Area detection method for hot stamping based on hot stamping label stamping technology

Abstract

The present application relates to the technical field of heat transfer label, and discloses a hot stamping area detection method based on hot stamping technology of heat transfer label.The method comprises the following steps: obtaining a motion trajectory coordinate sequence generated when a hot roller moves along a preset standard hot stamping track; then calculating the area coverage of the actual hot stamping area relative to the standard hot stamping pattern according to the motion trajectory coordinate sequence; if the area coverage is lower than a preset threshold, generating dynamic hot stamping quality benchmark model update parameters based on the difference data between the standard hot stamping quality sample and the current hot stamping result; and finally, reconstructing the hot stamping quality evaluation baseline according to the dynamic hot stamping quality benchmark model update parameters.The method can accurately capture the motion trajectory of the hot roller, objectively quantify the hot stamping area difference, dynamically optimize the hot stamping quality benchmark, improve the detection accuracy and adaptability, help maintain the stable production quality of heat transfer labels, and meet the real-time detection needs in large-scale production.

Description

Technical Field

[0001] This invention relates to the field of heat transfer label technology, specifically a method for detecting the hot stamping area based on heat transfer label hot stamping technology. Background Technology

[0002] In the field of heat transfer label production, the quality of hot stamping directly affects the label's recognizability, durability, and overall appearance. Hot stamping area, as one of the core indicators of hot stamping quality, has a significant impact on the stability of the production process due to the accuracy and timeliness of its detection. Currently, the industry relies heavily on manual visual judgment or traditional static inspection methods for detecting the hot stamping area of ​​heat transfer labels. Manual visual judgment is greatly affected by factors such as the inspector's subjective experience and fatigue level. Different inspectors may have different standards for judging the hot stamping area of ​​the same batch of labels, easily leading to misjudgments or omissions. Especially during mass production, manual inspection is inefficient and cannot meet the real-time inspection needs of large-scale production.

[0003] Traditional static inspection methods pre-set fixed inspection benchmarks and determine whether the hot stamping area is qualified by comparing the current hot stamping result with the fixed benchmark. However, in actual production, the operating status of heat transfer equipment is affected by various factors, such as temperature fluctuations and pressure changes of the hot press roller, mechanical wear of the equipment, and slight differences in the characteristics of raw materials. These factors can cause deviations between the actual hot stamping trajectory and the preset standard hot stamping trajectory, thus affecting the accuracy of the hot stamping area. Because the benchmark of traditional static inspection methods cannot be dynamically adjusted according to changes in equipment operating status and production environment, when the equipment has slight deviations, the static inspection benchmark will still judge according to the initial standard. This may misjudge qualified hot stamping products as unqualified, or fail to identify insufficient hot stamping area caused by equipment deviations in a timely manner, ultimately resulting in unstable product quality, increased production costs, and waste of resources.

[0004] Existing detection methods struggle to quickly pinpoint the root cause and provide effective solutions after identifying abnormal hot stamping areas. Typically, a comprehensive equipment inspection by technicians is required, a time-consuming process that increases production downtime and further impacts efficiency. Furthermore, the lack of a dynamic update mechanism for hot stamping quality benchmarks means that even after equipment adjustments, similar equipment deviations or environmental changes during subsequent production will recur, leading to inaccurate hot stamping area detection. This fails to fundamentally address the challenge of consistently controlling the quality of heat transfer label hot stamping, hindering technological upgrades and development in the heat transfer label manufacturing industry. Summary of the Invention

[0005] The purpose of this invention is to provide a method for detecting the hot stamping area based on thermal transfer label hot stamping technology, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides a method for detecting the hot stamping area based on thermal transfer label hot stamping technology, the method comprising:

[0007] Obtain the motion trajectory coordinate sequence generated when the hot press roller moves along a preset standard hot stamping trajectory;

[0008] The area coverage of the actual hot stamping area relative to the standard hot stamping pattern is calculated based on the motion trajectory coordinate sequence.

[0009] If the area coverage is lower than a preset threshold, then based on the difference data between the standard hot stamping quality sample and the current hot stamping result, a dynamic hot stamping quality benchmark model update parameter is generated.

[0010] The hot stamping quality assessment baseline is reconstructed based on the updated parameters of the dynamic hot stamping quality benchmark model.

[0011] Preferably, calculating the area coverage of the actual hot stamping area relative to the standard hot stamping pattern based on the motion trajectory coordinate sequence includes:

[0012] The motion trajectory coordinate sequence is mapped to a two-dimensional plane coordinate system to generate a polygonal outline of the hot stamping area.

[0013] Calculate the percentage of overlap between the outline polygon of the hot stamping area and the pre-stored standard hot stamping pattern polygon.

[0014] The percentage of overlapping area is output as the area coverage of the actual hot stamping area relative to the standard hot stamping pattern in the dynamic hot stamping quality benchmark model update process.

[0015] Preferably, if the area coverage is lower than a preset threshold, the dynamic hot stamping quality benchmark model update parameters are generated based on the difference data between the standard hot stamping quality sample and the current hot stamping result, including:

[0016] Extract temperature gradient distribution data, pressure distribution matrix, and motion speed sequence from standard hot stamping quality samples;

[0017] By comparing the temperature gradient distribution data, pressure distribution matrix, and motion speed sequence of the current hot stamping result, a three-dimensional parameter deviation vector is generated.

[0018] The parameters are updated based on the dynamic hot stamping quality benchmark model generated by the three-dimensional parameter deviation vector.

