Dacron fabric printing and dyeing water-saving automatic treatment system based on digital monitoring

Abstract

The invention discloses a polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring. According to the system, a printing and dyeing execution device, a filtering regeneration device, a data acquisition device and a system control device are integrated through modular design, temperature, pressure, flow velocity and resin saturation data in the printing and dyeing process are obtained in real time through a sensor network, and a dynamic correlation function is constructed based on the system control device to generate an accurate regulation and control instruction. Uniformity control of wastewater circulation, stability optimization of resin adsorption efficiency and remarkable improvement of the water resource utilization rate are achieved, and the problems that in a traditional process, the manual dependence degree is high, and resource waste is serious are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of textile printing and dyeing. Specifically, it relates to a water-saving automatic treatment system for polyester fabric printing and dyeing based on digital monitoring. Background Art

[0002] Polyester fabric printing and dyeing is one of the core links in the textile industry in terms of resource consumption and pollution emission. Traditional printing and dyeing wastewater treatment mostly uses an intermittent filtration system, where the water pump pressure and circulation flow rate are set manually and cannot respond in real time to the dynamic changes inside the printing and dyeing barrel. For example, when the resin adsorption is close to saturation, if the wastewater circulation flow rate is not adjusted in time, it will lead to incomplete filtration in local areas, an increase in the dye residue amount, and an increase in the COD (chemical oxygen demand) value.

[0003] In addition, the saturation monitoring of the filtration medium (such as activated carbon or ordinary resin) relies on regular sampling and testing, which is time-consuming and lagging. In related technologies, resin is usually replaced at fixed intervals, but the actual adsorption efficiency is significantly affected by factors such as temperature and pressure. Premature replacement causes waste of resources, and delayed replacement leads to a decline in filtration efficiency. Therefore, in related technologies, there are defects such as poor control accuracy and waste of resources in the control of the printing and dyeing process. Summary of the Invention

[0004] In view of the above-mentioned defects of the prior art, the technical problems to be solved by the present invention are how to improve the uniformity control of wastewater circulation and how to improve the stability of resin adsorption efficiency.

[0005] To solve at least one of the above-mentioned technical problems, the present invention proposes a water-saving automatic treatment system for polyester fabric printing and dyeing based on digital monitoring.

[0006] According to one aspect of the present disclosure, a water-saving automatic treatment system for polyester fabric printing and dyeing based on digital monitoring includes:

[0007] A printing and dyeing execution device, including a stainless steel box body and an internally installed printing and dyeing barrel, wherein the printing and dyeing barrel is configured with a dye liquor circulation pipeline and a wastewater outlet;

[0008] A filtration and regeneration device, connected to the wastewater outlet, including a solid resin filtration layer, a backwashing device, and a waste liquid recovery channel;

[0009] A data acquisition device: including a plurality of sensors for obtaining the printing and dyeing treatment parameters inside the printing and dyeing barrel;

[0010] A system control device for obtaining and processing the printing and dyeing treatment parameters, and constructing a dynamic correlation function and generating a printing and dyeing regulation instruction in combination with the printing and dyeing treatment parameters.

[0011] In a specific embodiment, in the data acquisition device, the multiple sensors include a temperature sensor, a pressure sensor, a water pump speed sensor, and an optical resin saturation sensor, and the multiple sensors are deployed in a ring topology on the inner wall of the printing and dyeing barrel, the dye liquor circulation pipeline, and the inlet of the solid resin filter layer.

[0012] In a specific embodiment, the system control device includes a data processing module;

[0013] The data processing module includes:

[0014] A data correction unit electrically connected to the data acquisition device, the data correction unit is used to obtain the printing and dyeing processing parameters and perform data correction processing on the printing and dyeing processing parameters to obtain calibrated printing and dyeing parameters;

[0015] A data fusion unit electrically connected to the data correction unit, the data fusion unit is used to perform data fusion on the calibrated printing and dyeing parameters to obtain initial printing and dyeing parameters.

[0016] In a specific embodiment, the data processing module further includes a redundancy check unit electrically connected to the data fusion unit;

[0017] The redundancy check unit is used to receive the initial printing and dyeing parameters, perform redundancy check on the initial printing and dyeing parameters in combination with a preset parameter threshold, and generate an exception reminder message according to the redundancy check result.

[0018] In a specific embodiment, the system control device further includes a function construction module;

[0019] The function construction module includes:

[0020] A data alignment unit electrically connected to the data processing module, the data alignment unit is used to obtain the initial printing and dyeing parameters and perform data alignment processing on the initial printing and dyeing parameters according to a preset sampling interval to obtain the aligned initial printing and dyeing parameters;

[0021] The data alignment unit is further used to perform data equalization processing on the aligned initial printing and dyeing parameters to obtain standard printing and dyeing parameters.

[0022] In a specific embodiment, the function construction module further includes:

[0023] A matrix construction unit electrically connected to the data alignment unit, the matrix construction unit is used to construct a dynamic association matrix in combination with the standard printing and dyeing parameters.

[0024] In a specific embodiment, the function construction module further includes:

[0025] A first function construction unit electrically connected to the matrix construction unit, the first function construction unit being configured to construct the dynamic association function and calculate a predicted resin saturation value.

