A Structural Curvature Measurement System Based on Digital Twin

Abstract

The present invention discloses a structural curvature measurement system based on digital twin, comprising: a discharge tip, an edge gateway, and an Internet of Things platform. The discharge tip includes a probe, an auxiliary circuit, and a voltage acquisition system; the probe includes two geometric shapes, namely a conical surface and a spherical head surface; the auxiliary circuit can boost a low-voltage DC power supply, and includes a flyback power transformer, a switching device, a rectifying circuit, and a DC power supply; the switching device can control the working state of the flyback power transformer; the voltage acquisition system includes a sampling circuit and an isolation device to obtain the real-time voltage value of the probe; the edge gateway can measure the critical discharge voltage V c and calibrate the correction coefficient k; the Internet of Things platform can update the model coefficient β through OTA. The overall system integrates sensor and Internet of Things technologies to achieve curvature measurement.

Description

Technical Field

[0001] The present invention relates to an intelligent monitoring device, and specifically to a structural curvature measurement system based on digital twin. Background Art

[0002] Curvature measurement is crucial in fields such as industrial inspection, materials science, and microfabrication, directly affecting the performance and quality of products. For example, during the production of optical lenses, tiny deviations in surface curvature directly affect the optical performance and imaging quality of the lenses. Currently, laser interferometers, contact probes, and optical profilers are commonly used curvature measurement tools. However, when dealing with complex surfaces or tiny curvatures, the measurement accuracy of these traditional devices often fails to meet strict industrial requirements, presenting obvious limitations. These limitations not only affect the reliability of measurement results but also restrict the further optimization and improvement of products.

[0003] Currently, some patent technologies related to curvature measurement have been publicly available on the market. For example, Chinese Patent CN201910760427.4 discloses an optical fiber curvature measurement sensor, its manufacturing method, and a measurement system. The solution realizes the measurement of optical fiber curvature and temperature by calculating the wavelength interval between the Mach-Zehnder interference peak and the resonant absorption peak in the transmission spectrum. However, optical fibers have specific physical dimensions and have obvious drawbacks in the field of micro-curvature measurement. The project applies the principle of tip discharge to curvature measurement and accurately detects the curvature change of the material surface through a non-contact discharge process. This technology overcomes the limitations of traditional contact measurement methods and can achieve high-precision measurement on complex surfaces and microstructures. By measuring the discharge voltage at different curvatures, the surface curvature of the object is deduced inversely.

[0004] To solve the above problems, we have developed a structural curvature measurement system based on digital twin, which combines sensor technology and Internet of Things technology to achieve efficient measurement of complex surface curvature. The overall system not only significantly improves the measurement accuracy but also greatly enhances the flexibility and reliability in industrial inspection. Summary of the Invention

[0005] In view of the above problems, the present invention provides a structural curvature measurement system based on digital twin, which mainly includes: a discharge tip, an edge gateway, and an Internet of Things platform:

[0006] The discharge tip includes a probe, an auxiliary circuit, and a voltage acquisition system; the probe has two geometric shapes, namely a conical surface and a spherical head surface. The conical shape has a lower critical discharge voltage and is suitable for measuring the surface to be measured with a large radius of curvature. The spherical head probe has multiple specifications, and the radii of curvature are respectively 、......、 ; The probe is made of stainless steel, with oxidation resistance, corrosion resistance and good electrical conductivity; The auxiliary circuit can boost the low-voltage DC power supply, including a flyback power transformer, a switching device, a rectifying circuit and a DC power supply; The switching device can control the working state of the transformer and is driven by an STM32L single-chip microcomputer; The voltage acquisition system includes a sampling circuit and an isolation device, which can convert the voltage of the probe into 0-5V, and then use an A / D conversion chip to measure the voltage value, and finally obtain the real-time voltage value of the probe;

