Gluing positioning method for automobile decorative plate

Abstract

The invention relates to the technical field of image processing, and discloses an automobile decorative plate gluing positioning method. The method comprises the following steps: acquiring a decorative plate image, identifying a contour to determine a gluing area, and detecting a material to select an adhesive; setting a reference point to calculate position deviation, and adjusting the position if the deviation is greater than a threshold value; environment temperature and humidity are detected and adjusted, and the surface of the gluing area is activated; generating a track to control coating, and adjusting parameters if the detection uniformity is low; glue distribution is analyzed, and curing parameters are set according to glue types to reach the standard. According to the automobile decorative plates made of different materials, based on material characteristic data and adhesive curing characteristics, self-adaptive accurate gluing positioning and differential curing treatment are achieved, and the quality stability and production efficiency of decorative plate bonding are improved.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and particularly to a method for positioning and applying glue to automotive trim panels. Background Art

[0002] As an important component in the assembly of automotive interior and exterior trims, the installation quality of automotive trim panels directly affects the appearance and service life of the vehicle. Traditional methods for installing automotive trim panels mainly include screw fastening, snap connection, and adhesive bonding. Among them, adhesive bonding is widely used in modern automotive manufacturing due to its flexible operation, beautiful appearance, shock absorption, and noise reduction. Existing glue application technologies for trim panels usually use manual operation or simple automated equipment for adhesive coating, and use heating devices to control the curing process of the adhesive. These methods have formed certain process standards in practical applications, including key links such as adhesive selection, surface treatment, and temperature control, ensuring the basic assembly quality requirements.

[0003] However, the existing methods for positioning and applying glue to trim panels have obvious limitations. First, the diversification of trim panel materials makes it difficult for traditional fixed-parameter glue curing methods to meet the characteristic requirements of different materials, often resulting in quality problems such as thermal deformation of the trim panel or insufficient curing of the adhesive. Second, the planning of the glue application trajectory usually relies on manual experience and lacks accurate data support, resulting in uneven distribution of the adhesive, insufficient bonding strength or waste in local areas. Third, the glue curing process lacks a real-time monitoring and adjustment mechanism and cannot perform differential treatment for the curing states of different areas, affecting the stability of the bonding quality. Fourth, the influence of environmental factors on the performance and curing effect of the adhesive has not been fully considered, and the adaptability under different temperature and humidity conditions is poor. These problems pose challenges in the installation process of automotive trim panels with high-quality requirements, and there is an urgent need for a more intelligent and precise method for positioning and applying glue. Summary of the Invention

[0004] This application provides a method for positioning and applying glue to automotive trim panels, which is used to achieve adaptive precise glue application positioning and differential curing treatment based on the material characteristic data and adhesive curing characteristics of automotive trim panels of different materials, improving the quality stability and production efficiency of trim panel bonding.

[0005] The present application provides a method for positioning and applying glue to an automotive trim panel. The method for positioning and applying glue to the automotive trim panel includes: obtaining an image of the surface of the trim panel, identifying the contour features of the trim panel, determining the coordinates of the glue application target area, and detecting the surface material of the trim panel, and selecting a matching adhesive according to the surface material of the trim panel; setting a positioning reference point, calculating the position deviation value of the trim panel, and if the position deviation value is greater than the first threshold, adjusting the position of the trim panel; detecting the environmental temperature and humidity, and if it exceeds the preset range, adjusting it, and performing a surface activation treatment on the glue application target area; generating a glue application trajectory, controlling a glue application device to apply the glue, and real-time detecting the uniformity of the glue application. If it is lower than the second threshold, adjusting the glue application parameters; collecting and analyzing the glue distribution image, setting the curing parameters according to the type of the adhesive, and performing a curing treatment until the third threshold is reached.

[0006] In the technical solution provided by the present application, by obtaining an image of the surface of the trim panel and identifying the contour features, the coordinates of the glue application target area can be accurately determined, avoiding the errors caused by traditional manual visual judgment and ensuring the accuracy of the glue application position. At the same time, by detecting the surface material of the trim panel, the accurate matching selection of the adhesive is realized, improving the bonding strength and durability. The technical feature of setting a positioning reference point and calculating the position deviation value establishes an accurate control mechanism for the spatial position of the trim panel. When the deviation value is greater than the first threshold, the adjustment process is automatically triggered to ensure that the trim panel is always in the best installation position, providing a stable basis for the subsequent glue application operation. The technical feature of environmental temperature and humidity detection and adjustment solves the problem of the influence of environmental factors on the performance of the adhesive in the traditional method. By controlling the environmental parameters within the preset range and combining the surface activation treatment of the glue application target area, the interfacial bonding force between the adhesive and the surface of the trim panel is significantly improved. The technical feature of generating a glue application trajectory based on the coordinates of the glue application target area and real-time detecting the uniformity of the glue application establishes a closed-loop control mechanism. When the uniformity is lower than the second threshold, real-time compensation is performed by adjusting the glue application parameters, ensuring the consistency of the glue application quality and reducing the problem of insufficient bonding strength caused by uneven application. The technical feature of collecting and analyzing the glue distribution image and setting the curing parameters according to the type of the adhesive realizes differential curing treatment. The curing process ends only when the curing degree reaches the third threshold, ensuring the full curing of the adhesive. By introducing artificial intelligence algorithms such as image recognition, material analysis, environmental monitoring, and real-time feedback, a data-driven decision-making mechanism is established. The algorithm features play a key role in the whole solution, especially in the links of contour recognition, material matching, uniformity evaluation, and curing degree monitoring. The algorithm model can adapt to the material and shape changes of different trim panels, automatically adjust relevant parameters, realize the intelligentization and precision of the process, greatly improve the accuracy and efficiency of the installation of automotive trim panels, and reduce the rework rate and material waste. Description of the Drawings

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

[0008] Figure 1 It is a schematic diagram of an embodiment of the method for gluing and positioning an automotive trim panel in an embodiment of the present application; Figure 2 It is a schematic flowchart of setting positioning reference points and calculating the position deviation value of the trim panel in an embodiment of the present application. Detailed implementation manners

[0009] The embodiments of the present application provide a method for gluing and positioning an automotive trim panel. The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims, and the above-mentioned drawings of the present application are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "comprising" or "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0010] For ease of understanding, the following describes the specific process of the embodiments of the present application. Please refer to Figure 1 An embodiment of the method for gluing and positioning an automotive trim panel in an embodiment of the present application includes: Step S101: Obtain the surface image of the trim panel, identify the contour features of the trim panel, determine the coordinates of the gluing target area, and detect the surface material of the trim panel, and select a matching adhesive according to the surface material of the trim panel; Step S102: Set positioning reference points, calculate the position deviation value of the trim panel. If the position deviation value is greater than the first threshold, adjust the position of the trim panel; Step S103: Detect the environmental temperature and humidity. If it exceeds the preset range, adjust it, and perform surface activation treatment on the gluing target area; Step S104: Generate a gluing trajectory, control the gluing device to apply the glue, and detect the uniformity of the glue coating in real time. If it is lower than the second threshold, adjust the gluing parameters; Step S105: Collect and analyze the glue distribution image, set the curing parameters according to the type of the glue, and perform curing treatment until the third threshold is reached.

[0011] It can be understood that the execution entity of this application can be a glue application positioning system for automotive trim panels, or it can also be a terminal or a server, and no specific limitation is made here. In the embodiments of this application, the server is taken as an example of the execution entity for illustration.

[0012] Specifically, the glue application positioning method for automotive trim panels obtains the surface image of the trim panel through an image acquisition device. A high-resolution industrial camera is often used, combined with an appropriate lighting system, to ensure capturing the fine details on the surface of the trim panel. After obtaining the image, the contour features of the trim panel are recognized. In this process, edge detection technology is used to extract the boundary lines of the trim panel from the image. Edge detection technology is based on the pixel intensity change rate in the image, which can accurately identify the object contour and generate an edge feature point set of the trim panel. These point sets constitute the outer contour of the trim panel. Based on the recognized contour features, the coordinates of the glue application target area are determined, that is, the specific position where the adhesive needs to be applied. The area is usually the part where the trim panel contacts the vehicle body after installation, and precise positioning is required to ensure the firm bonding of the trim panel.

[0013] At the same time, the surface material of the trim panel is detected. The spectral analysis method is adopted. By analyzing the reflection characteristics of light with different wavelengths on the surface of the trim panel, the material feature data is obtained. Common materials of the trim panel include ABS plastic, PC material, carbon fiber material, etc. Different materials have different surface characteristics and bonding requirements. According to the detected surface material, the most suitable adhesive type is selected from the preset adhesive database to ensure the bonding effect and durability.

[0014] Positioning reference points are set. The reference points are reference marks used for precise positioning during the installation of the trim panel. The reference points can be achieved through laser marking or mechanical positioning pins, forming recognizable spatial coordinate points on the trim panel. By measuring the difference between the actual positions of these reference points and the ideal installation positions, the position deviation value of the trim panel is calculated. The position deviation value is a key indicator to measure the placement accuracy of the trim panel. When the deviation value is greater than the preset first threshold (this threshold is usually set according to the product assembly accuracy requirements, generally in the range of 0.1 - 1.0 mm), the position of the trim panel needs to be adjusted.

[0015] In the preparation stage of the glue application environment, the temperature and humidity conditions of the working area are detected. The temperature and humidity parameters have a significant impact on the curing characteristics and bonding strength of the adhesive, and are controlled within the range required by the adhesive technical specifications. If the environmental temperature and humidity exceed the preset range, they are adjusted to the appropriate range through environmental control equipment. Subsequently, the surface activation treatment is carried out on the glue application target area, using plasma technology or chemical activators. The purpose is to increase the surface energy, break the surface inert layer, and improve the affinity of the trim panel surface to the adhesive.

[0016] Based on the coordinates of the caulking target area, a caulking trajectory is generated, which determines the coating path and distribution pattern of the adhesive. The caulking trajectory design follows the principle of uniform distribution to ensure that the adhesive can cover all areas that need to be bonded. Control the caulking equipment to perform coating along the set trajectory, and at the same time, monitor the uniformity of the adhesive coating in real time. The coating uniformity refers to the consistency of the adhesive distribution in the target area, and the width and continuity of the glue line are evaluated in real time through image analysis technology. If the uniformity is lower than the second threshold (usually set according to the product quality standard), adjust the caulking parameters, such as pressure, speed or flow rate, to ensure the quality of the adhesive coating.

