A method, system, medium and product for sensing a print substrate for drop precision regulation

Abstract

The application discloses a method, system, medium and product for precisely regulating ink drops on a printing substrate, and relates to the technical field of printing control. The method comprises the following steps: collecting surface feature data of the printing substrate, matching initial ejection parameters and theoretical spreading parameters corresponding to the surface feature data of the printing substrate from a preset parameter library; controlling an inkjet print head to eject probe ink drops on a test area of the printing substrate according to the initial ejection parameters, and obtaining a time sequence image of the probe ink drops; measuring the spreading diameters of the probe ink drops at each time node based on the time sequence image of the probe ink drops, so as to determine actual spreading parameters of the probe ink drops; comparing the actual spreading parameters with the theoretical spreading parameters to obtain a spreading deviation; determining an initial ejection parameter correction amount according to the spreading deviation and a pre-established parameter correction mapping relationship; calculating corrected ejection parameters based on the initial ejection parameter correction amount and the initial ejection parameters; and controlling the inkjet print head to perform inkjet printing on a printing area of the printing substrate according to the corrected ejection parameters. The above method realizes self-adaptive and precise regulation of ink drop ejection on the characteristics of the printing substrate.

Description

Technical Field

[0001] This application relates to the field of printing control technology, and in particular to a method, system, medium and product for precise control of ink droplets sensing the substrate. Background Technology

[0002] Inkjet printing technology, as a non-contact digital printing method, has been widely used in various fields such as graphic printing, packaging electronics, and textile printing. During inkjet printing, print quality depends not only on the hardware performance of the inkjet printhead itself but also on the interaction between ink droplets and the substrate surface. Different substrate materials have different surface energies, roughness, and porosity, among other physicochemical properties. These properties directly affect the spreading, penetration, and drying processes of ink droplets after they impact the substrate, thus determining the clarity, color saturation, and resolution of the final image.

[0003] Existing inkjet printing control methods typically employ a preset parameter retrieval scheme based on material classification. Technicians conduct extensive printing tests on various common substrates (such as coated paper, PET film, and pure cotton fabric) to calibrate standard jetting parameters (such as drive voltage, ignition waveform, and ink temperature) suitable for each material. Before executing a printing task, the operator simply selects the substrate material category in the control software, and the system automatically retrieves the corresponding standard jetting parameters and controls the inkjet printhead to complete the entire batch of printing jobs according to those parameters.

[0004] However, in practical applications, even substrates of the same type can exhibit significant differences in their physicochemical properties due to subtle variations in manufacturer, batch, storage environment (such as temperature and humidity changes), and surface coating processes. In such cases, if standardized inkjet parameters are still used for printing, the ink droplet spreading behavior on the substrate surface will deviate from expectations, severely reducing the final output quality of high-precision printing tasks. Summary of the Invention

[0005] This application provides a method, system, medium, and product for precise control of ink droplets sensing the substrate, used to achieve adaptive and precise control of ink droplet ejection on the characteristics of the substrate.

[0006] In a first aspect, this application provides a method for precise control of ink droplets sensing a printing substrate, applied to a control system. The method includes: acquiring surface feature data of the printing substrate; matching initial jetting parameters and theoretical spreading parameters corresponding to the surface feature data of the printing substrate from a preset parameter library; controlling the inkjet printhead to jet probe ink droplets in the test area of ​​the printing substrate according to the initial jetting parameters, and acquiring a time-series image of the probe ink droplets; measuring the spreading diameter of the probe ink droplets at each time node based on the time-series image of the probe ink droplets to determine the actual spreading parameters of the probe ink droplets; comparing the actual spreading parameters with the theoretical spreading parameters to obtain the spreading deviation; determining the initial jetting parameter correction amount according to the spreading deviation amount and a pre-established parameter correction mapping relationship; calculating the corrected jetting parameters based on the initial jetting parameter correction amount and the initial jetting parameters; and controlling the inkjet printhead to perform inkjet printing on the printing area of ​​the printing substrate according to the corrected jetting parameters.

[0007] By adopting the above technical solution, the limitations of traditional fixed parameters that cannot adapt to individual differences in the substrate are overcome. It can sense the actual state of ink droplet spreading in real time for different substrates and dynamically adjust the jetting parameters. This effectively solves the problem of ink droplet spreading deviating from expectations due to differences in substrate material, batch, and surface characteristics. It significantly improves the consistency and controllability of ink droplet jetting and spreading in inkjet printing, ensures the clarity, color uniformity, and resolution of high-precision printed patterns, and achieves adaptive and precise control of ink droplet jetting to substrate characteristics.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the substrate surface feature data includes the texture direction of the substrate surface, and the spreading diameter of the probe ink droplet at each time point is measured to determine the actual spreading parameters of the probe ink droplet. Specifically, this includes: measuring the spreading size of the probe ink droplet at each time point along the texture direction and the anti-texture direction, respectively, to obtain the primary spreading change rate and the secondary spreading change rate, wherein the anti-texture direction is perpendicular to the texture direction; and using the primary spreading change rate and the secondary spreading change rate as the actual spreading parameters.

[0009] By adopting the above technical solution, the ink droplet spreading size at different time points is measured along the texture direction (primary direction) and the perpendicular reverse texture direction (secondary direction), and the spreading change rate of the primary and secondary directions is calculated as the actual spreading parameters. This can accurately characterize the anisotropic characteristics of ink droplet spreading on the surface of textured substrates (such as textile fabrics and wood grain paper), providing a core basis for subsequent deviation comparison and parameter correction that conforms to the actual spreading law. This avoids inaccurate parameter correction due to ignoring the differences in texture direction, greatly improves the directional consistency of ink droplet spreading when printing textured substrates, and reduces problems such as blurred pattern edges and uneven texture.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, the theoretical spreading parameters include the theoretical principal direction rate of change and the theoretical secondary direction rate of change. The actual spreading parameters are compared with the theoretical spreading parameters to obtain the spreading deviation. Specifically, this includes: comparing the principal direction rate of change and the secondary direction rate of change with the theoretical principal direction rate of change and the theoretical secondary direction rate of change, respectively, to obtain the principal direction spreading deviation and the secondary direction spreading deviation; calculating the difference between the principal direction spreading deviation and the secondary direction spreading deviation to obtain the anisotropy deviation degree; and using the principal direction spreading deviation, the secondary direction spreading deviation, and the anisotropy deviation degree as the spreading deviation amount.

[0011] By adopting the above technical solution, the shortcomings of traditional deviation comparison, which only focuses on overall deviation and cannot distinguish between directional deviation and anisotropic deviation, are overcome. It can accurately locate the source of ink droplet spreading deviation (primary direction, secondary direction, or texture anisotropy), providing accurate and comprehensive deviation basis for subsequent targeted correction of jetting parameters. This ensures that the corrected jetting parameters can simultaneously correct the primary and secondary spreading deviations of ink droplets as well as anisotropic deviations, further enhancing the ability to accurately control ink droplet spreading on anisotropic substrates and significantly improving the overall uniformity and detail reproduction of printed patterns.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the initial jetting parameter correction amount is determined based on the spreading deviation amount and a pre-established parameter correction mapping relationship. Specifically, this includes: matching the driving waveform correction amount corresponding to the anisotropic deviation degree in the parameter correction mapping relationship; matching the droplet volume correction amount in the parameter correction mapping relationship based on the average of the primary spreading deviation and the secondary spreading deviation; and combining the driving waveform correction amount and the droplet volume correction amount as the initial jetting parameter correction amount.

[0013] By adopting the above technical solutions, the parameter correction is directional, targeted, and adaptable to the overall situation, which effectively improves the accuracy and effectiveness of jet parameter correction, ensures that the spread of ink droplets on the substrate is more in line with the design expectations, and further improves the detail reproduction and overall uniformity of the printed pattern.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, the process of establishing the parameter correction mapping relationship specifically includes: selecting multiple standard substrate samples, with different standard substrate samples corresponding to different substrate surface feature data; setting multiple sets of jetting parameter combinations for each standard substrate sample, the jetting parameter combinations including different driving waveform parameters and droplet volume parameters; controlling the inkjet printhead to jet calibration droplets onto the corresponding standard substrate sample according to each set of jetting parameter combinations, and acquiring the spreading data of each set of calibration droplets; calculating the spreading deviation corresponding to each set of jetting parameter combinations based on the spreading data; establishing a first mapping relationship between the anisotropy deviation and the driving waveform correction amount in the spreading deviation amount, and establishing a second mapping relationship between the mean of the primary spreading deviation and the secondary spreading deviation and the droplet volume correction amount; combining the first mapping relationship and the second mapping relationship as the parameter correction mapping relationship.

