Motion table ceramic part structure optimization method based on dynamic benchmarking

Abstract

The invention provides a motion table ceramic part structure optimization method based on dynamic benchmarking, and belongs to the technical field of dynamic analysis. In order to solve the problems of low modal characteristic test accuracy and high research and development cost of a motion table ceramic part, the invention provides a motion table ceramic part structure optimization method based on dynamic benchmarking, and the method comprises the following steps: S1, establishing a simulation digital model of the motion table ceramic part; s2, on the basis of modal data comparison of an experimental modal and a simulation calculation modal, a simulation digital model of the motion platform ceramic part is corrected; and S3, based on the key parameters influencing the modality of the motion table ceramic part, the corrected modal data of the simulation digital model of the motion table ceramic part and the modal data of the corresponding experimental modality, carrying out structure optimization on the motion table ceramic part. According to the method, the experimental mode and the calculation mode of the motion platform ceramic piece are benchmarked, the reliability of mode characteristic testing is improved, and the research and development cost is reduced through closed-loop iteration of virtual prediction-physical verification-model correction.

Description

Technical Field

[0001] The present application relates to the technical field of dynamic analysis, and in particular to a method for optimizing the structure of ceramic components of a moving table based on dynamic benchmarking. Background Art

[0002] As a core component in a photolithography machine, the ceramic motion stage provides high-precision guidance and support. Its modal characteristics (natural frequency, vibration mode, damping ratio, etc.) directly impact the dynamic stability, positioning accuracy, and anti-interference capabilities of the motion stage. During the development of ceramic motion stage components, experimental modal testing is typically used to determine their dynamic characteristics, which is then used for structural optimization.

[0003] shortcoming: 1. The boundary conditions (e.g., fixing method) of the experimental modal test must simulate the actual working conditions as closely as possible. However, in practice, complex constraints may exist (e.g., elastic support of air bearings, joint stiffness of multiple components). 2. In actual operation, ceramic components may be subjected to multiple field couplings such as heat, force, electricity, and magnetism. Modal testing is usually performed only under a single operating condition (such as room temperature and no load), which cannot capture the dynamic impact of multiple field coupling on modal characteristics.

[0004] 3. The ceramic components of the motion table have the characteristics of light weight, high stiffness and low thermal deformation, but the manufacturing cost is high, which leads to high cost of experimental modal testing, thereby increasing the R&D cost. Summary of the Invention

[0005] The purpose of this application is to address the existing issues of low accuracy and high R&D costs in modal property testing of ceramic components used in motion platforms. Therefore, this application provides a method for optimizing the structure of ceramic components used in motion platforms based on dynamic benchmarking. This method benchmarks the experimental and calculated modal properties of the ceramic components used in motion platforms, improving the reliability of modal property testing and reducing R&D costs through a closed-loop iteration of "virtual prediction - physical verification - model correction."

[0006] The present application provides a method for optimizing the structure of a ceramic component of a moving table based on dynamics benchmarking, including: S1 establishes a simulation digital model of the ceramic parts of the motion table; S2 corrects the simulation digital model of the ceramic component of the moving table based on the comparison of the modal data of the experimental modal and the simulation calculated modal; S3 performs structural optimization on the moving platform ceramic component based on key parameters that affect the modal state of the moving platform ceramic component, the modified modal data of the simulation digital model of the moving platform ceramic component, and the modal data of the corresponding experimental modal state.

[0007] In some embodiments, the step S2 corrects the simulated digital model of the ceramic component of the moving table based on the comparison of the modal data of the experimental modal data and the simulated modal data, including: S21: acquiring simulation modal data of the moving table ceramic component based on the simulation digital model of the moving table ceramic component; S22: manufacturing the moving table ceramic component based on the simulated digital model of the moving table ceramic component; S23: obtaining experimental modal data of the moving table ceramic component under experimental modal testing; S24: obtaining frequency errors of the simulated modal data and the experimental modal data based on the simulated modal data and the experimental modal data; S25: if the frequency error is greater than the preset threshold, then modify the simulation digital model of the moving table ceramic component and repeat S21-S24 until the frequency error is less than or equal to the preset threshold; and The step S3 performs structural optimization on the ceramic component of the moving platform based on key parameters that affect the modal state of the ceramic component of the moving platform, the modal data of the modified simulation digital model of the ceramic component of the moving platform, and the modal data of the corresponding experimental modal state, including: S31 Determine the key parameters that affect the modal behavior of the ceramic components of the motion table based on sensitivity analysis; S32 performs structural optimization on the moving table ceramic component corresponding to the simulated digital model of the moving table ceramic component that satisfies the frequency error ≤ the preset threshold based on the key parameters, the simulated modal data, and the experimental modal data, and repeats S21-S23 until the simulated modal data and the experimental modal data both meet the design requirements.

