Automatic control method and system for continuous processing of knitted fabric

Abstract

The application discloses an automatic regulation method and system for continuous processing of knitted fabric. The method comprises the following steps: rolling and sealing the fabric after immersion in the working liquid, attaching sensors and near-infrared probes on the inside and outside of the sealing film, and recording the initial concentration of hydrogen peroxide; calling the pre-marked stacking reaction benchmark under the same working condition, dividing the reaction process into fast, stable and slow reaction periods according to the change rule of hydrogen peroxide decomposition rate; making an initial judgment of abnormality based on temperature and air pressure data during the fast reaction period, and rechecking by infrared spectroscopy, and suspending the stacking and feeding back the abnormal type when the abnormality is confirmed; correcting the time point of entering the slow reaction period based on the concentration curve fitting degree and the relative deviation ratio during the stable reaction period; and capturing the stacking end point when the decomposition rate reaches the target value after entering the slow reaction period. The application realizes non-contact online monitoring and dynamic time length regulation of the stacking reaction, and improves the stability and consistency of the pretreatment effect.

Description

Technical Field

[0001] This invention relates to the field of pretreatment technology for knitted fabrics, and more specifically to an automated control method and system for continuous processing of knitted fabrics. Background Technology

[0002] In continuous processing of knitted fabrics, pretreatment is a crucial step in removing natural impurities from fibers (such as waxes, pectin, and cottonseed hulls on cotton) and oil stains introduced during spinning and weaving. Its purpose is to give the fabric good whiteness and absorbency (wicking effect), preparing it for subsequent dyeing or printing. Currently, in continuous processing, the flat-width cold pad-batch pretreatment process is widely used. Its main steps include: flat-width fabric feeding, padding with working solution, room temperature padding, short-steam reaction acceleration, high-efficiency flat-width washing, and fabric unloading.

[0003] The room temperature stacking stage is the core and key of the entire pretreatment process. Its task is to utilize the alkaline and humid environment maintained within a sealed system, under mild conditions without external heating, to allow hydrogen peroxide and auxiliary chemicals in the working solution to continuously oxidize, saponify, and swell with natural impurities on the fibers, achieving effective degradation of non-woven impurities and improving the hydrophilicity of the fibers. However, controlling this stage presents the following technical challenges: First, the decomposition of hydrogen peroxide during stacking is an invisible chemical reaction, requiring a precise balance between sufficient reaction and avoiding excessive reaction intensity; second, numerous and interconnected influencing factors exist. Too low a hydrogen peroxide decomposition rate leads to insufficient whiteness, while too high a rate causes irreversible fiber damage, directly affecting subsequent dyeing quality and fabric durability.

[0004] The existing technology for the stacking stage of the pretreatment of knitted fabrics in the flat-width cold pad-batch process has the following main shortcomings: (1) Existing methods mostly use post-event sampling and testing to evaluate the stacking effect. They cannot grasp the real-time decomposition of hydrogen peroxide during the stacking process. They lack non-contact online monitoring methods that do not damage the sealed environment or come into contact with chemical agents, making it difficult to detect and intervene in time when the reaction deviates.

[0005] (2) Existing processes usually set a fixed total stacking time based on experience values, which cannot be dynamically adjusted according to the actual reaction rate of the current batch of fabric. This can easily lead to excessive or insufficient hydrogen peroxide decomposition, resulting in uneven pretreatment effects, fiber damage, or waste of resources.

[0006] (3) Existing methods do not distinguish the reaction characteristics of different stages in the stacking reaction process, and cannot classify, identify and deal with abnormal situations such as decomposition that may occur too fast or too slow during the rapid reaction period. Summary of the Invention

[0007] In view of this, in order to solve the problems mentioned in the background art, an automated control method and system for continuous processing of knitted fabrics is proposed.

[0008] The technical solution adopted by this invention to solve its technical problem is: In a first aspect, the present invention provides an automated control method for continuous processing of knitted fabrics, comprising the following steps: S1. Roll up and seal the fabric after impregnation with the working fluid. Install flexible temperature and pressure sensors and near-infrared probes on the inside and outside of the sealing film, respectively, and record the initial concentration of hydrogen peroxide in the working fluid.

[0009] S2. Call the pre-calibrated stacking reaction benchmark under the same working conditions, including the hydrogen peroxide concentration change curve and the total stacking time. Based on the hydrogen peroxide decomposition rate change law, divide the current stacking reaction process into fast, stable and slow reaction periods in sequence.

[0010] S3. During the rapid reaction period, determine whether the hydrogen peroxide decomposition is abnormal based on the temperature and pressure data in the sealed space. If not, proceed to S4. If yes, retest the abnormality using the hydrogen peroxide concentration measured by infrared spectroscopy. If the abnormality is confirmed, suspend the stacking and report the type of abnormal decomposition. If the abnormality is not confirmed, proceed to S4.

[0011] S4. Obtain the measured hydrogen peroxide concentration change curve during the stable reaction period, and compare it with the corresponding curve segment in the benchmark to evaluate the relative deviation of the reaction rate, and correct the time point for entering the slow reaction period accordingly.

