Microfiber water-based synthetic leather and preparation method thereof

Abstract

The invention provides microfiber water-based synthetic leather and a preparation method thereof, and relates to the technical field of high-molecular compounds, and the preparation method comprises the following steps: collecting multi-dimensional initial data of microfiber base cloth in the soaking process of water-based polyurethane slurry, carrying out integrity verification and format standardization treatment on the obtained multi-dimensional initial data, and obtaining the microfiber water-based synthetic leather. Calculating a slurry permeation uniformity coefficient; basic indexes of the microfiber base cloth are collected, and an extrusion frequency multiplication index is calculated; a fixed permeation uniformity threshold value is set, and the output slurry permeation uniformity coefficient and the permeation uniformity threshold value are automatically compared and analyzed. Whether permeation reaches the standard or not is judged in real time in the soaking process, and the extrusion frequency is automatically adjusted, so that the uniformity and combination stability of slurry permeation are remarkably improved, the problem of insufficient or excessive permeation caused by dependence on fixed time or experience judgment in a traditional method is solved, and meanwhile, through historical data correction and a real-time compensation mechanism, the method is suitable for large-scale popularization and application. And the repeatability and controllability of the process are enhanced.

Description

Technical Field

[0001] This invention relates to the field of polymer compound technology, specifically to a superfiber waterborne synthetic leather and its preparation method. Background Technology

[0002] In the preparation of microfiber waterborne synthetic leather, immersing the base fabric in waterborne polyurethane slurry is a key step in achieving fiber-resin composite. Its significance lies in allowing the slurry to fully penetrate into the internal pores and fiber gaps of the microfiber base fabric, thereby forming a continuous and robust matrix-fiber composite structure, which directly determines the mechanical properties, feel, and durability of the synthetic leather. During this process, intelligent control of the extrusion frequency can effectively promote the penetration depth and uniform distribution of the slurry in the base fabric, preventing defects caused by local retention or insufficient penetration. Real-time judgment of whether the immersion is uniform is crucial, because only by achieving uniform penetration can we ensure that the final product has consistent performance, a smooth surface, and is free of dry spots or delamination, which is the core prerequisite for achieving high-quality and high-stability production.

[0003] In the prior art, CN109749405A discloses a method for preparing a nonionic waterborne polyurethane emulsion for synthetic leather that exhibits pseudoplasticity after thickening. This technique involves adjusting two factors in the emulsification step: the time required for the prepolymer to be completely added to the water and the water temperature. The prepared waterborne polyurethane emulsion, after being formulated into a working slurry, forms a film without cracks under the conditions of 120°C, a machine speed of 10 m / min, full blast, and a film thickness of 0.1–0.15 mm.

[0004] However, the aforementioned existing technologies rely on fixed soaking times and human experience to judge, lacking real-time collection and fusion analysis of multi-dimensional data such as the porosity of the base fabric, surface roughness, and slurry viscosity. This makes it impossible to quantify the uniformity of penetration and difficult to dynamically adjust process parameters. The process is an open-loop control, which cannot compensate for batch differences in real time through algorithms, nor can it automatically adjust the squeezing frequency during soaking to optimize penetration. Therefore, problems such as uneven penetration, local dry spots, or over-soaking are prone to occur. Moreover, the product quality fluctuates greatly and has poor consistency. Abnormal conditions can only be discovered afterward, and preventive intervention and closed-loop process optimization cannot be achieved.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a microfiber water-based synthetic leather and its preparation method, thereby solving the problems mentioned in the background art. This invention significantly improves the uniformity and bonding stability of the slurry penetration by automatically adjusting the extrusion frequency in real time during the soaking process to determine whether the penetration standard is met. This avoids the problems of insufficient or excessive penetration caused by relying on fixed time or experience-based judgment in traditional methods. Furthermore, the invention enhances the repeatability and controllability of the process through historical data correction and real-time compensation mechanisms.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A method for preparing microfiber water-based synthetic leather includes the following steps: S1: Real-time acquisition of multi-dimensional initial data of microfiber base fabric during the soaking process of water-based polyurethane slurry. The multi-dimensional initial data includes the porosity of the microfiber base fabric, the surface roughness of the base fabric, the viscosity of the slurry, and the soaking time. Each multi-dimensional initial data is transmitted to the central control system in real time, with a sampling frequency of 1-3 times per second, and the changing trend in the early stage of soaking is captured. S2: Verify the integrity of the multi-dimensional initial data obtained in step S1 and standardize the format. Establish a formula for calculating the slurry penetration state. Input the multi-dimensional initial data into the formula for calculating the penetration state and calculate the slurry penetration uniformity coefficient of the microfiber base fabric after soaking in water-based polyurethane slurry. S3: Collect the basic indicators of the microfiber base fabric, including the tensile strength of the base fabric, historical data correction coefficient, fiber arrangement density and interlayer bonding strength. Set up an extrusion-assisted algorithm model, input the basic indicators of the microfiber base fabric into the extrusion-assisted algorithm model, and calculate the extrusion frequency multiplication index. The extrusion frequency multiplication index is used to control the extrusion frequency of the microfiber base fabric during the water-based polyurethane slurry soaking process. S4: Set a fixed penetration uniformity threshold, and automatically compare the slurry penetration uniformity coefficient output in step S2 with the penetration uniformity threshold. If the slurry penetration uniformity coefficient is greater than or equal to the penetration uniformity threshold, the extraction mechanism is triggered. If the slurry penetration uniformity coefficient is less than the penetration uniformity threshold, the historical data correction coefficient is reassigned, the extrusion frequency multiplication index is adjusted, and the reassigned historical data correction coefficient is used to start the control cycle and re-soak for preparation.

