Intermediate frequency error suppression machining method based on trajectory planning and layered shaping

Abstract

The present invention belongs to the field of ultra-precision machining, and specifically discloses a method for suppressing intermediate frequency errors based on trajectory planning and layered shaping, including: constructing a tool influence function under the continuous linear feed state of the tool based on the Preston equation; analyzing the material removal function under trajectory stacking; constructing an online simulation program based on the material removal function in combination with different machining trajectories and layered shaping techniques; allocating the material properties of composite structure polishing tools according to machining requirements, preparing composite structure polishing tools through molds, and reducing tool edge effects. An experimental platform is built, and machining parameters are optimized in real time in combination with an online simulation program during the machining process. The present invention is used to suppress intermediate frequency errors caused by overly regular machining paths during machining, and suppresses intermediate frequency errors by superimposing different trajectories and changing relative positions.

Description

Technical Field

[0001] The present invention belongs to the field of ultra-precision machining, and in particular relates to a medium-frequency error suppression machining method based on trajectory planning and layered shaping. Background Art

[0002] Ultra-precision machining technology is a critical bottleneck in advanced equipment manufacturing, and nanometer precision is hailed as the "crown jewel" of ultra-precision machining technology. Ultra-precision machining of large-aperture optical components is a comprehensive application of new technological achievements from multiple disciplines, promoting the development of cutting-edge technologies in various fields, including civil and defense applications.

[0003] To ensure that laser devices achieve ideal laser beam quality and stable operation under high-throughput conditions, laser optical components are subject to stringent full-band precision control indicators, extreme low-defect control requirements, and high-efficiency, mass-produced, and engineered manufacturing goals. Currently, Computer Controlled Optical Surfacing (CCOS) is the primary method for high-precision and high-efficiency processing of aspheric optical components. At the same time, the intelligent polishing robot processing technology formed by the combination of industrial robots and CCOS has become an important development direction for optical component processing, enabling faster shaping capabilities (figuring), stronger mid-frequency error suppression and smoothing capabilities (smoothing), and higher surface quality (finishing).

[0004] CCOS technology is inevitably accompanied by machining trajectory design. To improve surface quality, the simplest approach is to increase trajectory density, but this significantly increases machining time and reduces efficiency. Furthermore, issues such as tool wear caused by excessive machining time are uncertainties in their impact on material removal. Therefore, trajectory planning is necessary to improve machining accuracy within a limited machining time. Preston showed that material removal is the result of the combined effects of force and velocity. The uneven distribution of material removal, resulting from the combined effects of the force and velocity fields, leads to complex and disordered trajectory planning. Currently, much research on trajectory planning focuses on improving uniform trajectory coverage, uniform coverage of contact areas, and uniform overlap of contact areas on curved surfaces, without considering the specific material removal, and thus failing to directly guarantee uniform material removal. Furthermore, the difficulty in rationally implementing trajectory planning and dwell time algorithms is a significant factor contributing to poor surface accuracy controllability, difficulty in effectively suppressing mid-frequency errors, and low surface quality.

[0005] Based on the above problems, the applicant proposed a medium frequency error suppression processing method based on trajectory planning and layered shaping. Summary of the Invention

[0006] In order to make up for the deficiencies of the prior art, the present invention provides a technical solution for a medium frequency error suppression processing method based on trajectory planning and layered shaping.

[0007] A medium-frequency error suppression machining method based on trajectory planning and layered shaping is disclosed. The machining method uses a composite structure center-feed liquid polishing tool with a central opening and four-way slots, and includes the following steps:

[0008] Step 1: Based on the Preston equation, the velocity distribution (Formula 2) and the dwell time (Formula 4) under continuous linear feed are combined to construct a material removal function, establish a three-dimensional material removal model (theoretical analysis model) under linear feed, and obtain a two-dimensional material removal profile image;

[0009] Step 2: Based on the established three-dimensional material removal model under the linear feed state, a material removal image is established when the tracks are superimposed, and the influence of the track spacing on the intermediate frequency error suppression effect is obtained;

