Lens polishing control method and system for sighting telescope

Abstract

The invention discloses a lens polishing control method and system for a sighting telescope, and relates to the technical field of lens processing, and the method comprises the steps: carrying out path position connection according to a control process node, a polishing control position and an execution time sequence relation, and obtaining a polishing preset track; a polishing monitoring image is obtained, polishing target recognition and polishing position positioning are carried out, and a polishing execution track is determined; and through grinding track fitting comparison, track deviation information is obtained, grinding effect evaluation is carried out, grinding effect comparison is carried out according to grinding target parameters, grinding deviation information is generated, and control parameter information is adjusted and controlled. The technical problems that in the prior art, due to the fact that the performance difference of different lens materials is large, the adaptation degree of grinding control parameters is low, and the lens grinding precision and quality are affected are solved, and the technical effects that through real-time evaluation of the grinding track and the grinding effect, self-adaptive optimization of the grinding control parameters is conducted, and the lens grinding precision and quality are improved are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of lens processing, and particularly relates to a lens grinding control method and system for a telescopic sight. Background Art

[0002] As a precision optical instrument, the lens grinding control technology of a telescopic sight is the key to ensuring the performance of the telescopic sight. With the progress of technology, modern telescopic sights have higher and higher requirements for the quality of lenses, and high-precision and high-stability optical performance needs to be achieved. The modern lens grinding control technology has shown a trend of digitalization, intelligence, and automation, greatly improving the grinding precision and efficiency. However, the characteristics such as hardness, toughness, and thermal conductivity of different lens materials vary greatly, resulting in a low adaptability of existing fixed grinding parameters, which will affect the grinding precision and quality of lenses. Summary of the Invention

[0003] This application provides a lens grinding control method and system for a telescopic sight, which is used to solve the technical problem in the prior art that the performance differences of different lens materials are large, resulting in low adaptability of grinding control parameters and affecting the grinding precision and quality of lenses.

[0004] In the first aspect of this application, a lens grinding control method for a telescopic sight is provided. The method includes: connecting a control module to obtain control parameter information, including control process nodes, grinding control positions, grinding speeds, grinding forces, grinding angles, and grinding target parameters; connecting the path positions according to the control process nodes and the grinding control positions according to the execution timing relationship to obtain a preset grinding trajectory; connecting an image monitoring module to obtain a grinding monitoring image, perform grinding target recognition, determine the center for grinding position positioning based on the grinding target recognition result, and determine the grinding execution trajectory; perform fitting comparison between the grinding execution trajectory and the preset grinding trajectory to obtain trajectory deviation information; evaluate the grinding effect based on the trajectory deviation information, in combination with the grinding speed, grinding force, and grinding angle, to obtain a grinding evaluation effect; compare the grinding target parameters with the grinding evaluation effect to obtain grinding deviation information; optimize the configuration of the grinding speed, grinding force, and grinding angle according to the grinding deviation information to obtain adjustment parameters, and perform adjustment control on the control parameter information based on the adjustment parameters.

[0005] The second aspect of the present application provides a lens grinding control system for a telescopic sight. The system includes: a control parameter information acquisition module, which is used to connect to a control module to acquire control parameter information, including control process nodes, grinding control positions, grinding speeds, grinding forces, grinding angles, and grinding target parameters; a grinding preset trajectory acquisition module, which is used to connect the path positions according to the control process nodes and the grinding control positions in the execution time sequence relationship to obtain a grinding preset trajectory; a grinding execution trajectory determination module, which is used to connect to an image monitoring module to acquire a grinding monitoring image, perform grinding target recognition, determine the center for grinding position positioning based on the grinding target recognition result, and determine the grinding execution trajectory; a trajectory fitting comparison module, which is used to perform fitting comparison between the grinding execution trajectory and the grinding preset trajectory to obtain trajectory deviation information; a grinding effect evaluation module, which is used to evaluate the grinding effect according to the trajectory deviation information, in combination with the grinding speed, grinding force, and grinding angle, to obtain a grinding evaluation effect; a grinding deviation information acquisition module, which is used to compare the grinding target parameters with the grinding evaluation effect to obtain grinding deviation information; a grinding adjustment control module, which is used to optimize the configuration of the grinding speed, grinding force, and grinding angle according to the grinding deviation information to obtain adjustment parameters, and adjust and control the control parameter information based on the adjustment parameters.