[0007] The auxiliary circuit directly drives the probe after boosting the power supply, so that charges accumulate at the tip and significantly enhance the local electric field strength; When the voltage reaches the critical discharge voltage, the surrounding medium is ionized, the system impedance changes suddenly, and the output voltage of the transformer fluctuates significantly; The critical discharge voltage is related to the surface curvature radius to be measured, and the specific relationship is:

[0008]

[0009] where The critical electric field strength of tip discharge is related to the type and pressure of the medium; The type of the medium is expressed as air; is the surface curvature radius to be measured; is a correction coefficient, specifically:

[0010]

[0011] where is the geometric shape parameter of the probe, is the distance between the probe and the surface of the part to be measured, is the angle between the probe and the part to be measured;

[0012] The edge gateway has a 485 interface and can run finite element program code; The edge gateway can perform two-way data interaction with the STM32L single-chip microcomputer to realize the measurement of the critical discharge voltage and the calibration of the correction coefficient ; The calibration of the correction coefficient is carried out by means of a combination of experiments and numerical simulations, and the specific process is as follows:

[0013] S1: Experiment system setup: Use a conical tip and a spherical tip to approach a metal ball with a standard curvature radius respectively to obtain the critical discharge voltage. Among them, the metal balls with standard curvature radii are 、……、 respectively, and the critical voltages are 、……、 ;

[0014] S2: Digital Twin Model Building: Obtain the discharge rules of the conical tip and the spherical tip at different input voltages through finite element simulation, and correct the model parameters of the finite element with the experimental results obtained in S1;

[0015] S3: Parameter Acquisition: By modifying the model parameters of the finite element, calculate the response rules of the model under different dielectrics, different discharge tips, different distances, and different curvature radii, for a total of groups;

[0016] S4: System Calibration: Use different dielectrics, different discharge tips, and different distances as independent variables , respectively , and , and use the correction coefficient as the dependent variable, and use a polynomial model to construct the relationship between the independent variable and the dependent variable. Specifically:

[0017]

[0018] are the model coefficients; subsequently, perform fitting on the groups of data obtained in S3, establish the error equation between the predicted value and the actual value of the correction coefficient , and obtain the optimal model coefficient through the least squares method. Specifically:

[0019]

[0020] The IoT platform supports the access of edge gateways and can realize two-way data interaction; the IoT platform can permanently store the critical discharge voltage , dielectric type, geometric parameters of the discharge tip and distance , and can subsequently correct the model coefficient according to the experimental data and send it to the edge gateway via OTA to realize the iteration of the correction coefficient ; the IoT platform has a visualization large screen and can visually display the data collected by the edge gateway.

[0021] The advantages of the present invention are as follows:

[0022] 1. Strong adaptability: This solution can adapt to various complex geometric shapes. Especially in the case of irregular surfaces where it is difficult to obtain accurate curvature by optical means, it realizes the curvature measurement of very sharp edges or fine structures;

[0023] 2. Efficient data utilization: Measure the curvature of the surface to be measured, and subsequently use the Internet of Things platform to achieve data distribution. Display the microscopic morphology of the object through a visualization large screen, which can be integrated with production equipment and control systems;

[0024] 3. Low cost: Compared with optical measurement systems, it has a lower cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, form a part of the present invention, and do not limit the embodiments of the present invention.

[0026] Figure 1 : Implementation steps of a curvature measurement system based on digital twin.

[0027] Figure 2 : Schematic diagram of a structural curvature measurement system: conical probe and spherical probe.

[0028] Figure 3 : Framework of the discharge tip auxiliary circuit and voltage acquisition system.

[0029] Figure 4 : Working principle of the flyback power transformer.

[0030] Figure 5 : Function modules of the Internet of Things platform. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] In order to make the purpose, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the embodiments and the drawings. The illustrative embodiments of the present invention and their descriptions are only used to explain the present invention and do not limit the present invention.

