A CNC cutting control method and system for an integrated lens barrel

Abstract

The application relates to the technical field of control, and discloses a CNC cutting control method and system for an integrated lens barrel, which comprises the following steps: fixing a tool by using a profilometer and performing three-dimensional calibration on the tool; determining whether the tool is polished to determine a cutting tool; determining a cutting predicted rotating speed according to a material property and a rotating speed prediction model of a to-be-cut lens barrel; and determining a rotating speed control strategy of the cutting predicted rotating speed according to a cutting friction coefficient. When the cutting friction coefficient is greater than a cutting friction coefficient threshold value, a cutting environment influence chain is constructed based on a cutting area; when no historical rotating speed control factor consistent with a rotating speed control factor exists in historical data, a rotating speed control set is determined based on the historical data; and a target rotating speed control factor is determined according to the rotating speed control factor and a rotating speed adjustment coefficient. The application has good dynamic control, and ensures the machining quality and stability of the integrated lens barrel.

Description

Technical Field

[0001] This invention relates to the field of control technology, and more specifically, to a CNC cutting control method and system for an integrated lens barrel. Background Technology

[0002] The lens barrel, also known as a vehicle-mounted lens barrel, is a specially made metal or plastic cylinder that holds the lens elements in place. The length of the lens barrel varies depending on the lens focal length, and its diameter matches the lens aperture. Currently, with traditional CNC (Computerized Numerical Control) machining of lens barrels, the cutting tools gradually wear down over time, making dynamic adjustments impossible. Furthermore, CNC machine tools mostly use pre-set fixed cutting speeds during machining, lacking corresponding control strategies and feedback mechanisms, leading to unstable cutting and even tool damage and workpiece scrap. This makes it difficult to guarantee the machining quality and stability of the integrated lens barrel.

[0003] Therefore, it is necessary to design a CNC cutting control method and system for integrated lens barrels to solve the problems existing in the current technology. Summary of the Invention

[0004] In view of this, the present invention proposes a CNC cutting control method and system for integrated lens barrels, which aims to solve the problems that the cutting tool will gradually wear down with the increase of the usage time, cannot be dynamically adjusted according to the actual situation, cannot make corresponding control strategies, lack of feedback mechanism leading to unstable cutting, and making it difficult to guarantee the machining quality and stability of integrated lens barrels.

[0005] In one aspect, the present invention proposes a CNC cutting control method for an integrated lens barrel, comprising:

[0006] The tool is fixed using a profilometer and 3D calibrated. The flatness of the tool is determined based on the 3D calibration. The flatness is then compared with the cutting flatness to determine whether the tool needs to be ground to determine the cutting tool.

[0007] The predicted cutting speed is determined based on the material properties of the lens barrel to be cut and the speed prediction model. The cutting friction coefficients of the lens barrel to be cut and the cutting tool are obtained. The speed control strategy of the predicted cutting speed is determined based on the cutting friction coefficients.

[0008] When the cutting friction coefficient is greater than the cutting friction coefficient threshold, the cutting area is determined according to the CNC cutting environment, a cutting environment influence chain is constructed based on the cutting area, the speed control factor is determined according to the cutting environment influence chain, and the speed control factor is compared with historical data. The target speed control factor is determined based on the comparison result.

[0009] When there is no historical speed control factor in the historical data that matches the speed control factor, a speed control set is determined based on the historical data, a speed adjustment coefficient of the speed control factor is determined based on the speed control set, and the target speed control factor is determined based on the speed control factor and the speed adjustment coefficient.

[0010] Furthermore, when using a profilometer to fix the tool and perform three-dimensional calibration on the tool, and determining the flatness of the tool based on the three-dimensional calibration, the process includes:

[0011] Obtain the position where the center of the cutting tool coincides with the axis of the profilometer, and fix the cutting tool according to the position of coincidence;

[0012] The scanning mode of the profilometer is determined based on the tool properties of the tool.

[0013] Based on the scanning mode, point cloud data is collected layer by layer at different focal depths and noise is reduced to construct point cloud data. A triangular mesh is constructed based on the point cloud data, and a fitting plane is determined based on the triangular mesh.

[0014] Determine the vertical distance from each point of the triangular mesh to the fitted plane, and use the difference between the maximum and minimum vertical distances as the flatness.

[0015] Furthermore, when comparing the flatness and the cutting flatness to determine whether the cutting tool needs to be ground, the following steps are included:

[0016] When the flatness is less than the cutting flatness, the tool is reselected and the flatness of the reselected tool is determined until the cutting flatness is achieved.

[0017] When the flatness is equal to the cutting flatness, the tool is not ground and is identified as the cutting tool.

[0018] When the flatness is greater than the cutting flatness, the tool is ground and the grinding flatness of the grinding tool is obtained. If the grinding flatness is equal to the cutting flatness, the grinding tool is determined as the cutting tool; otherwise, a new tool is selected.