[0019] Preferably, the step of reconstructing the hot stamping quality assessment baseline by updating parameters according to the dynamic hot stamping quality benchmark model includes:

[0020] Load the temperature weighting coefficient, pressure weighting coefficient, and speed weighting coefficient of the historical hot stamping quality benchmark model;

[0021] The proportional allocation of the temperature weighting coefficient, pressure weighting coefficient, and velocity weighting coefficient is adjusted according to the three-dimensional parameter deviation vector.

[0022] The hot stamping quality assessment baseline was reconstructed based on the adjusted weighting coefficients.

[0023] Preferably, the method further includes:

[0024] Real-time acquisition of temperature sensor data, pressure sensor data, and displacement encoder data during the movement of the hot press roller;

[0025] The temperature sensor data, pressure sensor data, and displacement encoder data are input into the reconstructed hot stamping quality assessment baseline to generate a real-time hot stamping quality deviation score.

[0026] Preferably, the step of inputting the temperature sensor data, pressure sensor data, and displacement encoder data into the reconstructed hot stamping quality assessment baseline to generate a real-time hot stamping quality deviation score includes:

[0027] The temperature deviation value is calculated based on the temperature sensor data and the temperature weighting coefficient of the reconstructed hot stamping quality assessment baseline.

[0028] The pressure deviation value is calculated based on the pressure sensor data and the pressure weighting coefficient of the reconstructed hot stamping quality assessment baseline.

[0029] The speed deviation value is calculated based on the speed weighting coefficient of the displacement encoder data and the reconstructed hot stamping quality assessment baseline.

[0030] The temperature deviation, pressure deviation, and speed deviation are combined to generate a real-time hot stamping quality deviation score.

[0031] Preferably, the method further includes:

[0032] When the real-time hot stamping quality deviation score exceeds the preset tolerance range, the hot stamping area is divided into grids.

[0033] Extract the temperature distribution feature vector, pressure distribution feature vector, and motion trajectory feature vector for each grid cell.

[0034] Preferably, the extraction of the temperature distribution feature vector, pressure distribution feature vector, and motion trajectory feature vector of each grid cell includes:

[0035] The temperature distribution feature vector of each grid cell is matched with the standard temperature template library for similarity.

[0036] The pressure distribution feature vector of each grid cell is matched with the standard pressure template library for similarity.

[0037] The motion trajectory feature vector of each grid cell is matched with the standard trajectory template library for similarity.

[0038] Output the set of coordinates of abnormal grid cells with a matching degree lower than a set threshold.

[0039] Preferably, the method further includes:

[0040] Optimization instructions for the motion trajectory of the hot press roller are generated based on the coordinate set of abnormal mesh cells;

[0041] The control parameters of the preset standard hot stamping trajectory are adjusted according to the hot press roller motion trajectory optimization command.

[0042] Preferably, the control parameters for adjusting the preset standard hot stamping trajectory according to the hot press roller motion trajectory optimization command include:

[0043] Analyze the spatial distribution pattern of the coordinate set of abnormal mesh elements;

[0044] Calculate the axial compensation, radial compensation, and angular velocity compensation of the hot press roller based on the spatial distribution pattern.

[0045] The axial compensation, radial compensation, and angular velocity compensation are written into the control parameters of the preset standard hot stamping trajectory.

[0046] Compared with the prior art, the beneficial effects of the present invention are:

[0047] This hot stamping area detection method based on thermal transfer label hot stamping technology accurately captures the positional information of the hot press roller during its actual operation by acquiring the coordinate sequence of the motion trajectory generated when the hot press roller moves along a preset standard hot stamping trajectory. This provides a detailed and reliable data foundation for subsequent hot stamping area calculation. Compared with traditional manual visual inspection that relies on subjective judgment, this coordinate sequence-based detection method avoids errors caused by human factors, making the description of the actual hot stamping area more objective and accurate, and more realistically reflecting the actual situation of the hot stamping area.

[0048] When calculating the area coverage of the actual hot stamping area relative to the standard hot stamping pattern, this method uses a motion trajectory coordinate sequence as a basis and obtains the area coverage through a scientific calculation method. This clearly quantifies the difference between the actual hot stamping result and the standard requirements. This quantified presentation of differences allows inspectors to intuitively understand the current hot stamping quality without relying on vague judgments based on experience, greatly improving the reliability of the inspection results. It also provides a clear reference for whether subsequent equipment adjustments are needed, avoiding incorrect or unnecessary adjustments due to vague judgments.

[0049] When the area coverage is below a preset threshold, this method generates dynamic hot stamping quality benchmark model update parameters based on the difference data between the standard hot stamping quality sample and the current hot stamping result. This process achieves dynamic optimization of the hot stamping quality benchmark. In actual production, changes in factors such as equipment operating status and raw material characteristics continuously affect the hot stamping effect. The generation of dynamically updated parameters can fully consider these real-time changing factors, making the hot stamping quality benchmark no longer a fixed static standard, but one that can be adaptively adjusted with changes in production conditions. This dynamic adjustment mechanism can effectively avoid the misjudgment problem caused by the inability of traditional static benchmarks to adapt to production changes, ensuring that even when there are slight changes in the production environment or equipment status, the hot stamping quality benchmark can still match the actual production needs.

[0050] After reconstructing the hot stamping quality assessment baseline based on updated parameters from the dynamic hot stamping quality benchmark model, the new assessment baseline better reflects the current production situation, providing a more accurate judgment standard for subsequent hot stamping quality inspection. During subsequent production, inspection based on the updated assessment baseline can more promptly and accurately identify whether the hot stamping area meets requirements, reducing misjudgments of qualified products or omissions of unqualified products due to benchmark deviations. Furthermore, because the assessment baseline can be continuously updated according to production changes, the entire hot stamping quality inspection system possesses good adaptability and flexibility, capable of handling the inspection needs of different production batches and equipment conditions, helping to maintain the stability of heat transfer label production quality.