[0017] After the coating is completed, the system collects images of the adhesive distribution, which are obtained through imaging equipment and used to evaluate the actual distribution of the adhesive. By analyzing the images, judge whether the adhesive coverage is complete and whether the thickness is uniform. According to the type of adhesive used, set the corresponding curing parameters, such as temperature, time and energy density. Different types of adhesives have different curing mechanisms and requirements, such as heat curing, UV curing or room temperature curing, etc. The system cures the adhesive according to the set parameters and monitors the curing progress through sensors to ensure that the third threshold, that is, the standard for complete curing of the adhesive, is reached.

[0018] For example, when installing the dashboard trim of a car, obtain the surface images of the trim and the installation position, and identify the precise contour of the trim through the edge detection algorithm. Determine the contact area between the trim and the dashboard as the caulking target position, and determine that the trim is made of chrome-plated ABS plastic through material detection. According to the material characteristics, select a suitable modified acrylate adhesive. Set four positioning reference points at the bottom of the trim. After measurement, it is found that the position of the trim has a deviation of 0.8 mm, exceeding the allowable value of 0.5 mm. The system guides the operator to adjust the position of the trim to the qualified range. The detected environmental conditions show that the workshop temperature is 27°C and the humidity is 68%, which do not meet the optimal curing conditions of the selected adhesive. Therefore, start local environmental adjustment and adjust the parameters of the caulking area to 23°C and 55% humidity. Perform plasma activation treatment on the bottom contact surface of the trim to enhance the surface affinity. The system generates a closed caulking trajectory along the edge of the trim, controls the equipment to perform the coating operation, and the monitoring shows that the width of the glue line fluctuates between 1.8 - 2.2 mm, meeting the uniformity requirements. After the coating is completed, perform imaging analysis on the adhesive distribution, confirm that the coverage rate meets the requirements, and set the curing temperature of 60°C and the curing time of 20 minutes according to the characteristics of the selected adhesive. Thermal imaging monitoring shows that the degree of curing meets the standard requirements, and the caulking and positioning process is completed.

[0019] In the embodiments of the present application, by acquiring the surface image of the decorative panel and identifying the contour features, the coordinates of the caulking target area can be accurately determined, avoiding the errors caused by traditional manual visual judgment and ensuring the accuracy of the adhesive coating position. At the same time, by detecting the surface material of the decorative panel, the accurate matching and selection of the adhesive are realized, improving the bonding strength and durability. The technical feature of setting the positioning reference point and calculating the position deviation value establishes an accurate control mechanism for the spatial position of the decorative panel. When the deviation value is greater than the first threshold, the adjustment process is automatically triggered to ensure that the decorative panel is always in the best installation position, providing a stable basis for the subsequent caulking operation. The environmental temperature and humidity detection and adjustment technical feature solves the problem of the influence of environmental factors on the performance of the adhesive in the traditional method. By controlling the environmental parameters within the preset range and combining with the surface activation treatment of the caulking target area, the interfacial bonding force between the adhesive and the surface of the decorative panel is significantly improved. The technical feature of generating the caulking trajectory based on the coordinates of the caulking target area and real-time detecting the evenness of the adhesive coating establishes a closed-loop control mechanism. When the evenness is lower than the second threshold, real-time compensation is performed by adjusting the caulking parameters, ensuring the consistency of the adhesive coating quality and reducing the problem of insufficient bonding strength caused by uneven coating. The technical feature of collecting and analyzing the adhesive distribution image and setting the curing parameters according to the type of adhesive realizes differential curing treatment. The curing process is ended only when the degree of curing reaches the third threshold, ensuring the full curing of the adhesive. By introducing artificial intelligence algorithms such as image recognition, material analysis, environmental monitoring, and real-time feedback, a data-driven decision-making mechanism is established. The algorithm features play a key role in the whole solution. Especially in the links of contour recognition, material matching, evenness evaluation, and degree of curing monitoring, the algorithm model can adapt to the material and shape changes of different decorative panels, automatically adjust relevant parameters, realize the intelligentization and precision of the process, greatly improve the accuracy and efficiency of the installation of automotive decorative panels, and reduce the rework rate and material waste.

[0020] In a specific embodiment, the process of executing step S101 may specifically include the following steps: (1) Collect surface images of the decorative panel at multiple angles through a multispectral imaging device, and perform image fusion processing on each surface image to obtain a high-definition fusion image of the decorative panel; (2) Perform contour extraction processing on the high-definition fusion image of the decorative panel, extract the edge feature point set of the decorative panel through an edge enhancement algorithm, and determine the shape contour map of the decorative panel according to the edge feature point set; (3) Based on the shape contour map, identify the structural change area on the decorative panel through region segmentation processing, and mark the area with a curvature change value greater than the curvature threshold as the key structural area; (4) Determine the coordinates of the caulking target area according to the matching degree between the key structural area and the preset caulking rules; (5) Use a reflection spectrum analyzer to scan the surface of the decorative board to obtain the reflection spectrum data of the decorative board surface; (6) Compare and analyze the reflection spectrum data with the standard spectrum in the material characteristic database, calculate the similarity coefficient, and determine the surface material type of the decorative board according to the similarity coefficient; (7) Based on the surface material type, screen out the adhesive that matches the surface material type from the adhesive formula database, and calculate the required amount of adhesive according to the area of the gluing target area.

[0021] Specifically, collect the surface images of the decorative board at multiple angles through a multispectral imaging device. The multispectral imaging device is a high-precision camera system that can simultaneously obtain image information in multiple bands such as visible light, infrared light, and ultraviolet light, and can capture material characteristics and surface details that are invisible to the human eye. The multispectral imaging device scans the decorative board from different angles (usually four orthogonal directions) to obtain multiple sets of original image data. These original images are integrated into a high-definition fused image through an image fusion processing algorithm. The image fusion processing uses the weighted average method combined with gradient domain analysis to selectively synthesize the high-quality information in each angle image. The image fusion process can be expressed as: ; where, represents the pixel value of the fused image at the coordinate point (x, y), represents the corresponding pixel value of the th angle image, is the weight coefficient of the corresponding image, is the number of angles.

[0022] Subsequently, perform contour extraction processing on the high-definition fused image of the decorative board, and extract the edge feature point set of the decorative board through an edge enhancement algorithm. The edge enhancement algorithm applies Gaussian filtering to the image to eliminate noise, and then calculates the image gradient to identify the regions where the pixel values change drastically. In specific implementation, an improved Canny edge detection algorithm is used. This algorithm includes four steps: Gaussian filtering, gradient calculation, non-maximum suppression, and double-threshold connection, and can extract continuous and accurate edge lines. After the edge feature point set is extracted, the discrete points are connected through B-spline curve fitting technology to form a continuous decorative board shape contour map, realizing the accurate description of the geometric shape of the decorative board.

[0023] Based on the acquired shape contour map, identify the structural change regions on the decorative panel through region segmentation processing. The region segmentation processing uses the watershed algorithm to divide the surface of the decorative panel into multiple sub-regions, and then calculates the curvature change value of each region. The curvature change value represents the degree of change in the surface geometry. The specific calculation method is to perform local quadratic surface fitting on the curved surface and then solve for the principal curvature. When the curvature change value of a certain region is greater than the preset curvature threshold, this region is marked as a key structural region. The curvature threshold is usually determined according to the material characteristics and installation requirements of the decorative panel. For automotive interior decorative panels, this threshold is generally set within the range of 0.05 - 0.1 range.

[0024] After marking the key structural regions, calculate the matching degree between these regions and the preset gluing rules to determine the coordinates of the gluing target regions. The preset gluing rules are the adhesive coating standards formulated based on the decorative panel type, installation location, and force-bearing conditions, including parameters such as joint type, edge distance, and coverage ratio. The matching degree calculation uses vector similarity analysis and can be expressed as:

[0025] where, represents the matching degree between the key structural region and the preset gluing rules, is the feature vector of the region containing attributes such as region area, average curvature, and boundary length, is the gluing rule vector, and represent the magnitudes of the two vectors respectively. The higher the matching degree value, the more suitable the region is as a gluing area. According to the calculation results, determine the set of coordinates of the gluing target regions.

[0026] While determining the gluing area, use a reflection spectrum analyzer to scan the surface of the decorative panel to obtain the reflection spectrum data of the decorative panel surface. The reflection spectrum analyzer is a precision instrument that can measure the reflectivity of the object surface to light of different wavelengths. It emits light containing multiple wavelengths onto the surface of the decorative panel and then records the intensities of the light of each wavelength reflected back to form a reflection spectrum data curve. These data can accurately reflect the molecular composition and microstructure of the material on the decorative panel surface.

[0027] Compare and analyze the acquired reflection spectrum data with the standard spectrum in the material feature database, calculate the similarity coefficient, and thus determine the surface material type of the decorative panel. The similarity coefficient calculation uses the spectral correlation analysis method, and the specific formula is as follows: ; where, represents the spectrum of the decorative panel to be measured The similarity coefficient with the standard spectrum in the database represents, and respectively, the reflectance values at the wavelength . is the wavelength weight coefficient, reflecting the importance of different wavelengths for material identification, is the number of sampling wavelength points. The similarity coefficient ranges from 0 to 1, and the closer the value is to 1, the more similar the two materials are. By comparing the similarity coefficients of the decorative panel to be measured with the standard materials in the database, the material with the highest similarity is selected as the surface material type of the decorative panel.

[0028] Based on the determined surface material type, adhesives matching the surface material type are screened from the adhesive formula database. The adhesive screening process considers factors such as the chemical compatibility, bonding strength, and environmental durability between the material and the adhesive, and uses a multi-attribute decision-making method for evaluation. At the same time, the required amount of adhesive is calculated according to the area of the gluing target area to ensure the rationality of the adhesive usage during the coating process and avoid waste or insufficient coating.