[0019] Furthermore, when determining the speed control strategy for the predicted cutting speed based on the cutting friction coefficient, it includes:

[0020] When the cutting friction coefficient is less than the cutting friction coefficient threshold, the spindle speed parameter is modified in the CNC system to control the predicted cutting speed.

[0021] When the cutting friction coefficient is equal to the cutting friction coefficient threshold, the mirror barrel to be cut is cut according to the predicted cutting speed and the cutting tool.

[0022] When the cutting friction coefficient is greater than the cutting friction coefficient threshold, the cutting area is determined according to the CNC cutting environment, a cutting environment influence chain is constructed based on the cutting area, a speed control factor is determined according to the cutting environment influence chain, and a target speed control factor is determined according to the speed control factor.

[0023] Furthermore, when determining the cutting area based on the CNC cutting environment and constructing the cutting environment influence chain based on the cutting area, the process includes:

[0024] Extending outwards from the geometric center of the CNC, a cylindrical space with radius r and height matching the highest point d of the CNC is formed, and the cylindrical space is evenly divided into several cutting areas;

[0025] Obtain environmental data for several cutting regions and construct the cutting environment influence chain.

[0026] Furthermore, when determining the speed control factor based on the cutting environment influence chain, and determining the target speed control factor based on the speed control factor, the process includes:

[0027] Determine the environmental data chain corresponding to the cutting environment influence chain based on the cutting environment influence chain;

[0028] The speed control factor is determined based on the environmental data in the environmental impact chain and the data in the environmental data chain;

[0029] When a historical speed control factor that matches the speed control factor exists in the historical data, the speed control factor is determined as the target speed control factor.

[0030] When there is no historical speed control factor in the historical data that matches the speed control factor, a speed control set is determined based on the historical data, and the target speed control factor is determined based on the speed control set.

[0031] Furthermore, when determining the speed control set based on the historical data, and determining the target speed control factor based on the speed control set, the process includes:

[0032] The historical speed control factors that are greater than the speed control factor in the historical data are assigned to the first speed control set;

[0033] The historical speed control factors that are smaller than the speed control factor in the historical data are assigned to the second speed control set;

[0034] All historical speed control factors in the first speed control set are converted into first control coordinate points, and all historical speed control factors in the second speed control set are converted into second control coordinate points;

[0035] The first control coordinate system and the second control coordinate system are determined based on the first control coordinate point and the second control coordinate point, respectively.

[0036] Furthermore, when determining the speed control set based on the historical data and determining the target speed control factor based on the speed control set, the method further includes:

[0037] The first control curve is determined by fitting all the first control coordinate points, and the second control curve is determined by fitting all the second control coordinate points.

[0038] Remove the first and second control coordinate points that were not fitted, and use the first control coordinate points on the first control fitting curve and the second control coordinate points on the second control fitting curve as speed control points.

[0039] The speed adjustment coefficient of the speed control factor is determined based on the speed control point, and the target speed control factor is determined based on the speed control factor and the speed adjustment coefficient.

[0040] Furthermore, when determining the speed adjustment coefficient of the speed control factor based on the speed control point, and determining the target speed control factor according to the speed control factor and the speed adjustment coefficient, the process includes:

[0041] Obtain the slope of all speed control points and determine the speed adjustment coefficient based on the slope;

[0042] The target speed control factor is the product of the speed adjustment coefficient and the speed control factor, and the target speed control factor is positively correlated with the predicted cutting speed.

[0043] Compared with existing technologies, the advantages of this invention are as follows: It utilizes a profilometer for three-dimensional tool calibration, accurately determining whether the tool needs grinding by comparing tool flatness with cutting flatness, ensuring the tool is in good working condition. This avoids insufficient precision due to tool wear, ensuring the reliability and stability of CNC control, and guaranteeing the machining accuracy and quality of the lens barrel. The predicted cutting speed is determined based on the material properties of the lens barrel to be cut and the speed prediction model, and the speed control strategy is determined in conjunction with the cutting friction coefficient. Compared with traditional fixed-parameter cutting, it can better adapt to the cutting requirements of lens barrels made of different materials. By determining the cutting area and constructing an environmental influence chain, a speed control factor is derived. Comparing this with historical data determines the degree of matching. If there is no corresponding historical speed control factor, a speed control set is determined based on the historical data to determine the speed adjustment coefficient, thereby determining the target speed control factor. This constructs a complete feedback mechanism, realizing a dynamic response to changes in the cutting environment, enabling the CNC to flexibly adjust the predicted cutting speed according to environmental conditions, improving the reliability and stability of control.

[0044] On the other hand, this application also provides a CNC cutting control system for an integrated lens barrel, applied to the aforementioned CNC cutting control method for an integrated lens barrel, comprising:

[0045] The data processing module is configured to use a profilometer to fix the tool and perform three-dimensional calibration on the tool, determine the flatness of the tool based on the three-dimensional calibration, compare the flatness with the cutting flatness, and determine whether to grind the tool to determine the cutting tool.