[0006] One or more technical solutions provided in the present application have at least the following technical effects or advantages: A lens grinding control method for a telescopic sight provided by the present application relates to the technical field of lens processing. By controlling process nodes and grinding control positions, path positions are connected to obtain a grinding preset trajectory. Through a grinding monitoring image, grinding target recognition and grinding position positioning are performed to determine the grinding execution trajectory. Furthermore, through grinding trajectory fitting comparison, trajectory deviation information is obtained, grinding effect evaluation and grinding effect comparison are performed, grinding deviation information is generated, and the control parameter information is adjusted and controlled, solving the technical problem in the prior art that due to large differences in the performance of different lens materials, the adaptability of grinding control parameters is low, affecting the grinding accuracy and quality of the lens, and achieving the technical effect of improving the grinding accuracy and quality of the lens through adaptive optimization of grinding control parameters. Description of the Drawings

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0008] Figure 1 It is a schematic flowchart of a lens grinding control method for a telescopic sight provided by an embodiment of the present application; Figure 2 It is a schematic flowchart of determining a grinding execution trajectory in a lens grinding control method for a telescopic sight provided by an embodiment of the present application; Figure 3 It is a schematic structural diagram of a lens grinding control system for a telescopic sight provided by an embodiment of the present application.

[0009] Explanation of reference numerals: Control parameter information acquisition module 11, grinding preset trajectory acquisition module 12, grinding execution trajectory determination module 13, trajectory fitting and comparison module 14, grinding effect evaluation module 15, grinding deviation information acquisition module 16, grinding adjustment control module 17. Detailed implementation manners

[0010] The present application provides a lens grinding control method for a telescopic sight, which is used to solve the technical problem that in the prior art, due to large differences in the performance of different lens materials, the adaptability of grinding control parameters is low, affecting the grinding accuracy and quality of the lens.

[0011] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0012] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0013] Example 1 As Figure 1 shown, the present application provides a method for controlling the lens grinding of a sight, and the method includes: P10: Connect to the control module and obtain control parameter information, including control process nodes, grinding control positions, grinding speeds, grinding forces, grinding angles, and grinding target parameters; Specifically, establish a reliable connection with the control module. The control module is the core component of the lens grinding equipment and is responsible for receiving and executing various control instructions. By establishing a data communication link, the accurate transmission and real-time update of control parameter information can be ensured. Obtain key control parameter information from the control module, including obtaining control process nodes, grinding control positions, grinding speeds, grinding forces, grinding angles, and grinding target parameters.

[0014] Among them, the control process nodes include various stages and steps of lens grinding, such as rough grinding, fine grinding, polishing, etc. Each node has specific operation requirements and parameter settings. The grinding control position refers to the specific position and posture of the lens on the grinding equipment, which is the key to ensuring that the lens can be ground along a preset trajectory. The grinding speed refers to the rotational speed of the grinding tool, which can directly affect the grinding efficiency and quality. The grinding force refers to the pressure or force exerted by the grinding tool on the lens, which can determine the depth and uniformity of grinding. The grinding angle refers to the angle between the grinding tool and the lens surface, which can affect the grinding effect and the surface quality of the lens. The grinding target parameters are the final indicators that the lens grinding is expected to achieve, such as the target surface roughness, target shape accuracy, etc., which are the basis for evaluating the grinding quality.

[0015] P20: According to the control process nodes and the grinding control positions, perform path position connection according to the execution time sequence relationship to obtain a preset grinding trajectory; Optionally, according to the control process nodes, obtain the execution time sequence relationship of different nodes, and then construct a logically coherent grinding process according to the execution time sequence relationship, and refine the grinding process according to the grinding control positions. Combine the grinding control positions with the control process nodes to determine the specific positions that the lens should be in under each node. Then connect these specific positions according to the execution time sequence relationship to form a continuous preset grinding trajectory. The execution time sequence relationship refers to the time sequence and dependency relationship between different nodes and positions. The preset grinding trajectory can be used as the basis and reference for subsequent grinding operations. During the actual grinding process, the control system will try to make the lens move and grind along the preset grinding trajectory to ensure the expected grinding effect and quality.

[0016] P30: Connect to the image monitoring module, obtain the grinding monitoring image, perform grinding target recognition, determine the center based on the grinding target recognition result for grinding position positioning, and determine the grinding execution trajectory. Further, as Figure 2 shown, step P30 of the embodiment of the present application further includes: P31: Identify the grinding target object and the grinding equipment in the grinding monitoring image, and obtain the grinding target object edge recognition result and the grinding equipment positioning recognition result. P32: Determine the center of the grinding target object according to the grinding target object edge recognition result, use the center of the grinding target object as the positioning center, and perform overlapping positioning with the grinding control position in the control parameter information. P33: Based on the overlapping positioning relationship, determine the grinding execution position according to the grinding equipment positioning recognition result. P34: Connect the grinding execution positions according to the monitoring time sequence relationship of the grinding monitoring image to obtain the grinding execution trajectory.

[0017] It should be understood that during the actual grinding process, the grinding target object is monitored in real time through the image monitoring module, thereby obtaining the grinding monitoring image. The grinding monitoring image includes multiple grinding images of multiple process nodes. Perform target recognition and positioning on the grinding monitoring image to determine the actual grinding execution trajectory.

[0018] Specifically, perform in-depth recognition processing on each of the grinding monitoring images one by one, including the recognition of the grinding target object, that is, the lens, and the grinding equipment, such as a grinding wheel or a grinding head. Through image processing technology, identify the edge of the lens and the specific position of the grinding equipment in each image, and obtain the grinding target object edge recognition result and the grinding equipment positioning recognition result.