[0015] By adopting the above technical solution, a reliable and standardized mapping basis is provided for parameter correction, which solves the problem of lack of quantitative standards and reliance on experience-based debugging in parameter correction. Through calibration with a large number of standard samples, the parameter correction mapping relationship has universality and stability, and can be adapted to substrates with different materials and surface characteristics.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, the spreading size of the probe ink droplet at each time node is measured along the texture direction and the anti-texture direction, respectively, to obtain the primary spreading change rate and the secondary spreading change rate. The anti-texture direction is perpendicular to the texture direction. Specifically, this includes: extracting the spreading contour of the probe ink droplet at each time node from the probe ink droplet time-series image, the probe ink droplet time-series image including the time-series image corresponding to each time node; determining the primary measurement axis and the secondary measurement axis based on the texture direction, the primary measurement axis being parallel to the texture direction and the secondary measurement axis being parallel to the anti-texture direction; measuring the maximum span of the spreading contour in each time-series image along the primary measurement axis to obtain the primary spreading size sequence at each time node; measuring the maximum span of the spreading contour in each time-series image along the secondary measurement axis to obtain the secondary spreading size sequence at each time node; performing curve fitting on the primary spreading size sequence to calculate the size change slope in the spreading stable stage as the primary spreading change rate; performing curve fitting on the secondary spreading size sequence to calculate the size change slope in the spreading stable stage as the secondary spreading change rate.

[0017] By adopting the above technical solution, the inaccuracy of subsequent deviation judgment and parameter correction caused by parameter measurement errors is avoided, ensuring the accuracy of the entire ink droplet control process from the source, and in particular, greatly improving the accuracy of the characterization of ink droplet spreading characteristics of textured substrates.

[0018] In some embodiments of the first aspect, before comparing the actual spreading parameters with the theoretical spreading parameters to obtain the spreading deviation, the method further includes: acquiring the internal ink temperature data of the inkjet printhead; calculating the current ink viscosity influence factor based on the internal ink temperature data and a preset ink temperature-viscosity characteristic curve; dynamically compensating the theoretical spreading parameters using the current ink viscosity influence factor to obtain the compensated theoretical spreading parameters; and comparing the actual spreading parameters with the compensated theoretical spreading parameters.

[0019] By adopting the above technical solutions, the problems of ink viscosity fluctuation and unstable ink droplet spreading are effectively solved, the printing system's ability to resist temperature fluctuations is enhanced, the stability and consistency of ink droplet spreading under different temperature conditions are guaranteed, and the stability and reliability of printing quality are further improved.

[0020] In a second aspect, embodiments of this application provide a control system comprising: one or more processors and a memory; the memory is coupled to the one or more processors and is used to store computer program code, the computer program code including computer instructions, wherein the one or more processors invoke the computer instructions to cause the control system to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a control system, cause the control system to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a control system, cause the control system to perform the method described in the first aspect and any possible implementation thereof.

[0023] Understandably, the control system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0025] 1. By adopting the above technical solution, the limitation of traditional fixed parameters being unable to adapt to individual differences in the substrate is overcome. It can sense the actual state of ink droplet spreading in real time for different substrates and dynamically correct the jetting parameters. This effectively solves the problem of ink droplet spreading deviating from expectations due to differences in substrate material, batch, and surface characteristics. It significantly improves the consistency and controllability of ink droplet jetting and spreading in inkjet printing, ensures the clarity, color uniformity, and resolution of high-precision printed patterns, and achieves adaptive and precise control of ink droplet jetting to substrate characteristics.

[0026] 2. By adopting the above technical solution, the ink droplet spreading size at different time points is measured along the texture direction (primary direction) and the perpendicular reverse texture direction (secondary direction), and the spreading change rate of the primary and secondary directions is calculated as the actual spreading parameters. This can accurately characterize the anisotropic characteristics of ink droplet spreading on the surface of textured substrates (such as textile fabrics and wood grain paper), providing a core basis for subsequent deviation comparison and parameter correction that conforms to the actual spreading law. This avoids inaccurate parameter correction due to ignoring the differences in texture direction, greatly improves the directional consistency of ink droplet spreading when printing textured substrates, and reduces problems such as blurred pattern edges and uneven texture.

[0027] 3. By adopting the above technical solution, the shortcomings of traditional deviation comparison, which only focuses on overall deviation and cannot distinguish between directional deviation and anisotropic deviation, are overcome. It can accurately locate the source of ink droplet spreading deviation (primary direction, secondary direction, or texture anisotropy), providing accurate and comprehensive deviation basis for subsequent targeted correction of jetting parameters. This ensures that the corrected jetting parameters can simultaneously correct the primary and secondary spreading deviations of ink droplets as well as anisotropic deviations, further enhancing the ability to accurately control ink droplet spreading on anisotropic substrates and significantly improving the overall uniformity and detail reproduction of printed patterns. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating a method for precisely controlling ink droplets on a printing substrate, as described in an embodiment of this application.

[0029] Figure 2 This is another flowchart illustrating the method for precisely controlling ink droplets on the printing substrate in the embodiments of this application;

[0030] Figure 3 This is a schematic diagram of the physical device structure of a control system in an embodiment of this application. Detailed Implementation

[0031] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0033] The following describes the process of the method provided in this implementation. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating a method for precisely controlling ink droplets on a printing substrate in an embodiment of this application.

[0034] S101. Collect surface feature data of the substrate and match the initial spraying parameters and theoretical spreading parameters corresponding to the surface feature data of the substrate from the preset parameter library;

[0035] The substrate refers to the target material carrier for inkjet printing, such as coated paper, PET film, glass substrate, and textile fabric, which are printing media with different surface properties. Substrate surface characteristic data refers to a set of quantitative parameters used to characterize the physicochemical properties of the substrate surface, including but not limited to parameters such as surface roughness, surface energy, contact angle, porosity, and ink absorption rate. For example, a PET film surface measured with a contact angle meter has a contact angle of 72° and a surface roughness Ra of 0.15 μm with a standard test liquid. The preset parameter library refers to a multidimensional lookup table or dataset pre-calibrated and stored through numerous experiments. This library establishes a correspondence between substrate surface characteristic data and jetting and spreading parameters. For example, it stores corresponding recommended parameter entries for different contact angle ranges and roughness level combinations. Initial jetting parameters refer to the inkjet printhead operating parameters directly retrieved from the preset parameter library by the control system before real-time correction. These parameters include jetting voltage, pulse width, jetting frequency, and droplet volume. For example, a jetting voltage of 24V, a pulse width of 8μs, and a droplet volume of 10pL. Theoretical spreading parameters refer to the descriptive parameters of the expected spreading behavior of ink droplets on the substrate surface, determined based on calibration experimental data in a preset parameter library under ideal conditions. These parameters include theoretical final spreading diameter, theoretical spreading rate, and theoretical equilibrium time. For example, the theoretical final spreading diameter is 45 μm and the theoretical equilibrium time is 120 ms.

[0036] Specifically, the control system detects the current substrate through a surface feature acquisition module integrated into the printing equipment. This module may include a contact angle measurement sensor, a surface roughness detection probe, and an optical reflectivity sensor. The control system digitizes the acquired multidimensional surface feature data to form a feature vector. Subsequently, using this feature vector as an index, the control system performs a multidimensional matching search in a preset parameter library. Employing a nearest neighbor search algorithm or interpolation method, it finds the parameter entry in the preset parameter library that most closely matches the surface feature data of the current substrate, thereby extracting the corresponding initial spraying parameters and theoretical spreading parameters. If the surface feature data of the current substrate falls exactly between two calibrated entries in the preset parameter library, the control system can also calculate the transition parameter value using linear interpolation or weighted averaging to ensure the accuracy and continuity of the matching results.

[0037] S102. Control the inkjet printhead to eject probe ink droplets in the substrate test area according to the initial ejection parameters, and acquire a probe ink droplet timing image;

[0038] Inkjet printheads are precision devices installed on printing equipment that eject ink from micro-nozzles in droplet form based on electrical signals. For example, piezoelectric inkjet printheads use the deformation of piezoelectric ceramics to generate pressure pulses that propel ink out of the nozzle. The substrate test area is a pre-defined, informal printing area on the substrate surface specifically designed for ejecting probe droplets for parameter calibration. This area is typically located in the blank space outside the substrate edge or printed content area, such as a 5mm x 10mm area reserved outside the left margin of an A4 sheet of paper. Probe droplets are test droplets ejected for parameter calibration purposes, not for forming the final pattern. They are usually one or more independent droplets used to observe and analyze the actual interaction between the droplets and the substrate surface. The detection droplet time sequence image refers to a set of ordered images obtained by continuously taking pictures at preset time intervals during the entire process of the detection droplet from the moment it contacts the substrate surface to the moment it spreads and tends to stabilize, using a high-speed imaging device. For example, if one frame is taken at a frequency of 5ms, the images are continuously taken from 0ms when the droplet contacts the substrate surface to 200ms, and a total of 41 time sequence images are obtained.

