A control and hardware synchronization system for visual alignment of large-area printed splicing

Abstract

This invention discloses a control and hardware synchronization system for visual alignment of large-area printed fabric splicing, relating to the fields of machine vision and image processing technology. The system includes: a data acquisition module that frequently acquires fabric deformation, environmental parameters, and visual feature data; a deformation prediction module that constructs prediction rules based on a database and outputs deformation parameters; a pre-compensation parameter module that calculates the offset and generates a pre-compensation set; a hardware synchronization module that synchronizes parameters using a precision time protocol; and a loop monitoring module that compares images and provides feedback correction instructions to ensure accurate and efficient splicing. This invention, by constructing a preset fabric deformation database and dedicated prediction rules, predicts the deformation trend of the splicing area in advance, generating accurate visual alignment parameters that adapt to different fabrics and working conditions, thus improving splicing accuracy. Simultaneously, by utilizing a precision time protocol for dynamic calibration and error correction, it achieves efficient collaboration between parameters and hardware, combined with closed-loop feedback optimization, ensuring stable splicing over long periods, improving production efficiency, and reducing costs.

Description

Technical Field

[0001] This invention relates to the field of machine vision and image processing technology, specifically to a control and hardware synchronization system for visual alignment of large-area printed splicing. Background Technology

[0002] In the textile, apparel, home furnishing, and outdoor decoration industries, the market demand for large-area printed products continues to grow. These products often require multi-unit printing and splicing to form a complete pattern, such as large-format curtains, wide carpets, and large decorative fabrics. The splicing accuracy directly determines the product's appearance integrity and visual effect, and is a core indicator affecting product quality. With the increasing variety of fabric materials, including cotton, silk, elastic fibers, and synthetic fabrics, and the fluctuating temperature and humidity conditions at the printing station during production, fabrics are prone to stretching and shrinkage during transport and printing, posing challenges to visual alignment during splicing. The industry urgently needs high-precision splicing control technology that can effectively address fabric deformation and achieve hardware synergy to meet the stable production needs under different fabrics and working conditions.

[0003] Current traditional large-area printing splicing technologies mostly adopt a "post-correction" approach, meaning that hardware parameters are adjusted manually or through simple programs after splicing deviations occur. This approach cannot predict fabric deformation trends in advance, leading to the accumulation of deviations and making it difficult to guarantee consistently high-precision splicing. Furthermore, traditional technologies lack systematic deformation data support for various fabric types, making it difficult to adapt to the inherent differences in fabric characteristics. Hardware synchronization often relies on fixed-cycle calibration, failing to dynamically adjust according to data acquisition rhythm and parameter update needs, easily resulting in asynchrony between pre-compensation parameters and hardware actions. In addition, some technologies do not establish a complete real-time monitoring and parameter feedback closed loop. After long-term production, splicing accuracy is easily affected by equipment wear and environmental changes, requiring frequent shutdowns for debugging. This not only reduces production efficiency but also increases material waste and production costs, making it difficult to meet the industry's requirements for efficient and high-precision production. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a control and hardware synchronization system for visual alignment of large-area printed splicing. This system constructs a preset fabric deformation database and exclusive deformation prediction rules, combined with customized deformation prediction and pre-compensation offset calculation formulas, forming a complete technical chain from fabric deformation prediction to visual alignment parameter generation. This system breaks through the traditional "deviation first, then correction" mode, predicting deformation trends in advance and generating accurate parameters suitable for different fabrics and working conditions. Simultaneously, it utilizes a precise time protocol for dynamic calibration and error correction to ensure efficient collaboration between parameters and hardware. Combined with closed-loop feedback optimization, it achieves stable splicing over long periods, improving production efficiency and reducing costs.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a control and hardware synchronization system for visual alignment of large-area printed splicing, the system comprising:

[0006] Data acquisition module: used to collect fabric deformation data, printing station environmental parameters, and visual feature data of splicing edges;

[0007] Deformation prediction module: It receives the output data from the data acquisition module, performs the calculation corresponding to the deformation prediction formula based on the deformation prediction rules constructed from the preset fabric deformation database, and outputs the deformation parameters of the fabric splicing area.