[0029] Taking the installation of the automotive dashboard trim strip as an example, a multi-spectral imaging device is used to scan the chrome trim strip from four angles: the front, side, top, and bottom to obtain image data including visible light, near-infrared, and ultraviolet bands. During image fusion processing, the system gives a lower weight to the chrome reflective area and a higher weight to the matte area, generating a clear high-definition fused image. The edge enhancement algorithm extracts 2563 feature points on the edge of the trim strip and forms a continuous contour map through B-spline curve fitting. The region segmentation process divides the surface of the trim strip into 32 sub-regions, calculates the curvature change value of each region, and finds that the curvature change values of 5 regions exceed the threshold of 0.07 . These regions are mainly distributed around the joints and fixing points of the trim strip. The matching degree of these 5 key regions with the preset gluing rules is calculated, and 3 regions are determined as the gluing target regions, and the coordinate point set forms a closed curve along the bottom edge of the trim strip. The reflection spectrum analyzer collects the reflection spectrum data of the trim strip surface at 5nm intervals in the wavelength range of 350 - 2500nm, compares it with the standard spectrum in the material database, and calculates that the similarity coefficient with the PC + ABS alloy material is 0.94, determining that the trim strip is made of chrome-treated PC + ABS material. According to this material property, modified acrylate adhesives are screened from the adhesive formula database, and at the same time, the required amount of adhesive is calculated to be 4.2 milliliters according to the total area of the gluing region.

[0030] In a specific embodiment, the process of executing step S102 may specifically include the following steps: (1) Based on the coordinates of the target area for gluing, a high-brightness characteristic marking pattern is projected on the decorative panel by a marking projector to form multiple identifiable positioning reference point coordinates; (2) Using visual sensors to collect images of the actual positions of multiple positioning reference point coordinates, and simultaneously extract the positions of multiple preset reference points on the work platform; (3) performing one-to-one coordinate transformation on the coordinates of multiple positioning reference points and the positions of multiple preset reference points to generate a position relationship data set of the decorative panel; (4) Performing difference calculation on the position information of each set of corresponding points in the position relationship data set and the standard installation position data to obtain multiple sets of position deviation data; (5) Extract the deviation components in the X-axis, Y-axis and Z-axis directions from multiple sets of position deviation data, and calculate the position deviation value by weighted average; (6) comparing the position deviation value with a first threshold value, and if the position deviation value is greater than the first threshold value, calculating a three-dimensional correction vector based on the multiple sets of position deviation data; (7) Based on the three-dimensional correction vector, the positioning mechanism is controlled to perform multi-degree-of-freedom adjustment on the position of the decorative panel until the position deviation value is less than or equal to a first threshold.

[0031] Specifically, Figure 2 As shown, it is a schematic diagram of the process of setting the positioning reference point and calculating the position deviation value of the decorative panel in the embodiment of the present application. After determining the coordinates of the target area for gluing, the decorative panel is accurately positioned to ensure that the adhesive can be accurately applied to the predetermined position. Based on the acquired coordinates of the target area for gluing, a high-brightness characteristic marking pattern is projected on the decorative panel by a marking projector to form a plurality of recognizable positioning reference point coordinates. A marking projector is an optical device that can accurately project a preset pattern onto the surface of an object. It uses laser or structured light technology to form high-contrast, high-precision marking points on the surface of the decorative panel. These marking points are usually in a grid or cross shape and have clear spatial position information.

[0032] Collect the actual position images of multiple positioning reference point coordinates through a vision sensor, and at the same time extract the positions of multiple preset reference points on the working platform. The vision sensor refers to a high-resolution industrial camera equipped with an appropriate light source and lens, which can clearly capture the position information of the marking points. The preset reference points on the working platform are pre-calibrated fixed points with known absolute spatial coordinates, serving as the benchmark for the entire positioning system. The vision sensor extracts the coordinate information of these two sets of points through image processing technology, providing a data basis for subsequent coordinate transformation. Perform one-to-one coordinate transformation on the coordinates of multiple positioning reference points and the positions of multiple preset reference points respectively to generate a position relationship dataset of the decorative panel. Coordinate transformation refers to converting the coordinate system of the reference points on the decorative panel to the global coordinate system of the working platform, and this process is realized through a rigid body transformation algorithm. The rigid body transformation keeps the relative distance between points unchanged and includes two parts: translation and rotation. Solve the optimal transformation matrix through the least squares method, map the point set on the decorative panel to the global coordinate system, and form a position relationship dataset of the decorative panel. This dataset contains the current spatial position and attitude information of the decorative panel.

[0033] Perform a difference operation on each set of corresponding point position information in the position relationship dataset and the standard installation position data to obtain multiple sets of position deviation data. The standard installation position data refers to the position coordinates that each reference point should be in under the ideal installation state of the decorative panel, and these data usually come from product design drawings or 3D models. The difference operation is to calculate the coordinate difference between the actual position and the ideal position to obtain the displacement values in the X, Y, and Z directions. Each reference point will generate a set of position deviation data, and multiple reference points will form multiple sets of position deviation data, which reflect the positioning errors of the decorative panel at different positions.

[0034] Extract the deviation components in the X-axis, Y-axis, and Z-axis directions from multiple sets of position deviation data, and calculate the position deviation value through weighted average. Decompose the position deviations of all reference points according to the coordinate axes to obtain the deviation components in the X-axis, Y-axis, and Z-axis directions respectively. Since the influence of reference points at different positions on the overall positioning accuracy is different, the weighted average method is used to calculate the comprehensive position deviation value. The weight coefficients are determined according to the importance, reliability, and representativeness of the reference points. The reference points close to the key structure or the caulking area are usually given higher weights. The position deviation value calculated by weighted average is a comprehensive index, reflecting the overall positioning deviation degree of the decorative panel.

[0035] Compare the position deviation value with the first threshold. If the position deviation value is greater than the first threshold, calculate the three-dimensional correction vector based on multiple sets of position deviation data. The first threshold refers to the allowable limit of the positioning accuracy of the decorative panel, which is set according to the product assembly requirements and the adhesive coating accuracy requirements, usually in the range of 0.1 - 1.0 millimeters. When the position deviation value exceeds the first threshold, it indicates that the position of the decorative panel does not meet the requirements for applying glue and needs to be adjusted. The three-dimensional correction vector refers to the translation and rotation amounts required to adjust the position of the decorative panel. By analyzing multiple sets of position deviation data and considering the rigid body characteristics of the decorative panel, calculate the correction path and amplitude.

[0036] Based on the three-dimensional correction vector, control the positioning mechanism to perform multi-degree-of-freedom adjustment on the position of the decorative panel until the position deviation value is less than or equal to the first threshold. The positioning mechanism is a mechanical device that can achieve precise multi-degree-of-freedom motion in space, usually including components such as linear guides, rotary platforms, and precision motors. According to the calculated three-dimensional correction vector, the positioning mechanism gradually adjusts the position of the decorative panel according to the predetermined adjustment sequence and step size. Visual feedback is continuously performed during the adjustment process to calculate the position deviation value in real time, forming a closed-loop control. When the position deviation value drops below the first threshold, it indicates that the decorative panel has reached the required positioning accuracy and the positioning process is completed.

[0037] For example, during the installation of the decorative panel of the car center console, after determining the glue application area of the decorative panel, the marking projector projects 16 cross-shaped light points on the panel, forming a grid of positioning reference points. The high-resolution industrial camera simultaneously captures the position images of these 16 reference points and 12 pre-calibrated reference points on the work platform. The image processing software extracts the precise pixel coordinates of the reference points and the reference points from the image and converts the pixel coordinates into physical space coordinates through the camera calibration parameters. Through the rigid body transformation algorithm, the coordinates of the 16 reference points on the decorative panel are transformed into the global coordinate system of the work platform to generate the current position data set of the panel. Compare this data set with the standard installation position specified in the design drawing to calculate the position deviation of each point. Analysis shows that the panel is on average offset by 0.75 millimeters in the X-axis direction, 0.42 millimeters in the Y-axis direction, and 0.23 millimeters in the Z-axis direction, and the comprehensive position deviation value is 0.88 millimeters. Considering that the first threshold for this type of center console decorative panel is 0.5 millimeters, the current position deviation exceeds the allowable range. Calculate the correction vector based on the deviation data. The panel needs to move 0.75 millimeters in the negative X-axis direction, 0.42 millimeters in the negative Y-axis direction, 0.23 millimeters in the positive Z-axis direction, and rotate 0.2 degrees clockwise around the Z-axis. The six-axis precision positioning platform receives this correction instruction and performs the position adjustment step by step. After each adjustment, recalculate the position deviation value. After three iterative adjustments, the position deviation value drops to 0.32 millimeters, meeting the accuracy requirements and completing the precise positioning of the decorative panel.

[0038] In a specific embodiment, the process of executing step S103 may specifically include the following steps: (1) Collect multi-point temperature data through a temperature sensor array distributed in the working space to form temperature distribution field data, and collect multi-point humidity data through a humidity sensor array to form humidity distribution field data; (2) Perform spatial interpolation calculation on the temperature distribution field data to obtain a temperature curve graph of the gluing area, and perform spatial interpolation calculation on the humidity distribution field data to obtain a humidity curve graph of the gluing area; (3) Compare the temperature values in the temperature curve graph of the gluing area with the upper and lower limit values of the temperature range. If the temperature range is exceeded, calculate a temperature adjustment instruction; (4) Compare the humidity values in the humidity curve graph of the gluing area with the upper and lower limit values of the humidity range. If the humidity range is exceeded, calculate a humidity adjustment instruction; (5) Control the environmental adjustment device according to the temperature adjustment instruction and the humidity adjustment instruction, adjust the temperature and humidity parameters of the working space, and determine the surface activation intensity parameter and the activation time parameter based on the surface material of the decorative board and the coordinates of the gluing target area; (6) Apply a plasma flow to the gluing target area through a surface treatment device to perform surface activation treatment and form an enhanced bonding interface layer.

[0039] Specifically, multi-point temperature data is collected through a temperature sensor array distributed in the working space to form temperature distribution field data. The temperature sensor array refers to a detection network formed by arranging multiple thermosensitive elements in a specific space. Usually, high-precision thermocouples or thermistors are used and distributed at key positions in the working area to form a detection lattice in three-dimensional space. Each sensor continuously collects the temperature value at its location and transmits the data to the data acquisition module. After signal conditioning and digital conversion, temperature distribution field data including time stamps, spatial positions, and temperature values is formed. At the same time, the humidity sensor array adopts a similar distribution method to collect multi-point humidity data to form humidity distribution field data. The humidity sensor array consists of multiple capacitive or resistive humidity detection elements, which can measure the moisture content in the air and output relative humidity values.