[0039] Specifically, after the control system completes the parameter matching in step S101, it immediately enters the actual detection phase to verify the actual performance of the initial jetting parameters on the current substrate. First, the control system automatically determines the position coordinates of the substrate test area based on the substrate's size information and the print job layout, and drives the printhead moving mechanism to position the inkjet printhead above the substrate test area. Then, according to the initial jetting parameters determined in step S101, the control system sends corresponding voltage waveform signals to the inkjet printhead's drive circuit, controlling the inkjet printhead to jet a preset number of probe ink droplets in the substrate test area. Simultaneously, the control system triggers a high-speed camera or stroboscopic imaging system installed near the printhead to begin synchronous image acquisition. The optical axis of the stroboscopic imaging system is typically set at a certain top or side angle to the substrate surface to clearly observe the spread of the probe ink droplets on the substrate surface. The stroboscopic imaging system continuously acquires images at preset time intervals until the ink droplet spread reaches a steady state. The control system then organizes and stores all acquired image frames in chronological order, forming complete probe ink droplet time-series image data.

[0040] S103. Based on the time-series image of the probe ink droplet, measure the spreading diameter of the probe ink droplet at each time node to determine the actual spreading parameters of the probe ink droplet;

[0041] In this context, "time node" refers to the moment in the time-series image sequence corresponding to each frame of the probe ink droplet, starting from the initial contact of the probe ink droplet with the substrate surface, such as sampling moments like 0ms, 5ms, and 10ms. "Spreading diameter" refers to the equivalent circular diameter of the liquid film or ink trail formed by the probe ink droplet on the substrate surface; that is, the maximum span of the wetted area of ​​the ink droplet when viewed from above. For example, the spreading diameter of an ink droplet at 50ms is 38μm. "Actual spreading parameters" refers to the set of parameters describing the actual spreading behavior of the ink droplet, obtained by analyzing and summarizing the actual measured values ​​of the spreading diameter at each time node in the probe ink droplet time-series image. These parameters include the actual final spreading diameter, the actual spreading rate curve, and the actual time to reach equilibrium. For example, the actual final spreading diameter is 52μm, the actual peak spreading rate is 0.8μm / ms, and the actual equilibrium time is 150ms.

[0042] Specifically, after the control system completes image acquisition in step S102, it immediately performs image processing and parameter extraction analysis on the acquired time-series images of the detected ink droplets. The control system sequentially loads each frame of the time-series image, performs preprocessing operations including grayscale conversion, noise filtering, and contrast enhancement, and then uses edge detection algorithms or threshold segmentation algorithms to identify the boundary contour of the ink droplet spreading area in each frame. After acquiring the boundary contour, the control system calculates the area enclosed by the boundary contour and equates it to a circle to calculate the equivalent diameter, or directly measures the maximum span of the boundary contour in the horizontal and vertical directions and takes the average as the spreading diameter. The control system records the spreading diameter corresponding to each time node to form a data sequence of spreading diameter changes over time. Then, through data fitting or feature extraction methods, it calculates the actual final spreading diameter, spreading rate change curve, spreading acceleration, and time to reach steady-state equilibrium from this data sequence, forming a complete set of actual spreading parameter descriptions.

[0043] Optionally, generally, the surface feature data of the substrate includes the texture direction of the substrate surface. Measuring the spreading diameter of the probe ink droplet at each time point to determine the actual spreading parameters of the probe ink droplet can be achieved in the following ways, without limitation: along the texture direction and against the texture direction, respectively measure the spreading size of the probe ink droplet at each time point to obtain the primary spreading change rate and the secondary spreading change rate, with the anti-texture direction perpendicular to the texture direction; use the primary spreading change rate and the secondary spreading change rate as the actual spreading parameters.

[0044] The texture direction refers to the main extension direction of the directional micro or macro textures formed on the surface of the substrate by the material's own structure or processing technology. Examples include the warp direction in textile fabrics, the extension direction of wood fibers in wood grain paper, or the orientation direction of molecular chains in uniaxially stretched PET films. The reverse texture direction refers to the direction perpendicular to the texture direction within the plane of the substrate surface. Examples include the weft direction in textile fabrics and the transverse direction perpendicular to the wood grain in wood grain paper. The principal direction spreading rate refers to the rate of change in the size of the ink droplet per unit time during the spreading process along the texture direction (i.e., the principal direction). It reflects the speed at which the ink droplet spreads along the texture direction of the substrate. For example, the spreading rate of ink droplets along the warp direction on textile fabrics is 0.65 μm / ms. The secondary spreading rate refers to the rate at which the size of the ink droplet changes per unit time during the spreading process along the reverse direction (i.e., the secondary direction). It reflects the speed at which the ink droplet spreads along a direction perpendicular to the grain. For example, the spreading rate of an ink droplet along the weft direction on a textile fabric is 0.42 μm / ms. The spreading size refers to the span of the boundary of the wetted area of ​​the ink droplet on the substrate surface in a specific measurement direction, that is, the maximum width of the ink droplet spreading area measured along a specified axis.

[0045] Specifically, after confirming that the current substrate is a textured substrate (for example, by identifying a clear directional texture structure on the substrate surface through surface feature data collected in step S101), the control system performs directional refinement processing on the measurement process of the spreading diameter in step S103. The control system first establishes an orthogonal measurement coordinate system with the texture direction as the primary direction and the anti-texture direction as the secondary direction based on the collected texture direction information. Subsequently, in the time-series images at each time point, the control system no longer only measures the overall equivalent diameter of the ink droplet spreading area, but independently measures the spreading size of the ink droplets along both the texture direction and the anti-texture direction. For textured substrates, due to the anisotropic characteristics of their surface microstructure—for example, the different distribution of yarn gaps along the warp and weft directions in textile fabrics, and the more tightly arranged fiber bundles along the wood grain direction in wood grain paper—the spreading behavior of ink droplets in the texture direction is usually significantly different from that in the anti-texture direction. The control system forms a time series of the spreading dimensions measured along the texture direction at each time point, and then calculates the slope of this series to obtain the primary spreading rate of change. Similarly, it forms a time series of the spreading dimensions measured along the reverse texture direction at each time point, and then calculates the slope of this series to obtain the secondary spreading rate of change. Finally, the control system combines the primary and secondary spreading rates of change as the actual spreading parameters. This parameter set can fully characterize the anisotropic characteristics of ink droplet spreading on the textured substrate surface, providing accurate experimental basis for the directional comparison with the theoretical spreading parameters in the subsequent step S104.

[0046] Optionally, in general, the spreading size of the probe droplet at each time node is measured along the texture direction and the anti-texture direction, respectively, to obtain the primary spreading change rate and the secondary spreading change rate. The anti-texture direction being perpendicular to the texture direction can be achieved in the following ways, which are not limited here: Extract the spreading contour of the probe droplet at each time node from the probe droplet time series image, which includes the time series image corresponding to each time node; Based on the texture direction, determine the primary measurement axis and the secondary measurement axis, with the primary measurement axis parallel to the texture direction and the secondary measurement axis parallel to the anti-texture direction; Measure the maximum span of the spreading contour in each time series image along the primary measurement axis to obtain the primary spreading size sequence at each time node; Measure the maximum span of the spreading contour in each time series image along the secondary measurement axis to obtain the secondary spreading size sequence at each time node; Perform curve fitting on the primary spreading size sequence to calculate the size change slope in the spreading stable stage, as the primary spreading change rate; Perform curve fitting on the secondary spreading size sequence to calculate the size change slope in the spreading stable stage, as the secondary spreading change rate.

[0047] The spreading profile refers to the closed boundary curve of the wetted area of ​​the probe ink droplet on the substrate surface, extracted through image processing in each frame of the time-series image. This curve depicts the complete external shape of the liquid film-covered area of ​​the ink droplet at the corresponding time point. For example, the spreading profile on anisotropic substrates usually presents an elliptical or irregular shape rather than a standard circle. The primary measurement axis is a linear reference axis set by the control system in the image coordinate system, parallel to the substrate texture direction, used to measure the spreading size along the texture direction. The secondary measurement axis is a linear reference axis set by the control system in the image coordinate system, parallel to the reverse texture direction, used to measure the spreading size along the direction perpendicular to the texture. The secondary measurement axis is orthogonal to the primary measurement axis. The maximum span refers to the distance between the two farthest endpoints of the spreading profile boundary along a specified measurement axis direction, i.e., the maximum projected length of the spreading profile in that direction. For example, the maximum span of the spreading profile along the primary measurement axis direction is 48 μm. The principal paving dimension sequence refers to an ordered data sequence composed of the maximum span values ​​of the paving profile measured along the principal measurement axis at each time point, arranged in chronological order. For example, {t0=0ms: 10μm, t1=5ms: 22μm, t2=10ms: 31μm, t3=15ms: 38μm, ..., t} n =200ms: 52μm}. The secondary paving dimension sequence refers to an ordered data sequence composed of the maximum span values ​​of the paving profile measured along the secondary measurement axis at each time point, arranged chronologically. For example, {t0=0ms: 10μm, t1=5ms: 18μm, t2=10ms: 24μm, t3=15ms: 29μm, ..., t n =200ms: 38μm}. Curve fitting refers to a data analysis method that uses mathematical function models to approximate and describe discrete data point sequences. Control systems can use polynomial fitting, exponential function fitting, or power law function fitting to fit the spreading size sequence, obtaining a continuous analytical function describing the spreading size change over time. The spreading stability stage refers to the later stage in the process of ink droplets spreading on the substrate surface, after the initial rapid diffusion stage, where the size change tends to be slow and relatively stable. In this stage, the growth rate of the spreading size is significantly lower than in the initial stage. For example, from 100ms to 200ms, the spreading size only slowly increases from 49μm to 52μm. The size change slope refers to the first derivative of the spreading size with respect to time or the slope of the linear regression on the fitted curve during the spreading stability stage. It represents the amount of change in the spreading size per unit time during this stage. For example, the size change slope of the main spreading in the stability stage is 0.03μm / ms.