[0019] Further, according to the grinding target object edge recognition result, determine the center position of the grinding target object in each image, and use the center position of the grinding object as the positioning center to perform overlapping positioning with the grinding control position in the control parameter information to ensure that the grinding operation can accurately target the target area of the lens and avoid grinding deviation caused by inaccurate positioning.

[0020] Further, based on the overlapping positioning relationship between the center position of the grinding object and the grinding control position in each grinding image, combined with the positioning recognition result of the grinding equipment, determine the specific grinding execution position of each process node, that is, the position that the grinding equipment should reach in each actual operation node, to ensure precise grinding of the lens.

[0021] Finally, according to the monitoring time sequence relationship of the polished monitoring images, connect the polishing execution positions of each process node to form a continuous polishing execution trajectory, which can reflect the real-time process of lens polishing and provide a reference basis for subsequent trajectory fitting comparison and deviation analysis.

[0022] Further, step P32 of the embodiment of the present application further includes: P32-1: Establish a polishing configuration relationship between the aiming scope polishing raw material and the polishing target result; P32-2: Based on the polishing configuration relationship, determine the overlapping center point, and construct a structure coordinate system with the overlapping center point as the origin. According to the polishing configuration relationship between the aiming scope polishing raw material and the polishing target result, fit the edge coordinates of the aiming scope polishing raw material and the polishing target result into the structure coordinate system; P32-3: Based on the control parameter information, perform polishing target fitting according to the control process node, polishing control position, and polishing target parameters to obtain the structure coordinate system of the control process node, which includes the edge coordinate points of the polishing target shape and the polishing control position coordinates; P32-4: Match according to the monitored polishing process node, obtain the structure coordinate system of the corresponding control process node, overlap the positioning center with the origin of the matching structure coordinate system, fit the polishing execution position into the matching structure coordinate system, and determine the overlapping positioning relationship.

[0023] Exemplarily, the process of determining the center of the polishing target object and performing overlapping positioning can be as follows: First, according to the design requirements and expected performance parameters of the aiming scope, establish a polishing configuration relationship between the polishing raw material and the polishing target result, including determining the material type, size, shape of the lens, and expected optical performance, etc.

[0024] Further, based on the polishing configuration relationship, determine the overlapping center point, which is the coincidence point of the center of the lens design and the polishing target center. And construct a structure coordinate system with the overlapping center point as the origin. According to the polishing configuration relationship between the aiming scope polishing raw material and the polishing target result, fit the edge coordinates of the aiming scope polishing raw material and the polishing target result into the structure coordinate system, that is, accurately align the raw material and the target result in the structure coordinate system to ensure that the operation can be accurately carried out according to the shape and size of the target result during the polishing process.

[0025] Further, based on the control parameter information, and according to the control process nodes, the grinding control positions, and the grinding target parameters, the grinding target is fitted. By matching the parameters such as the shape and size of the grinding target with the structural coordinate system, the structural coordinate system of each control process node is obtained, and the structural coordinate system includes the edge coordinate points of the grinding target shape and the coordinates of the grinding control positions, which can provide clear guidance for subsequent grinding operations.

[0026] Further, according to the monitored grinding process nodes for matching, the structural coordinate system of the corresponding control process node is found. Then, the previously determined positioning center, that is, the overlapping center point, is overlapped with the origin of the matching structural coordinate system, and then the grinding execution position is fitted into the matching structural coordinate system, so as to determine the overlapping positioning relationship between the grinding execution position and the grinding target, ensuring that the grinding operation can accurately target the design goal.

[0027] P40: Fit and compare the grinding execution trajectory with the grinding preset trajectory to obtain trajectory deviation information; Specifically, fit and compare the grinding execution trajectory with the grinding preset trajectory, and match and compare the key nodes on the two trajectories one by one to calculate the deviation between the two trajectories, such as calculating the deviations in multiple aspects such as position, direction, and speed, to obtain the trajectory deviation information. The trajectory deviation information can be used to evaluate the accuracy and precision of the grinding operation. If the deviation is too large, it means that the actual grinding operation deviates from the preset trajectory, which may cause problems such as uneven wear and shape distortion on the lens surface, thus affecting the performance and quality of the lens.

[0028] Further, after obtaining the trajectory deviation information, the embodiment of the present application further includes step P40a, and step P40a further includes: P41a: Determine the deviation distance and deviation angle according to the trajectory deviation information; P42a: Obtain the current grinding positioning, grinding speed, grinding force, and grinding angle; P43a: Taking the grinding target parameters as the evaluation target, calculate the grinding loss amount according to the deviation distance, deviation angle, current grinding positioning, grinding speed, grinding force, and grinding angle; P44a: When the grinding loss amount is not within the loss range, send a position adjustment instruction, and the position adjustment instruction is used to stop the current grinding control and adjust the grinding position according to the deviation distance and deviation angle.

