Intelligent measurement method of cylinder outer diameter based on three-jaw micrometer

Abstract

The present application provides an intelligent measurement method for the outer diameter of a cylinder based on a three-jaw micrometer, and relates to the field of intelligent measurement technology. By acquiring basic information of a target cylindrical part and a three-jaw micrometer, a three-dimensional simulated target is constructed for test analysis, strong limit data is set based on contact pressure damage and a limiter is configured, and a position constraint function is set based on the relative position of the contact and an automatic adjustment module is trained; a monitoring device is arranged in the measurement space of the target cylindrical part; real-time measurement data is acquired, and data analysis and adjustment decisions are performed in combination with the automatic adjustment module, and limit adjustment based on the limiter is performed, and measurement parameter control adjustment is performed on the three-jaw micrometer; parallel measurement of multiple spatial positions is performed, and the outer diameter measurement result is calculated based on the first measurement data and the parallel measurement data. The present application solves the technical problem that the traditional measurement method cannot accurately control the measurement parameters, resulting in limited measurement accuracy and consistency, and improves the accuracy and reliability of the measurement results.

Description

Technical Field

[0001] The present application relates to the field of intelligent measurement technology, and in particular to an intelligent measurement method for the outer diameter of a cylinder based on a three-jaw micrometer. Background Art

[0002] In the field of precision machinery manufacturing, three-jaw micrometer, as a classic measuring tool, is widely used to measure the outer diameter, inner diameter and depth of workpieces. Its measurement accuracy directly affects the quality and production efficiency of products. Traditionally, the measurement process of three-jaw micrometer is highly dependent on the skills and experience of the operator. The operator needs to manually adjust the position of the measuring claw and control the contact force with the workpiece to ensure the accuracy of the measurement. However, this process is easily affected by the operator's skill level, visual judgment and subjective judgment. Minor adjustment errors may introduce measurement errors, especially when facing workpieces with high precision requirements. The technical requirements of the operator are extremely high, which increases the difficulty of measurement. Secondly, for sensitive or high-value workpieces, such as precision parts made of soft materials, improper contact force may cause damage to the workpiece, which not only increases production costs, but also may affect the final performance of the product. Furthermore, manual operation is inefficient, especially when a large number of workpieces need to be measured in batches. The operator needs to repeatedly adjust the measurement parameters, which is time-consuming and easy to cause fatigue, reducing the overall production efficiency. Summary of the invention

[0003] The present application provides an intelligent measurement method for the outer diameter of a cylinder based on a three-jaw micrometer, which solves the technical problem that the traditional measurement method mainly relies on manual operation and cannot accurately control the measurement parameters, resulting in limited measurement accuracy and consistency, thereby achieving the technical effect of improving the accuracy and reliability of the measurement results.

[0004] In view of the above problems, the present application provides an intelligent measurement method for the outer diameter of a cylinder based on a three-jaw micrometer, the method comprising: obtaining basic information of the target cylindrical part and the three-jaw micrometer, and constructing a three-dimensional simulated target; performing test analysis according to the three-dimensional simulated target, setting strong limit data based on contact pressure damage, and setting a position constraint function based on the relative position of the contacts; configuring a limiter based on the strong limit data, and training an automatic adjustment module based on the constraint function, wherein a communication connection is established between the limiter and the automatic adjustment module; arranging a monitoring device for the measurement space of the target cylindrical part, wherein the monitoring device includes an image acquisition device and a force sensor; based on the monitoring device, acquiring real-time measurement data, combining the automatic adjustment module to perform data analysis and adjustment decisions, and executing limit adjustment based on the limiter to determine a measuring jaw control strategy; based on the measuring jaw control strategy, performing measurement parameter control adjustment on the three-jaw micrometer to determine the first measurement data; performing parallel measurement of multiple spatial positions, and calculating the outer diameter measurement result based on the first measurement data and the parallel measurement data.

[0005] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0006] The basic information of the target cylindrical part and the three-jaw micrometer is obtained, and a three-dimensional simulated target is constructed, which provides an accurate model basis for subsequent test analysis. Test analysis is performed according to the three-dimensional simulated target, strong limit data is set based on contact pressure damage, and position constraint function is set based on the relative position of the contact. This link effectively prevents damage and errors in the measurement process by simulating contact pressure and position under different working conditions. The limiter is configured based on the strong limit data, and the automatic adjustment module is trained based on the constraint function. The limiter and the automatic adjustment module establish a communication connection. The combination of the two realizes the precise control of measurement parameters and ensures that the movement of the three-jaw micrometer during the measurement process is accurate and safe. A monitoring device is arranged for the measurement space of the target cylindrical part, wherein the monitoring device includes an image acquisition device and a force sensor, which can obtain measurement data in real time and provide feedback for the automatic adjustment module. Based on the monitoring device, real-time measurement data is obtained, and data analysis and adjustment decisions are made in combination with the automatic adjustment module, and the limit adjustment based on the limiter is performed to determine the measurement jaw control strategy, ensuring the dynamic optimization of the measurement process. Based on the measuring jaw control strategy, the three-jaw micrometer is subjected to measurement parameter control adjustment to determine the first measurement data; parallel measurement of multiple spatial positions is performed, and the outer diameter measurement result is calculated based on the first measurement data and the parallel measurement data, thereby reducing accidental errors and ensuring that the measurement result has good repeatability and reliability.