[0048] Specifically, the control system executes the above-mentioned directional spreading measurement process according to the following refined procedure:

[0049] First, the control system sequentially loads image frames corresponding to each time node in the time-series image of the probe ink droplets. For each frame, preprocessing operations such as grayscale conversion, Gaussian filtering for noise reduction, and adaptive threshold segmentation are performed. Then, using the Canny edge detection algorithm or a gradient-based contour tracking algorithm, the complete closed boundary of the area where the probe ink droplets spread on the substrate surface is extracted from each frame—that is, the spreading contour. If the boundary of the ink droplet spreading area is locally blurred or discontinuous, the control system can also use morphological closing operations or spline curve interpolation to smooth and complete the contour.

[0050] Secondly, based on the substrate texture direction information acquired in step S101 (e.g., the angle θ between the texture direction and the horizontal axis of the image coordinate system), the control system establishes a primary measurement axis and a secondary measurement axis in the image coordinate system. The primary measurement axis passes through the geometric center point of the laid-out contour, with an orientation angle of θ, and is parallel to the texture direction; the secondary measurement axis also passes through the geometric center point of the laid-out contour, with an orientation angle of θ+90°, and is parallel to the reverse texture direction. The two axes are orthogonal to each other, together forming an orthogonal coordinate framework for directional measurement.

[0051] Then, the control system measures the span of the unfolded contour in each frame of the time-series image along both the primary and secondary measurement axes. Specifically, the control system projects the coordinates of all pixels on the unfolded contour onto the primary measurement axis and calculates the difference between the maximum and minimum projected values, which is the maximum span of the unfolded contour along the primary measurement axis in that frame. Similarly, the control system projects the coordinates of the contour pixels onto the secondary measurement axis and calculates the difference between the extreme values ​​of the projections, which is the maximum span along the secondary measurement axis. The control system, combined with the spatial resolution calibration parameters of the imaging system (i.e., the actual physical size corresponding to each pixel), converts the span value per pixel unit into an actual physical size value. After completing the above measurements frame by frame for all time nodes, the control system arranges the primary measurement axis span values ​​of each frame in chronological order to form a primary unfolded size sequence, and arranges the secondary measurement axis span values ​​of each frame in chronological order to form a secondary unfolded size sequence.

[0052] Finally, the control system performs curve fitting analysis on the main-direction spreading size sequence and the secondary-direction spreading size sequence respectively. The control system selects an appropriate fitting model (for example, for typical ink droplet spreading behavior, a power law function D(t)=a·t^b+c or an exponential decay growth function D(t)=D_max·(1-e^(-t / τ)) and other forms can be used for fitting), solves the fitting parameters through the least squares method, and obtains a fitting curve describing the continuous change of the spreading size over time. Subsequently, the control system identifies the start time point of the spreading stabilization stage according to the characteristics of the fitting curve—usually taking the second derivative of the fitting curve approaching zero or the spreading rate decreasing to a certain preset proportion (for example, 10%) of the peak rate as the determination criterion. After determining the time interval of the spreading stabilization stage, the control system calculates the average first derivative value of the fitting curve within this interval, that is, the size change slope, takes the size change slope of the main-direction spreading size sequence in the stabilization stage as the main-direction spreading change rate, and takes the size change slope of the secondary-direction spreading size sequence in the stabilization stage as the secondary-direction spreading change rate. The main-direction spreading change rate and the secondary-direction spreading change rate together constitute the core component of the actual spreading parameter, which accurately quantifies the difference in the steady-state spreading behavior of ink droplets in different directions on the surface of textured printing substrates.

[0053] S104. Comparing the actual spreading parameter with the theoretical spreading parameter to obtain a spreading deviation amount;

[0054] Wherein, the spreading deviation amount is a quantitative representation of the degree of difference between the actual spreading parameter and the theoretical spreading parameter, which is used to indicate the degree and direction of deviation of the ink droplet spreading behavior of the current printing substrate from the expected ideal state under actual inkjet conditions. For example, a final spreading diameter deviation of +7μm indicates that the actual spreading diameter is 7μm larger than the theoretical spreading diameter, and a final equilibrium time deviation of +30ms indicates that the actual time required to reach equilibrium is 30ms more than the theoretical time required to reach equilibrium.

[0055] Specifically, the control system performs item-by-item subtraction or ratio calculation on each component in the actual spreading parameter, including the actual final spreading diameter, actual spreading rate, actual equilibrium time, etc., and the corresponding component in the theoretical spreading parameter, including the theoretical final spreading diameter, theoretical spreading rate, theoretical equilibrium time, etc., to calculate the absolute deviation or relative deviation of each component. The control system combines the deviation values of all components to form a spreading deviation vector, which contains both the magnitude information of the deviation and the direction information of the deviation, that is, it can indicate whether the actual spreading is too large or too small, too fast or too slow. In addition, the control system can also assign weight coefficients to the deviations of each component to calculate a comprehensive deviation index, so as to uniformly measure the severity of the deviation degree and determine the correction strength in subsequent steps.

[0056] Optionally, in general, the theoretical spreading parameters include the theoretical principal direction rate of change and the theoretical secondary direction rate of change. The spreading deviation can be obtained by comparing the actual spreading parameters with the theoretical spreading parameters, which is not limited here: compare the principal direction rate of change and the secondary direction rate of change with the theoretical principal direction rate of change and the theoretical secondary direction rate of change, respectively, to obtain the principal direction spreading deviation and the secondary direction spreading deviation; calculate the difference between the principal direction spreading deviation and the secondary direction spreading deviation to obtain the anisotropy deviation degree; and use the principal direction spreading deviation, the secondary direction spreading deviation, and the anisotropy deviation degree as the spreading deviation amount.

[0057] The theoretical principal direction rate of change refers to the expected rate of change of ink droplet size per unit time under ideal conditions when spreading along the texture direction (principal direction) based on the surface feature data of the current substrate, as specified in the preset parameter library. This value is derived from the baseline value obtained after conducting a large number of standardized spreading experiments on similar substrates before leaving the factory. For example, the theoretical principal direction rate of change for a certain textile fabric is 0.60 μm / ms, which represents the expected spreading rate of ink droplets along the warp direction in the stable spreading stage under standard jetting parameters. The theoretical secondary direction rate of change refers to the expected rate of change of ink droplet size per unit time under ideal conditions when spreading along the reverse direction (secondary direction) based on the surface feature data of the current substrate, as specified in the preset parameter library. For example, the theoretical secondary direction rate of change for a certain textile fabric is 0.40 μm / ms, which represents the expected spreading rate of ink droplets along the weft direction in the stable spreading stage under standard jetting parameters. The primary spreading deviation refers to the difference between the actual measured primary spreading rate and the theoretical primary spreading rate. It characterizes the degree and direction to which the actual spreading behavior of the ink droplet along the texture direction deviates from the expected state. For example, when the actual primary spreading rate is 0.65 μm / ms and the theoretical primary spreading rate is 0.60 μm / ms, the primary spreading deviation is +0.05 μm / ms. A positive value indicates that the actual spreading rate is faster than the theoretical expectation. The secondary spreading deviation refers to the difference between the actual measured secondary spreading rate and the theoretical secondary spreading rate. It characterizes the degree and direction to which the actual spreading behavior of the ink droplet along the anti-texture direction deviates from the expected state. For example, when the actual secondary spreading rate is 0.48 μm / ms and the theoretical secondary spreading rate is 0.40 μm / ms, the secondary spreading deviation is +0.08 μm / ms. Anisotropy deviation refers to the difference between the primary and secondary spreading deviations. It quantifies the deviation of the directional unevenness of ink droplet spreading on the substrate from the theoretical expectation. For example, when the primary spreading deviation is +0.05 μm / ms and the secondary spreading deviation is +0.08 μm / ms, the anisotropy deviation is 0.05 - 0.08 = -0.03 μm / ms. A negative value indicates that the spreading deviation in the secondary direction is greater than that in the primary direction, meaning that the ink droplet spreading in the reverse direction exceeds expectations more significantly, and the unevenness in both directions is worsening. The spreading deviation amount is a multi-dimensional deviation description vector composed of three components: primary spreading deviation, secondary spreading deviation, and anisotropy deviation. This vector comprehensively represents the absolute amount of ink droplet spreading deviating from the expectation in each direction, as well as the relative amount of unevenness deviation between directions, providing complete deviation input information for subsequent parameter correction.