[0051] This method, in detecting anomalies in hot stamping area and generating updated parameters, indirectly reflects potential equipment deviations or raw material issues in the current production process, providing direction for technicians to analyze the causes of problems. By analyzing the discrepancies, technicians can more effectively inspect and adjust the equipment without conducting a comprehensive investigation, shortening problem-solving time and reducing losses from production interruptions. Simultaneously, continuous benchmark updates and baseline reconstruction help manufacturers gradually accumulate data experience in the production process, optimize production process parameters, and drive the production process towards greater efficiency and stability, thereby enhancing the company's competitiveness in the heat transfer label production field. Attached Figure Description

[0052] Figure 1 This is a schematic diagram illustrating the working principle of the hot stamping area detection method based on thermal transfer label hot stamping technology described in this invention.

[0053] Figure 2 A flowchart for calculating area coverage;

[0054] Figure 3 A flowchart for generating parameters to update the dynamic hot stamping quality benchmark model;

[0055] Figure 4 A flowchart for detailed calculation of real-time hot stamping quality deviation score. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Please see Figure 1 The present invention provides a method for detecting the hot stamping area based on hot stamping technology for thermal transfer labels, the method comprising:

[0058] The system acquires a sequence of motion trajectory coordinates generated during the movement of the hot press roller along a preset standard hot stamping trajectory. This sequence records the spatial positional changes of the hot press roller during the hot stamping operation. Based on this motion trajectory coordinate sequence, the area coverage of the actual hot stamping area relative to the predetermined standard hot stamping pattern is calculated. When the calculated area coverage is lower than a set threshold, it indicates a deviation in hot stamping quality. At this point, relevant data from a pre-stored standard hot stamping quality sample are extracted and compared with the current hot stamping result. Based on the comparison result, update parameters for a dynamic hot stamping quality benchmark model are generated. Finally, the updated parameters from the generated dynamic hot stamping quality benchmark model are used to reconstruct the hot stamping quality assessment baseline, ensuring the accuracy of subsequent hot stamping quality assessments.

[0059] Example 1: See Figure 2 During the movement of the hot press roller along a preset standard hot stamping trajectory, its spatial position changes are continuously and accurately recorded, forming a motion trajectory coordinate sequence. This sequence contains a series of three-dimensional coordinate points arranged in chronological order, representing the actual spatial path of the hot press roller's motion center or key reference point during the hot stamping operation. The system's preset two-dimensional plane coordinate system is established with the plane where the hot stamping substrate is located as the reference plane, typically selecting a fixed point on the substrate as the origin of the coordinate system. This two-dimensional plane coordinate system has a fixed and known mapping relationship with the spatial position of the hot stamping substrate. All three-dimensional coordinate points in the motion trajectory coordinate sequence are systematically mapped to this two-dimensional plane coordinate system according to preset spatial transformation rules. The mapping process involves rotation and translation transformations of the coordinate system to ensure that the projected positions of the spatial trajectory points on the two-dimensional plane accurately reflect their relative relationship with the hot stamping substrate plane. After mapping, a discrete set of two-dimensional coordinate points is obtained in the two-dimensional plane coordinate system, and these points correspond to the sequence of projected positions of the hot press roller on the substrate plane during its movement.

[0060] The system uses a specific contour construction algorithm to connect the mapped discrete two-dimensional coordinate points into a closed polygon. This algorithm identifies the boundary points of the trajectory based on the spatial order and proximity of the coordinate points, and eliminates outliers that may be caused by measurement noise, ultimately generating a contour polygon that best represents the actual hot stamping boundary area of ​​the hot stamping roller. This polygon is called the hot stamping area contour polygon, and its shape and extent directly define the actual physical coverage area formed on the substrate by this hot stamping operation. Standard hot stamping pattern polygon data is pre-stored in the system database or configuration file. This standard hot stamping pattern polygon accurately describes the shape, size, and position of the standard hot stamping area that the hot stamping roller should cover under ideal process conditions, serving as the geometric benchmark for hot stamping quality evaluation.

[0061] The system performs geometric calculations to determine the spatial overlap between the actual hot stamping area's outline polygon and the pre-stored standard hot stamping pattern polygon on a two-dimensional plane. This calculation is based on computational geometry principles. First, it requires accurately determining the spatial relationship between the two polygons and identifying their intersecting region. Common algorithms include scanline algorithms, convex hull decomposition algorithms, or polygon clipping techniques. The core of the calculation lies in finding the new polygonal region formed by the intersection of the two polygons, i.e., the overlapping region polygon. The area value of the overlapping region polygon is calculated. Simultaneously, the area value of the pre-stored standard hot stamping pattern polygon is obtained. The system calculates the ratio of the area of ​​the overlapping region polygon to the area of ​​the standard hot stamping pattern polygon. This ratio is a value between 0 and 1, where 0 indicates no overlap and 1 indicates complete overlap. This calculated area ratio is defined by the system as the area coverage of the actual hot stamping area relative to the standard hot stamping pattern. This area coverage is a quantitative indicator that objectively reflects the extent to which the actual hot stamping area covers the expected standard hot stamping area.