[0029] Optionally, after obtaining the trajectory deviation information, the grinding process can be finely adjusted according to the trajectory deviation information to ensure the accuracy and efficiency of grinding. Specifically, according to the trajectory deviation information, the deviation distance and deviation angle are determined, and the current grinding positioning, grinding speed, grinding force, and grinding angle of the grinding device are obtained, that is, the current working state of the grinding device. Further, taking the grinding target parameters as the evaluation target, combining the deviation distance, deviation angle, and the current grinding positioning, grinding speed, grinding force, and grinding angle of the grinding device, the grinding loss amount is calculated. The grinding loss amount is a comprehensive index, and the grinding loss amount can be calculated by quantitatively calculating the losses such as the decrease in lens quality and the reduction in grinding efficiency caused by the trajectory deviation, that is, quantitatively evaluating the effect of the current grinding process.

[0030] Further, the grinding loss amount is determined. When the grinding loss amount is not within the loss range, that is, beyond the preset loss range, it indicates that the current grinding trajectory deviation has significantly affected the lens quality and grinding efficiency. Then, a position adjustment instruction needs to be sent to stop the current grinding control and adjust the grinding position according to the deviation distance and deviation angle to correct the trajectory deviation in time and restore the accuracy and efficiency of the grinding process.

[0031] Further, step P44-1a in the embodiment of the present application further includes: P44-1a: When the grinding loss amount is within the loss range, according to the current grinding positioning, grinding speed, grinding force, and grinding angle, a smooth movement analysis is performed on the deviation distance and deviation angle to determine the movement adjustment parameters, and the control parameter information is adjusted and controlled by using the movement adjustment parameters; Among them, the smooth movement analysis is to adjust the control quantity curve of the grinding positioning, grinding speed, grinding force, and grinding angle with the minimum power loss value and the deviation distance and offset angle as the movement directions.

[0032] In a possible embodiment of the present application, when it is determined that the grinding loss amount is within the preset loss range, it indicates that although there are certain deviations in the current grinding process, it has not significantly affected the lens quality and grinding efficiency. In this case, there is no need to immediately stop the grinding control, and the current state can be optimized and adjusted to minimize the trajectory deviation as much as possible.

[0033] Specifically, based on parameters such as the current grinding positioning, grinding speed, grinding force, and grinding angle, a smooth movement analysis is performed on the deviation distance and deviation angle. The core objective of the smooth movement analysis is to adjust the control parameter curves of grinding positioning, speed, force, and angle in the direction of the deviation distance and deviation angle while minimizing the power loss value, that is, to gradually correct the deviation through a smooth movement trajectory rather than a sudden large adjustment, so as to ensure the stability and continuity of the grinding process. Through the smooth movement analysis, the movement adjustment parameters are determined, and the control parameter information can be fine-tuned using the movement adjustment parameters, thereby reducing the trajectory deviation and improving the accuracy and efficiency of grinding.

[0034] P50: According to the trajectory deviation information, combined with the grinding speed, grinding force, and grinding angle, evaluate the grinding effect to obtain the grinding evaluation effect; Further, before obtaining the grinding evaluation effect, the embodiment of the present application further includes step P50a, and step P50a further includes: P51a: Obtain a historical sample set, randomly select a first training sample set, the first training sample set includes grinding speed, grinding force, grinding angle, and grinding effect identification information, and configure an average weight for each training sample in the first training sample set; P52a: Use the first training sample set for neural network training to obtain an initial model; P53a: Calculate the prediction error probability based on the initial model, determine the error samples and mark them. The error samples are the training samples with incorrect prediction results. Reconfigure the weights of the error samples. The reconfigured weights are higher than the average weight, and randomly select a second training sample set from the historical sample set, configure the average weight of the samples in the second training sample set, combine them with the error samples, and train the initial model to obtain a second-generation model; P54a: Obtain the prediction error probability and error samples of the second-generation model, reconstruct a third training sample set, perform model training, repeat the iterative training until a preset target is reached, obtain the marking frequency of the error samples, extract the error samples that reach the preset frequency for mutation, and construct the nth training sample set; P55a: Use the nth training sample set to continuously iterate and train the n - 1 generation model until a preset number of times or a convergence requirement is reached; P56a: Set the model weight coefficient according to the prediction error probability of each generation of models, perform weighted fusion on all model parameters for the final model parameter configuration, and obtain a grinding evaluation model.

[0035] Specifically, based on the trace deviation information and parameters such as rotational speed, force, and angle during the grinding process, the final grinding effect is evaluated. Exemplarily, a grinding evaluation model can be used to evaluate the grinding effect based on the trajectory deviation information, the grinding rotational speed, grinding force, and grinding angle, and obtain the grinding evaluation effect, including the actual surface roughness, actual shape accuracy, etc.