[0007] In summary, this application integrates modern sensing technology, automatic control technology and three-dimensional simulation technology to achieve precise control of measurement parameters during the measurement process, reduce human errors, and avoid damage to the workpiece. It not only significantly improves the measurement accuracy and reliability, but also greatly improves the measurement efficiency and automation level.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic diagram of a flow chart of an intelligent method for measuring the outer diameter of a cylinder based on a three-jaw micrometer provided in an embodiment of the present application;

[0010] Figure 2 A schematic diagram of a process for setting strong limit data based on contact pressure damage in an intelligent measurement method for outer diameter of a cylinder based on a three-jaw micrometer provided in an embodiment of the present application;

[0011] Figure 3 A schematic diagram of a flow chart of setting a position constraint function based on the relative positions of contacts in an intelligent method for measuring the outer diameter of a cylinder based on a three-jaw micrometer provided in an embodiment of the present application. DETAILED DESCRIPTION

[0012] The embodiment of the present application provides an intelligent measurement method for the outer diameter of a cylinder based on a three-jaw micrometer, thereby solving the technical problem that the traditional measurement method mainly relies on manual operation and cannot accurately control the measurement parameters, resulting in limited measurement accuracy and consistency, thereby achieving the technical effect of improving the accuracy and reliability of the measurement results.

[0013] like Figure 1 As shown, the embodiment of the present application provides an intelligent measurement method for the outer diameter of a cylinder based on a three-jaw micrometer, the method comprising:

[0014] Step S1: Obtain basic information of the target cylindrical part and the three-jaw micrometer to construct a three-dimensional simulated target.

[0015] Specifically, the target cylindrical part refers to any cylindrical workpiece whose size needs to be measured. The three-dimensional simulation target is a high-precision virtual model built using three-dimensional modeling software or technology, which can accurately reflect the real physical properties and structure of the target cylindrical part and the three-jaw micrometer, and is used to simulate the actual measurement process. The basic information of the target cylindrical part includes its size, material properties and shape characteristics, and the basic information of the three-jaw micrometer includes its measurement range, accuracy, physical properties of the measuring claws, etc. By using computer-aided design software or reverse engineering scanning technology, this information can be accurately obtained, and then a three-dimensional simulation model of the target cylindrical part and the three-jaw micrometer can be constructed. For example, for a stainless steel cylindrical part with a diameter of 10mm, its surface texture and precise size can be obtained through a three-dimensional scanning device, and then combined with the measurement range and accuracy parameters of the three-jaw micrometer, a highly simulated three-dimensional model can be constructed using professional CAD software such as SolidWorks or CATIA, laying the foundation for subsequent test analysis.

[0016] Step S2: Performing test analysis based on the three-dimensional simulated target, setting strong limit data based on contact pressure damage, and setting a position constraint function based on the relative position of the contact.

[0017] Specifically, contact pressure damage refers to the phenomenon that when the probe claw contacts the cylindrical part, the surface or inside of the cylindrical part is damaged due to excessive pressure. Strong limit data refers to the maximum allowable contact pressure set, which is used to prevent damage to the cylindrical part during measurement. The relative position of the contact point refers to the relative position of the contact point between the probe claw and the cylindrical part, which has a direct impact on the measurement accuracy. The position constraint function is a mathematical function used to describe and control the optimal position of the contact point between the probe claw and the cylindrical part to ensure measurement accuracy.

[0018] Based on the constructed 3D model, a series of virtual tests are conducted to evaluate the possible damage to the cylindrical part caused by different contact pressures and positions, as well as the impact on the measurement accuracy. Through finite element analysis software such as ANSYS or Abaqus, the stress distribution when the probe claw contacts the cylindrical part can be simulated, and the strong limit data, that is, the maximum allowable contact pressure, can be set to avoid damaging the workpiece. Similarly, by setting the position constraint function, the probe claw is ensured to contact at the optimal position to improve the measurement accuracy. For example, for a cylindrical part made of soft material, it was found through test analysis that when the contact pressure exceeds 5N, the material surface begins to be damaged, so 5N is set as the strong limit data; at the same time, by analyzing the optimal angle and position of the probe claw in contact with the cylindrical part, the position constraint function is set to ensure that the probe claw contacts at the most suitable position to improve the accuracy and repeatability of the measurement.