[0062] After calculating the area coverage, the system uses this value as a key output. This output action is a clearly defined node in the system workflow. The calculated area coverage value is then passed to the subsequent processing stage of the system, namely the update process of the dynamic hot stamping quality benchmark model. In the update process, the area coverage value serves as a core input parameter to determine whether the current hot stamping quality meets the expected standards and may trigger subsequent model adjustment mechanisms. This value is used in the update process to evaluate the geometric fit of the hot stamping operation. The subsequent processing of the area coverage value follows a predetermined program logic. The entire process, from the input of the motion trajectory coordinate sequence to the final output of the area coverage value and the update process of the dynamic hot stamping quality benchmark model, constitutes a complete and automated geometric feature calculation module, serving the quantitative evaluation of hot stamping quality. The generation accuracy of the hot stamping area contour polygon directly affects the accuracy of the area coverage calculation. Therefore, the acquisition accuracy of the motion trajectory coordinate sequence, the accuracy of coordinate mapping, and the robustness of the contour construction algorithm are all factors that need to be considered in the technical implementation. Similarly, the accuracy of the pre-stored standard hot stamping pattern polygons must be guaranteed, ensuring they accurately reflect the geometric requirements of the ideal hot stamping pattern. The selection of the overlap area calculation algorithm needs to consider both computational efficiency and accuracy requirements; in large-scale production environments, efficient and stable algorithms are particularly important. As a core output parameter, the reliability of the area coverage calculation results provides an objective geometric basis for subsequent dynamic model updates. The entire implementation is strictly based on the input coordinate data and pre-stored standard pattern data, and through the system's geometric calculation logic, ultimately outputs a quantified area coverage result.

[0063] Example 2: See Figure 3The system maintains a dataset of standard hot stamping quality samples in a pre-set storage unit. This dataset contains multi-dimensional parameter information defining the ideal hot stamping process state. Specifically, it includes temperature gradient distribution data, which records the temperature values ​​and their gradients that the hot press roller should reach at different spatial points along the standard hot stamping trajectory; a pressure distribution matrix, which defines the standard pressure values ​​that the hot press roller should apply to different areas of the hot stamping substrate surface; and a motion speed sequence, which specifies the ideal motion speed that the hot press roller should maintain at different segments of the trajectory when moving along the preset standard hot stamping trajectory. These parameters together constitute the basic reference for evaluating hot stamping quality. The system synchronously collects and processes data generated by the currently executing or recently completed hot stamping operation, extracting three types of parameters corresponding to the standard sample: temperature gradient distribution data of the current hot stamping operation, the current pressure distribution matrix, and the current motion speed sequence. The system initiates a parameter comparison process. This process compares the temperature gradient distribution data of the current hot stamping result with the temperature gradient distribution data of the standard sample point by point in space. The comparison operation calculates the difference between the current temperature value and the standard temperature value at each corresponding spatial point, forming spatial distribution data reflecting the temperature deviation. The system compares the values ​​of corresponding matrix elements of the current pressure distribution matrix with those of the standard pressure distribution matrix. The comparison operation calculates the difference between the current pressure value and the standard pressure value within each corresponding region cell, forming a spatial distribution matrix reflecting the pressure deviation. The system then performs a point-by-point temporal comparison between the current motion speed sequence and the standard motion speed sequence. This comparison operation calculates the difference between the current motion speed and the standard motion speed at each corresponding time point or position point on the hot stamping trajectory, forming time-series data reflecting the speed deviation. Based on these independent comparison results, the system constructs a comprehensive three-dimensional parameter deviation vector. The first dimension of this vector integrates the spatial distribution information of the temperature deviation, typically formed by transforming the temperature deviation distribution data (e.g., flattening or feature extraction). The second dimension integrates the spatial distribution information of the pressure deviation, also formed by transforming the pressure deviation distribution matrix. The third dimension directly integrates the time-series information of the speed deviation. Finally, these three integrated data sequences are combined in a predetermined order to form a multi-dimensional vector structure, namely the three-dimensional parameter deviation vector. This vector comprehensively and structurally characterizes the overall deviation of the current hot stamping process parameters from the ideal standard parameters in three key dimensions: temperature, pressure, and speed. This three-dimensional parameter deviation vector is explicitly designated by the system as the update parameter for the dynamic hot stamping quality benchmark model, and is used in subsequent model adjustment processes.

[0064] Before updating the model, the system needs to load a historical hot stamping quality benchmark model. This historical model stores a set of weight coefficients that were previously defined or trained using historical data. Specifically, this includes temperature weight coefficients, which quantify the relative importance of temperature parameter changes on hot stamping quality; pressure weight coefficients, which quantify the relative importance of pressure parameter changes on hot stamping quality; and speed weight coefficients, which quantify the relative importance of motion speed parameter changes on hot stamping quality. These weight coefficients are typically set during model initialization and may be adjusted during historical operation. The system analyzes the received three-dimensional parameter deviation vector. The analysis focuses on identifying the magnitude, distribution characteristics, and trend direction of the temperature, pressure, and speed deviations represented by the three dimensions of the vector. Based on the deviation analysis results, the system initiates a weight coefficient proportional allocation adjustment mechanism. The adjustment logic follows these principles: for process parameter dimensions exhibiting significant deviations in the three-dimensional parameter deviation vector, their corresponding weight coefficients will be increased in the proportional allocation. The increase is usually related to the significance of this dimension's deviation relative to other dimension deviations. For process parameter dimensions exhibiting relatively small deviations in the three-dimensional parameter deviation vector, their corresponding weight coefficients will be reduced in the proportional allocation. The reduction is also proportional to the relative magnitude of their deviations. The adjustment operation directly affects the temperature weight coefficient, pressure weight coefficient, and speed weight coefficient. After adjustment, the relative proportions of these three coefficients in the overall model are updated. For example, if current data shows that the temperature deviation is significantly greater than the pressure and speed deviations, the temperature weight coefficient will be increased, increasing its proportion in the total weight; while the pressure and speed weight coefficients may be decreased, reducing their proportions. After the weight coefficient proportional allocation is adjusted, the system performs a reconstruction operation of the hot stamping quality assessment baseline. The reconstruction process uses the adjusted temperature, pressure, and speed weight coefficients as core input parameters. The reconstruction algorithm uses these updated weight coefficients, combined with other basic parameters or structures in the historical model, to recalculate and generate a new set of model parameters or structures through predefined mathematical operations or model update rules. This newly generated set of model parameters or structures constitutes the reconstructed hot stamping quality assessment baseline. This baseline model will replace the original historical model and be used for real-time quality assessment and monitoring of subsequent hot stamping operations.