[0008] Pre-compensation parameter module: Used to receive the output data of the deformation prediction module, perform the calculation corresponding to the pre-compensation offset calculation formula, and generate a visual alignment pre-compensation parameter set;

[0009] Hardware synchronization module: Used to receive the output data of the pre-compensation parameter module, and synchronize the pre-compensation parameters to each hardware unit through a precise time protocol. The synchronization process is combined with the calculation corresponding to the synchronous execution parameter formula.

[0010] The loop monitoring module is used to acquire images of the stitched area and compare them with standard stitched images to generate parameter correction instructions that are fed back to the deformation prediction module and the pre-compensation parameter module.

[0011] Furthermore, the data acquisition module has an acquisition frequency of no less than 100 Hz; the acquired fabric deformation data includes the transverse stretching and longitudinal shrinkage of the fabric, and the environmental parameters include the temperature and humidity of the printing station. The acquisition accuracy of the above data is as follows: fabric deformation data accuracy is no less than 0.01 mm, temperature accuracy is no less than ±0.5 degrees Celsius, and humidity accuracy is no less than ±1%RH.

[0012] Furthermore, the deformation sample of each fabric in the preset fabric deformation database contains deformation data of the fabric in the range of 0 to 5% elongation, and the sampling conditions cover the range of temperature from 15 to 40 degrees Celsius and humidity from 30% to 80% RH.

[0013] Furthermore, the process of constructing the deformation prediction rule is as follows: first, based on the fabric features obtained by the data acquisition module, the corresponding fabric type in the preset fabric deformation database is matched; then, the deformation association data corresponding to the fabric type is called; finally, the historical deformation time sequence features and environmental influence factors are integrated to construct the association calculation logic; the deformation association data includes the correspondence between the inherent deformation characteristics of the fabric and environmental parameters, which is determined by multiple calibration data under the same working condition.

[0014] Furthermore, in the deformation prediction module, the deformation prediction calculation formula is: ,in, For prediction The degree of deformation at the fabric splicing area at all times; This is a comprehensive coefficient representing the temporal deformation and inherent properties of the fabric. For the first The temporal weight of historical deformation at each moment; For the first The measured fabric deformation range at any given moment; This is the temperature influence coefficient; The difference between the temperature at the printing station at time t and the reference temperature under standard fabric conditions; γ is the temperature deformation coefficient of the corresponding fabric in the preset fabric deformation database; γ is the humidity influence coefficient. The difference between the humidity at the printing station at time t and the baseline humidity under standard fabric conditions; This is the humidity deformation coefficient of the corresponding fabric in the preset fabric deformation database.

[0015] Furthermore, in the pre-compensation parameter module, the formula for calculating the pre-compensation offset is: ,in, This represents the pattern offset of the printing unit; for The degree of deformation at the fabric splicing area at all times; The physical resolution of the printed pattern; For industrial camera pixel density; The elastic recovery coefficient of the fabric; This is the baseline offset calculated based on the visual feature data of the stitched edges.

[0016] Furthermore, the visual alignment pre-compensation parameter set includes: the pattern lateral offset of the printing unit, the pattern longitudinal offset, the industrial camera shooting angle adjustment value, and the camera focal length compensation value; each parameter is determined based on the result of the visual alignment pre-compensation pattern offset calculation formula, combined with the splicing edge visual feature data obtained by the data acquisition module.

[0017] Furthermore, the calibration cycle of the master clock and the slave clock of the precision time protocol is adapted and set according to the data acquisition frequency and the pre-compensation parameter update frequency, and the calibration cycle does not exceed 10 milliseconds.