[0046] The speed control module is configured to determine the predicted cutting speed based on the material properties of the lens barrel to be cut and the speed prediction model, obtain the cutting friction coefficient between the lens barrel to be cut and the cutting tool, and determine the speed control strategy of the predicted cutting speed based on the cutting friction coefficient.

[0047] The first adjustment module is configured to determine the cutting area based on the CNC cutting environment when the cutting friction coefficient is greater than the cutting friction coefficient threshold, construct a cutting environment influence chain based on the cutting area, determine the speed control factor based on the cutting environment influence chain, compare the speed control factor with historical data, and determine the target speed control factor based on the comparison result.

[0048] The second adjustment module is configured to, when there is no historical speed control factor in the historical data that matches the speed control factor, determine a speed control set based on the historical data, determine the speed adjustment coefficient of the speed control factor based on the speed control set, and determine the target speed control factor based on the speed control factor and the speed adjustment coefficient.

[0049] It is understandable that the aforementioned CNC cutting control method and system for integrated lens barrels have the same beneficial effects, and will not be elaborated further here. Attached Figure Description

[0050] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0051] Figure 1 A flowchart of a CNC cutting control method for an integrated lens barrel provided in an embodiment of the present invention;

[0052] Figure 2 This is a functional block diagram of a CNC cutting control system for an integrated lens barrel, provided as an embodiment of the present invention. Detailed Implementation

[0053] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0054] See Figure 1 As shown in some embodiments of this application, a CNC cutting control method for an integrated lens barrel includes:

[0055] S100: The tool is fixed and calibrated in three dimensions using a profilometer. The flatness of the tool is determined based on the three-dimensional calibration, and the flatness is compared with the cutting flatness to determine whether the tool needs to be ground and to determine the cutting tool.

[0056] S200: Determine the predicted cutting speed based on the material properties of the lens barrel to be cut and the speed prediction model, obtain the cutting friction coefficients of the lens barrel to be cut and the cutting tool, and determine the speed control strategy based on the cutting friction coefficients.

[0057] S300: When the cutting friction coefficient is greater than the cutting friction coefficient threshold, the cutting area is determined according to the CNC cutting environment, the cutting environment influence chain is constructed based on the cutting area, the speed control factor is determined according to the cutting environment influence chain, and the speed control factor is compared with historical data. The target speed control factor is determined based on the comparison result.

[0058] S400: When there is no historical speed control factor that matches the speed control factor in the historical data, determine the speed control set based on the historical data, determine the speed adjustment coefficient of the speed control factor based on the speed control set, and determine the target speed control factor based on the speed control factor and the speed adjustment coefficient.

[0059] Specifically, the tool is first calibrated in three dimensions using a profilometer. A three-dimensional profilometer is selected to scan the tool from all angles, thereby determining its flatness. The flatness of the tool directly affects the accuracy of subsequent cutting. Therefore, the flatness is compared with the cutting flatness, which is determined based on the process parameters of the lens barrel to be cut. This comparison helps determine whether the tool needs to be ground, ensuring the actual working condition of the cutting tool. Timely grinding can restore the cutting performance of the tool. By ensuring the condition of the cutting tool, the accuracy of CNC cutting of the lens barrel can be improved, errors caused by tool wear can be reduced, the machining quality of the one-piece lens barrel can be improved, and the scrap rate can be reduced. The predicted cutting speed is determined based on the material properties of the lens barrel to be machined and a speed prediction model. The material properties represent the material used in the lens barrel, such as iron, aluminum, and alloys. The speed prediction model is obtained from a machine learning model (convolutional neural network model). By training the machine learning model with data such as various material properties, feed rate, and depth of cut as training sets, a speed prediction model can be obtained and the predicted cutting speed can be output based on the material properties. However, different materials of the lens barrel to be machined and the cutting tool have different coefficients of cutting friction during cutting. The coefficient of cutting friction reflects the friction between the cutting tool and the lens barrel to be machined. If the predicted cutting speed does not consider the coefficient of cutting friction, it will cause the predicted cutting speed to increase or decrease abnormally. For example, if the coefficient of cutting friction is too small, it indicates that the cutting tool and the lens barrel to be machined are relatively smooth. When the cutting tool is controlled by the predicted cutting speed, there will be situations such as idling, resulting in an abnormal increase in the predicted cutting speed, which will affect the accuracy of the one-piece lens barrel. Therefore, the speed control strategy of determining the predicted cutting speed based on the coefficient of cutting friction can be adjusted accordingly according to the actual situation, ensuring machining quality and stability.