[0065] Example 3: See Figure 4Throughout the entire hot stamping process performed by the hot press roller, the system continuously and synchronously acquires raw data streams from various physical quantity sensors. Temperature sensor arrays installed at key locations or adjacent areas of the hot press roller generate real-time data reflecting the surface temperature distribution of the hot press roller at a set sampling frequency. This data includes spatial location information and its corresponding instantaneous temperature measurement. Similarly, pressure sensor arrays integrated into the hot press roller's pressure application mechanism or substrate support platform generate real-time data reflecting the pressure distribution applied by the hot press roller to the hot stamping substrate surface at a set sampling frequency. This data includes spatial location information and its corresponding instantaneous pressure measurement. A displacement encoder mechanically coupled to the hot press roller's drive mechanism generates real-time data streams reflecting the linear displacement and rotation angle of the hot press roller with high-precision temporal resolution. This data stream can be further analyzed to obtain the instantaneous velocity vector of the hot press roller, including velocity magnitude and direction information. These real-time data streams from the temperature sensors, pressure sensors, and displacement encoder are assigned a unified timestamp or location index within the system, ensuring a strict spatiotemporal correspondence between different physical quantity data.

[0066] The reconstructed hot stamping quality assessment baseline model runs continuously and provides a real-time data input interface. The aforementioned real-time acquired and pre-processed temperature sensor data streams, pressure sensor data streams, and displacement encoder data streams are continuously updated input information and transmitted in parallel to the model's real-time assessment module. This module contains independent and parallel deviation calculation units. The temperature deviation calculation unit receives the real-time temperature sensor data stream and simultaneously receives the currently effective temperature weighting coefficients from the reconstructed hot stamping quality assessment baseline model. This unit processes the input data according to a preset deviation calculation logic. This logic typically involves comparing the real-time acquired temperature data with the standard expected temperature value (or expected distribution) stored or calculated in the evaluation baseline. The comparison process considers spatial location correspondence and calculates the difference between the real-time temperature and the expected temperature at each spatial point or region. Finally, the unit outputs a scalarized temperature deviation value. This value quantifies the overall deviation of the current temperature distribution from the reconstructed baseline. The pressure deviation calculation unit receives real-time pressure sensor data streams and simultaneously receives the currently active pressure weighting coefficients from the reconstructed hot stamping quality assessment baseline model. This unit performs independent deviation calculation logic, spatially comparing real-time pressure data with the expected pressure value (or expected distribution) in the assessment baseline to calculate the magnitude of the pressure difference. Finally, this unit outputs a scalarized pressure deviation value. The unit quantifies the overall deviation of the current pressure distribution from the baseline. The velocity deviation calculation unit receives motion velocity information parsed in real time from the displacement encoder data stream, and simultaneously receives the currently effective velocity weighting coefficients from the reconstructed hot stamping quality assessment baseline model. This unit compares real-time velocity information (which may include velocity magnitude, direction, or rate of change) with the expected velocity values ​​(or expected sequences) in the evaluation baseline in terms of time or location, calculating the magnitude of the velocity difference. Finally, this unit outputs a scalarized velocity deviation value. This quantifies the overall deviation of the current motion speed from the baseline.

[0067] The system is designed with a specific real-time hot stamping quality deviation scoring function, whose input is the calculation results of the aforementioned three independent deviation values. , , And the corresponding weighting coefficients in the reconstructed baseline model. , , This function integrates deviation information from the three dimensions into a comprehensive score. One specific implementation of the scoring function uses a weighted Euclidean norm:

[0068]

[0069] In this formula: : Represents the real-time hot stamping quality deviation score (dimensionless). : Represents the temperature weighting coefficient (dimensionless) currently defined in the reconstructed hot stamping quality assessment baseline model. : Represents the current temperature deviation measurement value (unit: degrees Celsius °C) output by the temperature deviation calculation unit. : Represents the pressure weighting coefficient (dimensionless) currently defined in the reconstructed hot stamping quality assessment baseline model.

[0070] : Represents the current pressure deviation measurement value (unit: megapascals, MPa) output by the pressure deviation calculation unit.

[0071] : Represents the speed weighting coefficient (dimensionless) currently defined in the reconstructed hot stamping quality assessment baseline model.

[0072] : Represents the current speed deviation metric value (unit: mm / s) output by the speed deviation calculation unit.