[0008] Furthermore, in step S1, the porosity of the base fabric is used to evaluate the penetration depth and uniformity potential of the slurry inside the base fabric. The collected porosity data is immediately transmitted to the central control system in real time. The integrity of the values ​​is verified by an embedded verification algorithm to eliminate outlier interference. The trend prediction module is used to capture the initial dynamics of porosity changes and record the instantaneous fluctuations of pore expansion or contraction as the benchmark input for subsequent permeation calculations. The surface roughness of the base fabric is used to determine the adhesion performance and bonding stability of the base fabric interface. The acquisition frequency is maintained at a high frequency of 1-3 times per second. After the roughness data is acquired, it is synchronously transmitted to the central control system. After standardization format conversion to eliminate unit differences, the abrupt change trend of roughness in the early stage of immersion is tracked through time series analysis.

[0009] Furthermore, the slurry viscosity is used to reflect changes in the slurry's flow resistance and permeation rate. After the viscosity data is transmitted to the central control system in real time, a data smoothing and filtering algorithm is used to reduce the impact of noise and to align it with the time series to identify initial viscosity characteristics. The soaking time serves as a core reference variable for process continuity, used to correlate the temporal consistency of other multidimensional data. During the real-time transmission of time data to the central control system, it is synchronized with porosity, roughness, and viscosity data at the millisecond level through timestamp calibration. After capturing time-driven change characteristics, the temporal dimension integrity of the established overall dataset and the temporal alignment of subsequent calculations are controlled.

[0010] Furthermore, the formula for calculating the slurry permeability state in step S2 is as follows:

[0011] in: U is the uniformity coefficient of slurry penetration, which is used to quantify the uniformity of slurry penetration inside the microfiber base fabric. If the U value fluctuates greatly, it indicates that the base fabric structure is not uniform or the slurry fluidity is unstable. It is a proportionality constant used to integrate unit differences or calibrate experimental biases. It is initialized by weighted averaging of historical data and then fine-tuned based on real-time sampling data and model fitting residuals. Porosity is the porosity of the base fabric, used to quantify the volume percentage of pores within the base fabric. The surface roughness of the base fabric is used to quantify the unevenness of the base fabric surface. Increased roughness enhances the adhesion and diffusion of the slurry and reduces local dry spots. The viscosity of the slurry quantifies its flow resistance. As viscosity increases (e.g., from 0.5 Pa·s to 1.0 Pa·s), flow resistance increases, leading to a higher risk of uneven penetration; this is referred to as the slurry penetration uniformity coefficient. Decrease; Soaking time is the quantification of the duration of the slurry penetration process. Continuous increases generate marginal effects, increasing the formation of the natural logarithm function. Soaking time The continuous increase in the slurry penetration uniformity coefficient The growth rate of its contribution has slowed significantly; This is achieved using ln(1+T): When T is small (e.g., 10s-30s): In(11)≈ 2.4 → In(31)≈ 3.4, showing a significant increase; When T is large (e.g., 100s-200s): In(101)≈4.6→1n(201)≈5.3, the growth rate slows down significantly, and the increase is 15%, but the value of T doubles.