[0040] Spatial interpolation calculation is performed on the collected temperature distribution field data to obtain the temperature curve graph of the caulking area. Spatial interpolation calculation refers to a mathematical method of estimating the temperature values of unsampled points in space based on discrete temperature sampling point data. In this solution, the Kriging interpolation method is adopted. This method is based on the theory of regionalized variables, takes into account the spatial correlation between sampling points, and can generate a smooth temperature distribution curve. In the specific implementation process, a spatial coordinate system is established, the position coordinates of each sensor and its measured values are input into the algorithm, the semi-variance function of each point in space is calculated, the Kriging equations are constructed, the weight coefficients are solved, and the continuous temperature distribution surface of the entire caulking area is obtained. Similarly, the same interpolation method is applied to the humidity distribution field data to obtain the humidity curve graph of the caulking area.

[0041] The temperature values in the temperature curve graph of the caulking area are compared with the upper and lower limit values of the temperature range to determine whether they exceed the preset temperature range. The upper and lower limit values of the temperature range are the ideal working temperature intervals set according to the technical specifications of the adhesive used, and are usually recorded in the product data sheet of the adhesive. If the temperature values in any area of the temperature curve exceed this range, a temperature adjustment instruction needs to be calculated. The calculation of the temperature adjustment instruction is based on the temperature deviation value and the regional importance weight, and adopts the proportional-integral-derivative (PID) control principle, comprehensively considering the current deviation, the accumulation of historical deviations, and the trend of deviation changes, to generate an appropriate temperature control signal. For areas with too high temperature, a cooling instruction is generated; for areas with too low temperature, a heating instruction is generated, and the instruction contains information such as the adjustment direction, intensity, and priority. Similarly, the humidity values in the humidity curve graph of the caulking area are compared with the upper and lower limit values of the humidity range. If they exceed the humidity range, a humidity adjustment instruction is calculated using a similar method.

[0042] The environmental adjustment equipment is controlled according to the generated temperature adjustment instruction and humidity adjustment instruction to adjust the temperature and humidity parameters of the working space. The environmental adjustment equipment includes precision air conditioners, local heaters, dehumidifiers, humidifiers, etc. These devices accurately adjust the temperature and humidity of the working space according to the received adjustment instructions, in the specified intensity and direction. During the adjustment process, the temperature and humidity sensors continuously feedback real-time data to form a closed-loop control to ensure that the environmental parameters gradually reach the set range. At the same time, based on the surface material of the decorative board and the coordinates of the caulking target area, the surface activation intensity parameter and activation time parameter are determined. Different surface materials of decorative boards require different activation treatment conditions. For example, high molecular plastics such as ABS materials require higher intensity and shorter treatment time, while metal surfaces require medium intensity and longer treatment time. The surface activation intensity parameter is usually expressed in power density, and the activation time parameter is in seconds. These two parameters together determine the effect of the activation treatment.

[0043] Apply a plasma flow to the gluing target area through a surface treatment device for surface activation treatment to form an enhanced bonding interface layer. The surface treatment device is a special equipment capable of generating low-temperature plasma, usually composed of a discharge electrode, a gas supply system, and a control circuit. The plasma flow refers to a charged particle flow formed by the ionization of gas molecules under the action of an electric field, which has high activity and high energy characteristics and can change the molecular structure and chemical properties of the material surface. When the plasma flow acts on the surface of the decorative board, it can remove surface contaminants, break the inert bonds of surface molecules, introduce active groups, increase surface energy, and form an enhanced bonding interface layer that is conducive to the wetting and adhesion of the adhesive. The thickness of this interface layer is usually in the range of dozens to hundreds of nanometers, but significantly improves the bonding strength between the adhesive and the decorative board.

[0044] For example, during the installation of the decorative strip on the car door panel, 12 temperature sensors and 8 humidity sensors are arranged in the working space to form a monitoring network. The data acquisition system collects the data of each sensor once per second. The data of the past five minutes shows that the temperature distribution in the installation area of the decorative strip on the door panel is between 19°C and 31°C, and the humidity distribution is between 38% and 72%. The temperature curve graph obtained by Kriging interpolation shows that the central temperature in the installation area of the decorative strip reaches 31°C, and the edge temperature is 24°C, forming a temperature gradient with a high center and a low edge; the humidity curve graph shows that the humidity in the upper part of the installation area is 38%, and the humidity in the lower part reaches 72%, forming a humidity gradient in the vertical direction. According to the technical requirements of the polyurethane adhesive used, the ideal temperature range is 20°C to 25°C, and the humidity range is 45% to 65%. Since the actual temperature and humidity partially exceed the range, the system calculates the temperature adjustment instruction, requiring the central area to be cooled by 6°C. At the same time, it calculates the humidity adjustment instruction, requiring the humidity in the upper part to be increased by 7% and the humidity in the lower part to be decreased by 7%. According to these instructions, the control system starts the precision air conditioner to blow air directionally to cool the central area, and at the same time turns on the local dehumidifier to reduce the humidity in the lower area and turns on the small humidifier to increase the humidity in the upper area. After about 8 minutes of adjustment, the temperature in the working area is stabilized at 23±1°C, and the humidity is stabilized at 55±5%, meeting the process requirements. After the environmental parameters meet the standards, according to the PC material characteristics of the door panel decorative strip and the shape of the gluing area, the plasma treatment power is set to 120W, and the treatment time is 18 seconds. The surface treatment device performs plasma flow treatment on the bottom surface of the decorative strip along the predetermined gluing trajectory to form an active interface layer with a thickness of about 150 nanometers, effectively improving the adhesion ability of the adhesive.

[0045] In a specific embodiment, the process of executing step S104 may specifically include the following steps: (1) Construct a gluing guide point set based on the coordinates of the gluing target area, extract key inflection points and coating direction vectors from the guide point set, and sort the key inflection points according to the optimized path based on the coating direction vector to generate a gluing path guide line; (2) Smooth the glue application path guiding line, calculate the speed control parameters and glue volume control parameters at each node, and generate glue application trajectory data; (3) Convert the glue application trajectory data into glue application equipment control instructions, drive the glue application nozzle to move along the glue application trajectory, and apply the adhesive to the decorative board; (4) Real-time collect the glue line imaging data during the glue application process through a high-speed imaging system, and extract the glue line width value, glue line continuity index, and edge neatness index; (5) Calculate the glue line width value, glue line continuity index, and edge neatness index according to the weight combination to obtain the adhesive coating uniformity score; (6) Compare the adhesive coating uniformity score with the second threshold. If it is lower than the second threshold, calculate the glue application pressure adjustment amount and speed adjustment amount according to the insufficient score items; (7) According to the glue application pressure adjustment amount and speed adjustment amount, correct the glue application parameters, and continue to control the glue application equipment to perform supplementary coating on the uneven area.

[0046] Specifically, construct a glue application guiding point set based on the coordinates of the glue application target area, that is, convert the boundaries and internal key positions of the glue application area into discrete coordinate points. The glue application guiding point set is a set composed of multiple spatial coordinate points, and these points are usually distributed along the area where the adhesive needs to be coated. Extract the key inflection points and coating direction vectors from these guiding points. The key inflection points refer to the nodes where the direction in the guiding point set changes significantly, usually identified by calculating the angle formed by three adjacent points. When the angle change exceeds the preset threshold, this point is marked as a key inflection point; the coating direction vector represents the advancing direction of the adhesive coating, determined by the connecting line direction of two adjacent points. Based on the coating direction vector, sort the key inflection points according to the optimized path, generate the glue application path guiding line, and use an improved traveling salesman problem solving algorithm to minimize the total path length while ensuring coverage of all key points and avoiding unnecessary intersections and round trips.

[0047] Smooth the generated glue application path guiding line. This processing process uses the cubic spline interpolation method to connect the discrete path points into a smooth and continuous curve. The mathematical expression of the smoothing process is as follows: ; where represents the parameterized path curve, is the control point coordinate, is the d-order B-spline basis function, is the total number of control points, is the parameter variable, and the range is , Based on the smoothed path, calculate the speed control parameter and glue amount control parameter at each node. The speed control parameter determines the moving speed of the glue spraying nozzle at this node, while the glue amount control parameter determines the amount of adhesive released per unit time. The calculation formulas for these parameters are as follows: ; ; Among them, represents the speed control parameter at the path parameter s, is the basic speed value, is the speed adjustment coefficient, is the curvature value at this point, is the speed curvature sensitivity parameter; represents the corresponding glue amount control parameter, is the target glue line width, is the target glue line height, is the glue amount calibration constant. The above calculation results together form the glue spraying trajectory data, which contains information such as path point coordinates, speed parameters, and glue amount parameters.

[0048] Convert the glue spraying trajectory data into glue spraying equipment control instructions. According to the specific control characteristics of the glue spraying equipment, map the digital trajectory data into a command format recognizable by the equipment. The glue spraying equipment control instructions usually include three parts: position instructions, speed instructions, and pressure / flow instructions, which respectively control the movement of the nozzle position, the moving speed, and the amount of adhesive released. These instructions are transmitted to the controller of the glue spraying equipment through the communication interface to drive the glue spraying nozzle to move along the set glue spraying trajectory and apply adhesive to the decorative board. During the movement of the nozzle, the output amount of the adhesive is precisely controlled by a pressure pump or a piston pump to form a continuous and uniform glue line.

[0049] Real-time collect the glue line imaging data during the glue spraying process through a high-speed imaging system. The high-speed imaging system usually includes an industrial camera, a light source, and an image processing unit, which can capture high-resolution glue line images. Extract the glue line width value, glue line continuity index, and edge neatness index from the glue line image. This extraction process uses image analysis algorithms. The extraction formulas for the glue line characteristic parameters are as follows: ; ; ; Among them, represents the glue line width deviation index at the position , which reflects the consistency between the glue line width and the target width, is the number of width sampling points, is the actual glue line width measured at the position , is the target glue line width; is the glue line continuity index, is the cumulative length of the continuous section of the glue line, is the total detection length; is the edge uniformity index, is the number of edge sampling points, and are the deviation amounts of the left and right edges relative to the ideal edge at the sampling point respectively.