[0026] In a specific embodiment, the system control device further includes an instruction generation module;

[0027] The instruction generation module includes:

[0028] A second function construction unit electrically connected to the function construction module, the data initialization unit being configured to receive the dynamic association matrix and the predicted resin saturation value, and generate a target adjustment function in combination with the dynamic association matrix and the predicted resin saturation value.

[0029] In a specific embodiment, the instruction generation module further includes a data iteration unit electrically connected to the second function construction unit;

[0030] The data iteration unit is configured to perform iterative reasoning based on the target adjustment function, the pump pressure threshold range, and the flow rate threshold range to obtain a target pump pressure and a target flow rate.

[0031] In a specific embodiment, the instruction generation module further includes an instruction generation unit electrically connected to the data iteration unit;

[0032] The instruction generation unit is configured to receive the target pump pressure and the target flow rate, and generate the printing and dyeing control instruction based on the pump pressure and the target flow rate.

[0033] Implementing the present invention has the following beneficial effects:

[0034] In the present invention, the digital monitoring-based water-saving automatic processing system for polyester fabrics includes a printing and dyeing execution device, a filtration and regeneration device, a data acquisition device, and a system control device. Through the mutual cooperation among the devices, for example, the data acquisition device collects the printing and dyeing processing parameters in real time and sends them to the system control device. The system control device determines the printing and dyeing control instruction through the processing of the printing and dyeing processing parameters and the construction of the dynamic association function, so that the printing and dyeing execution device can perform the printing and dyeing of the fabric according to the printing and dyeing control instruction, thereby realizing the optimization of the wastewater circulation path and the improvement of the resin adsorption efficiency, and being able to greatly reduce the waste of resources such as water resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0036] Figure 1 It is the first architecture schematic diagram corresponding to the automated processing system provided by the embodiment of the present invention;

[0037] Figure 2 It is the second architecture schematic diagram corresponding to the automated processing system provided by the embodiment of the present invention;

[0038] Figure 3 It is the third architecture schematic diagram corresponding to the automated processing system provided by the embodiment of the present invention. Detailed implementation manners

[0039] Next, the technical solutions in the embodiments of this specification will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0040] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0041] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the drawings denote elements having the same or similar functions. Although various aspects of the embodiments are shown in the drawings, the drawings do not have to be drawn to scale unless otherwise specified.

[0042] The special word "exemplary" here means "serving as an example, an embodiment or an illustration". Any embodiment described as "exemplary" here does not have to be interpreted as being superior to or better than other embodiments.

[0043] In this text, the term "and / or" is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. Additionally, the term "at least one" in this text means any one of multiple types or any combination of at least two of multiple types. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set composed of A, B, and C.

[0044] In addition, for a better illustration of the present disclosure, numerous specific details are given in the following specific implementation manners. Those skilled in the art should understand that the present disclosure can also be implemented without certain specific details. In some instances, methods, means, elements, and circuits well-known to those skilled in the art are not described in detail to highlight the gist of the present disclosure.

[0045] Figure 1 It is the schematic diagram of the first architecture corresponding to the automated processing system provided by the embodiment of the present invention. As Figure 1 shown, the automated processing system for water-saving printing and dyeing of polyester fabrics based on digital monitoring includes:

[0046] The printing and dyeing execution device includes a stainless steel box body and an internally placed printing and dyeing barrel. The printing and dyeing barrel is configured with a dye liquor circulation pipeline and a wastewater outlet.

[0047] The filtration and regeneration device is connected to the wastewater outlet of the printing and dyeing barrel and includes a solid resin filtration layer, a backwashing device, and a waste liquid recovery channel.

[0048] The data acquisition device includes multiple sensors for obtaining the printing and dyeing processing parameters inside the printing and dyeing barrel.

[0049] The system control device is used to obtain and process the printing and dyeing processing parameters, and construct a dynamic association function and generate a printing and dyeing regulation instruction in combination with the printing and dyeing processing parameters.

[0050] In a specific embodiment, the automated processing system for water-saving printing and dyeing of polyester fabrics based on digital monitoring may include a printing and dyeing execution device, a filtration and regeneration device, a data acquisition device, and a system control device. Among them, the printing and dyeing execution device is used for printing and dyeing fabrics. It may include a stainless steel box body and a printing and dyeing barrel. The printing and dyeing barrel is configured with a dye liquor circulation pipeline and a wastewater outlet, and is also configured with a water pump for providing power to the dye liquor and / or wastewater. The rotational speed range thereof can be 500 - 2000 rpm, and the pressure regulation accuracy can be ±0.1 MPa.

[0051] The filtration and regeneration device is connected to the wastewater outlet of the printing and dyeing barrel and may include a solid resin filtration layer, a backwashing device, and a waste liquid recovery channel. Among them, the porosity of the solid resin can be 60% - 80%, and the specific surface area can be 300 - 500 m2 / g.

[0052] The data acquisition device can be composed of a distributed sensor network, including multiple sensors, and is used to acquire printing and dyeing processing data.