[0012] Furthermore, the proportionality constant is selected through the following process: The baseline value was initialized by matching historical batch penetration compliance data with real-time sampling parameters. Dynamic correction was then performed based on the measured porosity fluctuation range, slurry viscosity deviation, and roughness calibration factor of the current batch of microfiber base fabric. This dynamic correction included: first, accessing the historical database of the central control system, selecting successful immersion cases corresponding to the current process conditions, extracting the historical actual proportional constant value distribution when the penetration uniformity coefficient met the standard, and then calculating the initial proportional constant value using a weighted average. During real-time immersion, based on the fitting residuals of multi-dimensional initial data sampled 1-3 times per second and the preset permeation model, a least squares algorithm is used to generate... The real-time compensation coefficient β makes:

[0013] Furthermore, the real-time compensation coefficient β∈[0.9,1.1], in the successful soaking cases corresponding to the current process conditions, the error range of each multi-dimensional initial data is: similar base fabric porosity range ±5%, slurry viscosity tolerance ±10%, base fabric surface roughness range ±10%, and soaking time range ±20%.

[0014] Furthermore, in the extrusion-assisted algorithm model, the extrusion frequency multiplication index is calculated using the following formula:

[0015] in: It is the extrusion frequency multiplication index, used to control the multiplication rate of the extrusion frequency; For the tensile strength of the base fabric, When the tensile strength of the base fabric At that time, the demand for boosting increases rapidly, providing nonlinear enhancement of pressure resistance; This is a historical data correction factor used to retain the dynamic adjustment function. For example, C=1.2 means that an additional 20% needs to be added. Fiber arrangement density; is the interfacial bonding strength; is the safety threshold of layer strength. The calibration value in this embodiment is 0.4 kPa. When it is lower than this value, the base fabric structure is protected by significantly reducing the frequency; is the steepness coefficient; is the natural constant, which controls the turning speed of the Sigmoid curve (default y = 0.5) and affects the activation threshold sensitivity of B.

[0016] By establishing the Sigmoid function , the following is achieved: When B < B0: The function output approaches 0, the extrusion frequency doubling exponent F value decreases significantly, and the frequency is forced to decrease to prevent delamination; When B ≥ B0: The function approaches the interfacial bonding strength B, and the formula for the extrusion frequency doubling exponent F resumes positive correlation linear growth.

[0017] Furthermore, the regulation of the extrusion frequency of the microfiber base fabric during the immersion process in the aqueous polyurethane slurry is completed through the following formula:

[0018] Where: is the actually executed extrusion frequency, which is the value dynamically adjusted according to the base fabric state; is the preset reference extrusion frequency, which is set according to process experience or equipment standards; for example, when F = 1.2, it is 20% higher than the initial value. When F = 0.8, it is 80% of the initial value.

[0019] If the extrusion frequency doubling exponent , then the actually executed extrusion frequency is increased; If the extrusion frequency doubling exponent , then the actually executed extrusion frequency is decreased.

[0020] Furthermore, in step S4, a fixed penetration uniformity threshold is set as The process of automatically comparing the slurry penetration uniformity coefficient with the penetration uniformity threshold is as follows: If the slurry penetration uniformity coefficient , it is determined that the current immersion is qualified, and the qualified response mechanism is triggered: automatically save the current historical data correction coefficient , the immersion time and environmental variables to the process database, and move the microfiber base fabric out of the slurry pool and into the next process.

[0021] Furthermore, if the slurry penetration uniformity coefficient If the current penetration is uneven, a correction cycle protocol is initiated: the correction coefficients of historical data are adjusted. Reassign values, set the reassignment growth factor n, and reset the historical data correction factor. ,in .

[0022] A microfiber waterborne synthetic leather is prepared using the method described above. The microfiber waterborne synthetic leather comprises: a microfiber base fabric layer, a waterborne polyurethane layer, and a functionalized surface treatment layer. The microfiber base fabric layer includes island-type composite fibers and bonding fibers. The waterborne polyurethane layer includes a resin matrix, a crosslinking agent, and additives. The functionalized surface treatment layer includes a wear-resistant coating and a skin-feeling agent. The additives contain 2-3% nano-SiO2 and 0.5-1% waterborne fluorocarbon leveling agent.

[0023] Compared with the prior art, the beneficial effects of the present invention are: This invention collects multi-dimensional data in real time and uses a central control system for dynamic analysis and prediction, achieving precise quantification and adaptive process control of the permeation state of microfiber base fabric. Based on the closed-loop feedback mechanism of the slurry permeation uniformity coefficient and the extrusion-assisted algorithm model, it can determine whether the permeation meets the standard in real time during the soaking process and automatically adjust the extrusion frequency, thereby significantly improving the uniformity and bonding stability of slurry permeation. It avoids the problems of insufficient or excessive permeation caused by relying on fixed time or experience judgment in traditional methods. At the same time, through historical data correction and real-time compensation mechanisms, it enhances the repeatability and controllability of the process, ultimately achieving a high-efficiency, consistent, and traceable high-quality synthetic leather preparation process. Attached Figure Description