[0073] This formula uses various weighting coefficients. , , Magnify or reduce their corresponding deviation values ​​respectively. , , In overall score The contribution of each dimension to the final score. The larger the weighting coefficient, the greater the impact of deviations in its corresponding parameter on the final score. The structure of squares and square roots means that significant deviations in any dimension will affect the score. A significant increase. The rating generation function receives the latest... , , After input, the weight coefficients of the current model are immediately combined. , , Perform the above calculations. The calculated scalar value... The system outputs a real-time hot stamping quality deviation score. This score is a continuously updated value, changing as the hot stamping process progresses and sensor data is continuously input. The value changes dynamically, reflecting in real time the overall deviation of the current hot stamping quality status from the reconstructed hot stamping quality assessment baseline. (Scoring) The higher the value, the greater the deviation between the current overall parameters of the hot stamping operation and the expected baseline. The output is a real-time hot stamping quality deviation score. This data is provided to the system monitoring module or subsequent control logic as a core indicator for evaluating the real-time status of the hot stamping process. The entire process achieves online evaluation of hot stamping quality deviation based on multi-sensor real-time data streams and a dynamic weighting model.

[0074] Example 4: The system continuously monitors the real-time hot stamping quality deviation score. When the score exceeds the upper limit of the preset tolerance range, the system determines that there is a significant abnormality in the current hot stamping quality and automatically activates the abnormal area precise location process. This process first spatially divides the entire hot stamping area where the quality deviation alarm occurred. Based on the pre-configured grid division accuracy parameters, the system uniformly divides the target hot stamping area into several rectangular grid units of equal area on a two-dimensional plane. For example, a typical hot stamping area may be divided into a matrix of 5 rows and 5 columns, totaling 25 grid units. Each grid unit has clear boundary coordinates and a unique identifier, such as G01, G02, etc.

[0075] After mesh generation, the system initiates deep feature extraction of sensor data within each mesh cell. This operation is performed independently for each mesh cell. For temperature distribution characteristics, the system analyzes the raw temperature data sequence collected by all temperature sensors at the boundary and within the mesh cell during the hot stamping process. It calculates the average temperature value within the mesh cell, reflecting the overall heating level of the area. It calculates the direction of the temperature gradient within the mesh cell, for example, identifying whether the temperature increases or decreases from the center to the edge. It calculates the standard deviation of the temperature within the mesh cell, quantifying the uniformity or fluctuation of the temperature distribution within the area. Combining these calculated values, the system generates a feature vector representing the temperature distribution characteristics of the mesh cell. For pressure distribution characteristics, the system analyzes the readings of all pressure sensors acting on the mesh cell. It calculates the average pressure value within the mesh cell, reflecting the overall pressure level experienced by the area. It calculates pressure uniformity indices within the mesh cell, such as calculating the standard deviation of each pressure sensor reading from the average pressure of the cell, or the difference between the maximum and minimum values, characterizing the evenness of the pressure distribution. It identifies the highest pressure value occurring in the mesh cell during the hot stamping process. Combining these values, the system generates a feature vector representing the pressure distribution characteristics of the mesh cell. For motion trajectory characteristics, the system analyzes the trajectory data recorded by the displacement encoder when the center point or key reference point of the hot press roller passes through the grid cell. It calculates the degree of change in motion direction when the hot press roller's trajectory crosses the boundary of the grid cell, i.e., the trajectory curvature characteristic. It also calculates the rate of change of velocity of the hot press roller when entering, passing through, and leaving the grid cell. Finally, it calculates the cumulative residence time of the hot press roller within the space covered by the grid cell. Combining these values, the system generates a feature vector representing the motion trajectory characteristics of the grid cell. Each grid cell ultimately possesses three independent feature vectors: a temperature distribution feature vector, a pressure distribution feature vector, and a motion trajectory feature vector, as shown in Table 1.

[0076] Table 1: Feature Vector Data of Grid Cells in Hot Stamping Area

[0077] Grid cell ID Temperature distribution characteristic vector (°C) Pressure distribution eigenvector (MPa) Motion trajectory feature vector G01 [182.5,1.2,4.8] [1.65,0.18,1.95] [0.015,3.8,0.12] G02 [175.8,-0.8,8.2] [1.48,0.25,1.85] [0.032,5.1,0.08] G03 [188.2,0.5,3.5] [1.72,0.15,1.98] [0.008,2.5,0.15] ... ... ... ... G25 [180.1,1.0,5.0] [1.60,0.20,1.90] [0.010,3.0,0.13]

[0078] The system maintains a predefined library of standard templates, which stores the expected feature vector for each grid cell under ideal hot stamping conditions without quality defects. The standard temperature template library stores the ideal temperature distribution feature vector for each grid cell. The standard pressure template library stores the ideal pressure distribution feature vector for each grid cell. The standard trajectory template library stores the ideal motion trajectory feature vector for each grid cell. The system performs similarity matching calculations between the actual temperature distribution feature vector extracted from each grid cell and the standard temperature feature vector of the corresponding grid cell ID in the standard temperature template library. The matching calculation typically uses a specific distance metric algorithm, such as Euclidean distance or cosine similarity, to calculate the difference between the actual vector and the standard vector, and outputs a numerical score representing the temperature feature similarity. The system performs similarity matching calculations between the actual pressure distribution feature vector extracted from each grid cell and the standard pressure feature vector of the corresponding grid cell ID in the standard pressure template library, outputting a numerical score representing the pressure feature similarity. The system performs similarity matching calculations between the actual motion trajectory feature vector extracted from each grid cell and the standard trajectory feature vector of the corresponding grid cell ID in the standard trajectory template library, outputting a numerical score representing the motion trajectory feature similarity. Each grid cell, after undergoing the three independent similarity matching calculations mentioned above, will yield three similarity scores: temperature similarity score, pressure similarity score, and trajectory similarity score.