[0036] Among them, the construction process of the grinding evaluation model can be as follows: First, based on the historical grinding data records, a historical sample set is obtained, and a certain number of samples are randomly selected from the historical sample set as the first training sample set, and an initial average weight is configured for each training sample in the first training sample set. The first training sample set includes different grinding rotational speeds, grinding forces, grinding angles, and corresponding grinding effect identification information.

[0037] Further, the first training sample set is used for neural network training. By continuously adjusting the parameters inside the model to make the prediction result of the model closer to the real result, an initial model, that is, an initial grinding evaluation model, is obtained. Based on the initial model, the training samples are predicted, and the error probability between the prediction result and the actual result is calculated. The samples with incorrect predictions are marked as error samples, and the weights of the error samples are reconfigured to be higher than the average weight, so as to achieve the purpose of paying more attention to the error samples in subsequent training.

[0038] Further, a second training sample set is randomly selected from the historical sample set, and the average weight of the samples in the second training sample set is configured. Further, the second training sample set and the error samples are combined to perform secondary training on the initial model to obtain a second-generation model. Similarly, the prediction error probability and error samples of the second-generation model are obtained, a third training sample set is re-constructed, and model training is carried out, and so on. New training sample sets are continuously constructed and the model is trained until a preset target is reached. The preset target can be the proportion of the historical sample set that has completed training. At the same time, mutation processing is performed according to the marking frequency of the error samples. The error samples that reach the preset frequency are extracted for mutation. Mutation means making certain adjustments to the parameters of the error samples to generate new samples with different characteristics, and the mutated samples and the original samples together constitute the nth training sample set.

[0039] Further, the previous generation of the model is continuously iteratively trained using the nth training sample set until the preset number of training times is reached or the model converges, that is, the performance of the model no longer improves significantly. Finally, after all the iterative trainings are completed, a model weight coefficient is set for each generation of the model according to the prediction error probability of the model. The lower the prediction error probability of the model, the higher its weight coefficient, indicating that the model makes a greater contribution in the final evaluation. Further, according to the model weight coefficient, the parameters of all the models are weighted and fused to obtain a polished evaluation model that combines the advantages of multiple models for subsequent polished effect evaluation work.

[0040] P60: Compare according to the polished target parameters and the polished evaluation effect to obtain polished deviation information; P70: According to the polished deviation information, optimize the configuration of the polishing speed, polishing force, and polishing angle to obtain adjustment parameters, and adjust and control the control parameter information based on the adjustment parameters.

[0041] It should be understood that obtaining the polished target parameters, that is, the final indicators expected to be achieved in lens polishing, such as the target surface roughness, target shape accuracy, etc., compare the polished target parameters and the polished evaluation effect item by item, and perform parameter difference calculation. Exemplarily, by comparing the differences in indicators such as the target surface roughness and the actual surface roughness, the target shape accuracy and the actual shape accuracy, identify the parameters with deviations, as well as the magnitude and direction of the deviations, and use this as the polished deviation information.

[0042] Further, according to the polished deviation information, optimize the configuration of the polishing speed, polishing force, and polishing angle. An optimization algorithm or model, such as a global optimization algorithm, can be used to calculate appropriate adjustment parameters in combination with historical data and real-time feedback, that is, the adjustment ranges of the polishing speed, polishing force, and polishing angle, and adjust the control parameter information based on the adjustment parameters to correct the deviation of the polishing control parameters, and then perform lens polishing control according to the control parameter information to improve the polishing quality and efficiency.

[0043] Further, the embodiment of the present application further includes step P80, and step P80 further includes: P81: Establish a cooperation coefficient between the polishing speed and the polishing force; P82: According to the polished deviation information, determine the deviation distribution characteristics, and obtain the surface roughness of the mirror surface based on the deviation distribution characteristics; P83: Generate a polishing speed adjustment value according to the deviation distribution characteristics and the surface roughness of the mirror surface; P84: Analyze and calculate the polishing force according to the speed adjustment value and the cooperation coefficient to obtain a polishing force adjustment value; P85: Optimize and adjust the control parameter information according to the grinding speed adjustment value and the grinding force adjustment value.

[0044] In a possible embodiment of the present application, a cooperation coefficient between the grinding speed and the grinding force is established according to historical data or experimental data. The cooperation coefficient can reflect the grinding force required to obtain the best grinding effect at different speeds. Further, analyze the grinding deviation information to determine the distribution characteristics of the deviation, including the magnitude, direction, distribution range, etc. of the deviation. Calculate the surface roughness according to the deviation distribution characteristics.

[0045] Further, optimize the grinding speed according to the deviation distribution characteristics and the surface roughness, and combine the corresponding speed adjustment model or formula to generate a grinding speed adjustment value. The speed adjustment model or formula can be obtained by machine learning using empirical data. Further, analyze and calculate the grinding force according to the speed adjustment value and the cooperation coefficient, and deduce the grinding force adjustment value adapted to the speed adjustment value through the cooperation coefficient and the speed adjustment value. Finally, optimize and adjust the control parameter information according to the grinding speed adjustment value and the grinding force adjustment value to improve the grinding effect, reduce the deviation, and improve the surface smoothness of the mirror.

