Method for repairing abnormal curvature of curved glass

Abstract

The invention discloses a method for repairing abnormal curvature of curved glass, which comprises the following steps of: positioning a main repairing area, and identifying a compensation area of a new defect caused by heat conduction by adopting a prediction model. In the repairing process, through the synergistic effect of the main heat source and the auxiliary heat source, parameters of the main heat source and the auxiliary heat source are adjusted according to a global temperature field monitored in real time, management of the thermodynamic state in the repairing process is achieved, and the problem that the temperature field is uneven due to local heating is solved. The technical problem that new profile tolerance is out-of-tolerance or optical distortion is induced while original curvature abnormity is repaired is solved, and it is ensured that the shape precision and the optical performance of the repaired curved glass are synchronously improved.

Description

Technical Field

[0001] This invention relates to the field of glass curvature repair technology, and specifically to a method for repairing abnormal curvature of curved glass. Background Technology

[0002] Abnormal curvature in curved glass can compromise its structural integrity, leading to stress concentration and increasing the risk of spontaneous breakage. It can also cause optical distortion, affecting visual appeal and safety. During assembly, mismatched curvature can result in poor fit and seal failure. Therefore, repair aims to ensure the product's structural safety, optical performance, and assembly reliability, meeting design and application requirements.

[0003] In the thermal repair of curved glass with abnormal curvature, traditional overall heating methods inevitably create temperature gradients on the glass surface due to high thermal inertia and uneven heat transfer. Since glass is a poor conductor of heat, this uneven heating leads to differences in the degree of softening in different areas of the material. This can trigger uncontrollable plastic flow or thermal stress concentration at points of abrupt curvature change, often inducing new contour deviations or optical distortions while repairing the original abnormality, causing the repair process to become an endless cycle. Summary of the Invention

[0004] The purpose of this invention is to provide a method for repairing abnormal curvature of curved glass, so as to solve the technical problem in the prior art that the uneven temperature field causes new contour deviations or optical distortions while repairing the original curvature abnormality.

[0005] The technical solution of this invention is implemented as follows:

[0006] A method for repairing abnormal curvature of curved glass includes the following steps:

[0007] Step S1: Identify the curvature abnormal area in the glass to be inspected, and mark the curvature abnormal area as the main repair area;

[0008] Step S2: Based on the main repair area, obtain at least one compensation area for repairing the main repair area through a prediction model;

[0009] Step S3: Apply the main heat source for repair to the main repair area, and simultaneously apply an auxiliary heat source to the compensation area, while adjusting the temperature change value of the compensation area;

[0010] Step S4: Monitor the temperature field on the surface of the glass to be inspected, and adjust the control parameters of the main heat source and the auxiliary heat source according to the changes in the temperature field.

[0011] A further technical solution is that step S1 specifically includes:

[0012] Step S11: Using a three-dimensional optical scanning device, scan the surface contour of the curved glass to be inspected to obtain its three-dimensional point cloud data.

[0013] Step S12: Perform three-dimensional spatial matching and comparison between the three-dimensional point cloud data and the surface digital model in a unified coordinate system, and generate the first comparison result;

[0014] Step S13: Based on the first comparison result, calculate the normal deviation between the three-dimensional point cloud data and the surface of the curved digital model at various points;

[0015] Step S14: Determine the continuous region where the normal deviation exceeds the preset tolerance threshold as a curvature abnormal region;

[0016] Step S15: Mark all the curvature abnormality areas as the main repair area in the digital model or the associated control system.

[0017] A further technical solution is that step S12 specifically includes:

[0018] Step S121: Based on at least three non-collinear reference feature points on the surface digital model, and the corresponding actual feature points in the three-dimensional point cloud data, the three-dimensional point cloud data is registered using an iterative nearest point algorithm to transform the three-dimensional point cloud data to the coordinate system of the surface digital model.

[0019] Step S122: Calculate the normal deviation and Euclidean distance from each data point in the three-dimensional point cloud data to the theoretical surface of the curved digital model, and generate a dataset containing spatial differences.