[0019] Step S3: configuring a limiter based on the strong limit data, training an automatic adjustment module based on the constraint function, and establishing a communication connection between the limiter and the automatic adjustment module.

[0020] Specifically, the stopper is a device used to limit the pressure of the measuring jaw on the cylindrical part to not exceed the strong limit data, protecting the workpiece from damage. The automatic adjustment module is a software or hardware module that can automatically adjust the position and contact force of the measuring jaw according to the constraint function and real-time monitoring data. A wireless communication connection is established between the stopper and the automatic adjustment module to transmit data in real time during the measurement process.

[0021] Based on the strong limit data and position constraint function determined in step S2, the limiter is configured and the automatic adjustment module is trained. The limiter limits the contact force of the measuring claw by physical or electronic means to prevent it from exceeding the strong limit data and protect the workpiece from damage. The automatic adjustment module is trained according to the position constraint function through machine learning algorithms, such as neural networks or support vector machines, to achieve automatic optimization of the measuring claw position and contact force. For example, when configuring the limiter, an electronic pressure sensor and an electromagnetic braking system can be used. Once the contact force is detected to approach or reach 5N, the brake is immediately triggered to prevent damage to the workpiece. The automatic adjustment module is trained through a large amount of experimental data to learn how to automatically adjust the position and contact force of the measuring claw according to the size and material of the cylindrical part to achieve the best measurement effect.

[0022] Step S4: deploying a monitoring device in the measurement space of the target cylindrical part, wherein the monitoring device includes an image acquisition device and a force sensor.

[0023] Specifically, in order to monitor the key parameters in the measurement process in real time, it is necessary to deploy monitoring devices in the measurement space, including but not limited to image acquisition devices and force sensors. The image acquisition device is used to capture the image of the measuring claw in contact with the cylindrical part and monitor the position and state of the measuring claw. The force sensor is used to monitor the magnitude of the contact force between the measuring claw and the cylindrical part. For example, a high-speed industrial camera can be used to capture the instantaneous image of the contact between the measuring claw and the cylindrical part, and the position and contact state of the measuring claw can be identified through image analysis software; at the same time, the force sensor can monitor the change of the contact force in real time. Once it exceeds the set limit, it will immediately feedback to the automatic adjustment module to trigger the limit adjustment.

[0024] Step S5: Based on the monitoring device, real-time measurement data is acquired, data analysis and adjustment decisions are performed in combination with the automatic adjustment module, and the limit adjustment based on the limiter is performed to determine the control strategy of the measuring claw.

[0025] Specifically, the real-time measurement data is the position and contact force data of the measuring claw acquired by the image acquisition device and the force sensor. The measuring claw control strategy is the adjustment scheme of the measuring claw position and contact force determined by the automatic adjustment module.

[0026] With the help of the monitoring device, the image and force data are acquired in real time. The automatic adjustment module analyzes these data to determine whether the position and contact force of the measuring claw need to be adjusted. For example, if the image analysis shows that the measuring claw position deviates from the optimal position, or the force sensor detects that the contact force is close to 5N, the automatic adjustment module will adjust the measuring claw position and reduce the contact force to avoid damaging the workpiece and ensure the accuracy and safety of the measurement. Finally, the automatic adjustment module determines the measuring claw control strategy, including fine-tuning the rotation angle and movement distance of the measuring claw, and adjusting the size of the contact force to achieve the optimal measurement state.

[0027] Step S6: Based on the measuring jaw control strategy, the three-jaw micrometer is adjusted for measurement parameters to determine the first measurement data.

[0028] Specifically, the first measurement data is the first measurement result data recorded after the parameter adjustment is completed, when the target cylindrical part is measured. According to the jaw control strategy determined by the automated adjustment module, the three-jaw micrometer is precisely adjusted for measurement parameters, including the position and contact force of the jaws. For example, the automated adjustment module may instruct the jaws to rotate 10 degrees and move 2mm toward the cylindrical part, while adjusting the contact force to 4N to ensure the accuracy of the measurement and the safety of the workpiece. After the adjustment is completed, the measurement operation is performed and the first set of measurement data, i.e., the first measurement data, is recorded to provide a basis for subsequent analysis.

[0029] Step S7: performing parallel measurement of multiple spatial positions, and calculating the outer diameter measurement result based on the first measurement data and the parallel measurement data.

[0030] Specifically, in order to improve the accuracy and reliability of the measurement, it is necessary to repeat the measurement at multiple spatial positions and collect multiple sets of data. For example, parallel measurements are performed at different angles and positions of a cylindrical part, and each set of measurements follows the same jaw control strategy. After collecting multiple sets of data, the final outer diameter measurement results are calculated through data processing and statistical analysis methods, such as mean value, standard deviation, and least squares method. This process can eliminate random errors, improve the accuracy of the measurement, and ensure the reliability and consistency of the measurement results.