[0046] In summary, the embodiments of the present application have at least the following technical effects: In the present application, by controlling the process nodes and the grinding control positions, the path positions are connected to obtain a preset grinding trajectory. Through the grinding monitoring image, the grinding target is identified and the grinding position is located to determine the grinding execution trajectory. Then, through the fitting and comparison of the grinding trajectories, the trajectory deviation information is obtained, the grinding effect is evaluated and compared, the grinding deviation information is generated, and the control parameter information is adjusted and controlled.

[0047] It achieves the technical effect of improving the grinding accuracy and quality of the lens through the adaptive optimization of the grinding control parameters.

[0048] Embodiment 2 Based on the same inventive concept as the method for controlling the grinding of a lens for a telescopic sight in the foregoing embodiment, as Figure 3 shown, the present application provides a control system for grinding a lens for a telescopic sight. The system in the embodiments of the present application and the method embodiments are based on the same inventive concept. Among them, the system includes: A control parameter information acquisition module 11, which is used to connect to the control module to acquire control parameter information, including control process nodes, grinding control positions, grinding speeds, grinding forces, grinding angles, and grinding target parameters; A grinding preset trajectory acquisition module 12, which is used to connect path positions according to the control process nodes and the grinding control positions in the execution time sequence relationship to obtain a grinding preset trajectory; A grinding execution trajectory determination module 13, which is used to connect an image monitoring module, obtain a grinding monitoring image, perform grinding target recognition, determine a grinding position for positioning with the center of the grinding target recognition result, and determine a grinding execution trajectory; A trajectory fitting comparison module 14, which is used to perform fitting comparison between the grinding execution trajectory and the grinding preset trajectory to obtain trajectory deviation information; A grinding effect evaluation module 15, which is used to evaluate the grinding effect according to the trajectory deviation information, in combination with the grinding speed, grinding force, and grinding angle to obtain a grinding evaluation effect; A grinding deviation information acquisition module 16, which is used to compare according to the grinding target parameters and the grinding evaluation effect to obtain grinding deviation information; A grinding adjustment control module 17, which is used to optimize the configuration of the grinding speed, grinding force, and grinding angle according to the grinding deviation information to obtain adjustment parameters, and perform adjustment control on the control parameter information based on the adjustment parameters.

[0049] Furthermore, the grinding execution trajectory determination module 13 is further used to perform the following steps: Identify the grinding target object and the grinding equipment in the grinding monitoring image to obtain a grinding target object edge recognition result and a grinding equipment positioning recognition result; Determine the center of the grinding target object according to the grinding target object edge recognition result, use the center of the grinding target object as the positioning center, and perform overlapping positioning with the grinding control position in the control parameter information; Based on the overlapping positioning relationship, determine the grinding execution position according to the grinding equipment positioning recognition result; Connect the grinding execution positions according to the monitoring time sequence relationship of the grinding monitoring image to obtain the grinding execution trajectory.

[0050] Furthermore, the grinding execution trajectory determination module 13 is further used to perform the following steps: Establish a grinding configuration relationship between the aiming scope grinding raw material and the grinding target result; Based on the grinding configuration relationship, determine the overlapping center point, construct a structure coordinate system with the overlapping center point as the origin, and fit the edge coordinates of the aiming scope grinding raw material and the grinding target result into the structure coordinate system according to the grinding configuration relationship between the aiming scope grinding raw material and the grinding target result; Based on the control parameter information, perform grinding target fitting according to the control process node, grinding control position, and grinding target parameters to obtain the structure coordinate system of the control process node, which includes the edge coordinate points of the grinding target shape and the grinding control position coordinates; Match according to the monitored grinding process node, obtain the structure coordinate system of the corresponding control process node, overlap the positioning center with the origin of the matching structure coordinate system, fit the grinding execution position into the matching structure coordinate system, and determine the overlapping positioning relationship.

[0051] Further, the trajectory fitting and comparison module 14 is further configured to perform the following steps: Determine the deviation distance and deviation angle according to the trajectory deviation information; Obtain the current grinding positioning, grinding speed, grinding force, and grinding angle; Taking the grinding target parameters as the evaluation target, calculate the grinding loss amount according to the deviation distance, deviation angle, current grinding positioning, grinding speed, grinding force, and grinding angle; When the grinding loss amount is not within the loss range, send a position adjustment instruction, and the position adjustment instruction is used to stop the current grinding control and adjust the grinding position according to the deviation distance and deviation angle.