[0008] In some embodiments, the simulated digital model of the moving table ceramic component is structurally optimized, including topological optimization or size optimization of the simulated digital model of the moving table ceramic component; and the moving table ceramic component includes a main body, a groove portion located in the middle of the main body, and an edge thinning portion located at the edge of the main body, and the structural optimization order is the main body, the groove, and the edge thinning portion of the moving table ceramic component.

[0009] In some embodiments, the edge thinning portion covers the edge corner of the moving table ceramic component, and the distance between the edge thinning portion and the edge corner of the moving table ceramic component is ≥ 1 / 5 of the length of the shortest side at the corresponding edge corner.

[0010] In some embodiments, both the edge thinning portion and the groove portion are chamfered, and the chamfer radius of the groove portion is ≤30% of the groove portion depth, and the chamfer radius of the edge thinning portion is ≤20% of the edge thinning thickness.

[0011] In some embodiments, the simulated modal data includes low-order bending modal data and low-order torsional modal data; The experimental modal test of the moving table ceramic component includes taking the main body, the groove and the thinned portion of the moving table ceramic component as excitation positions respectively under the working modal test.

[0012] In some embodiments, the step of establishing a simulated digital model of the ceramic component of the motion platform includes: Based on finite element modeling, a simulation digital model of the ceramic component of the motion platform is established.

[0013] In some embodiments, obtaining the experimental modal data of the moving table ceramic component under the experimental modal test includes: The hammering method is used, and the vibration response is collected using an accelerometer; Extracting the experimental modal data based on frequency response function analysis; Analyze the vibration mechanism based on working deformation analysis to obtain the actual vibration shape.

[0014] In some embodiments, the modifying the simulated digital model of the ceramic component of the moving table includes: Simplifying the assumptions of the simulation digital model of the moving table ceramic component, wherein the assumptions include ignoring the porosity of the moving table ceramic component; and / or, The material parameters or boundary conditions of the simulation digital model of the ceramic component of the motion stage are adjusted, wherein the material parameters include elastic modulus and the boundary conditions include contact stiffness.

[0015] In some embodiments, the preset threshold is 10%.

[0016] Beneficial effects: By comparing the experimental modes of the ceramic parts of the motion table with the calculated modes, and through the closed-loop iteration of "virtual prediction-physical verification-model correction", the accuracy of the modal characteristic test of the ceramic parts is improved, and it is ensured that the modal characteristics of the ceramic parts meet the dynamic stability requirements of the lithography machine, the number of physical prototype trials is reduced, and the R&D cost is greatly reduced. The modal stability can be verified through accelerated life tests to ensure that the ceramic parts will not have resonance failure throughout the life cycle of the lithography machine.

[0017] Other features and corresponding beneficial effects of the present application are described in the latter part of the specification, and it should be understood that at least some of the beneficial effects become obvious from the description in the specification of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flowchart of this application; Figure 2 This is a schematic structural diagram of the ceramic component of the sports table of this application.

[0019] 1. Main body; 2. Groove; 3. Edge thinning. DETAILED DESCRIPTION

[0020] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0022] The ceramic part of the moving table of the edge thinning part 3 is a core component of the lithography machine that undertakes high-precision guidance and support. It has the characteristics of light weight, high rigidity and low thermal deformation, and its manufacturing cost is high.