[0031] Further, such as Figure 2 As shown, step S2 of the embodiment of the present application also includes:

[0032] Based on the material characteristics of the cylinder, the contact pressure damage is determined, wherein the contact pressure damage includes static contact damage and moving damage; the parameter conversion relationship between the pressure damage characteristics and the control parameters of the three-jaw micrometer is determined; in combination with the parameter conversion relationship, the first limit data based on the static contact damage is determined; in combination with the parameter conversion relationship, the second limit data based on the moving damage is determined; the contact status of the first limit data and the second limit data is marked to determine the strong limit data.

[0033] Specifically, contact pressure damage includes two types: static contact damage and moving damage. Static contact damage refers to the damage caused when the probe claw is in static contact with the cylindrical part due to the contact pressure exceeding the material's tolerance range. This type of damage is usually related to the area and pressure of the contact point. Moving damage refers to the scratches or wear on the surface of the cylindrical part due to the combined effect of friction and contact pressure when the probe claw moves relative to the cylindrical part during the measurement process. The pressure damage characteristics are physical quantities that describe the degree of contact pressure damage, including damage depth, damage area, damage degree, etc. First, through experiments or finite element analysis, the stress distribution when the probe claw contacts cylindrical parts of different materials is studied to determine the characteristics of static contact damage and moving damage. For example, use finite element analysis software such as ANSYS or Abaqus to simulate the stress distribution when the probe claw contacts the cylindrical part, and analyze the characteristics such as damage depth, width and area.

[0034] Control parameters refer to the parameters used to adjust the position and contact force of the three-jaw micrometer, including the distance the jaws move, the magnitude of the contact force, etc. The parameter-control conversion relationship refers to the mathematical model or relationship between the control parameters and the pressure damage characteristics, which is used to describe the effect of the change of the control parameters on the contact pressure damage. The mathematical model between the control parameters and the pressure damage characteristics is established by experimental data fitting or machine learning methods. First, data is collected through a series of experiments involving the measurement of cylindrical parts using a three-jaw micrometer at different contact forces and speeds. Parameters such as contact force, jaw movement speed, jaw position, and damage degree of the cylindrical parts are recorded in the experiment. Using the collected data, a mathematical model between control parameters such as contact force, jaw movement speed, etc. and damage characteristics such as damage depth, width, area, etc. is established through data analysis and modeling techniques such as linear regression, polynomial regression, neural network, etc. This model describes the expected degree of damage under given control parameters. For example, use Python's Scikit-learn library to train a linear regression model or a support vector machine model, with contact force and movement speed as input and damage depth and area as output, to establish a parameter-control conversion relationship.

[0035] Based on the established parameter-control conversion relationship, the maximum allowable contact force set to prevent damage in static contact and moving contact states is determined. First, an acceptable damage threshold is determined based on the physical properties of the material or the requirements of a specific application. Using the established parameter-control conversion relationship model, the maximum allowable contact force that can be applied by the probe claw in static contact and moving contact states without exceeding the damage threshold is inferred. Experiments are conducted to verify whether the calculated maximum allowable contact force can indeed prevent damage. If the experimental results are inconsistent with expectations, it may be necessary to adjust the parameter-control conversion relationship model or reset the damage threshold until the most appropriate maximum allowable contact force value, i.e., the first limit data and the second limit data, is found. Among them, the first limit data is determined based on static contact damage and is used to limit the threshold of the static contact pressure of the probe claw to prevent static contact damage. The second limit data is determined based on moving damage and is used to limit the threshold of the contact pressure and friction force during the moving process of the probe claw to prevent moving damage. The first limit data and the second limit data are marked with contact states to determine the final strong limit data. The contact state identification is a label or classification used to distinguish the contact state between the measuring claw and the cylindrical part, including "static contact" and "moving contact".

[0036] Through the above steps, it can be ensured that during the measurement process, whether in static contact or moving contact state, the contact force of the measuring claw on the cylindrical part is controlled within a safe range, effectively avoiding contact pressure damage, protecting the integrity of the cylindrical part and the accuracy of the measurement.

[0037] Furthermore, step S2 of the embodiment of the present application further includes:

[0038] Based on the horizontal space, determine the first relative position, wherein the positional relationship is the relative position of the measuring jaws of the three-jaw micrometer, with the contour and the center axis as the analysis basis; based on the vertical space, determine the second relative position; fit the first relative position and the second relative position to determine the relative position of the contact.

[0039] Furthermore, the relative position of the contact points in the embodiment of the present application includes the relative position distribution of each measuring claw based on the contour and the central axis of the target cylindrical part, and the vertical position relationship between the measuring claw and the contour surface.