[0050] The extracted glue line width value, glue line continuity index, and edge neatness index are combined and calculated according to the weights to obtain the adhesive coating uniformity score. This score is a comprehensive evaluation of the glue line quality, and the calculation formula is as follows: ； ； ； ； Among them, is the adhesive coating uniformity score (0 - 100 points), is the width quality score, is the continuity quality score, is the edge quality score, , , are the weight coefficients of the three indicators respectively, and satisfy + + = 1. This scoring method standardizes each indicator to the range of 0 - 100 points, which is convenient for comprehensively evaluating the overall quality of the glue line.

[0051] Compare the adhesive coating uniformity score with the second threshold. If it is lower than the second threshold, calculate the caulking pressure adjustment amount and speed adjustment amount according to the insufficient item of the score. The second threshold is the score representing the acceptable minimum glue line quality standard, usually set between 70 - 85 points. When the score is lower than the threshold, the caulking parameters need to be adjusted according to the specific insufficient item. If the main problem is uneven width, adjust the pressure parameter; if the main problem is poor continuity, adjust the speed parameter. The calculation of the adjustment amount follows the proportional-integral control principle, comprehensively considering the current deviation and historical cumulative deviation. According to the calculated caulking pressure adjustment amount and speed adjustment amount, correct the caulking parameters, and continue to control the caulking equipment to perform supplementary coating on the uneven area until the coating uniformity meets the requirements.

[0052] Taking the installation of the automotive instrument panel trim as an example, 102 glue application guiding points are extracted according to the coordinates of the glue application target area at the bottom of the trim, forming a continuous guiding point set. By analyzing the angular changes between adjacent points, 15 key inflection points are identified, which are mainly distributed at the bends and joints of the trim. The connection direction between every two inflection points determines the local coating direction vector. An improved genetic algorithm is used to optimize the path sorting of these 15 key inflection points, generating a glue application path guiding line with a total length of 368 millimeters. Cubic spline interpolation is applied to this guiding line for smoothing, with an interpolation node density of one node per 2 millimeters, generating a smooth and continuous curve. When calculating the control parameters, the base speed value is set at 5 millimeters per second, the target glue line width is 2 millimeters, and the height is 1 millimeter. In areas with a large curvature (such as the bend), the speed is automatically reduced to 3.2 millimeters per second, and at the same time, the glue output is increased to keep the cross-sectional area of the glue line consistent. After converting the glue application trajectory data into the device-specific format, it is sent to the glue application controller to drive the six-axis robotic arm to drive the glue application nozzle to precisely execute the trajectory. The high-speed camera system collects the glue line images at a rate of 60 frames per second, measures the glue line width at multiple cross-sectional positions through the edge detection algorithm, and calculates that the glue line width deviation index is 0.035; the continuity analysis finds that there is a short interruption at a sharp turn, and the glue line continuity index is 0.994; the edge analysis shows that the average deviation amounts of the left and right edges are 0.15 millimeters and 0.23 millimeters respectively, and the edge uniformity index is 0.905. According to the preset weights (width accounts for 40%, continuity accounts for 35%, and edge neatness accounts for 25%), the calculated coating uniformity score is 78 points, which is lower than the second threshold of 80 points. Analyzing the insufficient scoring items, it is found that the main problems lie in continuity and edge neatness. Therefore, the calculated pressure adjustment amount is to increase by 8%, and the speed adjustment amount is to decrease by 5%. After correcting the parameters, supplementary coating is performed on the problem area, and the second score reaches 83 points, meeting the quality requirements and completing the glue application operation.

[0053] In a specific embodiment, the process of executing step S105 may specifically include the following steps: (1) Perform image stitching processing on the adhesive distribution image to obtain the panoramic adhesive distribution image, and calculate the actual adhesive coverage area by extracting the boundary line of the adhesive coverage area from the panoramic adhesive distribution image; (2) Compare the actual adhesive coverage area with the theoretical coverage area to generate an adhesive distribution deviation map; (3) Query the adhesive curing characteristic database according to the type of adhesive to obtain the best curing temperature curve and curing time parameters of the adhesive; (4) Calculate the curing energy compensation coefficient for each area based on the adhesive distribution deviation map to generate a regionalized curing parameter matrix; (5)Control the curing equipment to perform differential curing treatment on the adhesive according to the regionalized curing parameter matrix, and use a thermal imaging system to monitor the curing temperature distribution of the adhesive in real time, and calculate the curing degree index; (6)Compare the curing degree index with the third threshold, and continuously adjust the curing parameters until the curing degree index reaches the third threshold.

[0054] Specifically, perform precise curing treatment on the adhesive to ensure the firm bonding of the decorative board. Perform image stitching on the adhesive distribution images to obtain a panoramic adhesive distribution map. Image stitching refers to fusing multiple local adhesive distribution images into a single panoramic image through an algorithm, using feature point matching and image registration techniques. In specific implementation, extract SIFT feature points (Scale-Invariant Feature Transform) from each local image, then screen out the matching feature point pairs through the RANSAC algorithm (Random Sample Consensus), calculate the transformation matrix between the images, and finally seamlessly stitch multiple images into a complete panoramic adhesive distribution map through an image fusion algorithm. After the panoramic map is generated, extract the boundary line of the adhesive coverage area from the panoramic map through an image segmentation algorithm. Commonly used segmentation algorithms include threshold-based segmentation, region growing method, or watershed algorithm, which identify the boundary between the adhesive and the background through pixel brightness or color differences. After the boundary line is extracted, use the pixel counting method to calculate the actual adhesive coverage area, that is, count the number of pixels inside the boundary line and convert it into the actual physical area according to the image resolution.

[0055] Compare the calculated actual adhesive coverage area with the theoretical coverage area to generate an adhesive distribution deviation map. The theoretical coverage area is the ideal coverage area calculated according to the design requirements of the decorative board and the caulking trajectory. The comparison process uses the regional overlap analysis method to calculate the overlap degree, missing area, and excess area between the actual coverage area and the ideal coverage area. The adhesive distribution deviation map is an image displayed in pseudo-color, usually using different colors to mark three states of the adhesive distribution: normal coverage area (theoretical and actual overlap), under-coated area (theoretical but actual absence), and over-coated area (theoretical absence but actual presence). This deviation map visually shows the quality status of the adhesive distribution and provides a basis for subsequent curing parameter settings.

[0056] Query the adhesive curing property database according to the type of adhesive to obtain the best curing temperature curve and curing time parameters of the adhesive. The adhesive curing property database is a professional dataset containing the curing property information of various adhesives, recording the curing behaviors of different adhesives under various conditions. The query process locates the corresponding adhesive record through the adhesive type code (such as two-component epoxy adhesive, polyurethane adhesive, acrylate adhesive, etc.), and then extracts the curing property information of the adhesive, including the best curing temperature curve (the curve of temperature changing with time) and curing time parameters (preheating time, holding time, cooling time, etc.). These parameters reflect the temperature and time conditions required for the adhesive to achieve the best bonding strength during the curing process.

[0057] Calculate the curing energy compensation coefficient for each region based on the adhesive distribution deviation map to generate a regionalized curing parameter matrix. The calculation of the curing energy compensation coefficient takes into account the deviation of the adhesive distribution in different regions and makes targeted compensation for the under-coated and over-coated regions. The calculation formula is as follows:

[0058] Where, is the curing energy compensation coefficient at position , is the basic compensation coefficient, is the relative distribution deviation value at this position (positive value indicates excess, negative value indicates deficiency), is the distribution sensitivity parameter, is the nominal thickness at this position, is the reference thickness. Through this formula, the corresponding energy compensation coefficient is calculated for the regions with uneven adhesive distribution. Regions with larger thickness require more energy, while regions with smaller thickness require less energy. Organize the compensation coefficients of each region into a matrix form, that is, the regionalized curing parameter matrix, which describes the curing energy distribution required at each point position on the two-dimensional plane.

[0059] Control the curing equipment to perform differential curing treatment on the adhesive according to the regionalized curing parameter matrix. At the same time, use a thermal imaging system to monitor the curing temperature distribution of the adhesive in real time and calculate the degree of cure index. Differential curing treatment means applying different curing energies to the adhesive by controlling the power output of the heating elements according to the curing parameter requirements of different regions. The curing equipment usually adopts an array of heating elements or a scanning heat source, which can achieve precise temperature control for different regions. During the curing process, the thermal imaging system continuously acquires the temperature distribution image on the surface of the adhesive. The thermal imaging system is a device that can detect infrared radiation and convert it into a visible temperature image, capable of non-contact measurement of the surface temperature of an object. Based on the temperature distribution data and the curing kinetics model of the adhesive, calculate the degree of cure index, which reflects the completion degree of the cross-linking reaction of the adhesive. The calculation formula is as follows:

[0060] where, represents the degree of cure index at time t and position (x, y), is the frequency factor, is the activation energy, R is the gas constant, is the temperature at position (x, y) at time , is the reaction order.

[0061] This formula is based on the Arrhenius equation, which describes the effect of temperature on the reaction rate, and calculates the curing degree of the adhesive in each region through cumulative calculation. Compare the calculated degree of cure index with the third threshold, and continuously adjust the curing parameters until the degree of cure index reaches the third threshold. The third threshold refers to the minimum acceptance standard for the curing degree of the adhesive, usually set at about 95%, indicating that the adhesive reaction has been fully completed and has the mechanical strength and environmental durability required by the design. When it is detected that the curing degree in a certain region is insufficient, the curing control system will automatically extend the curing time or increase the curing temperature of that region until the curing degree of all regions reaches or exceeds the third threshold, completing the entire sealant curing process.