[0010] Step 3: Based on the influence of track spacing on the intermediate frequency error suppression effect and combined with the two-dimensional material removal contour image, the optimal track spacing selection strategy for different processing tracks is obtained;

[0011] Step 4: A time-varying material removal model is constructed based on the material removal function described in step 1 and the influence of tool wear on the material removal function during long-term machining. A layered shaping method is used to perform reasonable trajectory planning based on a combination of machining parameters. The machining parameters include dwell time, single material removal depth, tool rotation speed, tool feed rate, downforce, tool material coefficient, and number of layers. Based on the relationship between the position of the layers and the influence of the trajectory type on the trajectory randomness, the optimal parameter combination for layered shaping is obtained to improve the mid-frequency error suppression effect.

[0012] Step 5: Build a test machining platform based on a centrally-fed liquid polishing tool for composite structures. Combined with the optimal trajectory spacing selection strategy obtained in Step 3 and the optimal parameter combination for layered modification obtained in Step 4, the time-varying material removal model is optimized based on the actual machining results under different machining trajectories and machining parameter combinations. An offline simulation system is designed, and this system is used to directly generate tool path files that can be recognized by the MOTOMAN robotic arm for machining.

[0013] Step 6: Detect the surface morphology of the workpiece, obtain the actual processing requirements, preliminarily formulate the processing parameters based on the time-varying material removal model, process the workpiece surface according to the processing parameters, detect the workpiece morphology in real time, adjust the processing parameters and processing trajectory according to the actual situation, and improve the surface processing quality of the optical component.

[0014] Furthermore, the material removal function in step 1 is:

[0015]

[0016] Where R is the distance between the selected point and the machining center, X, Y are the coordinate values of the selected point in the coordinate system of the entire machining area, β is the angle between the line connecting the selected point and the coordinate origin and the X-axis, θ is the angle value of each machining compared to the previous machining, n is the number of layered shaping layers, pl is the number of layers, H is the material removal depth, and H' is the final material removal depth.

[0017] Furthermore, the preparation method of the composite structure center liquid supply polishing tool includes:

[0018] S200, based on the actual processing effect required, liquid silicone rubber and silicon carbide abrasive grains are mixed, poured into a specific mold and solidified to form the processing layer of the composite structure center liquid supply polishing tool;

[0019] S201, changing the ratio of liquid silicone and silicon carbide abrasive grains, pouring the mixture into a mold and solidifying it to form a deformation layer of a composite structure center-feed liquid polishing tool with a smaller elastic modulus;

[0020] S202, bonding the processing layer, the deformation layer, and the rigid base to form a composite structure center-supply liquid polishing tool;

[0021] S203, opening a hole in the center of the liquid supply polishing tool at the center of the composite structure.

[0022] Furthermore, the offline simulation system of step 5 is designed by programming using the APPDESIGNER module in MATLAB. The offline simulation system predicts the material removal depth when the layered shaping method is used under different trajectories, facilitates previewing the processing effect, and facilitates selection of the appropriate processing method, which can reduce the number of actual processing and inspection times and save processing costs. At the same time, the program can directly generate a tool path file that can be recognized by the MOTOMAN robotic arm according to the processing parameters. There is no need to set up an additional tool path running program, and processing can be performed directly, thereby improving processing efficiency.

[0023] Furthermore, in step 6, a surface detection device is used to detect the surface of the inner processing workpiece in real time, and the relevant processing parameters are modified according to the actual situation in combination with the time-varying material removal model. If necessary, different processing trajectories and processing parameter combinations can be used between different layers to improve the medium-frequency error suppression effect.

[0024] Furthermore, the experimental processing platform constructed in step 5 includes a workbench, a workpiece clamping platform, a multi-degree-of-freedom robotic arm, an actuator and a composite structure central liquid supply polishing tool. The workpiece clamping platform is arranged on the workbench, which is used to clamp the workpiece. The multi-degree-of-freedom robotic arm is located on one side of the workbench, which is used to drive the actuator to move. The actuator is used to install the composite structure central liquid supply polishing tool and drive the composite structure central liquid supply polishing tool to work. The composite structure central liquid supply polishing tool is used to polish the workpiece.