[0018] Furthermore, in the hardware synchronization module, the formula for calculating the synchronization execution parameters is as follows: ,in, The pattern offset that is ultimately executed by the hardware; This is the theoretical pre-compensation offset. This is the synchronization error coefficient for the precision time protocol. This coefficient is calculated from the real-time deviation between the master and slave clocks and its value ranges from ±0.005. For parameter transmission delay time; This refers to the linear speed of the conveyor rollers.

[0019] Furthermore, the similarity comparison index used by the cyclic monitoring module is the structural similarity index; when this index is below 0.95, the parameter correction instruction generated by the cyclic monitoring module includes the weight adjustment value of the deformation prediction rule and the correction amount of the pre-compensation parameter. The weight adjustment value is used to update the temporal weights in the deformation prediction rule. .

[0020] Compared with existing technologies, this control and hardware synchronization system for visual alignment of large-area printed splicing has the following advantages:

[0021] I. This invention establishes a complete technical chain from fabric deformation prediction to visual alignment parameter generation by constructing a preset fabric deformation database and exclusive deformation prediction rules, coupled with customized deformation prediction formulas and pre-compensation offset calculation formulas. This chain breaks through the passive mode of "correcting deviations after deviations" in traditional large-area printing and splicing. Based on the fabric's own characteristics, historical deformation patterns, and real-time environmental conditions, it can predict the deformation trend of the splicing area in advance and generate the parameters required for visual alignment. This effectively adapts to the printing needs of different types of fabrics and different working conditions, avoids splicing misalignment problems caused by differences in fabric characteristics and environmental fluctuations, significantly improves the accuracy of printing and splicing, and reduces defective product losses caused by splicing deviations.

[0022] Second, this invention achieves efficient coordination between pre-compensation parameters and hardware actions through a dynamic calibration mechanism based on a precision time protocol, combined with error correction logic for synchronous execution parameter formulas. The system can flexibly adjust the clock calibration strategy according to actual data flow and parameter update requirements. Simultaneously, the error correction logic compensates for deviations in parameter transmission and hardware response, avoiding pre-compensation failures caused by hardware synchronization delays. Furthermore, the similarity comparison and parameter feedback closed loop constructed by the cyclic monitoring module can optimize deformation prediction rules and pre-compensation parameters in real time, ensuring stable splicing accuracy during long-term continuous printing, reducing the frequency of manual adjustments, improving overall production efficiency, and lowering equipment operation and maintenance costs.

[0023] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0025] Figure 1 This is a flowchart illustrating the overall system control and data interaction process.

[0026] Figure 2 Generate a logic flowchart for deformation prediction and pre-compensation parameters;

[0027] Figure 3 This is a flowchart of the hardware synchronization and closed-loop monitoring execution process. Detailed Implementation

[0028] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0029] Example 1:

[0030] like Figure 1 As shown, the first embodiment of this invention provides a control and hardware synchronization system for visual alignment of large-area printed splicing. This embodiment is applied to the continuous printing splicing production of 3-meter wide cotton and linen curtains in textile enterprises. The cotton and linen curtains need to be spliced ​​together by 3 sets of printing units to form a complete floral pattern. The cotton and linen fabric is prone to longitudinal shrinkage of 0.5%-1% due to the temperature and humidity changes in the workshop in the morning, noon and evening. The system of this invention is needed to achieve high-precision alignment throughout the process. The specific configuration and operation process of each module of the system are as follows:

[0031] First, the data acquisition module is activated. The laser displacement sensor on the module continuously collects the lateral stretch and longitudinal shrinkage of the cotton and linen fabric during the conveying process at a set frequency. Simultaneously, the temperature and humidity sensor is activated to collect real-time temperature and humidity data of the printing station. At the same time, a 5-megapixel industrial camera installed behind the printing unit is aimed at the edge of the fabric splicing and continuously collects the visual feature data of the edge outline of the floral pattern and the color gradient transition zone at the splicing point. All collected data is transmitted to the system data processing unit for temporary storage in real time.