[0060] It is understandable that reducing the predicted cutting speed by lowering motor parameters during CNC control is an adjustment within the existing control range and generally does not exceed the stable operating range of the CNC. However, when increasing the predicted cutting speed to address excessive cutting friction, the ambient temperature and humidity will have a certain impact on the predicted cutting speed. By analyzing the cutting area and constructing a cutting environment influence chain, the degree of influence of each factor on the predicted cutting speed can be clarified, thereby determining the speed control factor. Comparing this factor with historical data and determining the target speed control factor based on the matching of the speed control factor with historical data improves the accuracy and stability of control. If no matching is found, a speed control set is determined based on historical data, and the target speed control factor is determined based on the speed control factor and speed adjustment coefficient. Drawing on historical experience and combining it with the current actual environment provides a basis for controlling the predicted cutting speed, enabling dynamic adjustments according to different actual conditions. This enhances the adaptability and feedback capability of CNC control, ensures the quality and stability of integrated lens barrel machining, and reduces tool damage and workpiece scrap.

[0061] In some embodiments of this application, when using a profilometer to fix the tool and perform three-dimensional calibration on the tool, and determining the flatness of the tool based on the three-dimensional calibration, the process includes: obtaining the position where the center of the tool coincides with the axis of the profilometer; fixing the tool based on the coincident position; determining the scanning mode of the profilometer based on the tool properties; collecting and denoising point cloud data layer by layer at different depths of focus based on the scanning mode to construct point cloud data; constructing a triangular mesh based on the point cloud data; determining a fitting plane based on the triangular mesh; determining the vertical distance from each point of the triangular mesh to the fitting plane; and using the difference between the maximum and minimum vertical distances as the flatness.

[0062] Specifically, obtaining the alignment of the tool's center with the profilometer's axis and fixing the tool accordingly ensures its stability during scanning. Determining the profilometer's scanning mode based on the tool's properties takes into account the material differences of various tools. Different tool properties require different scanning methods to obtain accurate surface information. For example, tools include carbide tools, ceramic tools, coated tools, and steel tools. The confocal-interference composite mode is suitable for tools with low surface roughness and high precision requirements, such as carbide and ceramic tools. The white light interferometry mode is suitable for tools with complex surface structures or special color requirements, such as coated tools. For coated tools, it can clearly distinguish the interface between the coating and the substrate, as well as the coating's thickness and uniformity. Simultaneously, the white light interferometry's sensitivity to color helps detect color changes on the coating surface, thus judging the tool's surface quality. The laser scanning mode is used to measure metal tools, especially steel tools. Laser scanning effectively reflects laser light, resulting in clear measurement images. Furthermore, the laser scanning mode can accurately detect defects such as scratches and wear on the tool surface, making it suitable for quality inspection of metal tools. Targeted settings can fully utilize the profilometer's performance, allowing measurement results to better reflect the tool's flatness and laying the foundation for subsequent point cloud data construction.

[0063] Understandably, by collecting point cloud data layer by layer at different depths of focus using a scanning mode and then performing noise reduction, we can comprehensively acquire information about the tool surface at different depths, avoiding surface features that might be missed due to acquisition at a single depth of focus. On the other hand, noise reduction can effectively remove noise interference introduced during the acquisition process, allowing the point cloud data to accurately reflect the true shape of the tool surface. Based on the point cloud data, we can construct a triangular mesh, determine the fitting plane based on the triangular mesh, and then determine the vertical distance from each point of the triangular mesh to the fitting plane. The difference between the maximum and minimum vertical distances is used as the flatness, which can effectively reflect the degree of undulation and unevenness of the tool surface, avoiding errors caused by tool unevenness.

[0064] In some embodiments of this application, when comparing flatness and cutting flatness to determine whether to grind the tool to identify the cutting tool, the following steps are taken: when the flatness is less than the cutting flatness, a new tool is selected, and the flatness of the new tool is determined until the cutting flatness is achieved; when the flatness is equal to the cutting flatness, the tool is not ground, and the tool is identified as the cutting tool; when the flatness is greater than the cutting flatness, the tool is ground, and the ground flatness of the tool is obtained; if the ground flatness is equal to the cutting flatness, the ground tool is identified as the cutting tool; otherwise, a new tool is selected.

[0065] Specifically, the cutting flatness is determined based on the process parameters of the lens barrel to be cut. By comparing the flatness with the cutting flatness and taking corresponding measures, the cutting tool and the lens barrel to be cut can be accurately matched. When the flatness is less than the cutting flatness, the tool is reselected; when it is greater, grinding is performed; when they are equal, it is used directly. This ensures that the cutting tool is always in good working condition, avoids control errors caused by tool unevenness, and ensures that the CNC can accurately control the cutting process, enhancing the flexibility of control. When grinding, the grinding flatness is obtained in the same way as the flatness, which will not be repeated here. If the grinding flatness is equal to the cutting flatness, the grinding tool is determined as the cutting tool; otherwise, the tool is reselected. If the grinding flatness still does not meet the standard, it means that there are irreparable defects in the surface geometry of the tool, so a new tool is selected, which improves the reliability of CNC cutting control.