[0012] S5. After entering the slow reaction period, capture the moment when the hydrogen peroxide decomposition rate reaches the preset target value and take it as the end point of the stacking reaction, end the stacking and enter the next process.

[0013] Based on the above embodiments, step S1 includes: The knitted fabric after being impregnated with the working fluid is flattened and rolled up, and then wrapped with a sealing film. A flexible temperature sensor array and a pressure sensor array are attached to the inside of the sealing film, and multiple near-infrared probes are attached to the outside of the sealing film.

[0014] The working solution was sampled multiple times, and the hydrogen peroxide concentration in each sample was measured. The average value of the multiple measurements was taken as the initial concentration of hydrogen peroxide in the working solution and recorded.

[0015] Based on the above embodiments, step S2 includes: Extract the pre-calibrated stacking reaction baselines under different working conditions from the database. The baselines include the hydrogen peroxide concentration change curve over time and the total stacking time.

[0016] The temperature and humidity of the current stacking environment are collected, and combined with the fabric type and working fluid formula, a pre-calibrated stacking reaction benchmark under the same working conditions is selected to predict the hydrogen peroxide concentration change curve over time and the total stacking time of the current stacking reaction.

[0017] Based on the hydrogen peroxide concentration versus time curve, the hydrogen peroxide decomposition rate is calculated point by point, and a hydrogen peroxide decomposition rate versus time curve is generated, where the hydrogen peroxide decomposition rate is the ratio of the change in hydrogen peroxide concentration to the corresponding reaction time.

[0018] Calculate the absolute value of the slope of the tangent line at each point on the curve of hydrogen peroxide decomposition rate versus time, and obtain the rate of decrease of hydrogen peroxide decomposition rate at each point. Based on this rate of decrease, divide the curve into steeply decreasing segment, gently decreasing segment and horizontal segment in sequence.

[0019] The time periods corresponding to the steep descent, gradual descent, and horizontal phases are respectively defined as the rapid reaction period, stable reaction period, and slow reaction period in the current stacking reaction process.

[0020] Based on the above embodiments, the method for pre-calibrating the stacked reaction baseline through experiments includes: By setting and adjusting the working parameters of room temperature stacking, a variety of different working conditions can be obtained. These working parameters include the type of fabric, the working fluid formula, and the temperature and humidity of the stacking environment.

[0021] Under each working condition, after the fabric rolls are sealed and stacked, samples are taken at designated locations on the fabric rolls at fixed time intervals, and the hydrogen peroxide concentration of each sample is measured. The time point of each sampling is recorded synchronously until the hydrogen peroxide decomposition rate measured at a certain sampling time point reaches the preset target value, thereby obtaining multiple sets of detection data on hydrogen peroxide concentration. The cumulative stacking time corresponding to the cessation of sampling and measurement is determined as the total stacking time under that working condition.

[0022] Plot the hydrogen peroxide concentration as time on the x-axis and the hydrogen peroxide concentration as the y-axis, and draw a curve showing the change of hydrogen peroxide concentration over time based on multiple sets of detection data.

[0023] By changing the fabric roll and the sampling location, the above steps are repeated to obtain multiple hydrogen peroxide concentration change curves over time and multiple total stacking times. Then, the final hydrogen peroxide concentration change curve over time and the total stacking time under this condition are determined, thereby constructing the stacking reaction benchmark under this condition.

[0024] The stacked reaction baselines under all operating conditions are compiled and stored in the database.

[0025] Based on the above embodiments, the method for dividing the curve according to the decreasing rate of hydrogen peroxide decomposition includes: Starting from the first data point on the curve of hydrogen peroxide decomposition rate versus time, identify data points where the rate of decrease in hydrogen peroxide decomposition rate falls within the range of the rate of decrease corresponding to the preset steep descent segment. The continuous curve segment formed by the data points that meet this condition is defined as the steep descent segment, and the end point of the steep descent segment is recorded as the inflection point between the steep descent segment and the gradual descent segment.

[0026] Starting from the inflection point between the steep descent segment and the gradual descent segment, identify data points whose rate of hydrogen peroxide decomposition falls within the descent rate range corresponding to the preset gradual descent segment. The continuous curve segment formed by the data points that meet this condition is determined as the gradual descent segment, and the end point of the gradual descent segment is recorded as the inflection point between the gradual descent segment and the horizontal segment.

[0027] The remaining curve segment after the inflection point between the descent segment and the horizontal segment is defined as the horizontal segment.

[0028] Based on the above embodiments, the method for anomaly detection and re-verification in step S3 includes: S31. During the rapid response period, multiple monitoring time points are set according to the first time interval.

[0029] Acquire the temperature data of each node in the temperature sensor array and the air pressure data of each node in the air pressure sensor array within the sealed space at the current time point.

[0030] Calculate the heating rate of each temperature sensor node and the pressure rise rate of each pressure sensor node, and construct heating rate sequence and pressure rise rate sequence respectively.