[0025] Furthermore, the experimental processing platform also includes a pressure sensor, and the pressure sensor is configured as follows: the pressure sensor is installed in the workpiece clamping platform, and is used to detect the pressure value on the workpiece surface during the processing after the multi-degree-of-freedom robotic arm carries the composite structure center liquid supply polishing tool, and the pressure value is fed back to the multi-degree-of-freedom robotic arm in real time during the processing. The multi-degree-of-freedom robotic arm adjusts the downward pressure of the composite structure center liquid supply polishing tool according to the actual pressure value to ensure that the polishing pressure is constant during the entire processing process.

[0026] Furthermore, the layered shaping method in step 4 includes: carrying out reasonable trajectory planning, changing the tool dwell time, reasonably reducing the material removal depth during single removal, and effectively reducing the peak-to-valley value of the material removal profile; by stacking the material removal profiles with low peak-to-valley values to achieve a material removal depth equivalent to that of a single removal, the waviness of the material removal profile can be effectively improved without substantially sacrificing processing efficiency, thereby suppressing the mid-frequency error caused by the processing trajectory;

[0027] The trajectory planning in step 4 includes: reasonably controlling the trajectory spacing to suppress the waviness during single removal, so as to improve the intermediate frequency error suppression effect after layered shaping;

[0028] In step 4, the optimal parameter combination of layered shaping is obtained based on the influence of the inter-layer position relationship and the trajectory type on the trajectory randomness, and the improvement of the intermediate frequency error suppression effect specifically includes: improving the trajectory randomness by reasonably designing the variable combination of the inter-layer position relationship and the trajectory type, that is, selecting the disordered path method of the pseudo-random path during trajectory planning, combining the layered shaping method, and systematically rotating the trajectory relative to the processing area during each removal, changing the relative position relationship between layers, and further improving the intermediate frequency error suppression effect.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] During the CCOS machining process, when the introduced machining trajectory is too regular, regular scratches will often be left on the workpiece surface, resulting in the generation of intermediate frequency errors. Therefore, the present invention reasonably divides the machining depth of a single removal, and optimizes the uniformity of material removal during single-layer removal through trajectory planning. At the same time, the positional relationship between layers and the trajectory type are changed, and the direction disorder of the trajectory on the workpiece surface is improved by superimposing multiple machining processes, so as to achieve basically no loss of machining efficiency while suppressing the intermediate frequency error caused by the machining trajectory on the workpiece surface. At the same time, a material removal model under the continuous linear feed state of the tool is derived, and combined with the designed online simulation program, the machining effects under different machining parameters and trajectories are predicted, the number of inspections is reduced, the machining efficiency is improved, and the machining cost is saved, providing an important foundation for subsequent large-scale production and fine machining. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Flowchart of the present invention;

[0032] Figure 2 This is a schematic diagram of the experimental processing platform in the present invention in use;

[0033] Figure 3 This is a schematic diagram of tool processing in the linear feed state of the present invention;

[0034] Figure 4 Schematic diagram of the process of constructing a 3D material removal depth image of a grating track in the present invention;

[0035] Figure 5 Schematic diagram of the material removal profile at a cross section perpendicular to the track feed direction when the tool diameter is divisible by the track pitch in the present invention;

[0036] Figure 6 Schematic diagram of the material removal profile at a cross section perpendicular to the track feed direction when the tool diameter is not divisible by the track pitch in the present invention;

[0037] Figure 7 A schematic diagram of calculating the material removal depth when applying layered shaping in the present invention;

[0038] Figure 8 Schematic diagram of the layered shaping principle and process in the present invention

[0039] Figure 9 This is a schematic diagram of the structure of the composite structure center liquid supply polishing tool in the present invention;

[0040] Figure 10 This is a schematic diagram of the MATLAB interface and result prediction in the present invention.

[0041] In the figure: 100-multi-degree-of-freedom robotic arm, 200-actuator, 300-composite structure polishing tool, 3001-central liquid supply hole, 3002-flow channel, 301-machining layer, 302-deformation layer, 303-rigid base, 400-workpiece clamping platform, 500-workbench. DETAILED DESCRIPTION

[0042] The present invention will be further described below with reference to the accompanying drawings.

