obtained from the simulation is read into the Python program and stored.

[0037] The objective function is to calculate the average and variance of the current density around the blade profile, and use these as the target value for optimization by the differential evolution algorithm.

[0038] Specifically, the objective function is to calculate the average and variance of the current density around the stored blade profile in Python.

[0039] Differential evolution involves calculating the offset of the control points of the cathode profile curve based on the objective function calculation results, and updating the control points of the curve according to the offset to obtain the differentially evolved cathode profile.

[0040] Specifically, the differential evolution and cathode profile optimization evaluation is a cathode profile design optimization based on the differential evolution algorithm performed in Python. Assuming the number of cathode profile control points is m and the population size of the differential evolution algorithm is n, the cathode profile design optimization steps based on the differential evolution algorithm are as follows:

[0041] S1: Initialize the population and generate n m-dimensional matrices composed of random numbers, where the random numbers in each matrix are the offsets of the control points of the cathode profile curve. Each matrix represents a potential solution for the cathode profile. These random matrices constitute the initial population.

[0042] S2: Individual mutation. For each random matrix, a new random matrix is ​​generated through mutation operation.

[0043] S3: Crossover operation, which crosses the mutated random matrix with the original random matrix to generate a new random matrix;

[0044] S4: Evaluate the objective function; calculate the objective function for each newly generated random matrix.

[0045] S5: Selection operation, which selects the random matrix with a better objective function value as the next generation population by comparing the objective function values ​​of the newly generated random matrix and the original random matrix;

[0046] S6: Iterative operation, repeating S2-S5 to generate a new random matrix and gradually optimize the objective function value. The algorithm stops after a certain number of iterations or when the average value and variance are reached.

[0047] The entire optimization process of the differential evolution algorithm can be summarized as an iteration of the above steps. In each generation, through operations such as mutation, crossover, evaluation, and selection, the random matrix in the population is continuously updated in the hope of finding the optimal solution in the search space.

[0048] The cathode profile optimization evaluation involves conducting multiphysics coupled simulations using the cathode profile obtained after differential evolution, solving the objective function based on the simulation results, and selecting the cathode profile with the optimal objective function value as the optimized cathode profile.

[0049] Next, combined Figure 2 The following examples illustrate the specific steps of the cathode profile design optimization method for precision electrolytic machining of aero-engine blades provided by this invention.

[0050] (1) Take the existing cathode profiles of leaf basin and leaf back as the initial cathode profiles 1 and 2 of leaf back and leaf basin, and obtain the coordinate values ​​of the curve control point 3 of the initial cathode profiles of leaf back and leaf basin.

[0051] (2) Generate n m-dimensional matrices composed of random numbers, where the random number in each matrix is ​​the offset of the control point 4 of the cathode profile curve. The coordinate values ​​of the control point 3 of the initial cathode profile of the blade back and blade basin, together with the offset of the control point 4, constitute the random updated cathode profiles 5 and 6 of the blade back and blade basin. Each matrix represents a potential solution of the cathode profile. These random matrices constitute the initial population.

[0052] (3) Individual mutation: For each random matrix, a new random matrix is ​​generated through mutation operation.

[0053] (4) Cross operation: The mutated random matrix is ​​crossed with the initial random matrix to generate a new random matrix.

[0054] (5) Combine the generated random matrices with the coordinate values ​​of the curve control points 3 of the initial profile of the leaf back and leaf basin cathode to generate the variable and intersecting curve control points of the leaf back and leaf basin cathode. Use the curve fitting command to convert the variable and intersecting curve control points of the leaf back and leaf basin cathode into spline curves, and save the spline curves as dxf graphic files.

[0055] (6) Import the spline curve dxf graphic files of the newly generated blade back and blade basin cathode profiles into the multi-field coupling simulation software COMSOL in sequence, and simulate the distribution of current density during the precision electrolytic machining of the blade.

[0056] (7) Calculate the average and variance of the current density around the blade profile 7 corresponding to each newly generated blade back and blade basin cathode profile.

[0057] (8) Compare the mean and variance of the initial leaf back and leaf basin cathode profiles with the variant and crossover leaf back and leaf basin cathode profiles, and select the random matrix with better objective function value as the initial population of the next generation.