[0024] Figure 1 This is a schematic flowchart of the method for preparing microfiber waterborne synthetic leather according to the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0026] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0027] Example: Please see Figure 1 The present invention provides the following technical solutions: A method for preparing microfiber water-based synthetic leather includes the following steps: S1: In the preparation of microfiber waterborne synthetic leather, real-time acquisition of multi-dimensional initial data during the immersion of the microfiber base fabric in waterborne polyurethane slurry is a core element to ensure precise process control. Specifically, this acquisition process involves continuously monitoring the state changes of the base fabric in the slurry using high-precision sensors. The acquired multi-dimensional initial data mainly includes the porosity of the microfiber base fabric, the surface roughness of the base fabric, the viscosity of the slurry, and the immersion time. Among them, the porosity of the base fabric is used as a key indicator to assess the potential depth and uniformity of slurry penetration; the surface roughness of the base fabric directly reflects the interfacial adhesion performance and bonding stability between the base fabric and the slurry; the viscosity of the slurry quantifies the flow resistance and penetration efficiency of the slurry; and the immersion time serves as a fundamental parameter for process continuity, recording the duration of the slurry's effect on the base fabric. The initial data for each dimension are transmitted in real-time to the central control system through a high-speed data transmission channel, with the sampling frequency strictly maintained at a high frequency of once per second to fully capture key trend changes such as pore expansion, surface texture changes, or slurry rheological fluctuations in the early stages of immersion. In the microfiber base fabric impregnation process, the base fabric porosity is a core indicator, primarily used to accurately assess the potential penetration depth and distribution uniformity of waterborne polyurethane slurry within the base fabric, thereby predicting the efficiency of slurry filling pores and the quality of the final product. Porosity data is acquired in real-time by high-precision sensors and immediately transmitted to the central control system via a high-speed data transmission channel, ensuring timely information delivery. Within the central control system, an embedded verification algorithm performs rigorous integrity verification on the values, including data range checks and logical consistency analysis, effectively identifying and eliminating outliers caused by environmental interference or equipment errors, ensuring data reliability and accuracy. Subsequently, the system activates a trend prediction module, which, through real-time analysis of time-series data, keenly captures the dynamic changes in the pore structure during the initial impregnation stage, such as instantaneous fluctuations in pore expansion or contraction. These recorded fluctuation details provide a stable and real-time benchmark input for subsequent penetration uniformity calculations. The surface roughness of the base fabric is used to determine the adhesion performance and bonding stability of the base fabric interface. The acquisition frequency is maintained at a high frequency of once per second. After acquisition, the roughness data is synchronously transmitted to the central control system. After standardization format conversion to eliminate unit differences, the abrupt change trend of roughness in the early stage of immersion is tracked through time series analysis.

[0028] In the microfiber base fabric impregnation process, slurry viscosity is a key parameter, primarily used to accurately reflect the flow resistance of the waterborne polyurethane slurry and its direct impact on the permeation rate. Specifically, high viscosity significantly slows down the diffusion rate of the slurry in the base fabric, while low viscosity promotes rapid permeation. Viscosity data is acquired in real-time by dedicated sensors and transmitted instantly to the central control system via a high-speed network. Upon receiving the data, the system immediately applies data smoothing and filtering algorithms, such as moving average filters, to effectively eliminate random noise caused by environmental fluctuations or equipment interference, ensuring data stability and reliability. Subsequently, this processed data is rigorously aligned and matched with a time series. By analyzing data points linked to timestamps in real-time, the system identifies changes in viscosity characteristics during the initial impregnation stage, such as sudden changes in slurry flowability or abnormal rheological behavior, providing early warnings for subsequent process adjustments. Soaking time, as a core reference variable for the continuity of the entire soaking process, plays a crucial role in temporal coordination, ensuring the consistent correlation of multi-dimensional data such as porosity, roughness, and viscosity along the time axis. During real-time transmission of time data to the central control system, the system automatically performs timestamp calibration to ensure millisecond-level precise synchronization with porosity, roughness, and viscosity data, effectively avoiding timing misalignment issues caused by data transmission delays or clock drift. Through this precise synchronization, the system can efficiently capture time-driven changes, such as the cumulative effect of soaking time on the uniformity of slurry distribution. Subsequently, the system automatically adjusts the established overall dataset, strengthening the integrity of the time dimension and ensuring strict alignment of all multi-dimensional data on the timeline. This supports the temporal consistency of subsequent calculations and the accuracy of process decisions, avoiding analytical errors caused by timing deviations.