[0043] See also Figures 1-10 A method for suppressing intermediate frequency errors based on trajectory planning and layered shaping is disclosed. The polishing tool used in this method is a composite structure center-feed liquid polishing tool with a central opening and four-way slots. The present invention addresses the intermediate frequency errors caused by overly regular trajectory stacking in CCOS processing technology. Through reasonable trajectory planning and layered shaping methods, different processing paths are selected during trajectory planning at different processing stages. Combined with layered shaping technology, different combination parameters such as the number of layers, inter-layer positions, and trajectory spacing are selected to achieve the effect of improving trajectory disorder, reducing the intermediate frequency error on the workpiece surface, and improving the processing quality of the optical component surface. The method comprises the following steps:

[0044] Step 1: Based on the Preston equation, combined with the velocity distribution (velocity distribution is reflected in Formula 2) and the dwell time (dwell time is reflected in Formula 4) under the continuous linear feed state, a material removal function is constructed, a three-dimensional material removal model during linear feed is established, and a two-dimensional material removal profile image is obtained.

[0045] The material removal function is:

[0046]

[0047] Where R is the distance between the selected point and the machining center, X, Y are the coordinate values of the selected point in the coordinate system of the entire machining area, β is the angle between the line connecting the selected point and the coordinate origin and the X-axis, θ is the angle value of each machining compared to the previous machining, n is the number of layered shaping layers, pl is the number of layers, H is the material removal depth, and H' is the final material removal depth.

[0048] The construction process of the above material removal function includes:

[0049] like Figure 3 As shown in the figure, under the linear feed state of the tool, according to the Preston formula, the material removal function is obtained:

[0050] dh=K p pvdt (1)

[0051] Where dt is the dwell time of the polishing tool at a point, dh is the material removal depth per unit time dt, K p is the Preston coefficient, p is the pressure on the workpiece during machining, and v is the linear velocity of the tool through the contact point when it rotates. During movement, dt can be converted into the following formula:

[0052]

[0053] Among them, v f is the tool feed speed, dy is the distance the workpiece moves per unit time dt, and substituting (2) into (1) yields:

[0054]

[0055] Assuming the workpiece radius is a, in static compression, the polishing tool is controlled to apply a pre-polishing force F to the workpiece surface. Under the action of F, the polishing pad completely contacts the target surface. The resulting contact radius is considered to be consistent with the radius of the fixed polishing pad. The pressure generated at each point in the contact area is evenly distributed. Assuming the radius of the central liquid supply hole is r1 and the width of the flow channel is s, the value of each point in the contact area is:

[0056]

[0057] Where a is the tool radius, r1 is the radius of the central fluid supply hole, and s is the width of the flow channel. Calculation of the mean circumferential stress: The machining layer of the composite structure central fluid supply polishing tool with a flow channel is equivalent to a mean solid disk. The actual contact area ratio k is:

[0058]

[0059] The actual average pressure is:

[0060]

[0061] After integrating formula (3) in the xy region, it can be transformed into:

[0062]

[0063] Where b is the starting position of the tool when it passes a point on the workpiece, and c is the end position of the tool when it passes a point on the workpiece. The processing speed v can be converted by the following formula:

[0064]

[0065] Where ω is the angular velocity of the tool. The removal depth formula is:

[0066]

[0067] like Figure 4 As shown in the figure, in the actual machining process, the actual removal depth of a point on the workpiece is obtained by superimposing multiple trajectories. In the trajectory superposition direction, the actual removal depth of a point (x, y) on the workpiece varies under different trajectory spacings. Assume that the length range of the machining area is [-L, L] and the width is [-U, U]. There are M trajectories stacked in the Y-axis direction. The superposition depth in the X-axis direction is H1, and the superposition depth in the Y-axis direction is H2.