[0052] Further, the trajectory fitting and comparison module 14 is further configured to perform the following steps: When the grinding loss amount is within the loss range, perform smooth movement analysis on the deviation distance and deviation angle according to the current grinding positioning, grinding speed, grinding force, and grinding angle, determine the movement adjustment parameters, and use the movement adjustment parameters to adjust and control the control parameter information; Among them, the smooth movement analysis is to minimize the power loss value, and use the deviation distance and deviation angle as the movement directions to adjust the control quantity curve of the grinding positioning, grinding speed, grinding force, and grinding angle.

[0053] Further, the grinding effect evaluation module 15 is further configured to perform the following steps: Obtain a historical sample set, randomly select a first training sample set, the first training sample set includes grinding speed, grinding force, grinding angle, and grinding effect identification information, and configure an average weight value for each training sample in the first training sample set; Use the first training sample set to train a neural network to obtain an initial model; Based on the initial model, calculate the prediction error probability, determine the error samples and mark them. The error samples are the training samples with incorrect prediction results. Reconfigure the weights of the error samples. The reconfigured weights are higher than the average weight. Randomly select a second training sample set from the historical sample set, configure the average weight of the samples in the second training sample set, combine it with the error samples, and train the initial model to obtain a second-generation model; Obtain the prediction error probability and error samples of the second-generation model, reconstruct a third training sample set, conduct model training, and repeat the iterative training until a preset target is reached. Obtain the marking frequency of the error samples, extract the error samples that reach the preset frequency for mutation, and construct the nth training sample set; Use the nth training sample set to continuously iterate and train the (n - 1)th generation model until a preset number of times or convergence requirements are met; Set the model weight coefficient according to the prediction error probability of each generation of models, perform weighted fusion on all model parameters for the final model parameter configuration, and obtain a polished evaluation model.

[0054] Furthermore, the system further includes: A cooperation coefficient establishment module, which is used to establish the cooperation coefficient between the polishing speed and the polishing force; A mirror surface roughness acquisition module, which is used to determine the deviation distribution characteristics according to the polishing deviation information and obtain the mirror surface roughness based on the deviation distribution characteristics; A polishing speed adjustment value generation module, which is used to generate a polishing speed adjustment value according to the deviation distribution characteristics and the mirror surface roughness; A polishing force adjustment value acquisition module, which is used to perform polishing force analysis and calculation according to the speed adjustment value and the cooperation coefficient to obtain a polishing force adjustment value; A control parameter information optimization module, which is used to optimize and adjust the control parameter information according to the polishing speed adjustment value and the polishing force adjustment value.

[0055] It should be noted that the above sequence of embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above describes specific embodiments of this specification. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0056] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

[0057] This specification and the drawings are merely exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A lens grinding control method for a sighting scope, characterized in that: The method comprises: Connect to the control module to obtain control parameter information, including control process nodes, grinding control position, grinding speed, grinding force, grinding angle, and grinding target parameters; According to the control process node and the polishing control position, path positions are connected according to the execution timing relationship to obtain a preset polishing trajectory; Connect the image monitoring module, obtain the grinding monitoring image, perform grinding target recognition, determine the grinding position center based on the grinding target recognition result, and determine the grinding execution trajectory; Perform fitting comparison between the polishing execution trajectory and the polishing preset trajectory to obtain trajectory deviation information; According to the trajectory deviation information, the polishing effect is evaluated in combination with the polishing speed, polishing force, and polishing angle to obtain a polishing evaluation effect; Compare the polishing target parameters and the polishing evaluation results to obtain polishing deviation information; According to the grinding deviation information, the grinding speed, grinding intensity, and grinding angle configuration are optimized to obtain adjustment parameters, and the control parameter information is adjusted and controlled based on the adjustment parameters.

2. The method according to claim 1, characterized in that The method of determining the grinding position by centering the grinding target recognition result and determining the grinding execution trajectory includes: Identify the polishing target and the polishing equipment on the polishing monitoring image to obtain the polishing target edge recognition result and the polishing equipment positioning recognition result; Determine the center of the polishing target object according to the edge recognition result of the polishing target object, use the center of the polishing target object as the positioning center, and perform overlapping positioning with the polishing control position in the control parameter information; Based on the overlapping positioning relationship, according to the positioning identification result of the grinding equipment, determining the grinding execution position; According to the monitoring time sequence relationship of the polishing monitoring image, the polishing execution positions are connected to obtain the polishing execution trajectory.

3. The method according to claim 2, characterized in that Taking the center of the polishing target object as the positioning center and performing overlapping positioning with the polishing control position in the control parameter information, includes: Establish the grinding configuration relationship between the sight grinding material and the grinding target result; Based on the polishing configuration relationship, the overlapping center point is determined, and a structural coordinate system is constructed with the overlapping center point as the origin, and the edge coordinates of the polishing raw material of the sight and the polishing target result are fitted into the structural coordinate system according to the polishing configuration relationship between the sight polishing raw material and the polishing target result; Based on the control parameter information, the polishing target is fitted according to the control process node, the polishing control position, and the polishing target parameter to obtain a structural coordinate system of the control process node, which includes edge coordinate points of the polishing target shape and the polishing control position coordinates; Matching is performed according to the monitored polishing process nodes, the structural coordinate system of the corresponding control process node is obtained, the positioning center is overlapped with the origin of the matching structural coordinate system, the polishing execution position is fitted into the matching structural coordinate system, and the overlapping positioning relationship is determined.