[0053] Figure 2 It is the second architecture schematic diagram corresponding to the automated processing system provided by the embodiment of the present invention. As Figure 2 shown, in the data acquisition device, the multiple sensors include a temperature sensor, a pressure sensor, a water pump speed sensor, and an optical resin saturation sensor, and the multiple sensors are deployed in a ring topology structure on the inner wall of the printing and dyeing barrel, the dyeing solution circulation pipeline, and the inlet of the solid resin filter layer.

[0054] In a specific embodiment, the multiple sensors can include a temperature sensor, a pressure sensor, a water pump speed sensor, and an optical resin saturation sensor. Correspondingly, the printing and dyeing processing parameters can include the printing and dyeing temperature parameter obtained by the temperature sensor, the printing and dyeing pressure parameter obtained by the pressure sensor, the water pump speed parameter obtained by the water pump speed sensor, and the solid resin saturation parameter obtained by the optical resin saturation sensor.

[0055] Specifically, at the wastewater treatment site, the sensors can be divided into a temperature sensor group, a pressure sensor group, a water pump speed sensor group, a resin saturation sensor group, etc. according to the measurement object to achieve grouped management and parallel acquisition. First, power on and self-check the hardware to ensure that all sensors are in a readable state. For different sensor groups, they can be set at different positions of the printing and dyeing barrel. For example, for the temperature sensors, 4 temperature sensors can be selected and installed at the upper, middle, bottom, and outlet pipe inlet positions of the printing and dyeing barrel. Through grouping, temperature stratification and local overheating can be detected more quickly.

[0056] Figure 3 It is the third architecture schematic diagram corresponding to the automated processing system provided by the embodiment of the present invention. Please refer to Figure 2 and Figure 3 , the system control device includes a data processing module;

[0057] The data processing module includes:

[0058] A data correction unit electrically connected to the data acquisition device, which is used to obtain the printing and dyeing processing parameters and perform data correction processing on the printing and dyeing processing parameters to obtain calibrated printing and dyeing parameters;

[0059] A data fusion unit electrically connected to the data correction unit, which is used to perform data fusion on the calibrated printing and dyeing parameters to obtain initial printing and dyeing parameters.

[0060] A redundancy check unit electrically connected to the data fusion unit, which is used to receive the initial printing and dyeing parameters, perform redundancy check on the initial printing and dyeing parameters in combination with the preset parameter threshold, and generate an abnormal reminder message according to the redundancy check result.

[0061] In a specific embodiment, a data correction unit can be used to perform zero calibration and drift correction on the printing and dyeing process parameters, and apply a low-pass or Kalman filtering algorithm to eliminate high-frequency interference and random noise to obtain calibrated printing and dyeing parameters. The calibrated printing and dyeing parameters correspond to the printing and dyeing process parameters, and may include calibrated printing and dyeing temperature parameters, calibrated printing and dyeing pressure parameters, calibrated water pump speed parameters, and calibrated solid resin saturation parameters.

[0062] The following general calibration formula can be adopted (taking the printing and dyeing temperature parameter T_i as an example):

[0063] T_cal(i) = T_raw(i) - B

[0064] Wherein, T_cal(i) represents the calibrated reading of the i-th temperature sensor, that is, the calibrated printing and dyeing temperature parameter, with the unit of degree Celsius, which is a real-time variable and is output by the algorithm; T_raw(i) represents the original reading of the i-th temperature sensor, with the unit of degree Celsius, which is output by the hardware; B represents the temperature offset constant, which is obtained through regular calibration, and its range can be between 0.5°C and 2.0°C.

[0065] In addition, after calibration is completed, the data correction unit can also perform unified formatting processing on each group of calibrated printing and dyeing parameters for subsequent fusion analysis.

[0066] In a specific embodiment, the data correction and calibration can be performed on the original pulse signal of the water pump speed sensor. First, 1% - 3% of the interference pulses are deducted, and then it is converted into the speed N(t) to reduce the measurement fluctuation and obtain a stable speed reading.

[0067] For the data fusion unit, when the number of the same type of sensors set in the system is large, to improve the measurement accuracy, the data fusion unit can also perform mean, median or weighted fusion on the same group of data. The initial printing and dyeing parameters correspond to the printing and dyeing process parameters and the initial printing and dyeing parameters, and may include initial printing and dyeing temperature parameters, initial printing and dyeing pressure parameters, initial water pump speed parameters, and initial solid resin saturation parameters.

[0068] Still taking the temperature sensor group as an example, the fusion formula can be written as:

[0069] T_fuse = (w1*T_cal(1) + w2*T_cal(2) +... + wk*T_cal(k)) / (w1 + w2 +... + wk)

[0070] Among them, T_fuse represents the fused temperature reading, which is the initial printing and dyeing stability parameter in degrees Celsius and can be output by the fusion algorithm; T_cal(i) represents the calibrated reading of the i-th temperature sensor in degrees Celsius and is obtained from the previous step output; wi represents the weight assigned to the i-th temperature sensor, which is determined by historical stability or calibration results, and its range can be between 0.1 and 0.9; k is the number of sensors in the same group, which can be 2 to 5 and is configured according to actual needs.

[0071] Specifically, in the fusion formula, dividing by the sum of all weight coefficients when calculating the weighted average is to ensure the rationality, scientificity, and physical consistency of the fused data. For example, since the weights of different sensors may be different, directly adding them may cause the value to be too large or too small. Dividing by the sum of the weights can ensure that it remains within a reasonable temperature range and will not be distorted due to the influence of the weights.