[0066] In some embodiments of this application, the speed control strategy for determining the predicted cutting speed based on the cutting friction coefficient includes: when the cutting friction coefficient is less than the cutting friction coefficient threshold, modifying the spindle speed parameters in the CNC system to control the predicted cutting speed; when the cutting friction coefficient is equal to the cutting friction coefficient threshold, cutting the lens barrel to be cut according to the predicted cutting speed and the cutting tool; when the cutting friction coefficient is greater than the cutting friction coefficient threshold, determining the cutting area according to the CNC cutting environment, constructing a cutting environment influence chain based on the cutting area, determining the speed control factor according to the cutting environment influence chain, and determining the target speed control factor according to the speed control factor.

[0067] Specifically, when the cutting friction coefficient is less than the cutting friction coefficient threshold, the predicted cutting speed is controlled by modifying the spindle speed parameters and motor parameters in the CNC. This adjustment is within the existing control range and generally does not exceed the stable operating range of the CNC. The control strategy is relatively simple. When the cutting friction coefficient equals the threshold, cutting can be performed according to the determined predicted cutting speed and cutting tool, ensuring the consistency and stability of cutting control, reducing the quality risk caused by speed fluctuations, and ensuring the quality of the lens barrel. However, when the predicted cutting speed is increased accordingly for excessive cutting friction coefficient, environmental factors such as temperature and humidity will affect the predicted cutting speed. The control strategy is more complex. The cutting area is determined according to the CNC cutting environment. Different cutting areas may have differences in temperature, humidity, etc. By constructing an influence chain, environmental factors can be fully considered, and the influence between various factors can be comprehensively analyzed, thereby accurately controlling the predicted cutting speed of the CNC.

[0068] In some embodiments of this application, when determining the cutting area based on the CNC cutting environment and constructing the cutting environment influence chain based on the cutting area, the process includes: extending outwards from the geometric center of the CNC to form a cylindrical space with a radius of r and a height consistent with the highest point d of the CNC; uniformly dividing the cylindrical space into several cutting areas; acquiring environmental data of several cutting areas; and constructing the cutting environment influence chain.

[0069] Specifically, a regular cylindrical space is constructed based on the geometric center of the CNC to avoid omissions and deviations in environmental data acquisition. This space is then uniformly divided into several cutting zones, and environmental data such as temperature and humidity are specifically acquired for each cutting zone using sensors such as temperature and humidity sensors. The radius *r* is larger than the length and width of the CNC itself, ensuring the cylinder covers the entire CNC. The division of the cutting zones is determined based on the actual size of the cylindrical space and is not limited here. The cutting environment influence chain integrates environmental data from each cutting zone, enabling the CNC to dynamically adjust the predicted cutting speed according to environmental changes, thus enhancing the CNC cutting control's dynamic adaptability to complex and changing environments.

[0070] In some embodiments of this application, when determining the speed control factor based on the cutting environment influence chain and determining the target speed control factor based on the speed control factor, the process includes: determining an environmental data chain corresponding to the cutting environment influence chain based on the cutting environment influence chain; determining the speed control factor based on the environmental data on the environmental influence chain and the data on the environmental data chain; when a historical speed control factor consistent with the speed control factor exists in the historical data, determining the speed control factor as the target speed control factor; when no historical speed control factor consistent with the speed control factor exists in the historical data, determining a speed control set based on the historical data; and determining the target speed control factor based on the speed control set.

[0071] Specifically, the environmental data chain is the standard environmental data chain required by CNC, and the data on the environmental data chain corresponds one-to-one with the environmental data on the cutting environment influence chain. This allows for a comprehensive and detailed analysis of the impact of various environmental factors on the predicted cutting speed during the cutting process. When the environmental data on the cutting environment influence chain is greater than the data on the environmental data chain, the environmental data is classified into the first environmental influence chain. When the environmental data on the cutting environment influence chain is equal to the data on the environmental data chain, the environmental data is classified into the second environmental influence chain. When the environmental data on the cutting environment influence chain is less than the data on the environmental data chain, the environmental data is classified into the third environmental influence chain. The first quantity of environmental data on the first environmental influence chain and the third quantity of environmental data on the third environmental influence chain are counted. The speed control factor is determined according to the following formula:

[0072] ;

[0073] Where P represents the speed control factor, n represents the first quantity, m represents the third quantity, Ai represents the i-th environmental data on the first environmental influence chain, Fi represents the i-th data corresponding to the i-th environmental data on the first environmental influence chain, Bj represents the j-th environmental data on the third environmental influence chain, and Qj represents the j-th data corresponding to the j-th environmental data on the third environmental influence chain.

[0074] Specifically, historical data includes multiple historical speed control factors. When a historical speed control factor that matches the historical speed control factor exists in the historical data, it indicates that the historical speed control factor obtained through the formula matches the historical data. In this case, the speed control factor is directly determined as the target speed control factor, making full use of past control experience. At the same time, the historical data has been verified by actual control, so the target speed control factor determined in this way has high reliability. When no historical speed control factor that matches the historical speed control factor exists in the historical data, the target speed control factor is determined based on the speed control set. Even when encountering speed control factors that have never appeared before, it can cope with various complex and new environments, improving the flexibility and dynamic adaptability of CNC cutting predictive speed control. Furthermore, as the data on CNC control accumulates, the historical data will become richer and richer, and the speed control set will continue to improve. When facing various environments, it can more accurately determine the target speed control factor, thereby continuously optimizing cutting control.