[0032] Next, as Figure 2As shown, the deformation prediction module retrieves collected data from the data processing unit. First, it matches the cotton and linen fabric type in the preset fabric deformation database using the fabric texture recognition module. Then, it calls the corresponding deformation correlation data for that fabric type—data obtained from 20 sets of cotton and linen fabric deformation calibration experiments under different temperature and humidity conditions, including the correspondence between the inherent shrinkage characteristics of cotton and linen fabric and temperature and humidity changes. Subsequently, the module integrates the historical deformation time sequence characteristics from the past 10 minutes with the current temperature and humidity influencing factors, executes the calculation corresponding to the deformation prediction formula, and outputs the longitudinal shrinkage and transverse stretching deformation parameters of the cotton and linen fabric splicing area at the next moment. The parameter results are transmitted to the pre-compensation parameter module. The deformation prediction calculation formula is: ,in, For prediction The degree of deformation at the fabric splicing area at all times; This is a comprehensive coefficient representing the temporal deformation and inherent properties of the fabric. For the first The temporal weight of historical deformation at each moment; For the first The measured fabric deformation range at any given moment; This is the temperature influence coefficient; The difference between the temperature at the printing station at time t and the reference temperature under standard fabric conditions; γ is the temperature deformation coefficient of the corresponding fabric in the preset fabric deformation database; γ is the humidity influence coefficient. The difference between the humidity at the printing station at time t and the baseline humidity under standard fabric conditions; This is the humidity deformation coefficient of the corresponding fabric in the preset fabric deformation database.

[0033] Then, after receiving the deformation parameters, the pre-compensation parameter module combines them with the visual feature data of the flower edges acquired by the industrial camera, executes the calculation corresponding to the pre-compensation offset calculation formula, and generates a visual alignment pre-compensation parameter set. The pre-compensation offset calculation formula is as follows: ,in, This represents the pattern offset of the printing unit; for The degree of deformation at the fabric splicing area at all times; The physical resolution of the printed pattern; For industrial camera pixel density; The elastic recovery coefficient of the fabric; This is the baseline offset calculated based on the visual feature data of the splicing edge. This parameter set includes: the vertical offset of the printed unit pattern for vertical shrinkage, the horizontal offset of the pattern for horizontal stretching, the focal length compensation value of the industrial camera adapted to the surface texture of cotton and linen fabrics, and the angle adjustment value for adjusting the camera shooting angle. The parameter set is sent to the hardware synchronization module after being verified by the system.

[0034] Afterwards, the hardware synchronization module receives the pre-compensation parameter set. Based on the data acquisition frequency and the pre-compensation parameter update frequency, it adjusts the calibration cycle of the master clock of the precision time protocol and the slave clocks of the six printhead groups and three fabric conveyor rollers of the printing machine to the appropriate values. During synchronization, it performs calculations corresponding to the synchronization execution parameter formula. Combining the delay time of parameter transmission from the system to the hardware with the fabric conveyor roller's conveying speed of 1.2 meters per minute, it corrects the printhead inkjet timing and conveyor roller speed parameters to ensure that after the pre-compensation parameters are issued, the printhead inkjet position and the fabric conveying progress are precisely matched, avoiding pattern misalignment caused by synchronization deviations. The synchronization execution parameter calculation formula is as follows: ,in, The pattern offset that is ultimately executed by the hardware; This is the theoretical pre-compensation offset. This represents the synchronization error coefficient for the precision time protocol. For parameter transmission delay time; This refers to the linear speed of the conveyor rollers.

[0035] Finally, the loop monitoring module is activated. Its image comparison unit continuously retrieves real-time images of the splicing area captured by the industrial camera and compares them with the pre-stored 3-meter-wide standard spliced ​​image of cotton and linen curtains using a structural similarity index. When color breaks or outline misalignment are detected at the splicing point of the floral pattern, or when the index is below a set threshold, the module immediately generates parameter correction instructions. These instructions are fed back to the deformation prediction module to adjust the weighting of historical deformation time sequence features, and to the pre-compensation parameter module to optimize the pattern offset and camera focal length parameters. This ensures the continuous and complete floral pattern during subsequent printing and splicing processes, meeting the appearance quality requirements of the curtain products. Figure 3 As shown.