[0072] For the redundancy check unit, after the data fusion unit completes the fusion, if the data of a certain sensor deviates from the fusion result by more than the threshold, the redundancy check is triggered and it is marked as an abnormal sensor. For example, if the reading of one of the four temperature sensors differs from the average of the other three by more than 2°C, the redundancy alarm is triggered to remind to check the status of this sensor.

[0073] In addition, after performing the redundancy check on the initial printing and dyeing parameters, the initial printing and dyeing parameters after the redundancy check can be uniformly packaged according to the time stamp to form a comprehensive monitoring array for subsequent digital modeling. The data vector X(t) can be defined as follows:

[0074] X(t) = (T(t), P(t), N(t), S(t))

[0075] Among them, X(t) represents the multi-dimensional data flow vector at time t. T(t) represents the temperature (unit: degrees Celsius), which is fused from the temperature sensor group, that is, the initial printing and dyeing temperature parameter after the redundancy check; P(t) represents the pressure (unit: bar or Pa), which is fused from the pressure sensor group, that is, the initial printing and dyeing pressure parameter after the redundancy check; N(t) represents the pump speed (unit: revolutions per minute), which is fused from the speed sensor group, that is, the initial pump speed parameter after the redundancy check; S(t) represents the resin saturation (dimensionless, 0 to 1), which is fused from the saturation sensor group, that is, the initial solid resin saturation parameter after the redundancy check.

[0076] The above vector X(t) can be output to the subsequent digital model at a specified time interval for dynamic analysis. For example, X(t) can be collected once every 5 seconds, and the data is sent to the host computer and displayed on the monitoring interface, enabling the operator to observe the synchronous changes of the temperature, pressure, pump speed, and resin saturation state in the printing and dyeing barrel in real time, thereby improving the accuracy and stability of water-saving treatment.

[0077] Please continue to refer to Figure 2 and Figure 3 , the system control device further includes a function construction module;

[0078] The function construction module includes:

[0079] A data alignment unit electrically connected to the data processing module, which is used to obtain initial printing and dyeing parameters and perform data alignment processing on the initial printing and dyeing parameters according to a preset sampling interval to obtain aligned initial printing and dyeing parameters;

[0080] The data alignment unit is further used to perform data equalization processing on the aligned initial printing and dyeing parameters to obtain standard printing and dyeing parameters;

[0081] A matrix construction unit electrically connected to the data alignment unit, which is used to construct a dynamic correlation matrix in combination with the standard printing and dyeing parameters;

[0082] A first function construction unit electrically connected to the matrix construction unit, which is used to construct a dynamic correlation function and calculate the predicted resin saturation value.

[0083] In a specific embodiment, the function construction module can construct a dynamic correlation function by combining the multi-dimensional data stream vector X(t) with the characteristics of high-temperature and high-pressure printing and dyeing and the non-linear characteristics of resin adsorption, so as to determine the coupling relationship between temperature, pressure and saturation, in order to solve the problem of unstable absorption efficiency.

[0084] For the data alignment unit, the initial printing and dyeing parameters after redundancy check, that is, X(t), can be uniformly marked with time and dimension processed to ensure the comparability of each variable within the same sampling period.

[0085] Specifically, the data alignment unit includes time alignment of X(t). For example, if the temperature sampling interval is 5 seconds and the pressure sampling interval is 1 second, interpolation or downsampling is required to ensure that each variable has data at the unified time t.

[0086] Furthermore, after data alignment, the data alignment unit is also used to perform data equalization processing on the aligned initial printing and dyeing parameters to obtain standard printing and dyeing parameters. Specifically, each variable can be subtracted by its average value and divided by its standard deviation to make the distribution of variables with different dimensions balanced, which is convenient for subsequent correlation analysis. If the original range of a certain variable is too large, for example, the pressure can reach hundreds of bars, logarithmic transformation can be performed first and then standardized.

[0087] After the data alignment unit processes the initial printing and dyeing parameters, it can output multi-dimensional data that is time-aligned and standardized, which can be denoted as standard printing and dyeing parameters Z(t).

[0088] Z(t) = (z1(t), z2(t), z3(t), z4(t). Where z1(t) represents the normalized sequence of temperature (dimensionless); z2(t) represents the normalized sequence of pressure (dimensionless); z3(t) represents the normalized sequence of water pump speed (dimensionless); z4(t) represents the normalized sequence of resin saturation (dimensionless).

[0089] In a specific embodiment, assuming that the average original value of temperature is 80 °C and the standard deviation is 5 °C, then after normalizing the original temperature of 82 °C at a certain moment, we can get (82 - 80) / 5 = 0.4, indicating that the temperature at this moment is 0.4 standard deviations higher than the average value.