[0058] Specifically, after determining the actual spreading parameters (i.e., the primary spreading rate and the secondary spreading rate) in step S103, the control system immediately enters the directional comparison and analysis stage with the theoretical spreading parameters. The control system first extracts the theoretical primary spreading rate and the theoretical secondary spreading rate from the set of theoretical spreading parameters obtained in step S101. Then, the control system subtracts the theoretical primary spreading rate from the actually measured primary spreading rate to calculate the primary spreading deviation. The sign of this deviation indicates the direction of deviation in primary spreading—a positive value indicates that the actual spreading rate is higher than the theoretical expectation (i.e., the ink droplets spread too quickly in the texture direction, and the spreading area is too large), and a negative value indicates that the actual spreading rate is lower than the theoretical expectation (i.e., the ink droplets spread insufficiently in the texture direction, and the spreading area is too small). Similarly, the control system subtracts the theoretical secondary spreading rate from the actually measured secondary spreading rate to calculate the secondary spreading deviation, the meaning of which is similar to that of the primary spreading deviation.

[0059] Subsequently, the control system further calculates the difference between the primary and secondary spreading deviations to obtain the anisotropy deviation degree. The physical meaning of the anisotropy deviation degree is as follows: if the value is zero, it indicates that although there may be deviations in both the primary and secondary spreading directions, the degree of deviation in both directions is consistent, and the anisotropic characteristics of the ink droplet spreading are consistent with theoretical expectations. In this case, only a holistic adjustment of the ink droplet volume or jetting speed is needed to eliminate the deviation. If the value is not zero, it indicates that the degree of spreading deviation in the two directions is inconsistent, and the actual anisotropic characteristics of the substrate differ from the anisotropic characteristics calibrated in the preset parameter library. In this case, in addition to holistic adjustment, additional adjustments to parameters such as the drive waveform are needed to change the initial momentum distribution or impact posture of the ink droplets to correct the anisotropic deviation in a targeted manner. The larger the absolute value of the anisotropy deviation degree, the more severe the deviation from theoretical expectations in the spreading imbalance between the two directions, and the greater the adjustment force of the drive waveform needs to be in subsequent parameter corrections.

[0060] Ultimately, the control system combines the three components—primary directional spreading deviation, secondary directional spreading deviation, and anisotropic deviation—to form a complete spreading deviation vector. Compared to traditional single scalar deviation descriptions, this spreading deviation vector offers richer and more refined information: the primary and secondary directional spreading deviations reflect the absolute degree to which the spreading behavior deviates from theoretical expectations in each direction, providing a basis for subsequent overall jetting parameter corrections (such as droplet volume adjustment); the anisotropic deviation specifically reflects the additional deviation due to spreading imbalance between two directions, providing an independent basis for subsequent directional jetting parameter corrections (such as drive waveform adjustment). By decoupling and combining these three components as the spreading deviation quantity, the control system can match corresponding correction strategies for different types of deviations in subsequent step S105, achieving synchronous and accurate correction of both overall spreading deviation and directional anisotropic deviation. This avoids the problem of unclear correction direction or inappropriate correction force caused by a single deviation index failing to distinguish the source of the deviation.

[0061] S105. Determine the initial injection parameter correction amount based on the spreading deviation and the pre-established parameter correction mapping relationship;

[0062] The parameter correction mapping relationship refers to a mathematical model or lookup table established in advance through theoretical modeling, experimental calibration, or machine learning training, describing the correspondence between the spreading deviation and the required jet parameter adjustment. This relationship can convert the input spreading deviation into the corresponding jet parameter correction. Examples include multivariate linear mapping models based on fluid dynamics simulation and regression analysis, or nonlinear mapping models obtained through neural network training. The initial jet parameter correction refers to the adjustment increments or decrements applied to each component of the initial jet parameters to eliminate or reduce the spreading deviation. These include voltage correction, pulse width correction, jet frequency correction, and droplet volume correction. For example, a voltage correction of -1.5V means the jet voltage needs to be reduced by 1.5V, and a pulse width correction of +0.5μs means the pulse width needs to be increased by 0.5μs.

[0063] Specifically, the control system inputs the spreading deviation into a pre-established parameter correction mapping model. This model is typically established before the system leaves the factory or during periodic calibration by systematically changing the injection parameters and recording the corresponding spreading changes, thereby fitting a functional relationship between the spreading deviation and the required injection parameter adjustment. The parameter correction mapping can be implemented in various forms, such as multidimensional lookup tables combined with interpolation algorithms, multiple linear regression equations, PID controller gain matrices, or trained feedforward neural networks. The control system outputs an initial injection parameter correction corresponding to the current spreading deviation through forward or backward calculation of this mapping. The direction and magnitude of this correction ensure that the corrected injection effect converges to the desired state described by the theoretical spreading parameters.

[0064] Optionally, under normal circumstances, the initial jet parameter correction amount can be determined based on the spreading deviation and the pre-established parameter correction mapping relationship in the following ways, without limitation: match the driving waveform correction amount corresponding to the anisotropic deviation in the parameter correction mapping relationship; match the droplet volume correction amount in the parameter correction mapping relationship based on the average of the primary and secondary spreading deviations; and combine the driving waveform correction amount and the droplet volume correction amount as the initial jet parameter correction amount.

[0065] Among them, the drive waveform correction amount refers to the adjustment increment applied to the drive voltage waveform parameters currently used by the inkjet printhead to correct the anisotropic deviation of ink droplet spreading. The drive waveform parameters usually include the pulse rise slope, pulse duration, pulse peak voltage, and time interval of multi-pulse sequences. By changing the drive waveform, the initial velocity distribution of ink droplets at the nozzle exit, droplet shape, and momentum direction distribution when impacting the substrate can be controlled, thereby directionally affecting the spreading uniformity of ink droplets in different directions. For example, the drive waveform correction amount can be expressed as a set of adjustment instructions such as increasing the pulse width by +0.3μs or decreasing the pulse rise slope by -0.5V / μs. Droplet volume correction refers to the adjustment increment or decrease that needs to be applied to the current ejected droplet volume to correct the overall spreading deviation of the droplet in the primary and secondary directions (i.e. the common part of the deviation in the two directions). The droplet volume directly affects the total amount of liquid available for spreading after the droplet hits the substrate, and thus affects the final spreading size in all directions. For example, a droplet volume correction of -1.5 pL means that the ejection volume of each droplet needs to be reduced by 1.5 pL to reduce the overall spreading area. The mean of the primary and secondary spreading deviations refers to the value obtained by arithmetically averaging the primary and secondary spreading deviations. This mean reflects the common component of the spreading deviations in the two directions—that is, the overall trend of excessive or insufficient spreading regardless of direction. For example, when the primary spreading deviation is +0.05 μm / ms and the secondary spreading deviation is +0.08 μm / ms, the mean is (0.05 + 0.08) / 2 = +0.065 μm / ms, which means that the average spreading rate of the ink droplet in both directions is 0.065 μm / ms faster than theoretically expected, indicating a trend of excessive overall spreading.

[0066] Specifically, after the control system completes the calculation of the spreading deviation (including three components: primary spreading deviation, secondary spreading deviation, and anisotropic deviation) in step S104, it immediately enters the stage of determining the parameter correction amount. The control system adopts a hierarchical decoupling correction strategy, mapping the anisotropic component and the global component in the spreading deviation to different types of injection parameter corrections to achieve precise directional correction.

[0067] First, the control system extracts the anisotropic deviation component from the spreading deviation and uses it as the input query key to perform a matching search within a pre-established parameter correction mapping relationship. This mapping relationship stores corresponding entries between anisotropic deviation value ranges and corresponding drive waveform adjustment schemes. The control system determines the corresponding drive waveform correction amount by searching the range into which the current anisotropic deviation falls or through interpolation. The reason for linking the anisotropic deviation with the drive waveform correction amount is that the drive waveform directly determines the droplet formation process at the nozzle exit—different pulse waveforms produce droplets with different initial shapes and velocity distributions, thus affecting the momentum distribution at the moment of droplet impact on the substrate. When the anisotropic deviation is positive (major deviation greater than secondary deviation), it indicates that the droplet spreading along the texture direction is more than expected. The control system adjusts the drive waveform to make the droplet momentum distribution more uniform at the moment of impact or to tilt it appropriately towards the secondary direction. When the anisotropic deviation is negative, the waveform adjustment is performed in the opposite direction.