[0032] APPENDIX Figure 1-2 Disclosed is a structural curvature measurement system based on digital twin, which is characterized by mainly including: a discharge tip, an edge gateway, and an Internet of Things platform:

[0033] The discharge tip includes a probe, an auxiliary circuit, and a voltage acquisition system; the probe includes two geometric shapes, a conical surface and a spherical head surface. The conical shape has a lower critical discharge voltage and is suitable for measuring the surface to be measured with a large radius of curvature. The spherical head probe has multiple specifications, and the radii of curvature are respectively 、......、 ; The probe is made of stainless steel, with oxidation resistance, corrosion resistance and good electrical conductivity; The auxiliary circuit can boost the low-voltage DC power supply, including a transformer, a switching device, a rectifier circuit and a DC power supply; The switching device can control the working state of the transformer and is driven by an STM32L single-chip microcomputer; The voltage acquisition system includes a sampling circuit and an isolation device, which can convert the voltage of the probe into 0-5V, and then use an A / D conversion chip to measure the voltage value, and finally obtain the real-time voltage value of the probe;

[0034] The auxiliary circuit boosts the power supply and directly drives the probe, causing charges to accumulate at the tip and significantly enhancing the local electric field strength; When the voltage reaches the critical discharge voltage, the surrounding medium is ionized, the system impedance changes suddenly, and the output voltage of the transformer fluctuates significantly; The critical discharge voltage is related to the surface curvature radius to be measured, and the specific relationship is:

[0035]

[0036] where The critical electric field strength of tip discharge is related to the type and pressure of the medium; The medium type is expressed as air; is the surface curvature radius to be measured; is a correction coefficient, specifically:

[0037]

[0038] where is the geometric shape parameter of the probe, is the distance between the probe and the surface of the component to be measured, is the angle between the probe and the component to be measured.

[0039] Example 2

[0040] Curvature measurement is crucial in fields such as industrial inspection, materials science, and microfabrication, directly affecting the performance and quality of products. For example: In the manufacturing process of optical lenses, small deviations in surface curvature directly affect the optical performance and imaging quality of the lenses. The following example demonstrates the curvature measurement process:

[0041] The curvature radius of the lens ;

[0042] The distance between the tip and the specimen ;

[0043] The tip uses a spherical probe with a radius ;

[0044] The breakdown electric field strength in air ;

[0045] Calculate the geometric factor based on the calibrated model coefficient β ;

[0046]

[0047] Obtain the critical discharge voltage through the discharge tip auxiliary circuit and the voltage acquisition system , the radius of curvature of the lens is:

[0048]

[0049] Example 3

[0050] Appendix Figure 3 shows the framework of the discharge tip auxiliary circuit and the voltage acquisition system, which mainly includes a flyback power transformer, a switching device, a rectifier circuit, an MCU, a sampling circuit, and an isolation device. The system realizes the boost of the DC power supply.

[0051] Appendix Figure 4 shows the working principle of the flyback power transformer. By the turns ratio of the transformer and the switching device, the boost of the DC power supply is realized. The device stores energy on the primary side and then releases the energy through the secondary winding. The specific working process is as follows:

[0052] S1: Energy storage: When the switching device is turned on, the DC input voltage generates magnetic flux on the primary winding of the transformer through the primary coil, and the energy is stored in the magnetic core of the transformer;

[0053] S2: Energy transfer: When the switching device is turned off, the primary current drops rapidly, resulting in a rapid decrease in the magnetic flux of the primary winding. The magnetic field energy is transferred to the load through the secondary winding;

[0054] S3: Energy release and boost: The secondary winding generates an induced voltage, which is transmitted to the system load through the rectifier circuit. The amplitude of the output voltage can be controlled by the turns ratio of the primary and secondary windings;

[0055] S4: Periodic operation: This process cycles continuously, and the switch turns on and off at a high frequency, continuously transferring and boosting the energy from the DC input power supply to the output end.