[0090] Furthermore, after obtaining the standard printing and dyeing parameters Z(t), the matrix construction unit is used to conduct correlation analysis on the mutual influence among variables. Methods such as sliding window Pearson correlation and mutual information can be selected to achieve correlation analysis, and a dynamic correlation matrix C(t) is constructed. Suppose the correlation matrix C within a certain time period is a 4x4 square matrix:

[0091] C(t) = [[c11(t), c12(t), c13(t), c14(t)],

[0092] [c21(t), c22(t), c23(t), c24(t)],

[0093] [c31(t), c32(t), c33(t), c34(t)],

[0094] [c41(t), c42(t), c43(t), c44(t)]

[0095] Among them, c11(t), c22(t), c33(t), c44(t) respectively represent the correlation coefficients or autocovariances of z1, z2, z3, z4 with themselves, usually 1 or positively correlated. c12(t) can represent the correlation relationship between z1 and z2, such as the coupling degree between temperature and pressure at time t. Similarly, c13(t), c14(t), etc. can be inferred. The value range of each c_ij(t) is -1 to +1. If |c_ij(t)| is close to 1, it means that the correlation degree between the two variables is very high. t represents the correlation coefficient calculated in the t-th time window, which can be dynamically updated over time.

[0096] In a specific embodiment, during the printing and dyeing process, if there is a negative correlation between temperature and water pump speed, it may indicate that when the speed is high, the liquid disturbance in the barrel increases and heat is more easily dissipated; then at a certain moment, c13(t) may be -0.7, indicating a strong negative correlation between the two.

[0097] For the first function construction unit, to capture the non-linear dependence between resin saturation and temperature, pressure, and rotational speed, a multiple non-linear regression or a neural network-based model can be used to generate a dynamic correlation function and output the predicted value of the resin saturation at the next moment, that is, the predicted resin saturation value.

[0098] Specifically, to generate a dynamic correlation function based on multiple non-linear regression, the printing and dyeing parameters such as the initial printing and dyeing parameters can be standardized or normalized to obtain the standard printing and dyeing parameters, and data processing such as missing value filling and outlier removal can be performed on the standard printing and dyeing parameters. Then, the non-linear regression model is used for model training and model evaluation to obtain the dynamic correlation function.

[0099] Alternatively, for generating a dynamic correlation function based on a neural network model, it can be applied to situations with complex variable relationships. First, the printing and dyeing parameters such as the initial printing and dyeing parameters are standardized or normalized to obtain the standard printing and dyeing parameters, and data processing such as missing value filling and outlier removal is performed on the standard printing and dyeing parameters. Further, a neural network model such as a long short-term memory network (LSTM) is selected for model training and model evaluation to obtain the dynamic correlation function.

[0100] The dynamic correlation function can be simplified to the following multiple non-linear equation:

[0101] S_pred(t+1)

[0102] = a0 + a1*T(t) + a2*P(t) + a3*N(t) + f(T(t)*P(t), T(t)*N(t),...)

[0103] Where, S_pred(t+1) represents the predicted value of the resin saturation at time t+1, that is, the predicted resin saturation value, with a range of 0 to 1, where 0 represents unsaturated and 1 represents fully saturated; T(t) is the actual temperature in degrees Celsius, which can be obtained from the previous step Z(t) and the inverse standardization transformation; P(t) is the actual pressure in bars or pascals, which can be obtained from the previous step Z(t) and the inverse standardization transformation; N(t) is the actual water pump rotational speed in revolutions per minute, which can be obtained from the previous step Z(t) and the inverse standardization transformation; a0, a1, a2, and a3 are regression coefficients, with a range that can be between -10 and 10, obtained through historical data or training algorithms; f(..) is a non-linear interaction term, which can include T(t)*P(t), T(t)*N(t), P(t)*N(t), etc., and the specific form depends on actual requirements. This model can better reflect the dynamic changes in the resin adsorption efficiency due to multi-parameter coupling in a high-temperature and high-pressure environment.

[0104] The linear terms a1*T(t) + a2*P(t) + a3*N(t) represent the direct effects of temperature, pressure, and water pump speed on the resin saturation. For temperature T(t), when a1 > 0, as the temperature increases, the molecular motion of the resin speeds up, and the adsorption capacity increases, leading to an increase in resin saturation; when a1 < 0, if the excessive temperature causes the pores on the resin surface to collapse, it may reduce the adsorption capacity and result in a decrease in resin saturation.

[0105] For pressure P(t), when a2 > 0, high pressure can increase liquid permeability and the adsorption rate of the resin, thus increasing resin saturation; when a2 < 0, if the pressure is too high, it may cause the resin to deform, affecting the adsorption efficiency and even causing fluid retention, reducing resin saturation.

[0106] For the water pump speed N(t), when a3 > 0, a higher water pump speed can accelerate liquid flow, reduce the liquid boundary layer on the resin surface, and improve the mass transfer efficiency, thereby increasing saturation; when a3 < 0, if the water pump speed is too high, it may cause excessive shear force, affecting the stability of resin particles and even generating excessive turbulence, reducing the adsorption efficiency.

[0107] The non - linear interaction terms f(T(t)*P(t), T(t)*N(t)) represent the complex effects when multiple variables are coupled. For the temperature - pressure interaction term T(t)*P(t), if the temperature and pressure increase simultaneously, it may enhance liquid permeability, making it easier for the resin to absorb liquid and increasing resin saturation; however, if the pressure and temperature are both too high, it may cause the resin to deform, reducing the adsorption capacity and forming an "over - adsorption" phenomenon, instead reducing resin saturation. That is to say, a single linear term (such as a1*T(t)) describes the direct and independent effect of temperature on resin saturation. However, in a high - temperature and high - pressure environment, there are often coupling effects among various parameters, and considering them separately may not accurately describe the actual physical process. Although the dimensions of T(t)*P(t), T(t)*N(t), and P(t)*N(t) are different, the significance of introducing the interaction terms is to capture the non - linear coupling effects between two parameters. In this formula, such product terms should only be regarded as a kind of "weighting" factor.