[0068] For the stacking depth H1 in the x-axis direction, the following relationship exists:

[0069]

[0070]

[0071] For the stacking depth H2 in the y-axis direction, Figure 5 As shown, when the tool diameter is divisible by the track pitch, the following relationship exists:

[0072]

[0073]

[0074]

[0075] like Figure 6 As shown in Figure 2, when the tool diameter cannot be divided by the track spacing, then:

[0076]

[0077]

[0078]

[0079]

[0080] According to equations (10) to (18), the material removal depth H in the machining area during a single machining operation can be obtained as follows:

[0081] H(X,Y)=H1(X,Y)+H2(X,Y) (19)

[0082] like Figure 7 As shown in the figure, after the introduction of layered shaping, let pl be the number of layers, θ be the angle of each trajectory rotation, and β be the angle between the line connecting the point (x, y) and the origin and the X-axis. If the trajectory rotates clockwise, the final material removal depth H' can be expressed as:

[0083]

[0084] Step 2: Based on the established three-dimensional material removal model under the linear feed state, a material removal image is established when the trajectories are superimposed, and the influence of the trajectory spacing on the intermediate frequency error suppression effect is obtained.

[0085] Step 3: According to the influence of track spacing on the intermediate frequency error suppression effect and combined with the two-dimensional material removal contour image, the optimal track spacing selection strategy for different processing tracks is obtained.

[0086] In step 4, a time-varying material removal model is constructed by combining the material removal function described in step 1 and the influence of tool wear on the material removal function during long-term processing. In combination with the layered shaping method, reasonable trajectory planning is performed according to the combination scheme of processing parameters. The processing parameters include dwell time, single material removal depth, tool rotation speed, tool feed speed, down force, tool material coefficient and number of layers. Based on the influence of variables such as the inter-layer position relationship and trajectory type on the trajectory randomness, the optimal parameter combination of layered shaping is obtained to improve the mid-frequency error suppression effect.

[0087] In step 5, an experimental processing platform based on the composite structure center liquid supply polishing tool is built. The optimal trajectory spacing selection strategy obtained in step 3 and the optimal parameter combination of layered modification obtained in step 4 are combined. Based on the actual processing effects under different processing trajectories and processing parameter combinations, the theoretical analysis model is compared to optimize the three-dimensional material removal model.

[0088] Among them, such as Figure 2 As shown, the experimental processing platform includes a workbench 500, a workpiece clamping platform 400, a multi-degree-of-freedom robot arm 100, an actuator 200 and a composite structure central liquid supply polishing tool 300. The workpiece clamping platform 400 is arranged on the workbench 500, which is used to clamp the workpiece. The multi-degree-of-freedom robot arm 100 is located on one side of the workbench 500, which is used to drive the actuator 200 to move. The actuator 200 is used to install the composite structure central liquid supply polishing tool 300 and drive the composite structure central liquid supply polishing tool 300 to work. The composite structure central liquid supply polishing tool 300 is used to polish the workpiece.

[0089] Among them, the experimental processing platform also includes a pressure sensor, and the pressure sensor is configured as follows: the pressure sensor is installed in the workpiece clamping platform 400, and is used to detect the pressure value on the workpiece surface during the processing after the multi-degree-of-freedom robotic arm carries the composite structure center liquid supply polishing tool, and the pressure value is fed back to the multi-degree-of-freedom robotic arm in real time during the processing. The multi-degree-of-freedom robotic arm adjusts the downward pressure of the composite structure center liquid supply polishing tool according to the actual pressure value to ensure that the polishing pressure is constant during the entire processing process.

[0090] Step 6: Detect the surface morphology of the workpiece, obtain the actual processing requirements, preliminarily formulate the processing parameters based on the time-varying material removal model, process the workpiece surface according to the processing parameters, detect the workpiece morphology in real time, adjust the processing parameters and processing trajectory according to the actual situation, and improve the surface processing quality of the optical component.

[0091] Among them, surface detection equipment is used to detect the surface of the internally processed workpiece in real time, and relevant processing parameters are modified according to actual conditions. If necessary, different processing trajectories and processing parameter combinations can be used between different layers to improve the intermediate frequency error suppression effect.

[0092] Based on the invention, the material removal rules and surface roughness evolution mechanism can be systematically studied to form key processing technology solutions to achieve the ultra-precision processing goals of high precision, high quality and high efficiency of optical components.