[0075] In some embodiments of this application, when determining the speed control set based on historical data and determining the target speed control factor based on the speed control set, the process includes: assigning historical speed control factors greater than the speed control factor in the historical data to a first speed control set; assigning historical speed control factors less than the speed control factor in the historical data to a second speed control set; converting all historical speed control factors in the first speed control set into first control coordinate points; converting all historical speed control factors in the second speed control set into second control coordinate points; and determining a first control coordinate system and a second control coordinate system based on the first control coordinate points and the second control coordinate points, respectively.

[0076] In some embodiments of this application, when determining the speed control set based on historical data and determining the target speed control factor based on the speed control set, the method further includes: fitting all first control coordinate points to determine a first control fitting curve, fitting all second control coordinate points to determine a second control fitting curve, removing unfitted first and second control coordinate points, and using the first control coordinate points on the first control fitting curve and the second control points on the second control fitting curve as speed control points, determining the speed adjustment coefficient of the speed control factor based on the speed control points, and determining the target speed control factor based on the speed control factor and the speed adjustment coefficient.

[0077] Specifically, the time of the historical speed control factor in the first speed control set is used as the first X-axis coordinate value, and the value of the historical speed control factor in the first speed control set is used as the first Y-axis coordinate value. The first control coordinate point is determined based on the first X-axis coordinate value and the first Y-axis coordinate value. The time of the historical speed control factor in the second speed control set is used as the second X-axis coordinate value, and the value of the historical speed control factor in the second speed control set is used as the second Y-axis coordinate value. The first control coordinate point is determined based on the second X-axis coordinate value and the second Y-axis coordinate value. The time of the historical speed control factor is the time determined at that time. For example, if a historical speed control factor is obtained at 4:40, then the time of the historical speed control factor is recorded as 4:40. The curves are arranged in chronological order. The methods for determining the first control fitting curve and the second control fitting curve include polynomial fitting, spline interpolation, and least squares method, etc. The specific method can be selected according to the actual situation, and no specific limitation is made here. A first control coordinate system and a second control coordinate system are constructed to present historical speed control factors in an intuitive coordinate form, making the relationship between data clearer. The control coordinate points corresponding to the first and second control fitting curves are used as speed control points. These points represent representative and regular speed control situations in historical data. Based on these speed control points, the speed adjustment coefficient is determined, which can accurately reflect the regularity and trend of speed control in historical data, ensuring the consistency and stability of control.

[0078] In some embodiments of this application, when determining the speed adjustment coefficient of the speed control factor based on the speed control point and determining the target speed control factor based on the speed control factor and the speed adjustment coefficient, the method includes: obtaining the slope of all speed control points and determining the speed adjustment coefficient based on the slope, wherein the target speed control factor is the product of the speed adjustment coefficient and the speed control factor, and the target speed control factor is positively correlated with the predicted cutting speed.

[0079] Specifically, the maximum and minimum slopes are determined based on the slopes of all speed control points. Using the natural constant e as the base, the absolute value of the ratio of the maximum and minimum slopes is used as the logarithm to determine the speed adjustment coefficient. Assuming the speed adjustment coefficient is H and the speed control factor is P, the target speed control factor is H*P. The speed control factor is adjusted using the speed adjustment coefficient. When a larger target speed control factor is needed, the speed control factor is adjusted using the speed adjustment coefficient, improving the accuracy and stability of the predicted cutting speed control. Furthermore, the target speed control factor and the predicted cutting speed are positively correlated. Whether the target speed control factor is linear or nonlinear, the predicted cutting speed can be adjusted. When the predicted cutting speed is increased accordingly to address excessive cutting friction coefficient, the reliability and stability of the control are improved, thereby accurately controlling the predicted cutting speed of the CNC.

[0080] In summary, the beneficial effects of this invention are as follows: It utilizes a profilometer for three-dimensional tool calibration, accurately determining whether the tool needs grinding by comparing tool flatness with cutting flatness, ensuring the tool is in good working condition. This avoids insufficient precision due to tool wear, ensuring the reliability and stability of CNC control, and guaranteeing the machining accuracy and quality of the lens barrel. The predicted cutting speed is determined based on the material properties of the lens barrel to be cut and the speed prediction model, and the speed control strategy is determined in conjunction with the cutting friction coefficient. Compared to traditional fixed-parameter cutting, it can better adapt to the cutting requirements of lens barrels made of different materials. By determining the cutting area and constructing an environmental influence chain, a speed control factor is derived. Comparing this factor with historical data determines the degree of matching. If no corresponding historical speed control factor is found, a speed control set is determined based on the historical data to determine the speed adjustment coefficient, thereby determining the target speed control factor. This establishes a complete feedback mechanism, realizing a dynamic response to changes in the cutting environment, enabling the CNC to flexibly adjust the predicted cutting speed according to environmental conditions, thus improving the reliability and stability of control.