[0020] Step S123: Compare the dataset with a preset tolerance threshold and generate a three-dimensional deviation chromatogram and a statistical report of out-of-tolerance areas as the first comparison result.

[0021] A further technical solution is that step S2 specifically includes:

[0022] Step S21: Based on the geometric information of the curved surface digital model and the material thermophysical parameters of the curved glass, construct a finite element analysis model;

[0023] Step S22: In the finite element analysis model, define the energy parameters and application time of the main heat source applied to the main repair area, and perform coupled simulation to simulate the transient temperature field distribution and structural deformation field distribution during the repair process of the main repair area;

[0024] Step S23: Analyze the transient temperature field distribution and structural deformation field distribution, and extract the continuous deformation region that exceeds the preset critical temperature threshold or the structural deformation value exceeds the preset deformation tolerance threshold during the repair process due to heat conduction exceeding the preset critical temperature threshold.

[0025] Step S24: Define all potential continuous deformation regions identified in step S23 as compensation regions to which compensation is applied.

[0026] A further technical solution is that step S23 specifically includes:

[0027] Step S231: Post-process the simulation results of the transient temperature field distribution and structural deformation field distribution, and map the temperature field distribution and deformation field distribution data onto the mesh cells corresponding to the surface digital model;

[0028] Step S232: Compare the temperature value of each grid cell with its corresponding preset critical temperature threshold, and compare the structural deformation value of each grid cell with its corresponding preset deformation tolerance threshold.

[0029] Step S233: Identify all grid cells whose temperature values ​​exceed the preset critical temperature threshold or whose structural deformation values ​​exceed the preset deformation tolerance threshold, and cluster adjacent out-of-tolerance grid cells in space to form at least one continuous deformation region.

[0030] A further technical solution is that step S233 specifically includes:

[0031] Step S2331: Traverse all the mesh cells, mark the mesh cells whose temperature value exceeds the critical temperature threshold or whose structural deformation value exceeds the deformation tolerance threshold as out-of-tolerance state, and record their spatial location index.

[0032] Step S2332: Based on the mesh topology of the surface digital model, establish a spatial adjacency matrix between all mesh cells;

[0033] Step S2333: Based on the spatial adjacency matrix, search for all sets of out-of-range units that are directly or indirectly adjacent in space;

[0034] Step S2334: Define and output each connected set of out-of-tolerance units obtained in step S3 as the continuous deformation region.

[0035] A further technical solution is that step S2334 specifically includes:

[0036] Step S23341: Create a queue to be processed and an empty set;

[0037] Step S23342: Search all grid cells. If the current grid cell is an out-of-tolerance cell and is not in the empty set, then push it into the queue to be processed as a seed.

[0038] Step S23343: Pop the grid cell to be detected from the queue to be processed, add it to the preset connected set, and mark it as processed.

[0039] Step S23344: Query the adjacency matrix to find all adjacent cells of the grid cell to be detected. If the adjacent cell is an out-of-tolerance cell and has not been processed, push it into the processing queue.

[0040] Steps S2, S3, S4, and S5 are repeated until the queue to be processed is empty, and the current preset connected set is marked as the set of out-of-tolerance units.

[0041] A further technical solution is that step S3 includes:

[0042] Step S31: Control the main heat source to act on the main repair area, so that its temperature rises above the glass transition temperature, and control the auxiliary heat source to act on the compensation area;

[0043] Step S32: Obtain the actual temperature data of the compensation area during the repair process using a thermal imager;

[0044] Step S33: Compare the actual temperature data with a preset target temperature range to generate a second comparison result;

[0045] Step S34: Based on the second comparison result, adjust the power parameters of the auxiliary heat source;

[0046] Step S35: Maintain the temperature change value of the compensation area within the preset target temperature range until the repair operation of the main repair area is completed.

[0047] A further technical solution is that step S33 specifically includes:

[0048] Step S331: Calculate the deviation between the real-time temperature data of the compensation area and the median value of the preset target temperature range;

[0049] Step S332: Based on the deviation value, apply the proportional-integral-derivative control algorithm to calculate and output the adjustment amount of the auxiliary heat source power parameter.