[0056] The conditioning circuit effectively improves the performance of the flyback power transformer, ensuring the stable, efficient, and reliable operation of the system. The functions of the front-end rectifier circuit are as follows: 1. Input filtering: High-frequency noise and interference in the power supply; 2. EMI filtering: The flyback power supply generates electromagnetic interference during high-frequency switching operations; 3. Surge current suppression: When the power supply is turned on, a large transient surge current may be generated. The front-end conditioning circuit suppresses the surge current through a current-limiting device to protect the power supply and the transformer.

[0057] The functions of the backend rectifier circuit are as follows: 1. Output filtering: The current passes through the rectifier and filter circuits to convert the AC signal into a DC signal; the rectifier circuit can smooth the output voltage and reduce ripple and noise; 2. Voltage regulation: Through the feedback control system, the switching frequency or duty cycle is adjusted to keep the output voltage constant; 3. Overcurrent and overvoltage protection.

[0058] Implementation Example Four

[0059] The edge gateway has a 485 interface and can run finite element program code; the edge gateway can perform two-way data interaction with the STM32L single-chip microcomputer to achieve the measurement and calibration of the critical discharge voltage and correction coefficient calibration; the correction coefficient calibration is carried out by means of a combination of experiments and numerical simulations. The specific process is as follows:

[0060] S1: Experimental system setup: The conical tip and the spherical tip are respectively brought close to the metal ball with the standard radius of curvature to obtain the critical discharge voltage. Among them, the metal balls with the standard radius of curvature are respectively 、……、 , and the respective critical voltages are 、……、 ;

[0061] S2: Digital twin model setup: Obtain the discharge laws of the conical tip and the spherical tip at different input voltages through finite element simulation, and correct the model parameters of the finite element with the experimental results obtained in S1;

[0062] S3: Parameter acquisition: By modifying the model parameters of the finite element, calculate the response laws of the model under different dielectrics, different discharge tips, different distances, and different radii of curvature, totaling groups;

[0063] S4: System calibration: Take different dielectrics, different discharge tips, and different distances as independent variables , which are respectively , and , take the correction coefficient as the dependent variable, and use a polynomial model to construct the relationship between the independent variable and the dependent variable. Specifically:

[0064]

[0065] are the model coefficients; subsequently, perform fitting on the groups of data obtained in S3, establish the error equation between the predicted value and the actual value of the correction coefficient , and obtain the optimal model coefficients through the least squares method , specifically as follows:

[0066]

[0067] The specific solution process is as follows:

[0068] S1: Initialization: Select an initial point : Select The initial value of, denoted as ; Set the learning rate , take 0.001;

[0069] S2: Calculate the gradient: : In each iteration, calculate the gradient of the objective function At the current point The gradient vector Contains For each parameter The partial derivative of;

[0070]

[0071] S3: Update the parameters: Use the gradient information to update the parameter vector , moving it towards the minimum point, specifically as follows:

[0072]

[0073] Where Is the learning rate. The updated Is the new starting point for the next iteration;

[0074] S4: Check the convergence condition: Repeat S2 and S3 until the change in the model coefficients Between two iterations is less than the preset threshold , that is:

[0075] <

[0076] S5: Result output: When the convergence condition is met, stop the iteration and use the current point As the approximate minimum point, and the corresponding correction coefficient

[0077] Implementation Example Five

[0078] Appendix Figure 5Shows the functional modules of the Internet of Things platform. The Internet of Things platform supports the access of edge gateways and can achieve two-way data interaction; the Internet of Things platform can permanently store the critical discharge voltage Vc, medium type, discharge tip geometric parameter shape, distance distance, and curvature radius R, and can subsequently correct the model coefficients according to experimental data and send them to the edge gateway through the OTA method to achieve the iteration of the correction coefficient . The Internet of Things platform has a visual large screen and can intuitively display the data collected by the edge gateway.

[0079] The Internet of Things platform inherits device management, user management, and data management. It is the foundation for building intelligent factories and deploying artificial intelligence algorithms. Combining the engineering implementation experience of the past many years, the project can meet the needs of fields such as measurement and testing, aerospace, and electric power and energy.