[0040] Specifically, in three-dimensional space, the horizontal position relationship refers to the position in the plane parallel to the center axis of the cylindrical part. By analyzing the three-dimensional simulated target, measuring the horizontal distance between the measuring claw and the center axis of the cylindrical part, and their angular position in the circumferential direction, the relative position distribution of the measuring claw of the three-jaw micrometer in the circumferential direction, that is, the first relative position, is determined. Among them, the first relative position refers to the position relationship of the measuring claw relative to the contour and center axis of the cylindrical part in the horizontal space, which describes the distribution of the measuring claw in the circumferential direction.

[0041] The vertical position relationship refers to the position in the plane perpendicular to the center axis of the cylindrical part. In the three-dimensional simulation environment, the relative position of the measuring claw on the vertical plane, i.e., the second relative position, is determined by measuring the vertical distance between the measuring claw and the outline of the cylindrical part, simulating the distribution of the measuring claw in the radial or axial direction to ensure that the pressure of the measuring claw can be evenly distributed when in contact. Among them, the second relative position refers to the position relationship of the measuring claw relative to the outline and center axis of the cylindrical part in the vertical space, describing the distribution of the measuring claw in the radial or axial direction.

[0042] The relative position data in the horizontal space and the vertical space are integrated and fitted, and data analysis and fitting techniques, such as multivariate linear regression or nonlinear optimization algorithms, are used to determine the relative position of the contact points. For example, through multivariate linear regression, a position relationship model of the measuring claw in the circumferential direction and the radial direction can be established to accurately describe the contact position between the measuring claw and the contour surface of the cylindrical part. Based on the fitting results, the relative position of the contact point when the measuring claw contacts the cylindrical part can be determined. Among them, the relative position of the contact point includes the relative position distribution of each measuring claw based on the contour and center axis of the target cylindrical part, as well as the vertical position relationship between the measuring claw and the contour surface, to ensure that the measuring claw can contact the cylindrical part in the optimal position during the measurement process, avoid damage caused by excessive local pressure, and ensure the accuracy and repeatability of the measurement.

[0043] Through the above steps, the relative position of the contact point between the measuring jaws of the three-jaw micrometer and the target cylindrical part can be accurately determined, providing an important reference for the subsequent measurement process, ensuring that during the measurement process, the measuring jaws can contact the cylindrical part in the best state, thereby improving the accuracy and reliability of the measurement.

[0044] Further, such as Figure 3 As shown, step S2 of the embodiment of the present application also includes:

[0045] Based on the measurement accuracy requirement, a first tolerance interval is determined; based on the equipment accuracy of the three-jaw micrometer, a second error interval is determined; the difference between the first tolerance interval and the second error interval is calculated as the measurement degree of freedom; based on the measurement degree of freedom and the relative position of the contact, the position constraint function is constructed.

[0046] Specifically, first, clarify the measurement accuracy requirements and the equipment accuracy of the three-jaw micrometer. The measurement accuracy requirements refer to the specific requirements of the user or specific application scenario for the accuracy of the measurement results. For example, for the measurement of precision parts, the accuracy requirement may be ±0.01mm. The equipment accuracy is the accuracy level that the three-jaw micrometer itself can achieve, which is usually provided by the manufacturer, such as ±0.005mm.

[0047] Based on the accuracy requirements, the first tolerance interval is determined, that is, ±0.01mm. Based on the equipment accuracy, the second error interval is determined, that is, ±0.005mm. Among them, the first tolerance interval is determined according to the measurement accuracy requirements, and the allowable range of measurement value changes reflects the expected accuracy of the measurement results. The second error interval is the error range caused by the accuracy limitation of the three-jaw micrometer equipment, which reflects the accuracy limitation of the measuring tool. Calculate the difference between the first tolerance interval and the second error interval. This difference represents the allowable error range in the measurement operation, that is, the measurement freedom, under the premise of meeting the accuracy requirements, which represents the flexibility or fault tolerance in the measurement process.

[0048] Then, based on the measurement degrees of freedom and the relative positions of the contacts, mathematical modeling tools such as MATLAB or Python's NumPy library are used to construct a position constraint function. This function uses the measurement degrees of freedom as constraints to guide the optimal position adjustment of the measuring claws, ensuring that within the measurement degrees of freedom, the relative positions of the contacts can meet the accuracy requirements while avoiding damage to the object being measured.

[0049] For example, when measuring a cylindrical part with a diameter of 50mm, the accuracy requirement is ±0.01mm. The equipment accuracy of the three-jaw micrometer is ±0.005mm. Based on these parameters, it can be determined that the first tolerance interval is ±0.01mm, the second error interval is ±0.005mm, and the measurement freedom is ±0.005mm. Define variables: Let the position of the measuring claw in the circumferential direction be θ i , the vertical distance in the radial direction is d i . Construct the objective function: The goal is to minimize the error between the probe position and the ideal position, that is, ∑(θ i -θ0) 2 and∑(d i -d0) 2, where θ0 and d0 are the ideal positions. Construction constraint: The vertical distance d between the probe jaw and the cylindrical part contour i Must be in [d i -0.005,d i +0.005], and the distribution of the measuring claws must meet the uniformity requirements. Solution: Use the optimization function of MATLAB or Python, input the above objective function and constraints, and solve the measuring claw position that meets the requirements.