[0050] A further technical solution is that step S4 specifically includes:

[0051] Step S41: Obtain the global temperature distribution data of the surface of the glass to be inspected;

[0052] Step S42: Compare the global temperature distribution data with the preset temperature field model in real time to generate a third comparison result;

[0053] Step S43: Based on the third comparison result, control signals for adjusting the power of the main heat source and the auxiliary heat source are generated respectively through the control algorithm;

[0054] Step S44: Send the control signal to the power controller of the main heat source and the auxiliary heat source to adjust their output power.

[0055] The beneficial effects of this invention are as follows:

[0056] By locating the main repair area, a predictive model is used to identify compensation areas for new defects caused by heat conduction. During the repair process, the synergistic effect of the main heat source and auxiliary heat source, along with adjustments to their parameters based on real-time monitoring of the global temperature field, enables the management of the thermodynamic state of the repair process. This solves the technical problem of uneven temperature field caused by local heating, which induces new contour deviations or optical distortions while repairing the original curvature abnormalities. This ensures the simultaneous improvement of the shape accuracy and optical performance of the repaired curved glass. Attached Figure Description

[0057] Figure 1 This is a flowchart illustrating the overall method of the present invention;

[0058] Figure 2 This is a flowchart of step S1 of the present invention;

[0059] Figure 3 This is a flowchart of step S2 of the present invention;

[0060] Figure 4 This is a flowchart of step S3 of the present invention;

[0061] Figure 5 This is a flowchart of step S4 of the present invention. Detailed Implementation

[0062] To better understand the technical content of this invention, specific embodiments are provided below, and the invention will be further described in conjunction with the accompanying drawings.

[0063] See Figures 1 to 5 This invention provides a method for repairing abnormal curvature of curved glass, comprising the following steps:

[0064] Step S1: Identify the curvature abnormal area in the glass to be inspected and mark the curvature abnormal area as the main repair area;

[0065] Step S2: Based on the main repair area, obtain at least one compensation area for repairing the main repair area through a prediction model;

[0066] Step S3: Apply the main heat source for the main repair to the main repair area and simultaneously apply the auxiliary heat source to the compensation area, and adjust the temperature change value of the compensation area.

[0067] Step S4: Monitor the temperature field on the surface of the glass to be inspected, and adjust the control parameters of the main heat source and auxiliary heat source according to the changes in the temperature field.

[0068] It should be noted that the prediction model can be a thermodynamic-structural coupling model.

[0069] In this embodiment of the invention, the initial main repair area, i.e., the curvature anomaly region, is accurately identified and located through 3D scanning and comparison with a digital model. Using a predictive model, the heat conduction patterns in time and space during the repair of the main repair area are simulated and analyzed to predict compensation areas that will experience harmful deformation or stress concentration due to heat. During the repair execution phase, a global temperature feedback system is constructed through the synergistic effect of the main and auxiliary heat sources, combined with real-time infrared thermal imager monitoring data of the entire temperature field. This system dynamically adjusts the power parameters of the main and auxiliary heat sources. While eliminating the original curvature anomaly through the main heat source, it actively regulates the temperature of the compensation area using the auxiliary heat source, thereby suppressing and offsetting the non-uniform temperature field caused by heat diffusion and maintaining the dynamic balance of the entire workpiece's thermodynamic state. This ensures efficient repair of the original curvature anomaly while effectively avoiding secondary defects induced by uneven temperature fields, i.e., preventing new contour deviations or optical distortions, thus improving the yield and product quality of the curved glass repair process.

[0070] This invention locates the main repair area and then uses a predictive model to identify compensation areas for new defects caused by heat conduction. During the repair process, the synergistic effect of the main heat source and auxiliary heat source, along with adjustments to their parameters based on real-time monitoring of the global temperature field, enables the management of the thermodynamic state of the repair process. This solves the technical problem of uneven temperature field caused by local heating, which induces new contour deviations or optical distortions while repairing the original curvature abnormalities. It ensures the simultaneous improvement of the shape accuracy and optical performance of the repaired curved glass.