[0062] Taking the installation of a car door trim as an example, after the glue coating of the door trim is completed, adhesive distribution images are collected from different angles by four high-resolution cameras. Each camera captures a local area, covering approximately 40% of the total area, and there is an overlap area of approximately 15% between adjacent images. The image stitching algorithm extracts approximately 450 SIFT feature points from each image, finds 86 pairs of matching points through feature matching, calculates the transformation matrix between adjacent images, and generates a complete panoramic view of the adhesive distribution. The adhesive coverage area is extracted from the panoramic view by the Otsu threshold segmentation method, and the actual coverage area is calculated to be 5823 square millimeters, while the theoretical coverage area on the design drawing is 6100 square millimeters. Comparative analysis shows that there is an over-coated area of approximately 92 square millimeters (accounting for 1.5% of the theoretical area), and an under-coated area of approximately 369 square millimeters (accounting for 6.0% of the theoretical area), mainly distributed at the two corners of the decorative panel. Querying from the adhesive curing characteristic database, it is known that the optimal curing temperature of the two-component polyurethane adhesive used is 75°C, the preheating time is 2 minutes, the heat preservation time is 12 minutes, and the cooling time is 5 minutes. For the uneven coating areas, the curing energy compensation coefficient at each position is calculated. The coefficient for the under-coated area reaches 1.25, and the coefficient for the over-coated area drops to 0.85, forming a complete curing parameter matrix. The curing equipment controls the output power of 32 independent heating units according to the parameter matrix to implement differential heating for different areas. The thermal imaging system monitors the temperature distribution during the curing process in real time. The highest temperature reaches 78°C, the lowest temperature is 72°C, and the uniformity is controlled within the range of ±3°C. According to the curing kinetic parameters of the polyurethane adhesive, the curing degree indexes of each area after 12 minutes are calculated. The central area reaches 98.5%, and the edge area is 94.2%, lower than the third threshold of 95%. The system automatically extends the curing time of the edge area by 2 minutes. The re-detection result shows that the overall curing degree reaches 96.8%, exceeding the third threshold, and the curing process is completed.

[0063] In a specific embodiment, the process of performing the step of querying the adhesive curing characteristic database according to the type of adhesive may specifically include the following steps: (1) Extract the corresponding curing parameter record from the adhesive curing characteristic database according to the type code of the adhesive; (2) Obtain the key curing temperature points and transformation characteristic data of the adhesive from the curing parameter record; (3) Draw a temperature tolerance range diagram of the adhesive according to the key curing temperature points, and determine the upper and lower limits of the safe curing temperature; (4) Adjust the upper and lower limits of the safe curing temperature based on the surface material characteristics of the decorative panel to generate an adapted curing temperature range; (5) Select the optimal curing start temperature and end temperature within the adapted curing temperature range to construct the best curing temperature curve of the adhesive; (6) Determine three curing time parameters of the adhesive, namely the preheating time, the main curing time, and the cooling time, based on the optimal curing temperature curve and the transformation characteristic data.

[0064] Specifically, determine appropriate curing parameters according to the type of adhesive and the material characteristics of the decorative board. Extract the corresponding curing parameter records from the adhesive curing characteristic database based on the type code of the adhesive. The type code of the adhesive is an identifier for classifying and coding different adhesives. For example, EP represents epoxy adhesive, PU represents polyurethane adhesive, ACR represents acrylate adhesive, etc. The adhesive curing characteristic database is a data set integrating the curing characteristic information of various adhesives, including the technical parameters provided by the manufacturer and the experimental test data. The extraction process uses the database query method, inputs the type code of the adhesive as the retrieval condition, locates the corresponding record item in the database, and reads the curing parameter information contained in this record. These parameter information are usually stored in the form of structured data. Obtain the key curing temperature points and transformation characteristic data of the adhesive from the extracted curing parameter records. The key curing temperature points refer to the temperature values with special significance during the curing process of the adhesive, including the lowest curing start temperature, the optimal curing temperature, the highest safe temperature, etc. The transformation characteristic data describe the physical and chemical property changes of the adhesive during the curing process, including the gel time, the curing rate constant, the glass transition temperature, etc. These data usually come from experimental test methods such as differential scanning calorimetry and dynamic mechanical analysis, and reflect the curing behavior and performance characteristics of the adhesive under different temperature conditions. The data acquisition process involves parsing each field value from the parameter record and classifying and organizing them according to the physical meaning of the data.

[0065] Draw a temperature tolerance range graph of the adhesive based on the obtained key curing temperature points, and determine the upper and lower limits of the safe curing temperature. The temperature tolerance range graph is a graphical representation of the curing performance of the adhesive at different temperatures. The abscissa is the temperature value, and the ordinate is the curing performance index, such as the curing rate, the degree of curing, the strength, etc. The drawing process uses the multi-point interpolation method to connect the discrete key temperature point data into a continuous curve to form a complete temperature-performance relationship graph. From the temperature tolerance range graph, determine the upper and lower limits of the safe curing temperature. The upper limit temperature is usually the highest temperature at which the adhesive does not undergo thermal decomposition or significant performance degradation, and the lower limit temperature is the lowest temperature at which the adhesive can be effectively cured. These two limits constitute the safe temperature window for the curing of the adhesive. Exceeding this range may lead to insufficient curing or deterioration of the adhesive performance.

[0066] Based on the surface material properties of the decorative board, adjust the upper and lower limits of the safe curing temperature to generate an adapted curing temperature range. The surface material properties of the decorative board refer to the physical and chemical properties of the decorative board material, such as the heat distortion temperature, coefficient of thermal expansion, surface tension, etc. These properties directly affect the bonding effect between the adhesive and the decorative board. During the adjustment process, the temperature sensitivity of the material is considered. If the heat distortion temperature of the decorative board material is lower than the upper limit of the safe curing temperature of the adhesive, the upper limit temperature needs to be reduced to within the safe temperature range of the material; similarly, if the surface properties of the material change at low temperatures, affecting the bonding performance, the lower limit temperature needs to be adjusted accordingly. In addition, the thermal conductivity characteristics of the material also need to be considered. For materials with low thermal conductivity, the heating time needs to be extended or the temperature gradient needs to be adjusted to ensure that heat can be evenly conducted to the entire bonding interface. Through these adjustments, an adapted curing temperature range that can both meet the curing requirements of the adhesive and protect the decorative board material is generated.

[0067] Select the optimal curing start temperature and end temperature within the determined adapted curing temperature range to construct the best curing temperature curve of the adhesive. The optimal curing start temperature refers to the initial temperature at the beginning of the curing process, usually selected at the lower part of the adapted temperature range so that the adhesive can have sufficient fluidity to be evenly distributed; the optimal curing end temperature is the temperature at the end of the curing process, usually selected at a suitable value that can ensure sufficient curing and no damage to the material. The temperature curve is constructed using a piecewise function method, dividing the curing process into a preheating section, a main curing section, and a cooling section, and setting different temperature change rules for each section to comprehensively form a complete curing temperature curve. This curve describes the change trajectory of temperature over time from start to end, guiding the curing equipment to be controlled according to the set temperature to achieve the best curing effect of the adhesive.

[0068] According to the best curing temperature curve and the transformation characteristic data, determine the three curing time parameters of the adhesive: preheating time, main curing time, and cooling time. The preheating time refers to the time required to raise the temperature from room temperature to the curing start temperature, mainly to make the adhesive fully flow and wet the surface, and at the same time gradually release internal bubbles; the main curing time refers to the time the adhesive maintains at the curing temperature, during which most of the cross-linking reactions of the adhesive are completed to form a stable network structure; the cooling time refers to the time required to cool from the curing end temperature to room temperature. This process releases the internal stress of the adhesive to prevent cracking or deformation caused by rapid cooling. The determination of these three time parameters is based on the transformation characteristic data of the adhesive, comprehensively considering factors such as gel time, curing kinetics, glass transition, etc., to ensure that the adhesive can complete the curing process under appropriate temperature and time conditions and achieve the designed bonding strength and durability.

[0069] In a specific embodiment, the process of performing the step of adjusting the upper and lower limits of the safe curing temperature may specifically include the following steps: (1) Extract the heat distortion temperature and thermal stability parameters of the surface material of the decorative board from the material database; (2) Compare the heat distortion temperature with the upper limit of the safe curing temperature, and take the smaller value of the two as the adjusted upper limit of the curing temperature; (3) Compare the thermal stability parameters with the lower limit of the safe curing temperature to determine the lowest curing temperature that meets the characteristics of the surface material of the decorative board; (4) Determine the temperature transfer delay factor according to the thermal conductivity data of the surface material of the decorative board; (5) Based on the temperature transfer delay factor, construct a temperature change relationship between the adjusted upper limit of the curing temperature and the lowest curing temperature; (6) Determine the boundary values of the curing temperature range suitable for the adhesive by analyzing the corresponding relationship between the temperature change relationship and the curing efficiency of the adhesive.

[0070] Specifically, extract the heat distortion temperature and thermal stability parameters of the surface material of the decorative board from the material database. The material database is a professional dataset containing the physical and chemical properties of various decorative board materials, consisting of technical parameters and experimental test data provided by material manufacturers. The heat distortion temperature is the temperature threshold at which the material begins to exhibit significant deformation under load, usually determined by ASTM D648 or ISO 75 standard test methods. The thermal stability parameters describe the ability of the material to maintain its original properties in different temperature environments, including indicators such as the onset temperature of thermal degradation, the thermal oxidation index, and the long-term use temperature. The data extraction process uses a multi-keyword retrieval method. Locate the corresponding material record in the database according to the name or code of the decorative board material (such as ABS, PC, PP+EPDM, etc.), and then read the heat distortion temperature and thermal stability-related parameter values from the record. After the extraction is completed, compare the heat distortion temperature with the upper limit of the safe curing temperature, and take the smaller value of the two as the adjusted upper limit of the curing temperature. The upper limit of the safe curing temperature is the parameter obtained from the adhesive curing characteristics database in the previous step, indicating the highest temperature at which the adhesive can cure normally without decomposition or deterioration. The comparison process uses a simple principle of taking the smaller value, that is, if the heat distortion temperature of the decorative board material is lower than the upper limit of the safe curing temperature of the adhesive, then use the heat distortion temperature as the adjusted upper limit of the curing temperature; otherwise, use the upper limit of the safe curing temperature of the adhesive as the adjustment value. Ensure that the curing process does not cause deformation of the decorative board due to excessive temperature, and guarantee the appearance quality and dimensional accuracy of the product.