[0050] Through this series of steps, the position adjustment of the measuring jaws can be effectively guided and constrained to ensure efficient, accurate and safe measurement operations while meeting the accuracy requirements and equipment accuracy limitations.

[0051] Furthermore, the automatic adjustment module described in the embodiment of the present application includes a fully connected data identification unit and an adjustment decision unit, and the training of the automatic adjustment module in step S3 also includes:

[0052] Obtain correlation features of outer diameter measurement; traverse the correlation features, set an image processing method and a self-attention mechanism, wherein the image processing method is to strengthen the image elements of the correlation features and weaken the remaining image elements; based on the image processing method and the self-attention mechanism, perform data-driven training to obtain the data recognition unit.

[0053] Specifically, the automatic adjustment module includes a fully connected data recognition unit and an adjustment decision unit. The data recognition unit is built and trained based on a neural network model, in which all neurons are interconnected and used to process and identify the characteristics of input data. The adjustment decision unit makes decisions on how to adjust the parameters of the measuring equipment based on the results of the data recognition unit.

[0054] The specific training process includes: First, collect all the features that may affect the measurement accuracy during the outer diameter measurement process, that is, the correlation features of the outer diameter measurement, including but not limited to the parameter settings of the measuring equipment, the ambient temperature, the lighting conditions, the surface roughness of the measured object, etc. Traverse the above collected features and analyze the correlation between each feature and the measurement accuracy. For example, statistical analysis or machine learning algorithms, such as decision trees and random forests, can be used to evaluate the contribution of each feature to the measurement accuracy.

[0055] Based on the correlation of features, the image processing method is set, that is, the image is preprocessed before being input into the neural network to strengthen the image elements that are highly related to the measurement accuracy and weaken the irrelevant elements. At the same time, the self-attention mechanism is introduced so that the model can automatically focus on the areas related to the measurement accuracy and ignore the unimportant parts when processing image data. For example, if it is found that the edge clarity of the measured object is highly correlated with the measurement accuracy, then in image processing, the contrast of the edge area can be enhanced and the background area can be weakened. At the same time, in the self-attention mechanism, the model is set to give priority to the edge area.

[0056] Use a large dataset containing outer diameter measurement data and corresponding measurement results to train the fully connected data recognition unit. Design the network structure of the fully connected neural network, including input layer, hidden layer and output layer, where the hidden layer can have multiple layers and each layer contains multiple neurons. Determine the activation function, loss function and optimization algorithm, such as using ReLU as the activation function, cross entropy loss function, and Adam optimizer. Divide the prepared dataset into a training set and a validation set. The training set is used for model learning, and the validation set is used to monitor model performance and prevent overfitting. Use the training set data to train the model and update the model parameters through the back propagation algorithm to minimize the loss function. At the end of each training cycle, use the validation set to evaluate the model performance and adjust the model parameters such as learning rate, batch size, etc. based on the evaluation results. After the model training is completed, use the independent test set data to conduct a final evaluation of the model to ensure the generalization ability of the model. The evaluation indicators include accuracy, recall, F1 score, etc., depending on the nature of the problem. If the evaluation results are not ideal, it is necessary to return to the model building or data preparation stage, adjust the model parameters or data processing methods, and retrain. According to the model evaluation results, the model is further optimized, such as increasing the network depth, adjusting the learning rate, using a more complex network architecture, etc. Model training is an iterative process that requires multiple adjustments and optimizations until the model converges. During the training process, the model learns how to identify features related to measurement accuracy from the input image data, and how to use the self-attention mechanism to focus on these features to make accurate identification. Through data-driven training, a fully connected data recognition unit that can accurately identify the outer diameter measurement correlation features is finally obtained. This unit can be used as part of the automatic adjustment module for subsequent measurement data processing and adjustment decisions.

[0057] For example, when measuring the outer diameter of a cylindrical part, it is found that the ambient lighting has a significant impact on the measurement accuracy. When setting the image processing method, use Python's OpenCV library for image enhancement, such as local contrast enhancement, to enhance image details under poor lighting conditions. At the same time, in the self-attention mechanism, set the model to prioritize areas with large brightness changes in the image, which may contain more measurement information. Combined with deep learning frameworks such as TensorFlow or PyTorch for data-driven training, the model can learn how to identify and process image data under different lighting conditions, thereby improving the accuracy and reliability of outer diameter measurement.

[0058] Through the above steps, the automated adjustment module will be able to more accurately identify and process key features in outer diameter measurement, thereby improving measurement accuracy and efficiency.