[0029] S2: Verify the integrity of the multi-dimensional initial data obtained in step S1 and standardize the format. Establish a formula for calculating the slurry penetration state. Input the multi-dimensional initial data into the formula for calculating the penetration state and calculate the slurry penetration uniformity coefficient of the microfiber base fabric after soaking in water-based polyurethane slurry. The formula for calculating the slurry permeability state is:

[0030] in: It is the slurry penetration uniformity coefficient, used to quantify the uniformity of slurry penetration into the microfiber base fabric; It is a proportionality constant used to integrate unit differences or calibrate experimental biases; Porosity is the porosity of the base fabric, used to quantify the volume percentage of pores within the base fabric. The surface roughness of the base fabric is used to quantify the unevenness of the base fabric surface. Increased roughness enhances the adhesion and diffusion of the slurry and reduces local dry spots. To quantify the flow resistance of the slurry based on its viscosity; Soaking time is the quantification of the duration of the slurry penetration process. Continuous increases generate marginal effects, increasing the formation of the natural logarithm function. Soaking time The continuous increase in the slurry penetration uniformity coefficient The growth rate of its contribution has slowed significantly.

[0031] The proportionality constant is selected through the following process: The baseline value is initialized by matching historical batch penetration compliance data with real-time sampling parameters. Dynamic correction is then performed based on the measured porosity fluctuation range, slurry viscosity deviation, and roughness calibration factor of the current batch of microfiber base fabric. This dynamic correction includes: First, the central control system's global access function is activated to access multi-dimensional process files stored in the historical database. This allows for the precise selection of a set of successful immersion cases matching the current operating conditions, with particular attention paid to operational instances that meet quality standards for penetration uniformity. From these high-quality samples, the actual penetration ratio constant value sequence corresponding to the time of achievement is extracted. The trend characteristics and concentration intervals of this distribution are analyzed, and then a weighted average algorithm is used to determine an initial ratio constant value that reflects common patterns while also considering the weight of key influences. .

[0032] Following the real-time soaking phase, the system continuously collects multi-dimensional initial data, including temperature, pressure, soaking time, slurry rheological properties, and base fabric movement velocity, using multi-dimensional initial data sampled once per second and the fitting residuals of the preset permeation model. This data is then input into the preset permeation behavior prediction model for real-time fitting. By dynamically tracking the residuals between the model output and the actual measured response, an error feedback path is constructed using the least squares method to generate a real-time compensation coefficient β for adjusting control parameters, thereby continuously updating the dynamic proportional constant under the current permeation state. ,make:

[0033] Furthermore, the real-time compensation coefficient β∈[0.9,1.1], in the successful soaking cases corresponding to the current process conditions, the error range of each multi-dimensional initial data is: similar base fabric porosity range ±5%, slurry viscosity tolerance ±10%, base fabric surface roughness range ±10%, and soaking time range ±20%.

[0034] In this embodiment, a porosity error of ±5% is selected for the base fabric as a core structural parameter affecting permeability efficiency. Actual measured porosity values ​​often deviate from the design nominal value due to factors such as uneven sampling locations and differences in compression states. Experimental statistics show that approximately 12.7% of batches exceed the ±3% tolerance in mass production. Therefore, this embodiment relaxes the upper limit to ±5% as a prerequisite for inputting the compensation model. Slurry viscosity fluctuation (±8%): Measured using a rotational viscometer at a constant temperature of 25°C. The target viscosity for the standard formulation is 450±20 mPa·s, but due to solvent evaporation, temperature gradient, and stirring time, the actual measured value often ranges from 414 to 486 mPa·s. This variation directly affects the slurry's forward velocity under capillary action and requires weighted correction. Ambient temperature and humidity deviation (temperature ±3°C, relative humidity ±10%RH): The combined effect of temperature and humidity alters the evaporation rate of the slurry solvent and the degree of moisture absorption and swelling of the base fabric fibers, thereby indirectly regulating the effective penetration depth. Data analysis shows that for every 1°C increase, the equivalent permeability increases by approximately 2.3%. Coating pressure fluctuations (±7%): Minor leaks in the hydraulic system or servo response delays can cause the applied pressure to deviate from the set value; the typical operating pressure is 0.4 MPa ± 0.028 MPa. While increased pressure can accelerate the filling process, it may also cause false saturation—that is, the surface is sealed while the interior is not adequately wetted.