4. The method according to claim 1, characterized in that After fitting and comparing the polishing execution trajectory with the polishing preset trajectory to obtain trajectory deviation information, the method further includes: Determine the deviation distance and the deviation angle according to the trajectory deviation information; Get the current grinding position, grinding speed, grinding force, and grinding angle; Taking the grinding target parameters as evaluation targets, the grinding loss amount is calculated according to the deviation distance, deviation angle, current grinding position, grinding speed, grinding force, and grinding angle; When the grinding loss amount is not within the loss range, a position adjustment instruction is sent, and the position adjustment instruction is used to stop the current grinding control and adjust the grinding position according to the deviation distance and deviation angle.

5. The method according to claim 4, characterized in that The method further comprises: When the grinding loss is within the loss range, a smooth movement analysis is performed on the deviation distance and the deviation angle according to the current grinding position, grinding speed, grinding force, and grinding angle, a movement adjustment parameter is determined, and the control parameter information is adjusted and controlled using the movement adjustment parameter; The smooth movement analysis is to minimize the power loss value, take the deviation distance and the offset angle as the moving direction, and adjust the control amount curve of the grinding position, grinding speed, grinding force and grinding angle.

6. The method according to claim 1, characterized in that According to the trajectory deviation information, the polishing effect is evaluated in combination with the polishing speed, polishing force, and polishing angle. Before obtaining the polishing evaluation effect, the method includes: Obtain a historical sample set, randomly select a first training sample set, the first training sample set includes grinding speed, grinding force, grinding angle and grinding effect identification information, and configure an average weight for each training sample in the first training sample set; Using the first training sample set to perform neural network training to obtain an initial model; Calculate the prediction error probability based on the initial model, determine and mark error samples, the error samples are training samples with wrong prediction results, reconfigure the weights of the error samples, reconfigure the weights to be higher than the average weights, and randomly select a second training sample set from the historical sample set, configure the average weights of the samples in the second training sample set, combine them with the error samples, train the initial model, and obtain a second-generation model; Obtain the prediction error probability and error samples of the second-generation model, reconstruct the third training sample set, perform model training, repeat iterative training until the preset goal is reached, obtain the labeling frequency of the error samples, extract the error samples that reach the preset frequency for mutation, and construct the nth training sample set; Continuously iteratively train the n-1 generation model using the nth training sample set until a preset number of times is reached or convergence requirements are met; The model weight coefficients are set according to the prediction error probability of each generation of models, and all model parameters are weightedly fused to configure the final model parameters to obtain a polished evaluation model.

7. The method according to claim 1, characterized in that The method further comprises: Establish the matching coefficient between grinding speed and grinding intensity; Determining deviation distribution characteristics according to the polishing deviation information, and obtaining mirror roughness based on the deviation distribution characteristics; generating a grinding speed adjustment value according to the deviation distribution characteristics and the mirror surface roughness; Perform grinding force analysis and calculation according to the rotation speed adjustment value and the matching coefficient to obtain a grinding force adjustment value; The control parameter information is optimized and adjusted according to the grinding speed adjustment value and the grinding intensity adjustment value.

8. A lens grinding control system for a sighting scope, characterized in that: The system comprises: A control parameter information acquisition module, which is used to connect to the control module and acquire control parameter information, including control process nodes, grinding control positions, grinding speeds, grinding forces, grinding angles, and grinding target parameters; A grinding preset trajectory acquisition module, the grinding preset trajectory acquisition module is used to connect the path positions according to the control process nodes and the grinding control positions according to the execution timing relationship to obtain the grinding preset trajectory; A grinding execution trajectory determination module, which is used to connect to the image monitoring module, obtain the grinding monitoring image, perform grinding target recognition, determine the grinding position center based on the grinding target recognition result, and determine the grinding execution trajectory; A trajectory fitting and comparison module, the trajectory fitting and comparison module is used to perform fitting and comparison according to the polishing execution trajectory and the polishing preset trajectory to obtain trajectory deviation information; A grinding effect evaluation module, wherein the grinding effect evaluation module is used to evaluate the grinding effect according to the trajectory deviation information in combination with the grinding speed, grinding intensity, and grinding angle to obtain a grinding evaluation effect; A grinding deviation information acquisition module, wherein the grinding deviation information acquisition module is used to compare the grinding target parameters and the grinding evaluation effect to obtain the grinding deviation information; A grinding adjustment control module, wherein the grinding adjustment control module is used to optimize the grinding speed, grinding intensity, and grinding angle configuration according to the grinding deviation information, obtain adjustment parameters, and adjust and control the control parameter information based on the adjustment parameters.

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