[0023] At the same time, experimental modal testing is difficult to fully and truly simulate the complex constraints in actual working conditions (such as the elastic support of air bearings, the stiffness of multi-component connections) and multi-field coupling effects (such as thermal, mechanical, electrical, magnetic and other multi-field coupling effects), resulting in low accuracy of the modal characteristics obtained by the test.

[0024] The combination of these two factors results in extremely high R&D costs for ceramic parts of sports tables.

[0025] The embodiment of the present application provides a method for optimizing the structure of a moving table ceramic component based on dynamic benchmarking, which benchmarks the experimental mode of the moving table ceramic component with the calculated mode, and through the closed-loop iteration of "virtual prediction-physical verification-model correction", improves the accuracy of the modal characteristic test of the ceramic component, ensures that the modal characteristics of the ceramic component meet the dynamic stability requirements of the lithography machine, reduces the number of physical prototype trials, greatly reduces the R&D cost, and can verify the modal stability through accelerated life testing to ensure that the ceramic component has no resonance failure throughout the life cycle of the lithography machine.

[0026] See Figure 1 , Figure 1 This is a flowchart of the application.

[0027] This method includes: S1 establishes a simulation digital model of the ceramic parts of the motion table.

[0028] In one embodiment, a simulation digital model of the ceramic component of the motion table is established based on finite element modeling, such as ANSYS.

[0029] Modeling involves geometric features, material properties (elastic modulus, density, Poisson's ratio), and boundary conditions (fixed constraints or elastic supports).

[0030] S2 corrects the simulation digital model of the ceramic component of the motion table based on the comparison of the modal data of the experimental modal and the simulation calculated modal.

[0031] Specifically include: S21 obtains the simulated modal data of the ceramic components of the motion platform based on the simulated digital model of the ceramic components of the motion platform, that is, calculates the natural frequency, vibration mode and damping ratio.

[0032] In one embodiment, the simulated modal data includes low-order bending modal data and low-order torsional modal data, thereby improving the comprehensiveness, accuracy, and reliability of the simulated modal data.

[0033] S22 manufactures ceramic parts for the motion table based on the simulated digital model of the ceramic parts.

[0034] S23 obtains experimental modal data of the ceramic component of the motion table under the experimental modal test.

[0035] In one embodiment, a hammering method is used, and an acceleration sensor is used to collect the vibration response.

[0036] Furthermore, experimental modal data were extracted based on frequency response function (FRF) analysis.

[0037] Furthermore, the vibration mechanism is analyzed based on the operating deformation shapes (ODS) analysis to obtain the actual vibration shape.

[0038] In one embodiment, the experimental modal test of the moving table ceramic component includes using the main body 1, groove 2 and thinning portion of the moving table ceramic component as excitation positions under the working modal test, thereby improving the comprehensiveness, accuracy and reliability of the experimental modal data.

[0039] In other alternative embodiments, an exciter, preferably a bonded micro piezoelectric exciter, is used, and sinusoidal frequency sweep or burst random excitation is performed, and a scanning laser vibrometer is used to collect vibration responses.

[0040] S24 obtains the frequency errors of the simulated modal data and the experimental modal data based on the simulated modal data and the experimental modal data.

[0041] In S25 , if the frequency error is greater than the preset threshold, the simulation digital model of the ceramic component of the moving table is corrected, and S21 - S24 are repeated until the frequency error is less than or equal to the preset threshold.

[0042] In one embodiment, the preset threshold is 10%, which can balance cost and accuracy.

[0043] Preferably, the preset threshold is 5-6%, which further improves the accuracy and can improve the efficiency of structural optimization.

[0044] In one embodiment, correcting the simulation digital model of the ceramic component of the moving platform includes simplifying the assumptions of the simulation digital model of the ceramic component of the moving platform, such as ignoring the pores of the ceramic component of the moving platform.

[0045] In one embodiment, modifying the simulation digital model of the ceramic component of the moving platform includes adjusting material parameters or boundary conditions of the simulation digital model of the ceramic component of the moving platform, such as elastic modulus, contact stiffness, etc.

[0046] S3 performs structural optimization on the moving platform ceramic component based on key parameters that affect the modal state of the moving platform ceramic component, the modified modal data of the simulation digital model of the moving platform ceramic component, and the modal data of the corresponding experimental modal state.