[0035] S3: The system collects multiple basic physical and structural indicators of the microfiber base fabric in real time using sensors and detection equipment. These indicators include the tensile strength of the base fabric, the correction coefficient dynamically adjusted based on historical process data, the fiber density within the base fabric, and the bonding strength between fiber layers. Based on these key parameters, the system employs a dedicated extrusion-assisted algorithm model. This model intelligently analyzes the pressure state and penetration requirements of the base fabric during impregnation, using the collected basic indicators as real-time input variables for comprehensive calculation. This results in the calculation and output of a key extrusion frequency multiplication index. This index directly reflects the required level of extrusion strength adjustment under the current base fabric condition. Its core purpose is to precisely and dynamically control the frequency of mechanical extrusion experienced by the microfiber base fabric during the water-based polyurethane slurry impregnation stage, thereby optimizing slurry penetration and ensuring the structural integrity of the base fabric. In the extrusion-assisted algorithm model, the extrusion frequency multiplication index is calculated using the following formula:

[0036] in: It is the extrusion frequency multiplication index, used to control the multiplication rate of the extrusion frequency; For the tensile strength of the base fabric, When the tensile strength of the base fabric At that time, the demand for boosting increases rapidly, providing nonlinear enhancement of pressure resistance; The historical data correction coefficient is used to retain the dynamic adjustment function. The historical data correction coefficient is positively correlated with the exponential expansion of the compression frequency F. Fiber arrangement density; For interlayer bond strength; The layer strength safety threshold; This is the steepness coefficient; As a natural constant, the Sigmoid function is established. ,accomplish: When B < B0: The function output approaches 0, the extrusion frequency doubling index F value decreases significantly, and forced frequency reduction is used to prevent delamination; When B ≥ B0: The function approaches the interfacial bonding strength B, and the formula for the extrusion frequency doubling index F resumes positive correlation linear growth.

[0037] The regulation of the extrusion frequency during the immersion process of the ultra-fine fiber base fabric in the aqueous polyurethane slurry is completed through the following formula:

[0038] Where: is the actually executed extrusion frequency, the value dynamically adjusted according to the base fabric state; is the preset reference extrusion frequency, set according to process experience or equipment standards; If the extrusion frequency doubling index , then the actually executed extrusion frequency is increased; If the extrusion frequency doubling index , then the actually executed extrusion frequency is decreased.

[0039] [[ID=3'1]]S4: Set a fixed penetration uniformity threshold determined in advance based on material characteristics and process requirements, and automatically and continuously compare and monitor the real-time slurry penetration uniformity coefficient calculated and output in step S2 with this threshold in the central control system. If the system detects that the slurry penetration uniformity coefficient is greater than or equal to the set penetration uniformity threshold, the automatic extraction mechanism is immediately triggered, and this mechanism will control the mechanical device to smoothly remove the ultra-fine fiber base fabric from the slurry pool and transfer it to the subsequent drying or shaping process. If the system determines that the slurry penetration uniformity coefficient is less than the penetration uniformity threshold, the process adjustment program is automatically started: First, the historical data correction coefficient is intelligently re-assigned, thereby dynamically regulating the calculation result of the extrusion frequency doubling index, and then changing the extrusion frequency of the base fabric; Subsequently, the system will automatically start a new round of regulation cycle according to the updated parameters and re-control the base fabric to continue the immersion preparation until the penetration uniformity reaches the predetermined standard.

[0040] Set the fixed penetration uniformity threshold as The process of automatically comparing the slurry penetration uniformity coefficient with the penetration uniformity threshold is as follows: If the slurry penetration uniformity coefficient , it is determined that the current immersion meets the standard, and the qualified response mechanism is triggered: Automatically save the current historical data correction coefficient , the immersion time and environmental variables to the process database, remove the ultra-fine fiber base fabric from the slurry pool and enter the next process.

[0041] If the slurry penetration uniformity coefficient If the current penetration is uneven, a correction cycle protocol is initiated: the correction coefficients of historical data are adjusted. Reassign values, set the reassignment growth factor n, and reset the historical data correction factor. ,in In this embodiment, the historical data correction coefficient n=0.1. Each time an uneven penetration problem is detected, the historical data correction coefficient is adjusted. Multiply by 1.1 and update to replace the original data.

[0042] This embodiment also provides a microfiber waterborne synthetic leather, which is prepared using the method described above. The microfiber waterborne synthetic leather comprises a microfiber base fabric layer, an intermediate waterborne polyurethane impregnation layer, and an outermost functionalized surface treatment layer. The microfiber base fabric layer forms the basic framework of the product, typically using island-type composite fibers to provide an extremely fine fiber structure and highly realistic texture. Bonding fibers are used to fix the fiber network, giving the base fabric good dimensional stability and mechanical support.