[0081] In another preferred embodiment based on the above embodiments, see [reference] Figure 2 As shown, this embodiment provides a CNC cutting control system for an integrated lens barrel, applied to the aforementioned CNC cutting control method for an integrated lens barrel, including:

[0082] The data processing module is configured to use a profilometer to fix the tool and perform three-dimensional calibration on the tool. Based on the three-dimensional calibration, the flatness of the tool is determined, and the flatness is compared with the cutting flatness to determine whether the tool needs to be ground and to determine the cutting tool.

[0083] The speed control module is configured to determine the predicted cutting speed based on the material properties of the lens barrel to be cut and the speed prediction model, obtain the cutting friction coefficients of the lens barrel to be cut and the cutting tool, and determine the speed control strategy based on the cutting friction coefficients to determine the predicted cutting speed.

[0084] The first adjustment module is configured to determine the cutting area based on the CNC cutting environment when the cutting friction coefficient is greater than the cutting friction coefficient threshold, construct a cutting environment influence chain based on the cutting area, determine the speed control factor based on the cutting environment influence chain, compare the speed control factor with historical data, and determine the target speed control factor based on the comparison result.

[0085] The second adjustment module is configured to determine a speed control set based on historical data when there is no historical speed control factor that matches the speed control factor in the historical data, determine the speed adjustment coefficient of the speed control factor based on the speed control set, and determine the target speed control factor based on the speed control factor and the speed adjustment coefficient.

[0086] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0087] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0088] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0089] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not 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 modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A CNC cutting control method for an integrated lens barrel, characterized in that, include: The tool is fixed using a profilometer and 3D calibrated. The flatness of the tool is determined based on the 3D calibration. The flatness is then compared with the cutting flatness to determine whether the tool needs to be ground to determine the cutting tool. The predicted cutting speed is determined based on the material properties of the lens barrel to be cut and the speed prediction model. The cutting friction coefficients of the lens barrel to be cut and the cutting tool are obtained. The speed control strategy of the predicted cutting speed is determined based on the cutting friction coefficients. When the cutting friction coefficient is greater than the cutting friction coefficient threshold, the cutting area is determined according to the CNC cutting environment, a cutting environment influence chain is constructed based on the cutting area, the speed control factor is determined according to the cutting environment influence chain, and the speed control factor is compared with historical data. The target speed control factor is determined based on the comparison result. When there is no historical speed control factor in the historical data that matches the speed control factor, a speed control set is determined based on the historical data, a speed adjustment coefficient of the speed control factor is determined based on the speed control set, and the target speed control factor is determined based on the speed control factor and the speed adjustment coefficient. The construction of the cutting environment influence chain includes: Extending outwards from the geometric center of the CNC, a cylindrical space with radius r and height matching the highest point d of the CNC is formed, and the cylindrical space is evenly divided into several cutting areas; Obtain environmental data for several cutting regions and construct the cutting environment influence chain; Also includes: Determine the environmental data chain corresponding to the cutting environment influence chain based on the cutting environment influence chain; The speed control factor is determined based on the environmental data in the environmental impact chain and the data in the environmental data chain; The environmental data chain is the standard environmental data chain required by CNC, and the data on the environmental data chain corresponds one-to-one with the environmental data on the cutting environment influence chain. When the environmental data on the cutting environment influence chain is greater than the data on the environmental data chain, the environmental data is classified into the first environmental influence chain. When the environmental data on the cutting environment influence chain is equal to the data on the environmental data chain, the environmental data is classified into the second environmental influence chain. When the environmental data on the cutting environment influence chain is less than the data on the environmental data chain, the environmental data is classified into the third environmental influence chain. The first quantity of environmental data on the first environmental influence chain and the third quantity of environmental data on the third environmental influence chain are counted. The speed control factor is determined according to the following formula: ； Where P represents the speed control factor, n represents the first quantity, m represents the third quantity, Ai represents the i-th environmental data on the first environmental influence chain, Fi represents the i-th data corresponding to the i-th environmental data on the first environmental influence chain, Bj represents the j-th environmental data on the third environmental influence chain, and Qj represents the j-th data corresponding to the j-th environmental data on the third environmental influence chain.

2. The CNC cutting control method for an integrated lens barrel according to claim 1, characterized in that, When using a profilometer to fix the cutting tool and perform three-dimensional calibration on the cutting tool, and determining the flatness of the cutting tool based on the three-dimensional calibration, the process includes: Obtain the position where the center of the cutting tool coincides with the axis of the profilometer, and fix the cutting tool according to the position of coincidence; The scanning mode of the profilometer is determined based on the tool properties of the tool. Based on the scanning mode, point cloud data is collected layer by layer at different focal depths and noise is reduced to construct point cloud data. A triangular mesh is constructed based on the point cloud data, and a fitting plane is determined based on the triangular mesh. Determine the vertical distance from each point of the triangular mesh to the fitted plane, and use the difference between the maximum and minimum vertical distances as the flatness.