[0047] Specifically include: S31 determines the key parameters that affect the modal behavior of the ceramic components of the motion platform based on sensitivity analysis.

[0048] This analysis can effectively focus on the core parameters of design optimization and reduce unnecessary computing costs.

[0049] In one embodiment, the key parameters are the size of the moving table ceramic component and the spacing between its parts, that is, the size and spacing of the main body portion 1 , the groove portion 2 and the edge thinning portion 3 .

[0050] S32 performs structural optimization on the moving table ceramic component corresponding to the simulated digital model of the moving table ceramic component that satisfies the frequency error ≤ a preset threshold based on key parameters, simulation modal data, and experimental modal data, and repeats S21-S23 until both the simulation modal data and the experimental modal data meet the design requirements.

[0051] In one embodiment, the structural optimization is performed on the simulated digital model of the ceramic component of the moving platform, including topological optimization or size optimization of the simulated digital model of the ceramic component of the moving platform.

[0052] See Figure 2 , Figure 2 This is a schematic structural diagram of the ceramic component of the sports table of this application.

[0053] The structural optimization direction of the moving table ceramic component is to set specially shaped thinning areas in the middle and edges, that is, the moving table ceramic component generally includes a main body 1, a groove 2 located in the middle of the main body 1, and an edge thinning portion 3 located at the edge of the main body 1.

[0054] In one embodiment, the order of structural optimization is the main body 1, groove portion 2, and edge thinning portion 3 of the moving platform ceramic component, that is, the main body 1 of the moving platform ceramic component has the largest volume and the thickest thickness, and its structural optimization space is the largest. The groove portion 2 is located in the middle of the main body 1 and has little effect on the mechanical properties of the moving platform ceramic component. The edge thinning portion 3 has a greater effect on the mechanical properties of the moving platform ceramic component, and the edge shape has high requirements on the manufacturing process, and the structural optimization space is the smallest.

[0055] By performing structural optimization in sequence, the efficiency of structural optimization can be improved, thereby reducing R&D costs.

[0056] In one embodiment, the edge thinning portion 3 covers the edge corner of the moving table ceramic component, and the edge thinning portion 3 is ≥1 / 5 of the length of the shortest side of the edge corner corresponding to the edge corner of the moving table ceramic component, thereby taking into account lightweight, stiffness and deformation on the basis of modal characteristic optimization.

[0057] In one embodiment, both the edge thinning portion 3 and the groove portion 2 are chamfered, and the chamfer radius of the groove portion 2 is ≤30% of the depth of the groove portion 2, and the chamfer radius of the edge thinning portion 3 is ≤20% of the edge thinning thickness.

[0058] This method can greatly reduce the number of physical prototype trials, from the usual 5 rounds to 2-3 rounds, thereby greatly reducing R&D costs.

[0059] Moreover, through the closed-loop optimization of "simulation-testing-correction", a synergistic effect of "1+1>2" is achieved. Specifically, modal testing provides a "real benchmark" to verify the design and discover problems, and simulation benchmarking provides "predictive capabilities" to optimize the design and predict performance. The collaboration of the two can achieve "rapid iteration and precise design" and significantly improve the efficiency of structural optimization design.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for optimizing the structure of a ceramic component of a moving table based on dynamics benchmarking, characterized in that: include: S1 establishes a simulation digital model of the ceramic parts of the motion table; S2 corrects the simulation digital model of the ceramic component of the moving table based on the comparison of the modal data of the experimental modal and the simulation calculated modal; S3 performs structural optimization on the moving platform ceramic component based on key parameters that affect the modal state of the moving platform ceramic component, the modified modal data of the simulation digital model of the moving platform ceramic component, and the modal data of the corresponding experimental modal state.