[0043] The middle waterborne polyurethane layer serves as a key bonding and filling medium. Its composition includes a resin matrix as the main film-forming substance, a crosslinking agent that enhances the material's cohesion and hydrolysis resistance, and various additives that improve processing and performance. The outermost functionalized surface treatment layer directly determines the product's feel and durability. It includes an abrasion-resistant coating to improve surface scratch and wear resistance, and skin-feel additives that give the leather a soft, smooth, or moist feel and appearance.

[0044] In the additive system, 2% to 3% of nano-SiO2 is mixed in to enhance the mechanical properties and surface wear resistance of the material, and 0.5% to 1% of water-based fluorocarbon leveling agent is added at the same time to improve the smoothness, leveling and anti-adhesion effect of the coating surface.

[0045] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0046] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0047] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0048] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for preparing microfiber waterborne synthetic leather, characterized in that, Includes the following steps: S1: Real-time acquisition of multi-dimensional initial data of microfiber base fabric during the soaking process of water-based polyurethane slurry. The multi-dimensional initial data includes the porosity of the microfiber base fabric, the surface roughness of the base fabric, the viscosity of the slurry, and the soaking time. Each multi-dimensional initial data is transmitted to the central control system in real time, with a sampling frequency of 1-3 times per second, and the changing trend in the early stage of soaking is captured. S2: Verify the integrity of the multi-dimensional initial data obtained in step S1 and standardize the format. Establish a formula for calculating the slurry penetration state. Input the multi-dimensional initial data into the formula for calculating the penetration state and calculate the slurry penetration uniformity coefficient of the microfiber base fabric after soaking in water-based polyurethane slurry. S3: Collect the basic indicators of the microfiber base fabric, including the tensile strength of the base fabric, historical data correction coefficient, fiber arrangement density and interlayer bonding strength. Set up an extrusion-assisted algorithm model, input the basic indicators of the microfiber base fabric into the extrusion-assisted algorithm model, and calculate the extrusion frequency multiplication index. The extrusion frequency multiplication index is used to control the extrusion frequency of the microfiber base fabric during the water-based polyurethane slurry soaking process. S4: Set a fixed penetration uniformity threshold, and automatically compare the slurry penetration uniformity coefficient output in step S2 with the penetration uniformity threshold. If the slurry penetration uniformity coefficient is greater than or equal to the penetration uniformity threshold, the extraction mechanism is triggered. If the slurry penetration uniformity coefficient is less than the penetration uniformity threshold, the historical data correction coefficient is reassigned, the extrusion frequency multiplication index is adjusted, and the reassigned historical data correction coefficient is used to start the control cycle and re-soak for preparation.

2. The method for preparing microfiber waterborne synthetic leather according to claim 1, characterized in that: In step S1, the porosity of the base fabric is used to evaluate the penetration depth and uniformity potential of the slurry inside the base fabric. The collected porosity data is immediately transmitted to the central control system in real time. The integrity of the values ​​is verified by an embedded verification algorithm, the initial dynamics of porosity changes are captured, and the instantaneous fluctuations of pore expansion or contraction are recorded as the benchmark input for subsequent permeation calculations. The surface roughness of the base fabric is used to determine the adhesion performance and bonding stability of the base fabric interface. The acquisition frequency is maintained at a high frequency of 1-3 times per second. After the roughness data is acquired, it is synchronously transmitted to the central control system. After standardization format conversion to eliminate unit differences, the abrupt change trend of roughness in the early stage of immersion is tracked through time series analysis.

3. The method for preparing microfiber waterborne synthetic leather according to claim 2, characterized in that: The viscosity of the slurry is used to reflect the changes in the flow resistance and permeation rate of the slurry. After the viscosity data is transmitted to the central control system in real time, a data smoothing and filtering algorithm is used to reduce the impact of noise and to align with the time series to identify the initial viscosity characteristics. The soaking time is used to correlate the temporal consistency of other multidimensional data. During the real-time transmission of time data to the central control system, the time data is synchronized with porosity, roughness and viscosity data at the millisecond level through timestamp calibration. After capturing the time-driven change characteristics, the temporal dimension integrity of the established overall dataset and the temporal alignment of subsequent calculations are regulated.