[0059] Furthermore, step S7 of the embodiment of the present application further includes:

[0060] A preset moving distance is set, and multiple spatial positions are determined based on a standard of being greater than or equal to the preset moving distance; based on the first limit data, a strong constraint on the position movement of the target cylindrical part is performed for the multiple spatial positions; based on the second limit data, a strong constraint on the contact measurement of the target cylindrical part is performed for each spatial position.

[0061] Specifically, the preset moving distance is the minimum distance that the probe or probe claw moves in order to cover different measurement areas of the target cylindrical part when performing multi-spatial position measurement. Multi-spatial positions are multiple measurement positions determined according to the preset moving distance during the measurement process to ensure full coverage of the measurement surface of the cylindrical part. The strong constraint on position movement is a strict constraint on the movement of the probe between multiple spatial positions based on the first limit data, ensuring accurate measurement position movement while meeting physical limitations. The strong constraint on contact measurement is a strict constraint on the contact measurement at each spatial position based on the second limit data, ensuring accurate contact measurement while meeting measurement accuracy and equipment capacity limitations.

[0062] First, according to the measurement accuracy requirements and the size of the target cylindrical part, a preset moving distance is set to ensure that the probe can cover the entire measuring surface, while avoiding the reduction of measurement efficiency caused by too small a moving distance. Then, based on the preset moving distance, multiple spatial positions that need to be measured on the target cylindrical part are calculated and determined through coordinate calculation to ensure that the probe can evenly cover the measuring surface of the cylindrical part and avoid measurement blind spots. Considering the first limit data of the movement of the probe or the probe claw, set strong constraints on position movement, such as setting the moving speed and acceleration limits of the probe, to ensure safe and accurate movement within the physical limitations of the equipment. Considering the second limit data of the contact measurement, set strong constraints on the contact measurement, such as setting the pressure range when the contact contacts the cylindrical part, to ensure that while meeting the measurement accuracy requirements, damage to the cylindrical part is avoided. The above process can be performed through mechanical design software such as SolidWorks or AutoCAD for limit data analysis, and programming languages ​​such as Python or MATLAB for data processing and constraint setting. In this way, it can be ensured that the measurement at each spatial position meets the predetermined standards, thereby obtaining a more comprehensive and accurate measurement result of the outer diameter of the cylindrical part.

[0063] Furthermore, step S7 of the embodiment of the present application further includes:

[0064] The first measurement data and the parallel measurement data are identified, and valid measurement data are screened based on the discreteness of data distribution; the valid measurement data are traversed, mean processing is performed, and the outer diameter measurement result is determined.

[0065] Specifically, parallel measurement data refers to measurement data performed at multiple spatial locations. First, collect the first measurement data and parallel measurement data, which come from measurements at multiple spatial locations. Perform statistical analysis on the measurement data at each measurement location, calculate the mean, standard deviation and other statistics of the data, and evaluate the degree of discreteness of the data. Based on the discreteness of data distribution, use statistical methods to identify and exclude outliers and noise influences, and retain valid measurement data. For example, the 3σ criterion excludes data points outside three standard deviations of the mean, that is, any data point outside the mean plus or minus 3 times the standard deviation is considered an outlier. Traverse all the filtered valid measurement data and calculate their mean to eliminate random errors, determine the final outer diameter measurement result, and improve measurement accuracy.

[0066] Through the above steps, the measurement data can be effectively screened and processed, the influence of outliers and random errors can be eliminated, and more accurate and reliable outer diameter measurement results can be obtained.

[0067] In summary, the intelligent measurement method for the outer diameter of a cylinder based on a three-jaw micrometer provided in the embodiment of the present application has the following technical effects:

[0068] The basic information of the target cylindrical part and the three-jaw micrometer is obtained, and a three-dimensional simulated target is constructed, which provides an accurate model basis for subsequent test analysis. Test analysis is performed according to the three-dimensional simulated target, and an accurate parameter control conversion relationship model is established. Strong limit data is set based on contact pressure damage, and position constraint function is set based on the relative position of the contact. This link effectively prevents damage and errors in the measurement process by simulating contact pressure and position under different working conditions. The limiter is configured based on the strong limit data, and the automatic adjustment module is trained based on the constraint function. The limiter and the automatic adjustment module establish a communication connection. The combination of the two realizes the precise control of measurement parameters and ensures that the movement of the three-jaw micrometer during the measurement process is accurate and safe. A monitoring device is arranged for the measurement space of the target cylindrical part, wherein the monitoring device includes an image acquisition device and a force sensor, which can obtain measurement data in real time and provide feedback for the automatic adjustment module. Based on the monitoring device, real-time measurement data is obtained, and data analysis and adjustment decisions are made in combination with the automatic adjustment module, and the limit adjustment based on the limiter is performed to determine the control strategy of the measuring jaws, ensuring the dynamic optimization of the measurement process. Based on the measuring jaw control strategy, the three-jaw micrometer is subjected to measurement parameter control adjustment to determine the first measurement data; parallel measurement of multiple spatial positions is performed, and the outer diameter measurement result is calculated based on the first measurement data and the parallel measurement data, thereby reducing accidental errors and ensuring that the measurement result has good repeatability and reliability.