[0108] For the temperature - water pump speed interaction term T(t)*N(t), an increase in temperature usually reduces the liquid viscosity, and an increase in the water pump speed accelerates fluid flow. The combined effect of these two usually increases the adsorption rate and raises the resin saturation; however, if the water pump speed is too high, under high - temperature conditions, it may cause flow disorder and form turbulence, instead affecting the resin adsorption uniformity and making the saturation unstable.

[0109] That is, T(t), P(t), and N(t) have a non-linear influence on S_pred(t+1). When they are moderate, the saturation is increased, while being too high or too low may reduce the adsorption efficiency. It is necessary to find the optimal combination rather than simply increasing the temperature, pressure, and rotation speed.

[0110] Specifically, when operating at high temperature (>80°C) and high rotation speed (>1000 revolutions per minute), the saturation rate of the resin often accelerates. If it is actually measured that S(t)=0.6 and the temperature and pressure continue to increase, then S_pred(t+1) may quickly approach 0.8 or above, indicating that saturation is approaching.

[0111] Furthermore, to improve the accuracy of the model, during the operation of the automatic water-saving treatment system for polyester fabric printing and dyeing based on digital monitoring, adaptive correction can be performed by comparing S_pred(t) with the actual resin saturation S(t). If the deviation is large, coefficients such as a0 and a1 are adjusted or the non-linear interaction term is corrected. After completion of the correction, the dynamic correlation matrix and the latest predicted resin saturation value are output for subsequent intelligent control execution.

[0112] When |S_pred(t)-S(t)| exceeds the threshold, online correction is triggered to optimize the regression coefficients; the threshold can be, for example, 0.05 to 0.1. The correction algorithm can adopt least squares or gradient-based iterative update to enable the model to self-learn as the environmental parameters change. Thus, a dynamic correlation matrix C(t) such as the aforementioned 4x4 matrix that is continuously updated over time can be obtained, and the predicted resin saturation value S_pred(t+1) that can be updated over time can be obtained. Combining the dynamic correlation matrix C(t) and the predicted resin saturation value S_pred(t+1) can guide the adjustment of the next water pump rotation speed and system process.

[0113] In a specific embodiment, when the actually measured resin saturation S(t) is more than 0.1 lower than the model prediction twice in a row, it is speculated that the model's estimation of the saturation process under high temperature conditions is too conservative, and it is necessary to appropriately increase a2 (the pressure term coefficient) or introduce a higher-order interaction term of temperature and pressure in f(..) to more accurately capture the actual adsorption situation.

[0114] Please continue to refer to Figure 2 and Figure 3 , the system control device further includes an instruction generation module;

[0115] The instruction generation module includes:

[0116] A second function construction unit electrically connected to the function construction module. The data initialization unit is used to receive the dynamic correlation matrix and the predicted resin saturation value, and generate a target adjustment function in combination with the dynamic correlation matrix and the predicted resin saturation value.

[0117] A data iteration unit electrically connected to the second function construction unit; the data iteration unit is used to perform iterative reasoning based on the target adjustment function, the pump pressure threshold range, and the flow rate threshold range to obtain the target pump pressure and the target flow rate.

[0118] An instruction generation unit electrically connected to the data iteration unit; the instruction generation unit is used to receive the target pump pressure and the target flow rate, and generate a printing and dyeing regulation instruction based on the pump pressure and the target flow rate.

[0119] In a specific embodiment, the system control device, through the instruction generation module, according to the previously output dynamic correlation matrix and the predicted resin saturation value, uses fuzzy logic or an adaptive control algorithm to adjust the water pump pressure and the circulating flow rate in real time, realizing the refined control of the wastewater recycling and resin adsorption process, preventing the pump pressure from operating under non-optimal conditions, and improving the water resource utilization efficiency.

[0120] For the second function construction unit, first receive the dynamic correlation matrix and the predicted resin saturation value, and initialize the basic parameters such as variables and thresholds, and then construct the target adjustment function.

[0121] Specifically, first set the safe operating threshold. For example, when S_pred(t + 1) is greater than 0.9, the system should timely remind or prepare to replace the resin. Secondly, initialize the adjustable range to determine the maximum allowable pump pressure P_max and the minimum allowable pump pressure P_min of the system, and constrain the output within the range of [P_min, P_max]. In addition, it is also necessary to set the upper and lower limits of the circulating flow rate, such as the minimum flow rate Q_min and the maximum flow rate Q_max.

[0122] During actual deployment, the user can set P_min = 2 bar, P_max = 20 bar, and Q_min = 1 cubic meter per hour, Q_max = 8 cubic meters per hour on the upper computer interface, and write this information into the controller through the configuration file, so that it can automatically calculate the regulation instruction according to the subsequent input.