[0071] Preferably, step S1 specifically includes:

[0072] Step S11: Using a three-dimensional optical scanning device, scan the surface contour of the curved glass to be inspected to obtain its three-dimensional point cloud data.

[0073] Step S12: Perform three-dimensional spatial matching and comparison between the three-dimensional point cloud data and the surface digital model in a unified coordinate system, and generate the first comparison result;

[0074] Step S13: Based on the first comparison result, calculate the normal deviation between the 3D point cloud data and the surface of the curved digital model at various points;

[0075] Step S14: Determine the continuous region where the normal deviation exceeds the preset tolerance threshold as a curvature abnormal region;

[0076] Step S15: Mark all areas of curvature abnormality as the main repair area in the digital model or associated control system.

[0077] In this embodiment of the invention, geometric information of the curved glass surface is acquired through non-contact three-dimensional optical scanning to form three-dimensional point cloud data. The actual data is spatially aligned with the theoretical model using coordinates to establish a benchmark for comparison. Then, the degree of curvature anomaly is calculated from a geometric perspective by calculating the normal deviation between the actual contour and the theoretical model. Finally, abnormal areas are automatically identified based on a preset tolerance threshold and digitally marked, providing precise target localization for subsequent repairs.

[0078] In one example, taking a curved glass panel used in a building curtain wall as an example, its theoretical radius of curvature is 1500mm. Three-dimensional point cloud data containing 500,000 measurement points was obtained through scanning. After registering the 3D point cloud data with the curved surface digital model, calculations revealed a local area of ​​approximately 80mm × 60mm in the central region, with a normal deviation ranging from +0.25mm to +0.38mm, while the preset tolerance threshold is ±0.15mm. This area was identified as a curvature anomaly region. This area was marked in red in the digital model as the main repair area, and its boundary coordinates were recorded to guide subsequent repair work.

[0079] Preferably, step S12 specifically includes:

[0080] Step S121: Based on at least three non-collinear reference feature points on the curved surface digital model, and the corresponding actual feature points in the 3D point cloud data, the 3D point cloud data is registered with the nearest point algorithm to transform the 3D point cloud data to the coordinate system of the curved surface digital model.

[0081] Step S122: Calculate the normal deviation and Euclidean distance from each data point in the 3D point cloud data to the theoretical surface of the curved digital model, and generate a dataset containing spatial differences.

[0082] Step S123: Compare the dataset with the preset tolerance threshold and generate a three-dimensional deviation chromatogram and a statistical report of out-of-tolerance areas as the first comparison result.

[0083] In this embodiment of the invention, the centers of the four corner positioning holes of the curved glass are selected as reference feature points. Based on these reference feature points, the spatial coordinates of the measurement data and the curved digital model are unified using the Iterative Closest Point Algorithm (ICP algorithm), establishing a precise comparison benchmark. By calculating the normal deviation and Euclidean distance from each measurement point to the surface of the curved digital model, the differences between the curved glass and the curved digital model are calculated from different geometric dimensions. For example, after registering the measured point cloud with the theoretical model using the ICP algorithm, the registration error is less than 0.05 mm. Calculations revealed that the normal deviation of a certain area reached 0.25 mm (tolerance ±0.15 mm), and the Euclidean distance deviation was 0.18 mm. Next, by comparing the calculated normal deviation and Euclidean distance with a preset tolerance threshold and visualizing the output, the generated chromatogram shows that this area is a red abnormal area. The statistical report clearly indicates that the out-of-tolerance area accounts for 2.3% of the surface area as the first comparison result. The first comparison result is directly used for subsequent curvature abnormality area determination.

[0084] Preferably, step S2 specifically includes:

[0085] Step S21: Based on the geometric information of the curved surface digital model and the material thermophysical parameters of the curved glass, construct a finite element analysis model;

[0086] Step S22: In the finite element analysis model, define the energy parameters and application time of the main heat source applied to the main repair area, and perform coupled simulation to simulate the transient temperature field distribution and structural deformation field distribution during the repair process of the main repair area.

[0087] Step S23: Analyze the transient temperature field distribution and structural deformation field distribution, and extract the continuous deformation region that exceeds the preset critical temperature threshold or the structural deformation value exceeds the preset deformation tolerance threshold during the repair process due to heat conduction exceeding the preset critical temperature threshold.