[0079] The system sets a uniform matching threshold, which is used to determine whether a grid cell is abnormal. This threshold is a value between 0 and 1. The system checks the three similarity scores of each grid cell one by one. If any of the temperature similarity score, pressure similarity score, or motion trajectory similarity score of a grid cell is lower than the set matching threshold, the grid cell is marked as abnormal. The system collects all grid cells marked as abnormal. The aggregation operation is based on the grid cell's ID identifier. Finally, the system outputs a coordinate set containing the ID identifiers of all abnormal grid cells. For example, this set may contain data like {G02, G05, G07, G12, G23}, clearly indicating which specific spatial locations within the hot stamping area exhibit features that significantly deviate from the standard state, thereby accurately locating the area where the quality anomaly occurred.

[0080] Example 5: The system receives the set of coordinates of abnormal grid cells from the abnormal area positioning process as initial input. This set contains a list of unique identifiers for grid cells identified as having quality deviations, clearly indicating the specific spatial locations within the hot stamping area that require targeted intervention. The system analyzes this set of abnormal grid cell coordinates to extract its spatial distribution information. The analysis process focuses on identifying the geometric distribution characteristics of the abnormal grid cells on the two-dimensional plane of the hot stamping area. It identifies whether the abnormal grid cells exhibit spatial clustering, such as whether multiple abnormal cells are closely adjacent to form local abnormal blocks. It analyzes the distribution density changes of the abnormal grid cells at different axial positions in the hot stamping area to identify whether there is a phenomenon of frequent anomalies at specific axial positions. It determines whether the distribution of the abnormal grid cells exhibits obvious directional characteristics, such as a certain regular arrangement along or perpendicular to the direction of movement of the hot press roller. The identification results of this spatial distribution pattern provide a geometric basis for subsequent compensation calculations.

[0081] Based on the identified spatial distribution pattern characteristics, the system initiates the compensation calculation process. The required displacement compensation along the axis of the hot press roller is calculated. This compensation aims to correct uneven pressure distribution along the roller's length caused by axial deformation, assembly errors, or wear. The calculation primarily considers the aggregation degree and density gradient of abnormal grid cells at the axial projection position of the hot press roller. If abnormal points are concentrated in a certain axial region, the required positive or negative displacement compensation for that segment is calculated to balance the pressure. The required radial displacement compensation perpendicular to the plane of the hot stamping substrate is calculated. This compensation is used to adjust the vertical gap between the hot press roller surface and the hot stamping substrate, ensuring uniform pressure transmission to the substrate surface. The calculation primarily considers the deviation characteristics and spatial positional relationships of abnormal grid cells in the radial pressure distribution. If an abnormal point indicates excessively high or low local pressure, the required upward or downward fine-tuning amount for that corresponding position is calculated. The required angular velocity compensation for the hot press roller's rotation around its central axis is calculated. This compensation is used to dynamically adjust the linear velocity of the hot press roller near the abnormal area, optimizing the hot pressing contact time and thus improving heat transfer efficiency. The calculation primarily considers the deviation of the motion trajectory characteristics of abnormal mesh cells, their spatial position, and their mapping relationship with the rotation angle of the hot press roller. If the abnormal point indicates poor speed matching, the required acceleration or deceleration compensation amount within the corresponding angular range is calculated. The calculation process generates a set of specific compensation parameters: axial compensation, radial compensation, and angular velocity compensation. These compensation amounts are typically expressed as signed scalar values ​​or functions over a specific spatial position / angle range.

[0082] The system encapsulates the calculated axial, radial, and angular velocity compensation values ​​into a structured package, generating an optimization instruction for the hot press roller's motion trajectory. This instruction includes a clear instruction type identifier, target position or angle range information, and corresponding compensation values ​​or function expressions. The instruction format is designed for easy parsing and execution by the motion control system. The hot press roller's motion trajectory optimization instruction is transmitted to the hot press roller's motion control system. The motion control system receives the instruction and activates the parsing module. The parsing module reads the instruction content and extracts the specific values ​​or domains of the axial, radial, and angular velocity compensation values. The system accesses a database or configuration file storing preset standard hot stamping trajectory control parameters. This database stores a set of key parameters for controlling the hot press roller's motion, including the target position, speed curve, and pressure setpoint at each point along the trajectory. Based on the target position or angle range information specified in the optimization instruction, the system precisely locates the parameter segment that needs modification within the preset standard hot stamping trajectory control parameter set. Based on the parsed axial compensation value, the parameters controlling the axial translational motion of the hot press roller are adjusted by superimposing within the located parameter segment. The adjustment involves adding or subtracting the corresponding axial compensation value based on the original parameters. Based on the radial compensation amount obtained from the analysis, the parameters controlling the vertical displacement of the hot press roller are adjusted by superposition within the located parameter segment. The adjustment involves adding or subtracting the corresponding radial compensation amount from the original parameters. Based on the angular velocity compensation amount obtained from the analysis, the parameters controlling the rotational speed of the hot press roller are adjusted by superposition within the located parameter segment. The adjustment involves superimposing corresponding acceleration or deceleration compensation amounts within a specified angular range on the original speed curve.

[0083] After updating the preset standard hot stamping trajectory control parameters, the motion control system loads the updated control parameter set into the actuator drive module. Based on the new axial, radial, and angular velocity control parameters, the actuator drive module generates precise control signals to coordinate the axial movement mechanism, radial lifting mechanism, and rotary drive mechanism of the hot press roller. The hot press roller will strictly follow the optimized motion trajectory to perform subsequent hot stamping operations. When encountering problem areas identified by the abnormal grid cell coordinate set, the movement of the hot press roller will be dynamically fine-tuned according to the written compensation amount. In areas with axial convergence anomalies, the hot press roller will perform axial displacement compensation to alleviate local pressure unevenness. At radial pressure anomalies, the hot press roller will adjust its gap with the substrate to optimize the pressure application effect. In angular ranges with poor speed matching, the hot press roller will dynamically adjust its rotation speed to change the heat contact time. This targeted trajectory compensation based on abnormal position information aims to directly improve the heat transfer effect in previously identified local quality defect areas.