[0123] Furthermore, combining the above basic parameters such as variables and thresholds, the dynamic correlation matrix, and the predicted resin saturation value, through the target adjustment function of the second function construction unit, so that the system can take into account both the water saving efficiency and prevent excessive saturation too quickly.

[0124] The target adjustment function can achieve water conservation by minimizing the circulating flow rate Q(t) as much as possible while maintaining appropriate treatment effects, thereby reducing the energy consumption of the water pump; and, the target adjustment function can also prevent saturation by appropriately increasing the flow rate or reducing the pump pressure when S_pred(t+1) rises to a relatively high value, so as to prevent the adsorption efficiency from dropping sharply due to the local resin approaching saturation but the wastewater not being discharged in time. At the same time, in the form of weighted summation, the two goals of water conservation and anti-saturation can be assigned weights, denoted as w1, with a range of 0.4 to 0.6, and selected according to the actual working conditions.

[0125] For the construction of the target adjustment function, the optimization variables can be defined as P(t) and Q(t), then the target adjustment function F can be expressed as:

[0126] F = w1 * f1(P(t), Q(t), C(t)) + w2 * f2(s_pred(t+1), P(t), Q(t))

[0127] Among them, P(t) represents the pump pressure, Q(t) represents the flow rate, and F is the value corresponding to the target adjustment function, which can be calculated in real time. w1 and w2 are the weights for water conservation and anti-saturation respectively; f1(..) represents the water conservation function, and the smaller the value, the more water-saving, which can be measured by the ratio of Q(t) to the rated flow rate of the system; f2(..) represents the anti-saturation function, and the smaller the value, the more beneficial to the adsorption efficiency, which can be determined according to the coupling relationship between S_pred(t+1) and P(t), Q(t). When generating the target adjustment function, the initial estimates P(t), Q(t) for the next iterative solution can be obtained.

[0128] In a specific embodiment, w1 = 0.5 and w2 = 0.5 can be set to make the importance of water conservation and anti-saturation equivalent; f1(..) can be defined as Q(t) / Q_max, and the larger Q(t) is, the larger the value of f1(..); f2(..) can be defined as [S_pred(t+1)] 2 , to highlight the warning effect for the state close to saturation.

[0129] For the data iteration unit, after obtaining the target adjustment function F, iterative algorithms such as fuzzy logic and adaptive genetic algorithms are used to search within the feasible region of P(t) and Q(t) to minimize or optimize the output value of the target adjustment function F.

[0130] If the genetic algorithm is adopted, several groups of (P_i, Q_i) are first generated as the initial population; if fuzzy logic is adopted, several rules are defined, such as "if S_pred(t + 1) is high and the negative correlation between temperature and rotational speed in the correlation matrix is obvious, then reduce P(t) and increase Q(t)", and the objective value of each group of (P_i, Q_i) is calculated according to F and selection, crossover, mutation or fuzzy inference is carried out to gradually converge to the optimal solution. When the change in consecutive iteration results is less than the threshold (e.g., <1%) or the preset maximum number of iteration rounds is reached, the search is stopped.

[0131] If the adaptive genetic algorithm is adopted, 10 groups of candidate solutions are initially generated, such as P = 5 bar, Q = 2.0 m³ / h, etc. After 20 - 30 rounds of iteration, when it converges to P = 7 bar and Q = 1.5 m³ / h, the output value of the objective regulation function F reaches the lowest, and this is the preliminary optimal solution at this time, preparing to enter the next fine-tuning.

[0132] For the instruction generation unit, the optimal solution generated by the data iteration unit is fine-tuned according to the actual device characteristics, and a printing and dyeing regulation instruction is output. Among them, the printing and dyeing regulation instruction includes the final pump pressure setting value and the circulating flow rate value, so that the execution device can achieve the goals of water conservation and anti-saturation. The actual device characteristics can include safety policies and device response curves, such as the actual pressure output deviation of the water pump at different rotational speeds.

[0133] In addition, the actual device characteristics can also include that according to the actual characteristics of the water pump and pipeline, a tentative fine-tuning of P(t) within plus or minus 1 bar can be carried out to see if the output value of the objective regulation function F can be further reduced. And, if the process requirements have special restrictions on the flow rate, such as Q_min = 1.2 m³ / h to ensure that the chromaticity does not increase, then it is necessary to ensure that Q is not less than 1.2 m³ / h. When the fine-tuning has little interference to the system and the objective function has no significant improvement, it can be determined as the final output, and the corresponding target regulation instruction is generated.

[0134] The final output includes the optimal pump pressure setting value and the circulating flow rate value, and the target regulation instruction can be represented by the vector Y(t):

[0135] Y(t) = (P_opt(t), Q_opt(t))

[0136] Where Y(t) represents the target regulation instruction at time t, P_opt(t) represents the optimal pump pressure setting value, with the unit of bar, belonging to a real variable, obtained through iterative search and fine-tuning; Q_opt(t) represents the optimal circulating flow rate instruction, with the unit of m³ / h, belonging to a real variable, obtained through iterative search and fine-tuning.

[0137] Specifically, if P_opt(t) = 6.8 bar and Q_opt(t) = 1.6 m³ / h are obtained after fine-tuning, and it is observed that the resin saturation rate of increase has slowed down significantly and the water pump energy consumption has decreased significantly in the past ten minutes, then Y(t) = (6.8, 1.6) can be determined as the target control command and sent to the printing and dyeing execution device, so that the system operates stably at the balance point of water conservation and anti-saturation.