[0093] The structure of the composite structure center liquid supply polishing tool is as follows Figure 9 As shown, the preparation method includes:

[0094] S200, according to the actual required processing effect, liquid silicone and silicon carbide abrasive grains are mixed in a specific ratio, poured into a specific mold and solidified to form the processing layer 301 of the composite structure center liquid supply polishing tool.

[0095] S201, changing the ratio of liquid silicone and silicon carbide abrasive grains, pouring the mixture into a mold and solidifying it to form a deformation layer 302 of a composite structure center-feed liquid polishing tool with a smaller elastic modulus.

[0096] S202, bonding the processing layer 301, the deformation layer 302, and the rigid base 303 to form a composite structure center-supply liquid polishing tool.

[0097] S203, opening a hole in the center of the liquid supply polishing tool at the center of the composite structure.

[0098] During polishing, the polishing fluid is injected into the machining surface from the center of the tool, and the centrifugal force evenly disperses the polishing fluid to the contact area between the tool and the workpiece.

[0099] like Figure 10 As shown in the figure, the APPDESIGNER module in MATLAB is used to write a program and design an online simulation system to predict the material removal depth when the layered shaping method is used under different trajectories. This makes it convenient to preview the processing effect, select the appropriate processing method, reduce the actual processing and inspection times, and save processing costs. At the same time, the program can directly generate a tool path file that can be recognized by the MOTOMAN robot arm according to the processing parameters. There is no need to set up an additional tool path running program, and processing can be carried out directly, thereby improving processing efficiency.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A mid-frequency error suppression processing method based on trajectory planning and layered shaping, characterized in that: The polishing tool used in this processing method is a composite structure center-feed liquid polishing tool based on a central opening and four-way slots, which includes the following steps: Step 1: Based on the Preston equation, combined with the velocity distribution and dwell time under continuous linear feed, a material removal function is constructed to establish a three-dimensional material removal model during linear feed and obtain a two-dimensional material removal profile image, where the material removal function is: （22） Where R is the distance between the selected point and the machining center, X and Y are the coordinate values of the selected point in the coordinate system of the entire machining area, β is the angle between the line connecting the selected point and the coordinate origin and the X-axis, θ is the angle value of each machining compared to the previous machining, n is the number of layered shaping layers, pl is the number of layers, H is the material removal depth, and H' is the final material removal depth; Step 2: Based on the established three-dimensional material removal model under the linear feed state, a material removal image is established when the tracks are superimposed, and the influence of the track spacing on the intermediate frequency error suppression effect is obtained; Step 3: Based on the influence of track spacing on the intermediate frequency error suppression effect and combined with the two-dimensional material removal contour image, the optimal track spacing selection strategy for different processing tracks is obtained; Step 4: A time-varying material removal model is constructed based on the material removal function described in step 1 and the influence of tool wear on the material removal function during long-term machining. A layered shaping method is used to perform reasonable trajectory planning based on a combination of machining parameters. The machining parameters include dwell time, single material removal depth, tool rotation speed, tool feed rate, downforce, tool material coefficient, and number of layers. Based on the relationship between the position of the layers and the influence of the trajectory type on the trajectory randomness, the optimal parameter combination for layered shaping is obtained to improve the mid-frequency error suppression effect. Step 5: Build a test machining platform based on a centrally-fed liquid polishing tool for composite structures. Combined with the optimal trajectory spacing selection strategy obtained in Step 3 and the optimal parameter combination for layered modification obtained in Step 4, the time-varying material removal model is optimized based on the actual machining results under different machining trajectories and machining parameter combinations. An offline simulation system is designed, and this system is used to directly generate tool path files that can be recognized by the MOTOMAN robotic arm for machining. The preparation method of the composite structure center liquid supply polishing tool includes: S200, based on the actual processing effect required, liquid silicone rubber and silicon carbide abrasive grains are mixed, poured into a specific mold and solidified to form the processing layer of the composite structure center liquid supply polishing tool; S201, changing the ratio of liquid silicone and silicon carbide abrasive grains, pouring the mixture into a mold and solidifying it to form a deformation layer of a composite structure center-feed liquid polishing tool with a smaller elastic modulus; S202, bonding the processing layer, the deformation layer, and the rigid base to form a composite structure center-supply liquid polishing tool; S203, opening a hole in the center of the liquid polishing tool at the center of the composite structure; Step 6: Detect the surface morphology of the workpiece, obtain the actual processing requirements, preliminarily formulate the processing parameters based on the time-varying material removal model, process the workpiece surface according to the processing parameters, detect the workpiece morphology in real time, adjust the processing parameters and processing trajectory according to the actual situation, and improve the surface processing quality of the optical component.