[0088] Step S24: Define all potential continuous deformation regions identified in step S3 as compensation regions to which compensation is applied.

[0089] In this embodiment of the invention, a finite element analysis model is constructed using the geometric information and thermophysical parameters of a curved surface digital model, including a material with a thermal conductivity of 0.96 W / (m·K) and a specific heat capacity of 840 J / (kg·K). This model can simulate the transient temperature field distribution and the resulting structural deformation field distribution generated when a main heat source is applied to the main repair area. After establishing the finite element analysis model, a main heat source with a power of 800 W and an application time of 30 seconds is simulated to be applied to the main repair area. The simulation results show that a ring-shaped region is generated around the main repair area, with a temperature reaching 210°C (exceeding the preset critical temperature threshold of 180°C), and the calculated structural deformation value reaches 0.12 mm (exceeding the preset deformation tolerance threshold of 0.08 mm). This ring-shaped region is then identified as a continuous deformation region and formally defined as a compensation region for subsequent application of a compensation heat source.

[0090] Preferably, step S23 specifically includes:

[0091] Step S231: Post-process the simulation results of transient temperature field distribution and structural deformation field distribution, and map the temperature field distribution and deformation field distribution data onto the mesh element corresponding to the surface digital model;

[0092] Step S232: Compare the temperature value of each grid cell with its corresponding preset critical temperature threshold, and at the same time compare the structural deformation value of each grid cell with its corresponding preset deformation tolerance threshold.

[0093] Step S233: Identify all grid cells whose temperature values ​​exceed the preset critical temperature threshold or whose structural deformation values ​​exceed the preset deformation tolerance threshold, and cluster adjacent out-of-tolerance grid cells in space to form at least one continuous deformation region.

[0094] In this embodiment, simulation data of transient temperature field distribution and structural deformation field distribution are mapped to grid cells to establish a correspondence between data and spatial location. Then, a state determination is performed on each grid cell based on a comparison of a preset critical temperature threshold and a preset deformation tolerance threshold, using both temperature and deformation as physical quantities. Finally, a spatial clustering algorithm is used to integrate discrete out-of-tolerance cells into a continuous deformation region.

[0095] In one example, simulation data with a maximum temperature of 287°C and a maximum deformation of 0.15 mm were mapped to the corresponding mesh cells. The data were compared with a preset critical temperature threshold of 220°C and a preset deformation tolerance threshold of 0.10 mm. 86 out-of-tolerance mesh cells were identified and clustered to form a continuous deformation region with an area of ​​approximately 45 mm². This region was accurately defined as the target region that needs to be compensated.

[0096] Preferably, step S233 specifically includes:

[0097] Step S2331: Traverse all mesh cells, mark mesh cells whose temperature value exceeds the critical temperature threshold or whose structural deformation value exceeds the deformation tolerance threshold as out-of-tolerance state, and record their spatial location index.

[0098] Step S2332: Based on the grid topology of the curved surface digital model, establish the spatial adjacency matrix between all grid cells;

[0099] Step S2333: Based on the spatial adjacency matrix, search for all sets of out-of-range units that are directly or indirectly adjacent in space;

[0100] Step S2334: Define and output each set of connected out-of-tolerance cells obtained in step S3 as a continuous deformation region.

[0101] In this embodiment of the invention, all grid cells are traversed, and the initial marking of out-of-tolerance states is completed based on preset critical temperature thresholds and deformation tolerance thresholds. Then, a spatial adjacency relation matrix is ​​established according to the grid topology to clarify the spatial connection relationship between each cell. Finally, based on this matrix, the out-of-tolerance cells with adjacency relationships are aggregated into a continuous region through a connected component analysis algorithm.

[0102] In one example, taking a curved glass finite element model with 12,543 mesh elements as an example, after traversal, 87 mesh elements were found whose temperature exceeded the critical temperature threshold of 220℃ or whose deformation exceeded the deformation tolerance threshold of 0.10mm. The established adjacency matrix showed that the elements formed three independent clusters. Through connected component analysis, three connected sets containing 35, 28, and 24 elements were identified respectively. These three sets were output as three continuous deformation regions with areas of 28mm², 20mm², and 16mm², respectively.