[0058] (9) Iteration operation: Repeat (3) to (8) to generate a new random matrix and gradually optimize the objective function value. Stop the algorithm after a certain number of iterations or when the average value and variance are reached.

[0059] (10) Based on the random matrix output by the algorithm, select the cathode profile with the optimal objective function value as the optimized cathode profile.

[0060] In another embodiment, the present invention provides a computer-readable storage medium storing a computer program that causes a computer to execute the cathode profile design optimization method for precision electrolytic machining of aero-engine blades as described in Embodiment 1.

[0061] In another embodiment, the present invention proposes an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for optimizing the cathode profile design of precision electrolytic machining of aero-engine blades as described in Embodiment 1.

[0062] In the embodiments disclosed in this application, a computer storage medium may be a tangible medium that may contain or store programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0063] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0064] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades, characterized in that, include: Step 1: Input the initial cathode profile; Step 2: Based on the cathode profile, obtain the current density distribution around the blade profile through multiphysics coupling simulation; Step 3: Calculate the average and variance of the current density around the blade profile, which will serve as the objective function of the differential evolution algorithm; Step 4: Based on the objective function, use the differential evolution algorithm to calculate the offset of the control points of the cathode profile curve, and update the curve control points according to the offset to obtain the cathode profile after differential evolution. Step 5: Perform multiphysics coupling simulation on the differentially evolved cathode profile, solve the objective function based on the simulation results, and select the cathode profile with the optimal objective function value as the optimized cathode profile.

2. The method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades as described in claim 1, characterized in that: In step one, the cathode profile is a spline curve containing several control points. For the input cathode profile, the coordinate values ​​of each control point of the spline curve are read and stored. In Python, the coordinate values ​​of the control points are converted into spline curves through the spline curve generation command, and the generated spline curves are converted into DXF graphic files.

3. The method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades as described in claim 2, characterized in that: In step two, the solution for the current density distribution around the blade profile is performed in the multiphysics coupling simulation software COMSOL. The dxf graphic file of the cathode profile spline curve is imported into COMSOL using Python. Then, the simulation is started and post-processing is performed. The current density around the blade profile obtained from the simulation is read into the Python program and stored.

4. The method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades as described in claim 1, characterized in that: In step four, the differential evolution algorithm is executed in Python.

5. The method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades as described in claim 1, characterized in that: In step four, the specific process of obtaining the differentially evolved cathode profile is as follows: S1: Generate n initial random matrices composed of m-dimensional random numbers, where m is the number of control points of the cathode profile curve, and the random number in each initial random matrix is ​​the offset of the control point of the cathode profile curve. S2: For each initial random matrix, a new random matrix is ​​generated through a mutation operation, resulting in n mutated random matrices; S3: Perform a cross operation between the mutated random matrix and the initial random matrix to generate n cross-multiplied random matrices; S4: Calculate the objective function value for each initial random matrix, each mutated random matrix, and each crossover random matrix; S5: For each initial random matrix, compare its objective function value with the corresponding generated mutated random matrix and the crossover random matrix, and select the random matrix with the better objective function value from the three. Finally, n random matrices with better objective function values ​​are obtained as the initial population of the next generation. S6: Repeat S2-S5 until the iteration termination condition is met, and output n random matrices. Each output random matrix and the coordinate values ​​of the control points of the input cathode profile curve together constitute the cathode profile after differential evolution.

6. The method for optimizing the cathode profile design in precision electrolytic machining of aero-engine blades as described in claim 5, characterized in that: In S6, the iteration termination condition is the condition that the number of iterations is satisfied or the average value and variance of the current density around the blade profile are reached.

7. A computer-readable storage medium storing a computer program, characterized in that, The computer program causes the computer to execute the method for optimizing the cathode profile design of precision electrolytic machining of aero-engine blades as described in any one of claims 1-6.

8. An electronic device, characterized in that, include: The invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method for optimizing the cathode profile design of precision electrolytic machining of aero-engine blades as described in any one of claims 1-6.

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