[0138] As can be seen from the embodiments provided by the present invention above, in the present invention, the digital monitoring-based automatic water-saving treatment system for polyester fabrics includes a printing and dyeing execution device, a filtration and regeneration device, a data acquisition device, and a system control device. Through the mutual cooperation of each device, for example, the data acquisition device collects the printing and dyeing treatment parameters in real time and sends them to the system control device. The system control device determines the printing and dyeing control command through the processing of the printing and dyeing treatment parameters and the construction of the dynamic correlation function, so that the printing and dyeing execution device can realize the printing and dyeing of the fabric according to the printing and dyeing control command, thereby realizing the optimization of the wastewater circulation path and the improvement of the resin adsorption efficiency, and being able to significantly reduce the waste of resources such as water resources.

[0139] It should be noted that: the above has described various embodiments of the present disclosure. The above description is exemplary and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those of ordinary skill in the art corresponding to the technical field without departing from the scope and spirit of the described embodiments. The selection of the terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other ordinary skill in the art in the technical field to understand the disclosed embodiments.

Claims

1. A water-saving automatic treatment system for polyester fabric printing and dyeing based on digital monitoring, characterized in that, The system includes: A printing and dyeing execution device, including a stainless-steel box body and an internally placed printing and dyeing barrel, the printing and dyeing barrel being configured with a dyeing liquid circulation pipeline and a waste water outlet; A filtration and regeneration device, connected to the waste water outlet, including a solid resin filtration layer, a backwashing device, and a waste liquid recovery channel; A data acquisition device: including multiple sensors for obtaining printing and dyeing processing parameters inside the printing and dyeing barrel; A system control device for obtaining and processing the printing and dyeing processing parameters, and constructing a dynamic correlation function and generating a printing and dyeing regulation instruction in combination with the printing and dyeing processing parameters.

2. The polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring according to claim 1, characterized in that In the data acquisition device, the multiple sensors include a temperature sensor, a pressure sensor, a water pump speed sensor, and an optical resin saturation sensor, and the multiple sensors are deployed in a ring topology structure on the inner wall of the printing and dyeing barrel, the dyeing liquid circulation pipeline, and the inlet of the solid resin filtration layer.

3. The polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring according to claim 1, characterized in that, The system control device includes a data processing module; The data processing module includes: A data correction unit electrically connected to the data acquisition device, the data correction unit being used to obtain the printing and dyeing processing parameters and perform data correction processing on the printing and dyeing processing parameters to obtain calibrated printing and dyeing parameters; A data fusion unit electrically connected to the data correction unit, the data fusion unit being used to perform data fusion on the calibrated printing and dyeing parameters to obtain initial printing and dyeing parameters.

4. The polyester fabric printing and dyeing water-saving automatic processing system based on digital monitoring according to claim 3, characterized in that, The data processing module further includes a redundancy check unit electrically connected to the data fusion unit; The redundancy check unit is used to receive the initial printing and dyeing parameters, perform redundancy check on the initial printing and dyeing parameters in combination with preset parameter thresholds, and generate an abnormal reminder message according to the redundancy check result.

5. The polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring according to claim 1, characterized in that, The system control device further includes a function construction module; The function construction module includes: A data alignment unit electrically connected to the data processing module, the data alignment unit being used to obtain initial printing and dyeing parameters and perform data alignment processing on the initial printing and dyeing parameters according to a preset sampling interval to obtain aligned initial printing and dyeing parameters; The data alignment unit is further used to perform data equalization processing on the aligned initial printing and dyeing parameters to obtain standard printing and dyeing parameters.

6. The polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring according to claim 5, wherein The function construction module further includes: A matrix construction unit electrically connected to the data alignment unit, the matrix construction unit being used to construct a dynamic correlation matrix in combination with the standard printing and dyeing parameters.

7. The polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring according to claim 6, characterized in that, The function construction module further includes: A first function construction unit electrically connected to the matrix construction unit, the first function construction unit being used to construct the dynamic correlation function and calculate the predicted resin saturation value.

8. The polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring according to claim 1, wherein, The system control device further includes an instruction generation module; The instruction generation module includes: A second function construction unit electrically connected to the function construction module, the data initialization unit being used to receive the dynamic correlation matrix and the predicted resin saturation value, and generate a target adjustment function in combination with the dynamic correlation matrix and the predicted resin saturation value.

9. The polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring according to claim 8, characterized in that, The instruction generation module further includes a data iteration unit electrically connected to the second function construction unit; The data iteration unit is used to perform iterative reasoning based on the target adjustment function, the pump pressure threshold range, and the flow threshold range to obtain the target pump pressure and the target flow.

10. The polyester fabric printing and dyeing water-saving automatic processing system based on digital monitoring according to claim 9, characterized in that, The instruction generation module further includes an instruction generation unit electrically connected to the data iteration unit; The instruction generation unit is configured to receive the target pump pressure and the target flow rate, and generate the printing and dyeing regulation instruction based on the pump pressure and the target flow rate.

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