[0103] Preferably, step S2334 specifically includes:

[0104] Step S23341: Create a queue to be processed and an empty set;

[0105] Step S23342: Search all grid cells. If the current grid cell is an out-of-tolerance cell and is not in an empty set, push it into the processing queue as a seed.

[0106] Step S23343: Pop the grid cell to be detected from the queue to be processed, add it to the preset connected set, and mark it as processed.

[0107] Step S23344: Query the adjacency matrix to find all adjacent cells of the grid cell to be detected. If an adjacent cell is an out-of-tolerance cell and has not been processed, push it into the processing queue.

[0108] Steps S2, S3, S4, and S5: Repeat steps S3 and S4 until the queue to be processed is empty, and mark the current preset connected set as the set of out-of-tolerance cells.

[0109] In this embodiment of the invention, a queue to be processed and an empty set are established as the basic structure for data processing. The starting point for regional growth is determined by seed search. Then, the process of popping the current unit, adding it to the connected set, querying adjacent units, and pushing in new seeds is executed in a loop. The adjacency matrix is ​​used as the search basis to finally complete the aggregation of all connected out-of-tolerance units.

[0110] In one example, when analyzing 12,543 mesh elements of curved glass, an empty set and queue are initialized. Mesh element number 3056 is found to be an out-of-tolerance element and has not been processed; it is pushed into the processing queue as a seed. Mesh element 3056 is popped from the processing queue and added to connected set 1. Further investigation reveals that its adjacent elements 3055 and 3057 are also out-of-tolerance elements, which are then pushed into the processing queue. This process is repeated until all 58 connected elements in the region have been processed, ultimately outputting a complete set of out-of-tolerance elements.

[0111] Preferably, step S3 specifically includes:

[0112] Step S31: Control the main heat source to act on the main repair area, so that its temperature rises above the glass transition temperature, and control the auxiliary heat source to act on the compensation area.

[0113] Step S32: Obtain the actual temperature data of the compensation area during the repair process using a thermal imager;

[0114] Step S33: Compare the actual temperature data with the preset target temperature range to generate a second comparison result;

[0115] Step S34: Based on the second comparison result, adjust the power parameters of the auxiliary heat source;

[0116] Step S35: Maintain the temperature change value of the compensation area within the preset target temperature range until the repair operation of the main repair area is completed.

[0117] In this embodiment of the invention, the main repair area is heated to 650°C by controlling the main heat source to reach above the glass transition temperature. At the same time, the auxiliary heat source is turned on to act on the compensation area. The actual temperature of the compensation area is monitored by a thermal imager as 195°C. This temperature is compared with the preset target temperature range of 180-220°C and found to be too low. Based on this comparison result, the power of the auxiliary heat source is increased from 800W to 850W. Through continuous adjustment, the temperature of the compensation area is finally stabilized at 205°C and maintained until the main repair area is repaired. This achieves temperature control of the compensation area and ensures that it is maintained within the preset temperature range throughout the entire repair process.

[0118] Preferably, step S33 specifically includes:

[0119] Step S331: Calculate the deviation between the real-time temperature data of the compensation area and the median value of the preset target temperature range;

[0120] Step S332: Based on the deviation value, apply the proportional-integral-derivative control algorithm to calculate and output the adjustment amount of the auxiliary heat source power parameters.

[0121] In this embodiment of the invention, the difference between the current temperature state and the ideal state is calculated by calculating the deviation between the real-time temperature and the median of the target temperature range. Based on this deviation, a proportional-integral-derivative (PID) control algorithm is applied for comprehensive calculation, wherein the proportional term responds to the current deviation, the integral term eliminates accumulated errors, and the derivative term predicts the changing trend, ultimately outputting a precise adjustment amount for the auxiliary heat source power parameters.