3. The CNC cutting control method for an integrated lens barrel according to claim 2, characterized in that, When comparing the flatness and the cutting flatness to determine whether the cutting tool needs to be ground, the following steps are included: When the flatness is less than the cutting flatness, the tool is reselected and the flatness of the reselected tool is determined until the cutting flatness is achieved. When the flatness is equal to the cutting flatness, the tool is not ground and is identified as the cutting tool. When the flatness is greater than the cutting flatness, the tool is ground and the grinding flatness of the grinding tool is obtained. If the grinding flatness is equal to the cutting flatness, the grinding tool is determined as the cutting tool; otherwise, a new tool is selected.

4. The CNC cutting control method for an integrated lens barrel according to claim 3, characterized in that, When determining the predicted cutting speed based on the cutting friction coefficient, the speed control strategy includes: When the cutting friction coefficient is less than the cutting friction coefficient threshold, the spindle speed parameter is modified in the CNC system to control the predicted cutting speed. When the cutting friction coefficient is equal to the cutting friction coefficient threshold, the mirror barrel to be cut is cut according to the predicted cutting speed and the cutting tool. When the cutting friction coefficient is greater than the cutting friction coefficient threshold, the cutting area is determined according to the CNC cutting environment, a cutting environment influence chain is constructed based on the cutting area, a speed control factor is determined according to the cutting environment influence chain, and a target speed control factor is determined according to the speed control factor.

5. The CNC cutting control method for an integrated lens barrel according to claim 4, characterized in that, When determining the speed control factor based on the cutting environment influence chain, and determining the target speed control factor based on the speed control factor, the process includes: When a historical speed control factor that matches the speed control factor exists in the historical data, the speed control factor is determined as the target speed control factor. When there is no historical speed control factor in the historical data that matches the speed control factor, a speed control set is determined based on the historical data, and the target speed control factor is determined based on the speed control set.

6. The CNC cutting control method for an integrated lens barrel according to claim 5, characterized in that, When determining the speed control set based on the historical data, and determining the target speed control factor based on the speed control set, the process includes: The historical speed control factors that are greater than the speed control factor in the historical data are assigned to the first speed control set; The historical speed control factors that are smaller than the speed control factor in the historical data are assigned to the second speed control set; All historical speed control factors in the first speed control set are converted into first control coordinate points, and all historical speed control factors in the second speed control set are converted into second control coordinate points; The first control coordinate system and the second control coordinate system are determined based on the first control coordinate point and the second control coordinate point, respectively.

7. The CNC cutting control method for an integrated lens barrel according to claim 6, characterized in that, When determining the speed control set based on the historical data, and determining the target speed control factor based on the speed control set, the method further includes: The first control curve is determined by fitting all the first control coordinate points, and the second control curve is determined by fitting all the second control coordinate points. Remove the first and second control coordinate points that were not fitted, and use the first control coordinate points on the first control fitting curve and the second control coordinate points on the second control fitting curve as speed control points. The speed adjustment coefficient of the speed control factor is determined based on the speed control point, and the target speed control factor is determined based on the speed control factor and the speed adjustment coefficient.

8. The CNC cutting control method for an integrated lens barrel according to claim 7, characterized in that, When determining the speed adjustment coefficient of the speed control factor based on the speed control point, and determining the target speed control factor based on the speed control factor and the speed adjustment coefficient, the process includes: Obtain the slope of all speed control points and determine the speed adjustment coefficient based on the slope; The target speed control factor is the product of the speed adjustment coefficient and the speed control factor, and the target speed control factor is positively correlated with the predicted cutting speed.

9. A CNC cutting control system for an integrated lens barrel, applied to the CNC cutting control method for an integrated lens barrel as described in any one of claims 1-8, characterized in that, include: The data processing module is configured to use a profilometer to fix the tool and perform three-dimensional calibration on the tool, determine the flatness of the tool based on the three-dimensional calibration, compare the flatness with the cutting flatness, and determine whether to grind the tool to determine the cutting tool. The speed control module is configured to determine the predicted cutting speed based on the material properties of the lens barrel to be cut and the speed prediction model, obtain the cutting friction coefficient between the lens barrel to be cut and the cutting tool, and determine the speed control strategy of the predicted cutting speed based on the cutting friction coefficient. The first adjustment module is configured to determine the cutting area based on the CNC cutting environment when the cutting friction coefficient is greater than the cutting friction coefficient threshold, construct a cutting environment influence chain based on the cutting area, determine the speed control factor based on the cutting environment influence chain, compare the speed control factor with historical data, and determine the target speed control factor based on the comparison result. The second adjustment module is configured to, when there is no historical speed control factor in the historical data that matches the speed control factor, determine a speed control set based on the historical data, determine the speed adjustment coefficient of the speed control factor based on the speed control set, and determine the target speed control factor based on the speed control factor and the speed adjustment coefficient.

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