[0080] On the left side of the Internet of Things platform is the navigation bar, which specifically includes the following functional modules:

[0081] 1. Home page: Data large screen;

[0082] 2. Device management: Products, devices, groups;

[0083] 3. Operation and maintenance monitoring: Remote configuration, online debugging, log service, OTA upgrade;

[0084] 4. System management: User management, role management, menu list, interface management, log management.

[0085] The OTA upgrade module can send the model coefficient β to the edge gateway to achieve the iterative optimization of the correction coefficient k.

[0086] The specific implementation methods described above have elaborated in detail the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific implementation manners of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A structural curvature measurement system based on digital twins, characterized in that: Includes: Discharge Tips, Edge Gateways and IoT Platforms: The discharge tip includes a probe, an auxiliary circuit and a voltage acquisition system; the probe includes two geometric shapes: a conical surface and a spherical head surface. The conical shape has a lower critical discharge voltage and is suitable for measuring a surface with a large curvature radius. The spherical head probe has a variety of specifications, and the curvature radius is respectively ,......, ; The probe is made of stainless steel, which has oxidation resistance, corrosion resistance and good conductivity; the auxiliary circuit can boost the low-voltage DC power supply, including a flyback power transformer, a switching device, a rectifier circuit and a DC power supply; the switching device is driven by an STM32L microcontroller to control the working state of the flyback power transformer; the voltage acquisition system includes a sampling circuit and an isolation device, which can convert the voltage of the probe into 0-5V, and then use an A / D conversion chip to measure the voltage value, and finally obtain the real-time voltage value of the probe; The auxiliary circuit directly drives the probe after boosting the power supply, so that the charge is gathered at the tip and the local electric field strength is significantly enhanced; when the voltage reaches the critical discharge voltage, the surrounding medium is ionized, the system impedance suddenly changes, and the output voltage of the flyback power transformer has obvious fluctuations; the critical discharge voltage It is related to the radius of curvature of the surface to be measured. The specific relationship is: in Refers to the critical electric field strength of tip discharge, which is related to the type and pressure of the medium; the medium type is expressed as air; is the radius of curvature of the surface to be measured; is a correction factor, specifically: in are the geometric parameters of the probe, is the distance between the probe and the surface of the object to be tested, is the angle between the probe and the object to be tested; The edge gateway has a 485 interface and can run finite element program code; the edge gateway can perform two-way data interaction with the STM32L microcontroller to achieve critical discharge voltage Measurement and correction factors Calibration; the correction factor The calibration is carried out by combining experiments and numerical simulation. The specific process is as follows: S1: Test system construction: Use metal balls with cone tips and spherical tips close to standard curvature radius to obtain critical discharge voltage. The metal balls with standard curvature radius are ,……, , and their critical voltages are ,……, ; S2: Digital twin model construction: The discharge rules of the cone tip and the ball tip at different input voltages are obtained through finite element simulation, and the finite element model parameters are corrected through the experimental results obtained in S1; S3: Parameter acquisition: The response law of the model under different media, different discharge tips, different distances and different curvature radii is obtained through finite element simulation, a total of Group; S4: System calibration: using different media, different discharge tips and different distances as independent variables , respectively , and , the correction factor As the dependent variable, the response surface method is used to describe the relationship between the independent variable and the dependent variable, specifically: is the model coefficient; the subsequent S3 Fit the data and establish the correction coefficient The error equation between the predicted value and the actual value is used to obtain the optimal model coefficients through the least squares method. , specifically: The IoT platform supports the access of edge gateways and can realize two-way data interaction; the IoT platform can , medium type, discharge tip geometry parameters and distance Permanent storage, the model coefficients can be adjusted based on experimental data later Make corrections and send them to the edge gateway via OTA to achieve the correction coefficient Iteration; The IoT platform has a large visual screen that can intuitively display the data collected by the edge gateway.

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