[0069] Overall, the embodiments of the present application achieve precise control of measurement parameters during the measurement process by integrating modern sensing technology, automated control technology, and three-dimensional simulation technology, reduce human errors, and avoid damage to the workpiece. This not only significantly improves the measurement accuracy and reliability, but also greatly improves the measurement efficiency and automation level.

[0070] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent measurement method for the outer diameter of a cylinder based on a three-jaw micrometer, characterized in that: The method comprises: Obtain basic information of the target cylindrical part and the three-claw micrometer to construct a three-dimensional simulated target; Performing test analysis according to the three-dimensional simulated target, setting strong limit data based on contact pressure damage, and setting a position constraint function based on the relative position of the contact; A limiter is configured based on the strong limit data, an automatic adjustment module is trained based on the constraint function, and a communication connection is established between the limiter and the automatic adjustment module; Arranging a monitoring device for the measurement space of the target cylindrical part, wherein the monitoring device comprises an image acquisition device and a force sensor; Based on the monitoring device, real-time measurement data is obtained, data analysis and adjustment decisions are made in combination with the automatic adjustment module, and the limit adjustment based on the limiter is performed to determine the control strategy of the measuring claw; Based on the measuring jaw control strategy, the three-jaw micrometer is adjusted for measuring parameters and control to determine the first measuring data; Performing parallel measurement of multiple spatial positions, and calculating an outer diameter measurement result based on the first measurement data and the parallel measurement data; The step of setting strong limit data based on contact pressure damage includes: Determine contact pressure damage based on the material properties of the cylinder, wherein the contact pressure damage includes static contact damage and movement damage; Determine the parameter-control conversion relationship between the pressure damage characteristics and the control parameters of the three-jaw micrometer; In combination with the parameter-control conversion relationship, determining first limit data based on the static contact damage; In combination with the parameter-control conversion relationship, determining second limit data based on the movement damage; Performing contact state identification on the first limit data and the second limit data to determine the strong limit data; Wherein, the setting of the position constraint function based on the relative position of the contact point includes: Based on the measurement accuracy requirement, determine the first tolerance interval; Determining a second error interval based on the equipment accuracy of the three-jaw micrometer; Calculate the difference between the first tolerance interval and the second error interval as the measurement degree of freedom; The position constraint function is constructed based on the measured degrees of freedom and the relative positions of the contact points.

2. The intelligent measurement method for outer diameter of a cylinder based on a three-claw micrometer according to claim 1, characterized in that: Determine the relative positions of the contacts, including: Based on the horizontal space, determining a first relative position, wherein the positional relationship is the relative position of the measuring jaws of the three-jaw micrometer, with the contour and the central axis as the analysis basis; Based on the vertical space, determining a second relative position; The first relative position and the second relative position are fitted to determine the relative position of the contact point.

3. The intelligent measurement method for outer diameter of a cylinder based on a three-claw micrometer according to claim 2, characterized in that: The relative position of the contact point includes the relative position distribution of each measuring claw and the vertical position relationship between each measuring claw and the contour surface based on the contour and the central axis of the target cylindrical part.

4. The intelligent measurement method for outer diameter of a cylinder based on a three-claw micrometer according to claim 1, characterized in that: The automatic adjustment module includes a fully connected data identification unit and an adjustment decision unit, and the training automatic adjustment module includes: Obtaining correlation characteristics of outer diameter measurement; Traversing the correlation features, setting an image processing method and a self-attention mechanism, wherein the image processing method is to strengthen the image elements of the correlation features and weaken the remaining image elements; Based on the image processing method and the self-attention mechanism, data-driven training is performed to obtain the data recognition unit.

5. The intelligent measurement method for outer diameter of a cylinder based on a three-claw micrometer according to claim 1, characterized in that: The performing of parallel measurement of multiple spatial positions comprises: Setting a preset moving distance, and determining multiple spatial positions with the distance being greater than or equal to the preset moving distance as a standard; Based on the first limit data, strong constraints are imposed on the position movement of the target cylindrical part to be measured for the multiple spatial positions; Based on the second limit data, a strong constraint on the contact point measurement of the target cylindrical part is performed for each spatial position.

6. The intelligent measurement method for outer diameter of a cylinder based on a three-claw micrometer according to claim 1, characterized in that: The calculated outer diameter measurement result includes: Identify the first measurement data and the parallel measurement data, and screen valid measurement data based on data distribution discreteness; The valid measurement data are traversed, averaged, and the outer diameter measurement result is determined.

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