[0036] In summary, this embodiment addresses the scenario of wide-width printing and splicing of cotton and linen curtains. Through the collaborative efforts of the laser displacement sensor, temperature and humidity sensor, and industrial camera in the data acquisition module, comprehensive data on fabric deformation, working conditions, and edge vision are acquired. The deformation prediction module, relying on the specific deformation correlation data and historical time-series characteristics of cotton and linen fabrics, calculates and outputs accurate deformation parameters using a deformation prediction formula. The pre-compensation parameter module combines visual features to generate a complete parameter set including pattern offset and camera parameters. The hardware synchronization module dynamically adjusts the clock calibration cycle and corrects transmission delay and conveying speed deviations by synchronously executing parameter formulas, achieving collaboration between the printhead and conveyor rollers. The cyclic monitoring module compares images in real time and provides feedback for correction, effectively solving the problem of temperature and humidity-sensitive deformation of cotton and linen fabrics. This ensures the continuous and complete splicing of floral patterns on 3-meter-wide curtains, meeting the high-precision and stable production requirements of large-area textile printing.

[0037] Example 2:

[0038] like Figure 1As shown, the second embodiment of this invention provides a control and hardware synchronization system for visual alignment of large-area printed splicing. This embodiment is applied to the printing and splicing production of elastic polyester fiber sportswear panels in sportswear enterprises. The sportswear panels are 1.5m × 0.8m front panels of finished garments, which need to be spliced ​​together by two sets of printing units to form side stripe patterns. Elastic polyester fiber fabric is prone to 1%-2% rebound deformation after stretching. Traditional technology is prone to stripe misalignment. The system of this invention needs to be adapted to its elastic characteristics. The specific configuration and operation process of each module of the system are as follows:

[0039] First, the data acquisition module is activated. The tension sensor and laser displacement sensor on the module work together to collect the longitudinal stretch of the elastic polyester fiber fabric during the conveying and printing process at a set frequency. Since the sportswear fabric needs to be spliced ​​with stripes along the longitudinal direction, the longitudinal stretch is the core data to be collected. At the same time, the workshop constant temperature system, together with temperature and humidity sensors, stably controls the temperature of the printing station at 25±1℃ and collects humidity data in real time to avoid temperature fluctuations from aggravating the elastic deformation of the fabric. In addition, an industrial camera installed 30 cm above the fabric positioning device continuously collects the visual feature data of the fluorescent color alignment marks of the stripes on the side of the fabric. All collected data is transmitted to the system cache module in real time.

[0040] Next, the deformation prediction module retrieves the collected data from the cache module, matches the elastic polyester fiber fabric type in the preset fabric deformation database through the fabric elasticity coefficient detection unit, and calls the deformation correlation data corresponding to the fabric type. This data includes elastic rebound curves under 5 different tensile forces, as well as the influence of humidity on the rebound rate. Subsequently, the module integrates the historical time sequence characteristics of the stretching-rebound of the cut pieces in the past 5 minutes, executes the calculation corresponding to the deformation prediction formula, focuses on predicting the longitudinal shrinkage deformation parameters caused by elastic rebound after the cut pieces are printed, and sends the parameter results to the pre-compensation parameter module in real time.

[0041] Then, after receiving the deformation parameters, the pre-compensation parameter module combines them with the visual feature data of the fluorescent alignment markers to perform the calculation corresponding to the pre-compensation offset calculation formula, generating a visual alignment pre-compensation parameter set for elastic fabrics. This parameter set includes: the longitudinal offset of the stripe pattern considering the shrinkage of the fabric, the adjustment value of the industrial camera's 15-degree downward shooting angle to adapt to the slight three-dimensional curvature of the fabric, the camera focal length compensation value to ensure clear recognition of the fluorescent markers, and the lateral fine-tuning offset to assist in the positioning of the fabric. After system compatibility verification, the parameter set is transmitted to the hardware synchronization module.