[0084] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0085] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for detecting an area of hot stamping based on a heat transfer label hot stamping technique, characterized by, The method comprises the following steps: acquiring a motion trajectory coordinate sequence generated by the hot press roller when moving along a preset standard hot stamping track; calculating the area coverage of the actual hot stamping area relative to the standard hot stamping pattern according to the motion trajectory coordinate sequence; if the area coverage is lower than a preset threshold, generating dynamic hot stamping quality benchmark model update parameters based on the difference data between the standard hot stamping quality sample and the current hot stamping result; reconstructing the hot stamping quality evaluation baseline according to the dynamic hot stamping quality benchmark model update parameters; if the area coverage is lower than a preset threshold, generating dynamic hot stamping quality benchmark model update parameters based on the difference data between the standard hot stamping quality sample and the current hot stamping result; extracting the temperature gradient distribution data, pressure distribution matrix and motion speed sequence of the standard hot stamping quality sample; comparing the temperature gradient distribution data, pressure distribution matrix and motion speed sequence of the current hot stamping result to generate a three-dimensional parameter deviation vector; and generating dynamic hot stamping quality benchmark model update parameters according to the three-dimensional parameter deviation vector; the step of reconstructing the hot stamping quality evaluation baseline according to the dynamic hot stamping quality benchmark model update parameters comprises the following steps: loading the temperature weight coefficient, pressure weight coefficient and speed weight coefficient of the historical hot stamping quality benchmark model; adjusting the proportional distribution of the temperature weight coefficient, pressure weight coefficient and speed weight coefficient according to the three-dimensional parameter deviation vector; and reconstructing the hot stamping quality evaluation baseline based on the adjusted weight coefficient proportion; real-time collecting temperature sensor data, pressure sensor data and displacement encoder data during the movement of the hot press roller; inputting the temperature sensor data, pressure sensor data and displacement encoder data into the reconstructed hot stamping quality evaluation baseline to generate a real-time hot stamping quality deviation score.

2. The method for detecting the area of hot stamping based on the heat transfer label hot stamping technology according to claim 1, characterized in that, the step of calculating the area coverage of the actual hot stamping area relative to the standard hot stamping pattern according to the motion trajectory coordinate sequence comprises the following steps: mapping the motion trajectory coordinate sequence to a two-dimensional plane coordinate system to generate a hot stamping area contour polygon; calculating the overlapping area proportion of the hot stamping area contour polygon and the pre-stored standard hot stamping pattern polygon; outputting the overlapping area proportion as the area coverage of the actual hot stamping area relative to the standard hot stamping pattern to the dynamic hot stamping quality benchmark model update process.

3. The method of detecting the area of the hot stamping according to the heat transfer label stamping technique according to claim 2, characterized by, the step of inputting the temperature sensor data, pressure sensor data and displacement encoder data into the reconstructed hot stamping quality evaluation baseline to generate a real-time hot stamping quality deviation score comprises the following steps: calculating a temperature deviation value according to the temperature sensor data and the temperature weight coefficient of the reconstructed hot stamping quality evaluation baseline; calculating a pressure deviation value according to the pressure sensor data and the pressure weight coefficient of the reconstructed hot stamping quality evaluation baseline; calculating a speed deviation value according to the displacement encoder data and the speed weight coefficient of the reconstructed hot stamping quality evaluation baseline; fusing the temperature deviation value, pressure deviation value and speed deviation value to generate a real-time hot stamping quality deviation score.

4. The method of detecting the area of hot stamping based on heat transfer label stamping technology according to claim 3, characterized in that, The method further comprises the following steps: when the real-time hot stamping quality deviation score exceeds a preset tolerance range, performing grid segmentation on the hot stamping area; extracting the temperature distribution feature vector, pressure distribution feature vector and motion trajectory feature vector of each grid unit.

5. The method of detecting the area of the hot stamping according to the heat transfer label stamping technique according to claim 4, characterized by, The extracting the temperature distribution feature vector, the pressure distribution feature vector and the motion trajectory feature vector of each grid cell comprises: The temperature distribution feature vector of each grid cell is matched with a standard temperature template library in similarity; The pressure distribution feature vector of each grid cell is matched with a standard pressure template library in similarity; The motion trajectory feature vector of each grid cell is matched with a standard trajectory template library in similarity; The abnormal grid cell coordinate set with a matching degree lower than a set threshold is output.

6. The method of detecting the area of hot stamping based on heat transfer label stamping technology according to claim 5, wherein, Further comprising: Generating a hot press roller motion trajectory optimization instruction based on the abnormal grid cell coordinate set; Adjusting the control parameters of the preset standard thermoprint trajectory according to the hot press roller motion trajectory optimization instruction.

7. The method of detecting the area of hot stamping based on heat transfer label hot stamping technology according to claim 6, characterized in that, The adjusting the control parameters of the preset standard thermoprint trajectory according to the hot press roller motion trajectory optimization instruction comprises: Analyzing the spatial distribution mode of the abnormal grid cell coordinate set; Calculating the axial compensation amount, the radial compensation amount and the angular velocity compensation amount according to the spatial distribution mode; Writing the axial compensation amount, the radial compensation amount and the angular velocity compensation amount into the control parameters of the preset standard thermoprint trajectory.

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