4. The method for preparing microfiber waterborne synthetic leather according to claim 1, characterized in that: The formula for calculating the slurry permeability state in step S2 is: in: It is the slurry penetration uniformity coefficient, used to quantify the uniformity of slurry penetration into the microfiber base fabric; It is a proportionality constant used to integrate unit differences or calibrate experimental biases; Porosity is the porosity of the base fabric, used to quantify the volume percentage of pores within the base fabric. The surface roughness of the base fabric is used to quantify the unevenness of the base fabric surface. Increased roughness enhances the adhesion and diffusion of the slurry and reduces local dry spots. This refers to the viscosity of the slurry, used to quantify the flow resistance of the slurry; Soaking time is the duration used to quantify the slurry penetration process. Continuous increases generate marginal effects, increasing the formation of the natural logarithm function. Soaking time The continuous increase in the slurry penetration uniformity coefficient The growth rate of its contribution has slowed down.

5. The method for preparing microfiber waterborne synthetic leather according to claim 4, characterized in that: The proportionality constant is selected through the following process: The baseline value was initialized by matching historical batch penetration compliance data with real-time sampling parameters. Dynamic correction was then performed based on the measured porosity fluctuation range, slurry viscosity deviation, and roughness calibration factor of the current batch of microfiber base fabric. This dynamic correction included: first, accessing the historical database of the central control system, selecting successful immersion cases corresponding to the current process conditions, extracting the historical actual proportional constant value distribution when the penetration uniformity coefficient met the standard, and then calculating the initial proportional constant value using a weighted average. During real-time immersion, based on the fitting residuals of multi-dimensional initial data sampled 1-3 times per second and the preset permeation model, a least squares algorithm is used to generate... The real-time compensation coefficient β makes: Furthermore, the real-time compensation coefficient β∈[0.9,1.1], in the successful soaking cases corresponding to the current process conditions, the error range of each multi-dimensional initial data is: similar base fabric porosity range ±5%, slurry viscosity tolerance ±10%, base fabric surface roughness range ±10%, and soaking time range ±20%.

6. The method for preparing microfiber waterborne synthetic leather according to claim 4, characterized in that: In the extrusion-assisted algorithm model, the extrusion frequency multiplication index is calculated using the following formula: in: It is the extrusion frequency multiplication index, used to control the multiplication rate of the extrusion frequency; For the tensile strength of the base fabric, When the tensile strength of the base fabric At that time, the demand for boosting increases rapidly, providing nonlinear enhancement of pressure resistance; This is a historical data correction coefficient used to retain the dynamic adjustment function; Fiber arrangement density; For interlayer bond strength; The layer strength safety threshold; This is the steepness coefficient; As a natural constant, the Sigmoid function is established. ,accomplish: When B < B0: The function output approaches 0, the squeezing frequency multiplication exponent F decreases, and forced frequency reduction is used to prevent stratification; When B ≥ B0: the function approaches the interlayer bonding strength B, and the formula for the extrusion frequency multiplication exponent F resumes positive linear growth.

7. The method for preparing microfiber waterborne synthetic leather according to claim 6, characterized in that: The control over the extrusion frequency of the microfiber base fabric during the immersion process in the water-based polyurethane slurry is achieved using the following formula: in: This is the actual extrusion frequency, dynamically adjusted based on the condition of the base fabric. The preset reference extrusion frequency is set based on process experience or equipment standards. If the exponential increase in compression frequency The actual squeezing frequency is... Improve; If the exponential increase in compression frequency The actual squeezing frequency is... Reduce it.

8. The method for preparing microfiber waterborne synthetic leather according to claim 7, characterized in that: In step S4, a fixed permeation uniformity threshold is set as follows: The process for automatically comparing the slurry penetration uniformity coefficient with the penetration uniformity threshold is as follows: If the slurry penetration uniformity coefficient If the current soaking condition is deemed satisfactory, the qualified response mechanism will be triggered: the current historical data correction coefficient will be automatically saved. Soaking time The environmental variables are added to the process database, and the microfiber base fabric is removed from the slurry tank and moved to the next process.

9. The method for preparing microfiber waterborne synthetic leather according to claim 8, characterized in that: If the slurry penetration uniformity coefficient If the current penetration is uneven, a correction cycle protocol is initiated: the correction coefficients of historical data are adjusted. Reassign values, set the reassignment growth factor n, and reset the historical data correction factor. ,in .

10. A microfiber water-based synthetic leather, characterized in that, The microfiber waterborne synthetic leather is prepared based on the method described in claims 1-9. The microfiber waterborne synthetic leather comprises: a microfiber base fabric layer, a waterborne polyurethane, and a functionalized surface treatment layer. The microfiber base fabric layer contains island-type composite fibers and bonding fibers. The waterborne polyurethane contains a resin matrix, a crosslinking agent, and additives. The functionalized surface treatment layer contains a wear-resistant coating and a skin-feeling agent. The additives contain 2-3% nano-SiO2 and 0.5-1% waterborne fluorocarbon leveling agent.

Images