[0122] In one example, the preset target temperature range is 180-220℃, with a midpoint of 200℃. The calculated real-time temperature of the compensation area is 192℃, with a deviation of -8℃. Using a proportional-integral-derivative (PID) control algorithm, based on this deviation, the output is adjusted to increase the auxiliary heat source power by 65W, gradually bringing the temperature closer to the target midpoint. This system can quickly respond to temperature fluctuations and eliminate steady-state errors, ensuring that the temperature in the compensation area remains stably within the preset target range, effectively preventing secondary deformation defects caused by inaccurate temperature control.

[0123] Preferably, step S4 specifically includes:

[0124] Step S41: Obtain the global temperature distribution data of the glass surface to be inspected;

[0125] Step S42: Compare the global temperature distribution data with the preset temperature field model in real time to generate the third comparison result;

[0126] Step S43: Based on the third comparison result, control signals for adjusting the power of the main heat source and the auxiliary heat source are generated respectively through the control algorithm;

[0127] Step S44: Send the control signal to the power controllers of the main heat source and the auxiliary heat source to adjust their output power.

[0128] In this embodiment of the invention, an infrared thermal imager was used to obtain temperature distributions on the glass surface at 320°C (main repair area), 185°C (compensation area), and 95°C (other areas). Comparison with a preset uniform temperature field model revealed that the temperature gradient exceeded the allowable range. A PID control algorithm was used to calculate a control signal that required reducing the main heat source power by 50W and increasing the auxiliary heat source power by 30W. After this adjustment, the overall temperature distribution became more uniform, effectively preventing thermal stress deformation and achieving precise coordinated control of the output power of the two heat sources.

[0129] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for repairing abnormal curvature of curved glass, characterized in that, Includes the following steps: Step S1: Identify the curvature abnormal area in the glass to be inspected, and mark the curvature abnormal area as the main repair area; Step S2: Based on the main repair area, obtain at least one compensation area for repairing the main repair area through a prediction model; Step S3: Apply the main heat source for repair to the main repair area, and simultaneously apply an auxiliary heat source to the compensation area, while adjusting the temperature change value of the compensation area; Step S4: Monitor the temperature field on the surface of the glass to be inspected, and adjust the control parameters of the main heat source and the auxiliary heat source according to the changes in the temperature field.

2. The method for repairing abnormal curvature of curved glass according to claim 1, characterized in that, Step S1 specifically includes: Step S11: Using a three-dimensional optical scanning device, scan the surface contour of the curved glass to be inspected to obtain its three-dimensional point cloud data. Step S12: Perform three-dimensional spatial matching and comparison between the three-dimensional point cloud data and the surface digital model in a unified coordinate system, and generate the first comparison result; Step S13: Based on the first comparison result, calculate the normal deviation between the three-dimensional point cloud data and the surface of the curved digital model at various points; Step S14: Determine the continuous region where the normal deviation exceeds the preset tolerance threshold as a curvature abnormal region; Step S15: Mark all the curvature abnormality areas as the main repair area in the digital model or the associated control system.

3. The method for repairing abnormal curvature of curved glass according to claim 2, characterized in that, Step S12 specifically includes: Step S121: Based on at least three non-collinear reference feature points on the surface digital model, and the corresponding actual feature points in the three-dimensional point cloud data, the three-dimensional point cloud data is registered using an iterative nearest point algorithm to transform the three-dimensional point cloud data to the coordinate system of the surface digital model. Step S122: Calculate the normal deviation and Euclidean distance from each data point in the three-dimensional point cloud data to the theoretical surface of the curved digital model, and generate a dataset containing spatial differences. Step S123: Compare the dataset with a preset tolerance threshold and generate a three-dimensional deviation chromatogram and a statistical report of out-of-tolerance areas as the first comparison result.

4. The method for repairing abnormal curvature of curved glass according to claim 1, characterized in that, Step S2 specifically includes: Step S21: Based on the geometric information of the curved surface digital model and the material thermophysical parameters of the curved glass, construct a finite element analysis model; Step S22: In the finite element analysis model, define the energy parameters and application time of the main heat source applied to the main repair area, and perform coupled simulation to simulate the transient temperature field distribution and structural deformation field distribution during the repair process of the main repair area. Step S23: Analyze the transient temperature field distribution and structural deformation field distribution, and extract the continuous deformation region that exceeds the preset critical temperature threshold or the structural deformation value exceeds the preset deformation tolerance threshold during the repair process due to heat conduction exceeding the preset critical temperature threshold. Step S24: Define all potential continuous deformation regions identified in step S23 as compensation regions to which compensation is applied.