[0068] Secondly, the control system calculates the arithmetic mean of the primary and secondary spreading deviations. This mean eliminates the differences between the two directions, retaining only the commonality of the overall spreading deviation. The control system uses this mean as the input query key to retrieve the corresponding droplet volume correction amount from the parameter correction mapping relationship. The reason for establishing a correlation between the deviation mean and the droplet volume correction amount is that changes in droplet volume have an approximately proportional overall impact on the spreading size in all directions—increasing the droplet volume will increase the spreading size in all directions, while decreasing the droplet volume will decrease the spreading size in all directions. When the deviation mean is positive, it indicates that the overall droplet spreading is too large, and the control system matches a negative droplet volume correction amount to reduce the amount of ejected droplets; when the deviation mean is negative, it indicates that the overall droplet spreading is insufficient, and the control system matches a positive droplet volume correction amount to increase the amount of ejected droplets.

[0069] Finally, the control system combines the matched drive waveform correction and droplet volume correction to form a complete initial ejection parameter correction. In this combined correction, the drive waveform correction is responsible for correcting the directional imbalance deviation of droplet spreading (anisotropic deviation), and the droplet volume correction is responsible for correcting the overall size deviation of droplet spreading (common deviation). The two work together to ensure that the corrected ejection parameters can not only eliminate the average spreading deviation in each direction, but also correct the spreading inconsistency between directions, thus achieving comprehensive and precise control of droplet spreading behavior.

[0070] Optionally, under normal circumstances, the establishment of the parameter correction mapping relationship can be achieved in the following way, without limitation: Select multiple standard substrate samples, with different standard substrate samples corresponding to different substrate surface feature data; set multiple sets of jetting parameter combinations for each standard substrate sample, including different drive waveform parameters and droplet volume parameters; control the inkjet printhead to jet calibration droplets onto the corresponding standard substrate sample according to each set of jetting parameter combinations, and obtain the spreading data of each set of calibration droplets; based on the spreading data, calculate the spreading deviation corresponding to each set of jetting parameter combinations; establish a first mapping relationship between the anisotropy deviation and the drive waveform correction in the spreading deviation, and establish a second mapping relationship between the mean of the primary and secondary spreading deviations and the droplet volume correction; combine the first and second mapping relationships as the parameter correction mapping relationship.

[0071] Among them, the standard substrate samples refer to the representative substrate materials with known and precisely calibrated surface feature data selected during the parameter correction mapping relationship establishment stage. These samples cover different material types and different surface property levels of substrates that may be encountered in practical applications. For example, PET film samples with surface roughness Ra=0.05μm, 0.15μm, 0.30μm and 0.50μm are selected, as well as textile fabric samples with texture direction angles of 0°, 45° and 90°, and coated paper samples with different surface energy levels, etc., which together constitute a standard sample set covering a multi-dimensional feature space. Ejection parameter combinations refer to paired parameter configurations composed of drive waveform parameters and droplet volume parameters according to the experimental design scheme. Each set of ejection parameter combinations represents a specific ejection working state, such as {drive waveform A + droplet volume 8pL}, {drive waveform A + droplet volume 10pL}, {drive waveform B + droplet volume 8pL}, {drive waveform B + droplet volume 10pL}, etc. The drive waveform parameters can include different pulse width values ​​(such as 6μs, 8μs, 10μs) and different pulse rise edge slope values, while the droplet volume parameters can include different nominal droplet volume values ​​(such as 6pL, 8pL, 10pL, 12pL, 14pL). Calibration droplets refer to test droplets ejected according to each set of preset ejection parameter combinations during the parameter correction mapping relationship establishment stage. They are used to collect spreading data and calibrate the mapping relationship. Their function is similar to the probe droplets before formal printing, but there are more of them and they cover a wider range of parameter variations. Spreading data refers to the quantitative descriptive data set obtained by observing and measuring the spreading process of calibration ink droplets on the surface of various standard substrate samples. This includes information such as the primary spreading dimension, secondary spreading dimension, and spreading profile morphology at each time point. The acquisition and processing methods are the same as those for processing the probe ink droplets in steps S102 and S103. The first mapping relationship refers to a mathematical model or lookup table describing the correspondence between the magnitude of the anisotropy deviation and the amount of correction to the driving waveform required to eliminate the deviation. Examples include a regression equation or piecewise linear interpolation table with the anisotropy deviation as the independent variable and the adjustment amount of the driving waveform parameters as the dependent variable. The second mapping relationship refers to a mathematical model or lookup table describing the correspondence between the mean magnitudes of the primary and secondary spreading deviations and the amount of ink droplet volume correction required to eliminate the overall deviation. Examples include a regression equation or piecewise linear interpolation table with the mean deviation as the independent variable and the amount of ink droplet volume adjustment as the dependent variable.

[0072] Specifically, establishing the parameter correction mapping relationship is a systematic calibration process automatically executed by the control system or assisted by technicians during the factory calibration or periodic maintenance calibration of the printing system. Its purpose is to establish a quantitative correspondence between the spreading deviation and the jet parameter correction through a large amount of controlled experimental data. This process is executed sequentially according to the following steps:

[0073] The first step involves the control system or technicians selecting a variety of representative standard substrate samples based on the range of substrate types involved in the target application scenario. Selection principles include: broad material type coverage (e.g., encompassing paper-based, film-based, fabric-based, glass-based, etc.); gradient changes in surface characteristic data within the same material type (e.g., a textile fabric with a gradual change in texture density from sparse to dense); and precise calibration of the surface characteristic data of each sample using sophisticated instruments (e.g., contact angle measuring instruments, surface roughness meters, texture direction analyzers, etc.). Each standard substrate sample corresponds to a set of known substrate surface characteristic data, including precise values ​​for parameters such as texture direction, surface roughness, surface energy, and contact angle.

[0074] The second step involves the control system setting multiple different combinations of ejection parameters for each standard substrate sample, following orthogonal experimental design or full factorial experimental design. Each combination includes a specific configuration of driving waveform parameters (such as specific pulse width, rise time slope, peak voltage, etc.) and a specific configuration of droplet volume parameters. By performing systematic grid sampling or Latin hypercube sampling within the respective value ranges of the driving waveform parameters and droplet volume parameters, it is ensured that the experimental data covers key regions in the parameter space, providing sufficient data support for establishing continuous mapping relationships in the future.

[0075] Third, the control system drives the inkjet printhead to sequentially eject calibration ink droplets onto the corresponding standard substrate samples according to each set of ejection parameter combinations. For each pairing of standard substrate sample and each set of ejection parameter combinations, the control system repeatedly ejects multiple calibration ink droplets to improve the statistical reliability of the measurement data. Simultaneously, the control system triggers the high-speed imaging system to synchronously acquire images of the spreading process of each set of calibration ink droplets on the surface of the standard substrate sample, and extracts the spreading size time series of each set of calibration ink droplets along the main measurement axis and secondary measurement axis according to the image processing and size measurement methods described in step S103, forming a complete spreading data record.

[0076] In the fourth step, based on the spreading data of each group of calibration ink droplets, the control system calculates the primary and secondary spreading change rates of each group of calibration ink droplets according to the methods described in steps S103 and S104. These rates are then compared with the theoretical primary and secondary spreading change rates of the corresponding standard substrate sample under standard jetting parameters. This allows the control system to calculate the spreading deviation generated by each jetting parameter combination on the corresponding standard substrate sample, including primary spreading deviation, secondary spreading deviation, and anisotropy deviation. Simultaneously, the control system records the parameter difference between the jetting parameter combination used to generate this spreading deviation and the standard jetting parameters, i.e., the corresponding drive waveform adjustment and droplet volume adjustment.

[0077] The fifth step involves the control system summarizing and analyzing the experimental data corresponding to all standard substrate samples and all jetting parameter combinations, establishing a first mapping relationship and a second mapping relationship. For the establishment of the first mapping relationship, the control system extracts anisotropic deviation values ​​and corresponding drive waveform adjustment data pairs from all experimental data. Regression analysis methods (such as multinomial regression, support vector regression, or Gaussian process regression) are used to fit the data pairs, establishing a continuous mapping function with anisotropic deviation as input and the required drive waveform correction as output; alternatively, the data pairs are grouped and discretized according to anisotropic deviation value intervals, establishing a piecewise lookup table combined with linear interpolation for the mapping structure. For the establishment of the second mapping relationship, the control system extracts the mean data of the primary and secondary spreading deviations and corresponding droplet volume adjustment data pairs from all experimental data. Similar regression analysis methods or lookup table methods are used to establish a continuous mapping function with the mean deviation as input and the required droplet volume correction as output. During the process of establishing the mapping relationship, the control system can also perform cross-validation on the fitted model to evaluate the model's prediction accuracy and generalization ability, ensuring that the mapping relationship has reliable prediction accuracy within the training data range and within a reasonable extrapolation range.