[0071] Compare the thermal stability parameters with the lower limit of the safe curing temperature to determine the minimum curing temperature that meets the surface material characteristics of the decorative board. The lower limit of the safe curing temperature also comes from the previous step and represents the lowest temperature at which the adhesive can be effectively cured. The comparison process uses a comprehensive evaluation method, considering various thermal stability indicators of the decorative board material at low temperatures to determine a temperature threshold that can not only meet the curing requirements of the adhesive but also have no negative impact on the material. If the material already shows instability (such as embrittlement, increased hygroscopicity, etc.) near the lower limit of the safe curing temperature of the adhesive, the minimum curing temperature needs to be increased; if the material maintains good stability at this temperature, the lower limit of the safe curing temperature of the adhesive can be used as the minimum curing temperature. Determine the temperature transfer delay factor based on the thermal conductivity data of the surface material of the decorative board. Thermal conductivity is a physical quantity that describes the ability of a material to conduct heat, with the unit of W / (m·K), and is also extracted from the material database. The temperature transfer delay factor refers to the time delay parameter that needs to be considered for the temperature difference between the surface and the interior due to the thermal conduction characteristics of the material during the curing process. The determination process uses a thermal conduction model analysis method. According to the thickness, geometric shape, and thermal conductivity of the decorative board, calculate the time and temperature gradient required for heat to transfer from the heat source to the adhesive layer. Materials with high thermal conductivity (such as metals) transfer heat quickly and have a small delay factor; materials with low thermal conductivity (such as plastics) transfer heat slowly and have a large delay factor. Through this calculation, a quantitative parameter reflecting the thermal conduction characteristics of the material is obtained, providing a basis for subsequent temperature control.

[0072] Based on the temperature transfer delay factor, a temperature change relationship is constructed between the adjusted upper limit of the curing temperature and the lowest curing temperature. The temperature change relationship refers to the curve of temperature variation with time during the curing process. The construction process uses the piecewise function method, dividing the curing process into a heating section, a constant temperature section, and a cooling section. In the heating section, considering the thermal inertia and conduction delay of the material, an appropriate heating rate is designed to avoid excessive temperature difference between the surface and the interior. In the constant temperature section, the holding time is determined according to the temperature transfer delay factor to ensure that the heat is fully conducted to the entire adhesive layer. In the cooling section, also considering the thermal properties of the material, a reasonable cooling rate is designed to prevent internal stress and deformation caused by rapid cooling. A temperature-time curve considering the thermal properties of the material is generated, which describes the temperature control strategy for the entire curing process. By analyzing the correspondence between the temperature change relationship and the curing efficiency of the adhesive, the boundary values of the suitable curing temperature range are determined. The curing efficiency refers to the degree of completion of the curing reaction of the adhesive per unit time, which is closely related to temperature and usually reaches the best balance at medium temperatures. The analysis process uses the multi-objective optimization method, considering three factors: curing rate, degree of cure, and material stability. According to the temperature change relationship, the curing rate and degree of cure of the adhesive at different temperatures are calculated; combined with the stability evaluation of the material at each temperature, the temperature range that can ensure both full curing of the adhesive and material stability is found; considering the production efficiency factor, the temperature range that can complete curing within a reasonable time is selected within the effective range.

[0073] In a specific embodiment, the process of performing the step of determining the boundary values of the suitable curing temperature range may specifically include the following steps: (1) Select multiple representative temperature points from the temperature change relationship to form a temperature detection point sequence; (2) Match each temperature value in the temperature detection point sequence with the curing efficiency data of the adhesive to form a temperature-curing efficiency comparison chart; (3) Find the temperature range with the best curing efficiency in the temperature-curing efficiency comparison chart and mark it as the preferred temperature range; (4) Combine the thermal stress limit value of the surface material of the decorative board to screen out the safe temperature range that will not cause thermal deformation of the decorative board; (5) Determine the temperature threshold that can meet the design strength requirements by analyzing the bonding strength data of the adhesive under various temperature conditions; (6) Combine the intersection of the preferred temperature range, the safe temperature range, and the temperature threshold to determine the boundary values of the suitable curing temperature range.

[0074] Specifically, multiple representative temperature points are selected from the temperature change relationship to form a temperature detection point sequence. The temperature change relationship refers to the temperature-time curve constructed in the previous steps, which shows the dynamic change characteristics of temperature during the curing process. The selection of representative temperature points adopts a method combining equal-interval sampling and key point strengthening, that is, basic temperature points are selected at fixed intervals (usually 5°C or 10°C) throughout the temperature range, and additional sampling points are added to the inflection points, plateau regions, and critical regions in the temperature curve to ensure that there are sufficient data points in the key temperature intervals to support the analysis. For example, for a curing process with a temperature range of 40 - 90°C, 40°C, 50°C, 60°C, 70°C, 80°C, 90°C can be selected as the basic temperature points, and sampling points such as 65°C, 67°C, 69°C, etc. are added near the key temperature such as the gel point of the adhesive (such as 65°C) to form a detection point sequence containing multiple temperature values.

[0075] Match each temperature value in the temperature detection point sequence with the curing efficiency data of the adhesive to form a temperature-curing efficiency comparison chart. The curing efficiency data usually comes from the technical parameter table provided by the adhesive supplier or the laboratory test results, which describe the curing rate and degree of the adhesive at different temperatures. The matching process uses the method of looking up tables and interpolation. For each temperature point in the sequence, find the corresponding efficiency value from the curing efficiency data; if there is no directly corresponding data for a certain temperature point, calculate the estimated value through linear interpolation or spline interpolation methods. After the matching is completed, use the temperature points as the abscissa and the corresponding curing efficiency as the ordinate to draw a two-dimensional curve graph to visually display the relationship between temperature and curing efficiency. Find the temperature range with the best curing efficiency in the temperature-curing efficiency comparison chart and mark it as the preferred temperature interval. The search process uses the peak recognition method. The curing efficiency curve usually shows a trend of rising first and then falling, and reaches the highest value in a certain temperature interval in the middle. Specifically, when operating, find the global maximum point of the curing efficiency, and then expand from this point to both sides to find the continuous temperature interval where the efficiency value is not lower than 90% (or other preset thresholds) of the maximum value, and mark the interval as the preferred temperature interval. The interval represents the temperature range that is most suitable for the curing of the adhesive from the perspective of curing efficiency. Usually, the adhesive cures quickly and has a high degree of curing in this interval, and can reach the ideal bonding strength in a short time.

[0076] Combined with the thermal stress limit of the decorative board surface material, a safe temperature range that will not cause thermal deformation of the decorative board is screened out. The thermal stress limit refers to the maximum stress value that the material can withstand during the heating process. Exceeding this value may cause the material to deform, crack or suffer other damages. The screening process is based on thermal stress analysis, considering the geometric dimensions, material properties and fixing methods of the decorative board, and calculating the thermal stress values generated at different temperatures. The determination of the safe temperature range is achieved by comparing the calculated thermal stress with the thermal stress limit of the material to find the temperature range where the thermal stress does not exceed the limit. This process ensures that during the curing process, the decorative board will not undergo permanent deformation or damage due to excessive temperature, guaranteeing the appearance quality and assembly accuracy of the product. By analyzing the adhesive strength data of the adhesive under various temperature conditions, the temperature threshold that can meet the design strength requirements is determined. The adhesive strength data refers to the maximum adhesive strength value that the adhesive can achieve after curing at different temperatures, usually obtained through standard tensile, shear or peel tests. The analysis process uses the threshold comparison method, comparing the adhesive strength data at each temperature with the strength value required by the design to find all temperature points that can meet the strength requirements and determine the temperature threshold. This threshold ensures that in actual use, the adhesive joint can withstand the expected mechanical load and environmental stress, providing sufficient safety margin.

[0077] By comprehensively optimizing the intersection of the preferred temperature range, the safe temperature range and the temperature threshold, the boundary values of the adapted curing temperature range are determined. Using the set intersection operation algorithm, the temperature ranges obtained from the three conditions are regarded as mathematical sets, and their intersection is calculated to obtain the temperature range that simultaneously meets the requirements of curing efficiency, material safety and strength. If there is an overlapping part among the three ranges, the overlapping range is directly taken as the adapted curing temperature range; if the overlapping range is very small or does not exist, it is necessary to evaluate the weights of each condition, giving priority to material safety, and appropriately relaxing the curing efficiency or strength requirements without affecting the decorative board to find the best balance point. Through this systematic multi-objective optimization method, the boundary values of the adapted curing temperature range that takes into account various requirements are determined.

[0078] Taking the installation of the automotive instrument panel decorative panel as an example, a total of 10 temperature points, namely 40°C, 50°C, 55°C, 60°C, 65°C, 70°C, 75°C, 80°C, 85°C, and 90°C, were selected from the temperature change curve from 40°C to 90°C as the temperature detection point sequence. By querying the technical data sheet of the acrylic-modified epoxy adhesive used in this project, the curing efficiency data corresponding to each temperature point were obtained. For example, the curing efficiency at 60°C is 0.68 mm² / min (representing the cross-linking area of the adhesive in the transverse direction per unit time), at 70°C is 1.23 mm² / min, and at 80°C is 1.85 mm² / min. These data were plotted into a temperature-curing efficiency control chart, and it was found that the curing efficiency increases with the increase in temperature, but the increase rate significantly slows down after 85°C, and the curve tends to be flat. Through peak analysis, it was determined that the curing efficiency in the 75 - 85°C range is the highest, which is marked as the preferred temperature range. Considering that the decorative panel uses a PC / ABS composite material with a heat distortion temperature of 105°C, but according to the thermal stress analysis, when the temperature exceeds 95°C, the thermal stress in the edge area of the panel begins to approach the yield limit of the material. Therefore, 95°C was determined as the upper limit of the safe temperature, forming a safe temperature range of 40 - 95°C. Then, the bonding strength data of the adhesive after curing for 24 hours at each temperature were analyzed, and it was found that for the samples cured below 60°C, their shear strength could not meet the minimum strength of 12 MPa required by the design. 60°C was determined as the temperature threshold for strength requirements. Finally, taking the intersection of the preferred temperature range (75 - 85°C), the safe temperature range (40 - 95°C), and the strength requirement temperature range (60 - 100°C), 75 - 85°C was obtained as the boundary value of the adapted curing temperature range. In practical applications, the curing temperature was set at 80°C, which not only ensured a sufficiently high curing efficiency, but also had a sufficient safety margin, while meeting the strength requirements, achieving the optimal control of the curing process.