2. The intermediate frequency error suppression processing method based on trajectory planning and layered shaping according to claim 1 is characterized in that: The offline simulation system of step 5 is designed by programming using the APP DESIGNER module in MATLAB. The offline simulation system predicts the material removal depth when the layered shaping method is used under different trajectories, facilitates previewing the processing effect, and facilitates selection of the appropriate processing method. It can reduce the number of actual processing and inspection times and save processing costs. At the same time, the program can directly generate a tool path file that can be recognized by the MOTOMAN robotic arm according to the processing parameters. There is no need to set up an additional tool path operation program, and processing can be performed directly, thereby improving processing efficiency.

3. The intermediate frequency error suppression processing method based on trajectory planning and layered shaping according to claim 1 is characterized in that: In step 6, a surface detection device is used to detect the surface of the inner processing workpiece in real time, and relevant processing parameters are modified according to actual conditions. If necessary, different processing trajectories and processing parameter combinations can be used between different layers to improve the intermediate frequency error suppression effect.

4. The intermediate frequency error suppression processing method based on trajectory planning and layered shaping according to claim 1 is characterized in that: The experimental processing platform constructed in step 5 includes a workbench, a workpiece clamping platform, a multi-degree-of-freedom robotic arm, an actuator and a composite structure central liquid supply polishing tool. The workpiece clamping platform is arranged on the workbench, which is used to clamp the workpiece. The multi-degree-of-freedom robotic arm is located on one side of the workbench, which is used to drive the actuator to move. The actuator is used to install the composite structure central liquid supply polishing tool and drive the composite structure central liquid supply polishing tool to work. The composite structure central liquid supply polishing tool is used to polish the workpiece.

5. The intermediate frequency error suppression processing method based on trajectory planning and layered shaping according to claim 4 is characterized in that: The experimental processing platform also includes a pressure sensor, which is configured as follows: the pressure sensor is installed in the workpiece clamping platform, and is used to detect the pressure value on the workpiece surface during the processing after the multi-degree-of-freedom robotic arm carries the composite structure center liquid supply polishing tool, and feeds back the pressure value to the multi-degree-of-freedom robotic arm in real time during the processing. The multi-degree-of-freedom robotic arm adjusts the downward pressure of the composite structure center liquid supply polishing tool according to the actual pressure value to ensure that the polishing pressure is constant during the entire processing process.

6. The intermediate frequency error suppression processing method based on trajectory planning and layered shaping according to claim 1 is characterized in that: The layered shaping method in step 4 includes: carrying out reasonable trajectory planning, changing the tool dwell time, reasonably reducing the material removal depth during single removal, and effectively reducing the peak-to-valley value of the material removal profile; by stacking the material removal profiles with low peak-to-valley values to achieve a material removal depth equivalent to that of a single removal, the waviness of the material removal profile can be effectively improved without sacrificing processing efficiency, thereby suppressing the mid-frequency error caused by the processing trajectory; The trajectory planning in step 4 includes: reasonably controlling the trajectory spacing to suppress the waviness during single removal, so as to improve the intermediate frequency error suppression effect after layered shaping; In step 4, the optimal parameter combination of layered shaping is obtained based on the influence of the inter-layer position relationship and the trajectory type on the trajectory randomness, and the improvement of the intermediate frequency error suppression effect specifically includes: improving the trajectory randomness by reasonably designing the variable combination of the inter-layer position relationship and the trajectory type, that is, selecting the disordered path method of the pseudo-random path during trajectory planning, combining the layered shaping method, and systematically rotating the trajectory relative to the processing area during each removal, changing the relative position relationship between layers, and further improving the intermediate frequency error suppression effect.

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