[0078] In the sixth step, the control system stores the established first and second mapping relationships in the system parameter library, which together form a complete parameter correction mapping relationship. In the subsequent parameter calibration process for formal printing (i.e., step S105), the control system can call this parameter correction mapping relationship, inputting the real-time calculated spreading deviation to quickly obtain the corresponding initial jetting parameter correction. Since this parameter correction mapping relationship is established based on systematic experimental data from multiple standard substrate samples and multiple sets of jetting parameter combinations, it covers the general laws between spreading deviation and parameter correction under different material types and surface characteristics. Therefore, it possesses good versatility and adaptability, and can provide reliable parameter correction guidance for various substrates encountered in practical applications.

[0079] S106. Calculate the corrected injection parameters based on the initial injection parameter correction amount and the initial injection parameters;

[0080] Among them, the corrected jetting parameters refer to the final set of working parameters used to control the inkjet printhead to perform formal printing, which is obtained by superimposing the initial jetting parameters and the correction amount of the initial jetting parameters. This set of working parameters has been specifically adjusted to adapt to the actual surface condition of the current substrate. For example, the corrected jetting voltage is 22.5V (initial 24V plus correction amount -1.5V) and the corrected pulse width is 8.5μs (initial 8μs plus correction amount +0.5μs).

[0081] Specifically, the control system adds each component of the initial ejection parameters to its corresponding correction component to generate the corrected ejection parameters. During the calculation, the control system also performs parameter validity checks, including verifying whether the corrected parameter values ​​exceed the hardware's allowable operating range for the inkjet printhead. For example, it checks whether the ejection voltage exceeds the maximum withstand voltage of the printhead's piezoelectric ceramics and whether the pulse width is shorter than the printhead's minimum response time. If a corrected parameter exceeds the allowable range, the control system limits it to the nearest boundary value and records a limiting alarm. Simultaneously, the control system verifies the coupling constraints between the parameters to ensure that the corrected parameter combinations do not lead to abnormal ejection phenomena such as satellite droplets, nozzle clogging, or ink splashing.

[0082] S107. Control the inkjet printhead to perform inkjet printing on the printing area of ​​the substrate according to the corrected jetting parameters.

[0083] The printing area of ​​the substrate refers to the effective area on the substrate surface that needs to receive ink droplet deposition to form the final pattern or text, as determined according to the printing task content. This differs from the substrate test area in step S102, which is only used for detection and calibration. The printing area is the target area that carries the final output content, such as a designated pattern area within a 210mm × 297mm printable range on an A4 sheet of paper, where text and graphics are arranged according to the layout design. Inkjet printing refers to the production process in which the control system drives the inkjet printhead to eject ink droplets line by line or area by area onto the substrate surface according to the printing pattern data, causing a large number of ink droplets to deposit at predetermined positions and densities to form a complete pattern or text.

[0084] Specifically, the control system first loads the corrected ejection parameters into the control register of the inkjet printhead drive circuit, replacing the original initial ejection parameter configuration. Then, according to the pattern bitmap data and print path planning information in the printing task, the control system coordinates and controls the printhead movement mechanism and the substrate transport mechanism, causing the inkjet printhead to scan line by line relative to the substrate printing area along a preset scanning path. During the scanning motion, the control system sends ejection or non-ejection on / off commands to each nozzle of the inkjet printhead in real time based on the pattern pixel data corresponding to the current printhead position. When the nozzle receives the ejection command, it generates drive pulses according to the corrected ejection parameters, ejecting ink droplets with optimized volume and velocity to precise positions on the substrate surface. Because the corrected ejection parameters have been adaptively adjusted for the actual surface condition of the substrate, the ink droplet spreading behavior in the substrate printing area will be closer to the theoretical expectation, thus ensuring that the final printed pattern has accurate ink dot size, uniform coverage density, and clear edge contours, effectively improving print quality and consistency.

[0085] By adopting the above technical solution, the limitations of traditional fixed parameters that cannot adapt to individual differences in the substrate are overcome. It can sense the actual state of ink droplet spreading in real time for different substrates and dynamically adjust the jetting parameters. This effectively solves the problem of ink droplet spreading deviating from expectations due to differences in substrate material, batch, and surface characteristics. It significantly improves the consistency and controllability of ink droplet jetting and spreading in inkjet printing, ensures the clarity, color uniformity, and resolution of high-precision printed patterns, and achieves adaptive and precise control of ink droplet jetting to substrate characteristics.

[0086] The following provides a more detailed description of the process of the method provided in this implementation. Please refer to [link / reference]. Figure 2 This is another flowchart illustrating the method for precisely controlling ink droplets on the printing substrate in this application embodiment.

[0087] S201. Collect surface feature data of the substrate and match the initial spraying parameters and theoretical spreading parameters corresponding to the surface feature data of the substrate from the preset parameter library.

[0088] For details, please refer to step S101, which will not be repeated here.

[0089] S202. Control the inkjet printhead to eject probe ink droplets in the substrate test area according to the initial ejection parameters, and acquire a probe ink droplet timing image.

[0090] For details, please refer to step S102, which will not be repeated here.

[0091] S203. Based on the time-series image of the probe ink droplet, measure the spreading diameter of the probe ink droplet at each time node to determine the actual spreading parameters of the probe ink droplet.

[0092] For details, please refer to step S103, which will not be repeated here.

[0093] S204. Obtain the internal ink temperature data of the inkjet printhead.

[0094] The internal ink temperature data refers to the numerical information reflecting the actual temperature state of the ink, which is collected in real time by a temperature sensor installed inside the ink cavity of the inkjet printhead or adjacent to the ink flow channel. For example, the current ink temperature is 32.5°C as measured by a thermistor or thermocouple embedded in the printhead substrate.

[0095] Specifically, the control system sends sampling commands to the temperature sensor integrated inside the inkjet printhead and reads the returned analog voltage signal or digital temperature value. Because the internal ink temperature dynamically changes during continuous operation due to factors such as mechanical vibration energy dissipation of the piezoelectric ceramic, Joule heat conduction in the drive circuit, and ambient temperature fluctuations, the control system needs to collect real-time temperature data each time it performs parameter calibration, rather than using historical temperature records. The control system performs analog-to-digital conversion, filtering, noise reduction, and calibration compensation on the raw signal returned by the temperature sensor to obtain an accurate internal ink temperature value. If the inkjet printhead is equipped with multiple temperature sensors distributed in different locations, the control system can also perform weighted averaging of the readings from each sensor or take representative readings to obtain comprehensive data that best reflects the actual ink temperature at the nozzle.

[0096] S205. Calculate the current ink viscosity influence factor based on the internal ink temperature data and the preset ink temperature-viscosity characteristic curve.

[0097] The preset ink temperature-viscosity characteristic curve refers to a functional relationship curve describing the viscosity of the currently used ink as a function of temperature, which is pre-determined experimentally and stored in the control system. This curve typically shows a non-linear decreasing trend in viscosity with increasing temperature. For example, a UV-curable ink has a viscosity of 12 mPa·s at 25℃, 9.5 mPa·s at 30℃, and 7.8 mPa·s at 35℃. A continuous curve model is established for each measurement point using exponential fitting or the Arrhenius equation. The current ink viscosity influence factor refers to the ratio or offset of the viscosity value corresponding to the current measured ink temperature to the viscosity value corresponding to the standard reference ink temperature. It is used to indicate the degree and direction of the ink viscosity deviating from the standard operating conditions under the current temperature. For example, when the standard reference ink temperature is 25℃ and the corresponding viscosity is 12 mPa·s, while the current measured ink temperature is 32.5℃ and the corresponding viscosity is 8.6 mPa·s, the viscosity influence factor can be expressed as 8.6 / 12≈0.717, indicating that the current viscosity is only 71.7% of the standard viscosity.

[0098] Specifically, firstly, the control system retrieves the temperature-viscosity characteristic curve equation or fitting equation coefficients corresponding to the currently used ink model. Then, the control system substitutes the acquired measured ink temperature value into the temperature-viscosity characteristic curve equation, and obtains the actual ink viscosity value corresponding to the current ink temperature through interpolation or equation solving. Subsequently, the control system performs a ratio or difference calculation between this actual ink viscosity value and the benchmark viscosity value at a preset standard reference temperature to calculate the current ink viscosity influence factor. This factor reflects the actual deviation of the ink viscosity: when the factor is less than 1, it indicates that the current ink viscosity is lower than the standard value, and the ink droplet spreading on the substrate surface will tend to increase; when the factor is greater than 1, it indicates that the current ink viscosity is higher than the standard value, and the ink droplet spreading will tend to decrease. By calculating the current ink viscosity influence factor, the control system provides a quantitative basis for subsequent temperature-related dynamic compensation of the theoretical spreading parameters.

[0099] S206. Dynamically compensate the theoretical spreading parameters using the current ink viscosity influencing factor to obtain the compensated theoretical spreading parameters.