[0079] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

1. A method for gluing and positioning automobile decorative panels, characterized in that: The method for gluing and positioning the automobile decorative panel comprises: Acquire a surface image of the decorative board, identify the contour features of the decorative board, determine the coordinates of the target area for gluing, detect the surface material of the decorative board, and select a matching adhesive according to the surface material of the decorative board; Setting a positioning reference point, calculating a position deviation value of the decorative panel, and adjusting the position of the decorative panel if the position deviation value is greater than a first threshold value; Detecting the ambient temperature and humidity, and adjusting if they are beyond a preset range, and performing surface activation treatment on the target area for gluing; Generate a gluing trajectory, control the gluing equipment to apply the adhesive, and detect the adhesive application uniformity in real time. If it is lower than the second threshold, adjust the gluing parameters; Collect and analyze adhesive distribution images, set curing parameters according to the type of adhesive, and perform curing until a third threshold is reached.

2. The method for gluing and positioning automobile decorative panels according to claim 1, characterized in that: The step of acquiring a surface image of the decorative board, identifying contour features of the decorative board, determining coordinates of a target area for gluing, detecting a surface material of the decorative board, and selecting a matching adhesive according to the surface material of the decorative board includes: The surface images of the decorative plate at multiple angles are collected by a multi-spectral imaging device, and each of the surface images is subjected to image fusion processing to obtain a high-definition fused image of the decorative plate; Performing contour extraction processing on the high-definition fused image of the decorative panel, extracting an edge feature point set of the decorative panel through an edge enhancement algorithm, and determining a shape contour map of the decorative panel according to the edge feature point set; Based on the shape contour map, identifying the structural change area on the decorative plate through region segmentation processing, and marking the area with a curvature change value greater than a curvature threshold as a key structural area; Determining the coordinates of the gluing target area according to the matching degree between the key structural area and the preset gluing rule; Scanning the surface of the decorative board using a reflection spectrum analyzer to obtain reflection spectrum data of the surface of the decorative board; Comparing and analyzing the reflection spectrum data with the standard spectrum in the material feature database, calculating the similarity coefficient, and determining the surface material type of the decorative board according to the similarity coefficient; Based on the surface material type, an adhesive matching the surface material type is screened out from an adhesive formula database, and the required amount of adhesive is calculated according to the area of ​​the gluing target area.

3. The method for gluing and positioning automobile decorative panels according to claim 2, characterized in that: The setting of the positioning reference point, calculating the position deviation value of the decorative plate, and adjusting the position of the decorative plate if the position deviation value is greater than a first threshold value, includes: Based on the coordinates of the gluing target area, a high-brightness characteristic marking pattern is projected on the decorative plate by a marking projector to form a plurality of identifiable positioning reference point coordinates; The actual position images of the coordinates of multiple positioning reference points are collected by visual sensors, and the positions of multiple preset reference points on the working platform are extracted at the same time; Performing one-to-one coordinate transformation on the coordinates of the plurality of positioning reference points and the positions of the plurality of preset reference points to generate a position relationship data set of the decorative panel; Performing difference calculation on each set of corresponding point position information in the position relationship data set and the standard installation position data to obtain multiple sets of position deviation data; Extracting deviation components in the X-axis, Y-axis and Z-axis directions from the multiple sets of position deviation data, and calculating the position deviation value by weighted average; Comparing the position deviation value with the first threshold, and if the position deviation value is greater than the first threshold, calculating a three-dimensional correction vector based on the multiple sets of position deviation data; Based on the three-dimensional correction vector, the positioning mechanism is controlled to perform multi-degree-of-freedom adjustment on the position of the decorative panel until the position deviation value is less than or equal to the first threshold.

4. The method for gluing and positioning automobile decorative panels according to claim 1, characterized in that: The detected ambient temperature and humidity are adjusted if they exceed a preset range, and the surface activation treatment is performed on the target area for gluing, including: The temperature sensor array distributed in the workspace collects temperature data at multiple points to form temperature distribution field data, and the humidity sensor array collects humidity data at multiple points to form humidity distribution field data; Performing spatial interpolation calculation on the temperature distribution field data to obtain a temperature curve diagram of the gluing area, and performing spatial interpolation calculation on the humidity distribution field data to obtain a humidity curve diagram of the gluing area; Compare the temperature value in the temperature curve of the glue application area with the upper limit and lower limit of the temperature range, and if it exceeds the temperature range, calculate the temperature adjustment instruction; Compare the humidity value in the humidity curve of the glue application area with the upper limit and lower limit of the humidity range, and if it exceeds the humidity range, calculate a humidity adjustment instruction; Controlling the environment adjustment device according to the temperature adjustment instruction and the humidity adjustment instruction, adjusting the temperature and humidity parameters of the working space, and determining the surface activation strength parameter and the activation time parameter based on the surface material of the decorative panel and the coordinates of the gluing target area; A plasma flow is applied to the target glue application area by a surface treatment device to perform surface activation treatment to form an enhanced bonding interface layer.

5. The method for gluing and positioning automobile decorative panels according to claim 1, characterized in that: The method of generating a gluing trajectory, controlling the gluing equipment to perform coating, and detecting the adhesive coating uniformity in real time, and adjusting the gluing parameters if the uniformity is lower than a second threshold, includes: Constructing a glue application guide point set based on the coordinates of the glue application target area, extracting key inflection points and coating direction vectors from the guide point set, and sorting the key inflection points according to the optimized path based on the coating direction vector to generate a glue application path guide line; Smoothing the guide line of the gluing path, calculating the speed control parameter and the glue quantity control parameter at each node, and generating gluing trajectory data; Convert the glue trajectory data into a glue device control instruction, drive the glue nozzle to move along the glue trajectory, and apply adhesive to the decorative panel; The high-speed camera system is used to collect the glue line imaging data in real time during the gluing process, and the glue line width value, glue line continuity index and edge uniformity index are extracted; The glue line width value, the glue line continuity index and the edge neatness index are calculated according to weight combination to obtain an adhesive coating uniformity score; Compare the adhesive coating uniformity score with the second threshold value, and if it is lower than the second threshold value, calculate the glue pressure adjustment amount and the speed adjustment amount according to the insufficient score; The gluing parameters are corrected according to the gluing pressure adjustment amount and the speed adjustment amount, and the gluing equipment is continuously controlled to perform additional coating on the uneven area.

6. The method for gluing and positioning automobile decorative panels according to claim 1, characterized in that: The collecting and analyzing the adhesive distribution image, setting the curing parameters according to the type of adhesive, and performing the curing process until the third threshold is reached include: Performing image stitching processing on the adhesive distribution image to obtain an adhesive distribution panorama, and calculating the actual adhesive coverage area by extracting the adhesive coverage area boundary line from the adhesive distribution panorama; Comparing the actual adhesive coverage area with the theoretical coverage area to generate an adhesive distribution deviation map; Querying an adhesive curing characteristic database according to the type of the adhesive to obtain an optimal curing temperature curve and curing time parameters of the adhesive; Calculate the curing energy compensation coefficient of each region based on the adhesive distribution deviation map to generate a regionalized curing parameter matrix; Controlling the curing equipment to perform differential curing treatment on the adhesive according to the regionalized curing parameter matrix, and monitoring the curing temperature distribution of the adhesive in real time through a thermal imaging system to calculate a curing degree index; The curing degree index is compared with the third threshold, and the curing parameters are continuously adjusted until the curing degree index reaches the third threshold.

7. The method for gluing and positioning automobile decorative panels according to claim 6, characterized in that: The step of querying the adhesive curing characteristic database according to the type of the adhesive to obtain the optimal curing temperature curve and curing time parameters of the adhesive includes: According to the type code of the adhesive, extracting corresponding curing parameter records from the adhesive curing characteristic database; Obtaining key curing temperature points and transition characteristic data of the adhesive from the curing parameter record; Draw a temperature tolerance range diagram of the adhesive according to the key curing temperature point to determine the upper and lower limits of the safe curing temperature; Based on the surface material characteristics of the decorative board, the upper and lower limits of the safe curing temperature are adjusted to generate an adaptive curing temperature range; Selecting the optimal curing starting temperature and ending temperature within the adapted curing temperature range to construct an optimal curing temperature curve for the adhesive; According to the optimal curing temperature curve and the transformation characteristic data, three curing time parameters of the adhesive, namely, preheating time, main curing time, and cooling time, are determined.

8. The method for gluing and positioning automobile decorative panels according to claim 7, characterized in that: The step of adjusting the upper and lower limits of the safe curing temperature based on the surface material characteristics of the decorative board to generate an adaptive curing temperature range includes: Extracting the thermal deformation temperature and thermal stability parameters of the surface material of the decorative panel from the material database; Compare the thermal deformation temperature with the upper limit of the safe curing temperature, and take the smaller value of the two as the upper limit of the curing temperature after adjustment; Comparing the thermal stability parameter with the lower limit of the safe curing temperature to determine the lowest curing temperature that satisfies the surface material characteristics of the decorative board; Determining a temperature transfer delay factor according to thermal conductivity data of the surface material of the decorative panel; constructing a temperature change relationship between the adjusted upper curing temperature limit and the minimum curing temperature based on the temperature transfer delay factor; The boundary value of the adapted curing temperature range is determined by analyzing the corresponding relationship between the temperature variation relationship and the curing efficiency of the adhesive.

9. The method for gluing and positioning automobile decorative panels according to claim 8, characterized in that: The step of determining the boundary value of the adapted curing temperature range by analyzing the corresponding relationship between the temperature change relationship and the curing efficiency of the adhesive comprises: Selecting a plurality of representative temperature points from the temperature variation relationship to form a temperature detection point sequence; Matching each temperature value in the temperature detection point sequence with the curing efficiency data of the adhesive to form a temperature-curing efficiency comparison chart; Find the temperature range with the best curing efficiency in the temperature-curing efficiency comparison chart, and mark it as the preferred temperature range; Combined with the thermal stress limit of the surface material of the decorative panel, a safe temperature range that will not cause thermal deformation of the decorative panel is screened out; By analyzing the bonding strength data of the adhesive under various temperature conditions, a temperature threshold that can meet the design strength requirements is determined; The boundary value of the adapted curing temperature range is determined by comprehensively considering the intersection of the preferred temperature range, the safe temperature range and the temperature threshold.

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