5. The method for repairing abnormal curvature of curved glass according to claim 4, characterized in that, Step S23 specifically includes: Step S231: Post-process the simulation results of the transient temperature field distribution and structural deformation field distribution, and map the temperature field distribution and deformation field distribution data onto the mesh cells corresponding to the surface digital model; Step S232: Compare the temperature value of each grid cell with its corresponding preset critical temperature threshold, and compare the structural deformation value of each grid cell with its corresponding preset deformation tolerance threshold. Step S233: Identify all grid cells whose temperature values ​​exceed the preset critical temperature threshold or whose structural deformation values ​​exceed the preset deformation tolerance threshold, and cluster adjacent out-of-tolerance grid cells in space to form at least one continuous deformation region.

6. The method for repairing abnormal curvature of curved glass according to claim 5, characterized in that, Step S233 specifically includes: Step S2331: Traverse all the mesh cells, mark the mesh cells whose temperature value exceeds the preset critical temperature threshold or whose structural deformation value exceeds the preset deformation tolerance threshold as out-of-tolerance state, and record their spatial location index. Step S2332: Based on the mesh topology of the surface digital model, establish a spatial adjacency matrix between all mesh cells; Step S2333: Based on the spatial adjacency matrix, search for all sets of out-of-tolerance units that are directly or indirectly adjacent in space; Step S2334: Define and output each set of connected out-of-tolerance units obtained in step S2333 as the continuous deformation region.

7. The method for repairing abnormal curvature of curved glass according to claim 6, characterized in that, Step S2334 specifically includes: Step S23341: Create a queue to be processed and an empty set; Step S23342: Search all grid cells. If the current grid cell is an out-of-tolerance cell and is not in the empty set, then push it into the queue to be processed as a seed. Step S23343: Pop the grid cell to be detected from the queue to be processed, add it to the preset connected set, and mark it as processed. Step S23344: Query the adjacency matrix to find all adjacent cells of the grid cell to be detected. If the adjacent cell is an out-of-tolerance cell and has not been processed, push it into the processing queue. Steps S2, S3, S4, and S5 are repeated until the queue to be processed is empty, and the current preset connected set is marked as the set of out-of-tolerance units.

8. The method for repairing abnormal curvature of curved glass according to claim 7, characterized in that, Step S3 specifically includes: Step S31: Control the main heat source to act on the main repair area, raising its temperature above the glass transition temperature, and control the auxiliary heat source to act on the compensation area; Step S32: Obtain the actual temperature data of the compensation area during the repair process using a thermal imager; Step S33: Compare the actual temperature data with a preset target temperature range to generate a second comparison result; Step S34: Based on the second comparison result, adjust the power parameters of the auxiliary heat source; Step S35: Maintain the temperature change value of the compensation area within the preset target temperature range until the repair operation of the main repair area is completed.

9. The method for repairing abnormal curvature of curved glass according to claim 8, characterized in that, Step S33 specifically includes: Step S331: Calculate the deviation between the real-time temperature data of the compensation area and the median value of the preset target temperature range; Step S332: Based on the deviation value, apply the proportional-integral-derivative control algorithm to calculate and output the adjustment amount of the auxiliary heat source power parameter.

10. The method for repairing abnormal curvature of curved glass according to claim 9, characterized in that, Step S4 specifically includes: Step S41: Obtain the global temperature distribution data of the surface of the glass to be inspected; Step S42: Compare the global temperature distribution data with the preset temperature field model in real time to generate a third comparison result; Step S43: Based on the third comparison result, control signals for adjusting the power of the main heat source and the auxiliary heat source are generated respectively through the control algorithm; Step S44: Send the control signal to the power controller of the main heat source and the auxiliary heat source to adjust their output power.

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