[0042] Afterwards, the hardware synchronization module receives the pre-compensation parameter set. First, based on the acquisition frequency corresponding to the deformation rate of the elastic fabric, it adjusts the master clock of the precision time protocol and the slave clock calibration cycle of the fabric vacuum adsorption positioning device and the four printing nozzles to the appropriate value. During the synchronization process, it performs calculations corresponding to the synchronization execution parameter formulas. Combining the delay time of parameter transmission from the system to the hardware and the moving speed of the fabric positioning device, it corrects the adsorption force of the positioning device and the inkjet interval of the nozzles to ensure that the fabric positioning position and the inkjet position of the nozzles are accurately matched after the pre-compensation parameters are issued, avoiding splicing deviations caused by elastic rebound.

[0043] Finally, the cyclic monitoring module is activated. Its image analysis unit continuously compares the structural similarity index of the real-time acquired side stripe images of the cut pieces with the standard stripe alignment images, focusing on detecting the overlap of the fluorescent alignment marks. When the stripe alignment deviation is detected to exceed the allowable range or the index is lower than the set threshold, the module immediately generates a parameter correction command. On the one hand, it feeds back to the deformation prediction module to adjust the prediction logic of the elastic rebound trend; on the other hand, it feeds back to the pre-compensation parameter module to optimize the stripe pattern offset. At the same time, the correction signal is sent to the cut piece positioning device to fine-tune the cut piece position, ensuring that the side stripes are continuous and misaligned after the sportswear cut pieces are printed and spliced, meeting the appearance and wearing adaptation requirements of sportswear.

[0044] In summary, this embodiment focuses on the striped splicing scenario of elastic polyester fiber sportswear panels. The data acquisition module uses a tension sensor to collect the longitudinal stretch of the panels, a constant temperature system works with a temperature and humidity sensor to stabilize the temperature and collect humidity data, and an industrial camera collects stripe fluorescent alignment mark data. The deformation prediction module calls the elastic fabric rebound curve data and uses a deformation prediction formula to predict the rebound deformation. The pre-compensation parameter module combines the fluorescent marks to generate a parameter set adapted to the elastic characteristics, including rebound compensation offset and camera tilt angle adjustment value. The hardware synchronization module adapts to the deformation rate adjustment calibration cycle and optimizes the coordination between the positioning device and the printhead by synchronously executing the parameter formula. The cyclic monitoring module verifies and corrects the stripe alignment marks in real time, successfully avoiding misalignment problems caused by elastic fabric rebound, ensuring accurate side stripe splicing of sportswear panels, and meeting the appearance and adaptation requirements of apparel printing.

[0045] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A control and hardware synchronization system for visual alignment of large-area printed splicing, characterized in that, The system includes: Data acquisition module: used to collect fabric deformation data, printing station environmental parameters, and visual feature data of splicing edges; Deformation prediction module: Receives output data from the data acquisition module, executes calculations corresponding to the deformation prediction formula based on deformation prediction rules constructed from a preset fabric deformation database, and outputs deformation parameters of the fabric splicing area. The construction process of the deformation prediction rules is as follows: first, the fabric features obtained by the data acquisition module are matched with the corresponding fabric type in the preset fabric deformation database; then, the deformation association data corresponding to that fabric type is called; finally, historical deformation time series features and environmental influence factors are fused to construct the association calculation logic. The deformation association data includes the correspondence between the inherent deformation characteristics of the fabric and environmental parameters, determined by multiple calibration data under the same working condition. Pre-compensation parameter module: Used to receive the output data of the deformation prediction module, perform the calculation corresponding to the pre-compensation offset calculation formula, and generate a visual alignment pre-compensation parameter set; Hardware synchronization module: Used to receive the output data of the pre-compensation parameter module, and synchronize the pre-compensation parameters to each hardware unit through a precise time protocol. The synchronization process is combined with the calculation corresponding to the synchronous execution parameter formula. The loop monitoring module is used to acquire images of the stitched area and compare them with standard stitched images to generate parameter correction instructions that are fed back to the deformation prediction module and the pre-compensation parameter module.