[0100] Dynamic compensation refers to the process by which the control system adaptively adjusts and corrects predetermined parameters based on changes in the current real-time operating conditions. The calculation is updated in real time with each collected ink temperature change; for example, during continuous printing, as the printhead temperature gradually increases, the compensation calculated during each calibration will change accordingly. The compensated theoretical spreading parameters refer to the set of parameters that more closely approximate the expected spreading behavior under the current actual ink conditions, obtained by correcting the original theoretical spreading parameters after applying viscosity influence factors. These parameters include the compensated theoretical final spreading diameter, the compensated theoretical spreading rate, and the compensated theoretical equilibrium time.

[0101] Specifically, the control system reads each component of the original theoretical spreading parameters and, based on a pre-established viscosity influence compensation model, uses the viscosity influence factor to correct each component. The viscosity influence compensation model is typically based on the physical relationship between ink droplet spreading and viscosity in fluid mechanics. For example, according to Tanner's law, the relationship between spreading radius and viscosity follows a power law. The control system uses this to multiply the theoretical final spreading diameter by a negative power of the viscosity influence factor to obtain the compensated final spreading diameter. Similarly, the theoretical spreading rate and theoretical equilibrium time are also compensated separately based on their respective physical dependencies on viscosity. After each compensation, the control system recombines the compensated components to form a set of compensated theoretical spreading parameters. This parameter set describes the expected spreading behavior, taking into account the impact of the current ink temperature deviating from standard operating conditions. Therefore, as a subsequent comparison benchmark, it can more realistically reflect the reasonable expected value under current conditions, avoiding the erroneous attribution of spreading deviations caused by temperature fluctuations to other factors.

[0102] S207. Compare the actual spreading parameters with the compensated theoretical spreading parameters.

[0103] Among them, the compensated theoretical spreading parameters refer to the set of theoretical spreading expected parameters after dynamic compensation and correction of the current ink viscosity influencing factors, which has taken into account the influence of ink temperature changes on spreading behavior.

[0104] Specifically, the method for comparing the actual spreading parameters with the compensated theoretical spreading parameters can be found in step S104, and will not be repeated here.

[0105] S208. Compare the actual spreading parameters with the theoretical spreading parameters to obtain the spreading deviation.

[0106] For details, please refer to step S104, which will not be repeated here.

[0107] S209. Determine the initial injection parameter correction amount based on the spreading deviation and the pre-established parameter correction mapping relationship.

[0108] For details, please refer to step S105, which will not be repeated here.

[0109] S210. Based on the initial injection parameter correction amount and the initial injection parameters, calculate the corrected injection parameters.

[0110] For details, please refer to step S106, which will not be repeated here.

[0111] S211. Control the inkjet printhead to perform inkjet printing on the printing area of ​​the substrate according to the corrected jetting parameters.

[0112] For details, please refer to step S107, which will not be repeated here.

[0113] The control system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of the control system in an embodiment of this application.

[0114] It should be noted that, Figure 3 The structure of the control system shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0115] like Figure 3As shown, the control system includes a CPU 301, which can perform various appropriate actions and processes based on a program stored in the read-only memory ROM 302 or a program loaded from the storage section 308 into the random access memory RAM 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0116] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0117] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by CPU 301, it performs the various functions defined in the present invention.

[0118] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0119] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0120] Specifically, the control system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the method for precise control of ink droplets sensing the printing substrate provided in the above embodiment.

[0121] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the control system described in the above embodiments; or it may exist independently and not be assembled into the control system. The storage medium carries one or more computer programs that, when executed by a processor of the control system, cause the control system to implement the method for precise control of ink droplets sensing the printing substrate provided in the above embodiments.

[0122] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0123] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0124] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for precise control of ink droplets sensing a printing substrate, characterized in that, Applied to a control system, the method includes: Collect surface feature data of the substrate and match the initial spraying parameters and theoretical spreading parameters corresponding to the surface feature data of the substrate from a preset parameter library; Control the inkjet printhead to eject probe ink droplets in the substrate test area according to the initial ejection parameters, and acquire a timing image of the probe ink droplets; Based on the time-series image of the probe ink droplet, the spreading diameter of the probe ink droplet at each time node is measured to determine the actual spreading parameters of the probe ink droplet; The actual spreading parameters are compared with the theoretical spreading parameters to obtain the spreading deviation. Based on the spreading deviation and the pre-established parameter correction mapping relationship, the initial injection parameter correction amount is determined; Based on the initial injection parameter correction amount and the initial injection parameters, the corrected injection parameters are calculated; The inkjet printhead is controlled to perform inkjet printing on the printing area of ​​the substrate according to the modified jetting parameters.

2. The method according to claim 1, characterized in that, The substrate surface feature data includes the texture direction of the substrate surface. The measurement of the spreading diameter of the probe ink droplet at various time points, to determine the actual spreading parameters of the probe ink droplet, specifically includes: The spreading size of the probe ink droplet at each time node is measured along the texture direction and the reverse texture direction, respectively, to obtain the main direction spreading change rate and the secondary direction spreading change rate, wherein the reverse texture direction is perpendicular to the texture direction. The primary directional spreading change rate and the secondary directional spreading change rate are used as the actual spreading parameters.

3. The method according to claim 2, characterized in that, The theoretical spreading parameters include the theoretical principal direction rate of change and the theoretical secondary direction rate of change. The step of comparing the actual spreading parameters with the theoretical spreading parameters to obtain the spreading deviation specifically includes: The primary direction spreading rate and the secondary direction spreading rate are compared with the theoretical primary direction spreading rate and the theoretical secondary direction spreading rate, respectively, to obtain the primary direction spreading deviation and the secondary direction spreading deviation. The difference between the primary direction spreading deviation and the secondary direction spreading deviation is calculated to obtain the anisotropy deviation degree; The primary direction spreading deviation, the secondary direction spreading deviation, and the anisotropy deviation are used as the spreading deviation amount.

4. The method according to claim 3, characterized in that, The step of determining the initial injection parameter correction amount based on the spreading deviation and the pre-established parameter correction mapping relationship specifically includes: Match the driving waveform correction amount corresponding to the anisotropy deviation in the parameter correction mapping relationship; Based on the average of the primary spreading deviation and the secondary spreading deviation, the droplet volume correction amount is matched and obtained in the parameter correction mapping relationship; The driving waveform correction amount and the droplet volume correction amount are combined as the initial ejection parameter correction amount.

5. The method according to claim 4, characterized in that, The process of establishing the parameter correction mapping relationship specifically includes: A variety of standard printing substrate samples are selected, and the different standard printing substrate samples correspond to different surface feature data of the printing substrate; Multiple sets of jetting parameter combinations are set for each of the standard substrate samples, and the jetting parameter combinations include different driving waveform parameters and ink droplet volume parameters; The inkjet printhead is controlled to spray calibration ink droplets onto the corresponding standard substrate sample according to each set of spraying parameters, and the spreading data of each set of calibration ink droplets is obtained. Based on the spreading data, the spreading deviation corresponding to each group of spraying parameter combinations is calculated; Establish a first mapping relationship between the anisotropy deviation and the driving waveform correction in the spread deviation, and establish a second mapping relationship between the mean of the primary spread deviation and the secondary spread deviation and the droplet volume correction. The first mapping relationship and the second mapping relationship are combined as the parameter to correct the mapping relationship.

6. The method according to claim 2, characterized in that, The spreading size of the probe ink droplet at various time points is measured along the texture direction and the anti-texture direction, respectively, to obtain the primary direction spreading change rate and the secondary direction spreading change rate. The anti-texture direction is perpendicular to the texture direction. Specifically, this includes: The spreading contours of the probe ink droplets at each time node are extracted from the probe ink droplet time series image, wherein the probe ink droplet time series image includes the time series image corresponding to each time node; Based on the texture direction, a primary measurement axis and a secondary measurement axis are determined, wherein the primary measurement axis is parallel to the texture direction and the secondary measurement axis is parallel to the reverse texture direction; The maximum span of the unfolding contour in each of the time series images is measured along the main measurement axis to obtain the main-direction unfolding size sequence at each time node; the maximum span of the unfolding contour in each of the time series images is measured along the secondary measurement axis to obtain the secondary-direction unfolding size sequence at each time node. Curve fitting is performed on the primary directional spreading size sequence to calculate the slope of size change during the spreading stabilization stage, which is taken as the primary directional spreading change rate; curve fitting is also performed on the secondary directional spreading size sequence to calculate the slope of size change during the spreading stabilization stage, which is taken as the secondary directional spreading change rate.

7. The method according to claim 1, characterized in that, Before the step of comparing the actual spreading parameters with the theoretical spreading parameters to obtain the spreading deviation, the method further includes: Obtain the internal ink temperature data of the inkjet printhead; Calculate the current ink viscosity influence factor based on the internal ink temperature data and the preset ink temperature-viscosity characteristic curve; The theoretical spreading parameters are dynamically compensated using the current ink viscosity influencing factor to obtain the compensated theoretical spreading parameters. The actual spreading parameters are compared with the compensated theoretical spreading parameters.

8. A control system, characterized in that, The control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the control system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the control system, it causes the control system to perform the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the control system, the control system performs the method as described in any one of claims 1-7.

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