2. The method for optimizing the structure of a moving table ceramic component based on dynamics benchmarking according to claim 1, characterized in that: The S2 corrects the simulation digital model of the ceramic component of the moving table based on the comparison of the modal data of the experimental modal and the simulation calculated modal, including: S21: acquiring simulation modal data of the moving table ceramic component based on the simulation digital model of the moving table ceramic component; S22: manufacturing the moving table ceramic component based on the simulated digital model of the moving table ceramic component; S23: obtaining experimental modal data of the moving table ceramic component under experimental modal testing; S24: obtaining frequency errors of the simulated modal data and the experimental modal data based on the simulated modal data and the experimental modal data; S25: if the frequency error is greater than the preset threshold, then modify the simulation digital model of the moving table ceramic component and repeat S21-S24 until the frequency error is less than or equal to the preset threshold; and The step S3 performs structural optimization on the ceramic component of the moving platform based on key parameters that affect the modal state of the ceramic component of the moving platform, the modal data of the modified simulation digital model of the ceramic component of the moving platform, and the modal data of the corresponding experimental modal state, including: S31 Determine the key parameters that affect the modal behavior of the ceramic components of the motion table based on sensitivity analysis; S32 performs structural optimization on the moving table ceramic component corresponding to the simulated digital model of the moving table ceramic component that satisfies the frequency error ≤ the preset threshold based on the key parameters, the simulated modal data, and the experimental modal data, and repeats S21-S23 until the simulated modal data and the experimental modal data both meet the design requirements.

3. The method for optimizing the structure of a moving table ceramic component based on dynamics benchmarking according to claim 2, characterized in that: The simulated digital model of the moving table ceramic component is structurally optimized, including topological optimization or size optimization of the simulated digital model of the moving table ceramic component; and the moving table ceramic component includes a main body, a groove portion located in the middle of the main body, and an edge thinning portion located at the edge of the main body, and the structural optimization order is the main body of the moving table ceramic component, the groove portion, and the edge thinning portion.

4. The method for optimizing the structure of a moving table ceramic component based on dynamics benchmarking according to claim 3, characterized in that: The edge thinning portion covers the edge corner of the moving table ceramic component, and the distance between the edge thinning portion and the edge corner of the moving table ceramic component is greater than or equal to 1 / 5 of the length of the shortest side at the corresponding edge corner.

5. The method for optimizing the structure of a moving table ceramic component based on dynamics benchmarking according to claim 3, characterized in that: The edge thinning portion and the groove portion are both chamfered, and the radius of the chamfer of the groove portion is ≤30% of the depth of the groove portion, and the radius of the chamfer of the edge thinning portion is ≤20% of the edge thinning thickness.

6. The method for optimizing the structure of a moving table ceramic component based on dynamic benchmarking according to any one of claims 3 to 5, characterized in that: The simulation modal data includes low-order bending modal data and low-order torsional modal data; The experimental modal test of the moving table ceramic component includes taking the main body, the groove and the thinned portion of the moving table ceramic component as excitation positions respectively under the working modal test.

7. The method for optimizing the structure of a moving table ceramic component based on dynamics benchmarking according to claim 2, characterized in that: The method of establishing a simulation digital model of the ceramic component of the motion platform includes: Based on finite element modeling, a simulation digital model of the ceramic component of the motion platform is established.

8. The method for optimizing the structure of a moving table ceramic component based on dynamics benchmarking according to claim 2, wherein: The obtaining of experimental modal data of the moving table ceramic component under experimental modal testing includes: The hammering method is used, and the vibration response is collected using an accelerometer; Extracting the experimental modal data based on frequency response function analysis; Analyze the vibration mechanism based on working deformation analysis to obtain the actual vibration shape.

9. The method for optimizing the structure of a moving table ceramic component based on dynamics benchmarking according to claim 2, characterized in that: The method of modifying the simulation digital model of the ceramic component of the moving table includes: Simplifying the assumptions of the simulation digital model of the moving table ceramic component, wherein the assumptions include ignoring the porosity of the moving table ceramic component; and / or, The material parameters or boundary conditions of the simulation digital model of the ceramic component of the motion stage are adjusted, wherein the material parameters include elastic modulus and the boundary conditions include contact stiffness.

10. The method for optimizing the structure of a moving table ceramic component based on dynamics benchmarking according to claim 2, characterized in that: The preset threshold is 10%.

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