2. The control and hardware synchronization system for visual alignment of large-area printed splicing according to claim 1, characterized in that, The data acquisition module has an acquisition frequency of no less than 100 Hz; the acquired fabric deformation data includes the transverse stretch and longitudinal shrinkage of the fabric, and the environmental parameters include the temperature and humidity of the printing station. The acquisition accuracy of the above data is as follows: fabric deformation data accuracy is no less than 0.01 mm, temperature accuracy is no less than ±0.5 degrees Celsius, and humidity accuracy is no less than ±1%RH.

3. The control and hardware synchronization system for visual alignment of large-area printed splicing according to claim 1, characterized in that, The preset fabric deformation database contains deformation samples for each fabric, including deformation data of the fabric in the range of 0 to 5% elongation. The sampling conditions cover the range of temperature from 15 to 40 degrees Celsius and humidity from 30% to 80% RH.

4. The control and hardware synchronization system for visual alignment of large-area printed splicing according to claim 1, characterized in that, In the deformation prediction module, the deformation prediction calculation formula is: ,in, For prediction The degree of deformation at the fabric splicing area at all times; This is a comprehensive coefficient representing the temporal deformation and inherent properties of the fabric. For the first The temporal weight of historical deformation at each moment; For the first The measured fabric deformation range at any given moment; This is the temperature influence coefficient; The difference between the temperature at the printing station at time t and the reference temperature under standard fabric conditions; γ is the temperature deformation coefficient of the corresponding fabric in the preset fabric deformation database; γ is the humidity influence coefficient. The difference between the humidity at the printing station at time t and the baseline humidity under standard fabric conditions; This is the humidity deformation coefficient of the corresponding fabric in the preset fabric deformation database.

5. The control and hardware synchronization system for visual alignment of large-area printed splicing according to claim 4, characterized in that, In the pre-compensation parameter module, the formula for calculating the pre-compensation offset is: ,in, This is the theoretical pre-compensation pattern offset for the printing unit; for The degree of deformation at the fabric splicing area at all times; The physical resolution of the printed pattern; For industrial camera pixel density; The elastic recovery coefficient of the fabric; This is the baseline offset calculated based on the visual feature data of the stitched edges.

6. The control and hardware synchronization system for visual alignment of large-area printed splicing according to claim 1, characterized in that, The visual alignment pre-compensation parameter set includes: the pattern lateral offset of the printing unit, the pattern longitudinal offset, the industrial camera shooting angle adjustment value, and the camera focal length compensation value; each parameter is determined based on the result of the visual alignment pre-compensation pattern offset calculation formula, combined with the splicing edge visual feature data obtained by the data acquisition module.

7. The control and hardware synchronization system for visual alignment of large-area printed splicing according to claim 1, characterized in that, The calibration cycle of the master clock and the slave clock of the precision time protocol is adapted and set according to the data acquisition frequency and the pre-compensation parameter update frequency, and the calibration cycle does not exceed 10 milliseconds.

8. The control and hardware synchronization system for visual alignment of large-area printed splicing according to claim 1, characterized in that, In the hardware synchronization module, the formula for calculating the synchronization execution parameters is as follows: ,in, The pattern offset that is ultimately executed by the hardware; This is the theoretical pre-compensation pattern offset for the printing unit; This represents the synchronization error coefficient for the precision time protocol. For parameter transmission delay time; This refers to the linear speed of the conveyor rollers.

9. The control and hardware synchronization system for visual alignment of large-area printed splicing according to claim 4, characterized in that, The similarity comparison index used by the cyclic monitoring module is the structural similarity index. When this index is below 0.95, the parameter correction instruction generated by the cyclic monitoring module includes the weight adjustment value of the deformation prediction rule and the correction amount of the pre-compensation parameter. The weight adjustment value is used to update the temporal weights in the deformation prediction rule. .

Images