[0031] S32. Based on the temperature and pressure data during the rapid reaction period of the stacked reaction under the same historical operating conditions, determine the reference range of the heating rate and pressure rise rate at the current time point.

[0032] S33. If an abnormal value exceeding the corresponding reference range appears in the heating rate sequence or pressure rise rate sequence at the current time point, and the magnitude of the abnormal value exceeding the reference range is greater than the preset over-threshold, then it is determined that there is an abnormality in the decomposition of hydrogen peroxide, and S34 is executed.

[0033] Otherwise, if there is no abnormality, execute S35.

[0034] S34. Trigger multiple near-infrared probes to collect the spectrum of the working fluid on the fabric roll surface, measure the hydrogen peroxide concentration by infrared spectroscopy, and record the collection time.

[0035] Based on the stacking reaction baseline, the baseline value of hydrogen peroxide concentration corresponding to this collection time is extracted.

[0036] The hydrogen peroxide concentration measured by each near-infrared probe is compared with the benchmark value. If the deviation between the measured value and the benchmark value of hydrogen peroxide concentration is greater than the preset deviation threshold, and the number of near-infrared probes that meet the deviation condition reaches the preset number threshold, then an anomaly is confirmed and stacking is suspended.

[0037] Otherwise, it will be considered an unconfirmed anomaly and proceed to S35.

[0038] S35. Continue monitoring the hydrogen peroxide decomposition status at the next time point until the rapid reaction period ends.

[0039] Based on the above embodiments, the method for obtaining the abnormal decomposition type in step S3 includes: If the abnormal values ​​in the heating rate sequence or pressure rise rate sequence exceed the upper limit of the corresponding reference range, and the measured value of hydrogen peroxide concentration is lower than the benchmark value, then the abnormal decomposition type is determined to be decomposition too fast.

[0040] If the abnormal value in the heating rate sequence or pressure rise rate sequence is lower than the lower limit of the corresponding reference range, and the measured value of hydrogen peroxide concentration is higher than the benchmark value, then the abnormal decomposition type is determined to be decomposition too slow.

[0041] Based on the above embodiments, step S4 includes: S41. During the stable reaction period, set several monitoring time points according to the second time interval, obtain the hydrogen peroxide concentration measured by each near-infrared probe at each monitoring time point, and plot the measured hydrogen peroxide concentration change curve during the stable reaction period accordingly.

[0042] S42. Extract the curve segment corresponding to the stable reaction period from the pile reaction baseline as the baseline hydrogen peroxide concentration change curve.

[0043] S43. Calculate the degree of agreement between the measured concentration change curve and the reference concentration change curve.

[0044] If the degree of agreement reaches the preset threshold, there is no need to adjust the time point for entering the slow reaction period.

[0045] Otherwise, corrections are required, and S44 should be executed.

[0046] S44. Take the first derivative of the measured concentration change curve and the reference concentration change curve to obtain the measured decomposition rate change curve and the reference decomposition rate change curve, and align the two in time sequence.

[0047] S45. Obtain the cumulative area of ​​the region enclosed by the curve segments located above and below the reference rate curve in the measured rate curve, and further calculate the ratio of the cumulative area of ​​the upper region to the cumulative area of ​​the lower region to obtain the relative deviation ratio of the reaction rate.

[0048] S46. Based on the relative deviation ratio, determine the correction direction and correction duration for the time point entering the slow reaction period: If the relative deviation ratio is greater than 1, it indicates that the measured rate is greater than the reference rate. The time point for entering the slow reaction period needs to be advanced, and the advance delay time should be calculated: subtract 1 from the relative deviation ratio and multiply the difference by the total duration of the original steady reaction period.

[0049] If the relative deviation ratio is less than 1, it indicates that the measured rate is less than the reference rate. The time point for entering the slow reaction period needs to be delayed, and the delay time is calculated: subtract the difference between 1 and the relative deviation ratio, and multiply it by the total duration of the original steady reaction period.

[0050] Based on the above embodiments, step S5 includes: After entering the slow reaction period, the hydrogen peroxide concentration is continuously monitored at preset time intervals, and the current hydrogen peroxide decomposition rate is calculated in combination with the initial hydrogen peroxide concentration.

[0051] Once the hydrogen peroxide decomposition rate calculated at a certain monitoring time point reaches the preset target value, that time point is determined as the end point of the stacking reaction, the stacking ends, and the process proceeds to the next step.

[0052] Secondly, the present invention also provides an automated control system for continuous processing of knitted fabrics, comprising: Initial data acquisition module: After the fabric is impregnated with the working fluid, it is rolled up and sealed. Flexible temperature and pressure sensors and near-infrared probes are attached to the inside and outside of the sealing film, respectively, and the initial concentration of hydrogen peroxide in the working fluid is recorded.

[0053] Reaction stage division module: Calls the pre-calibrated stacking reaction benchmark under the same working conditions, including the hydrogen peroxide concentration change curve and the total stacking time. Based on the change law of hydrogen peroxide decomposition rate, the current stacking reaction process is divided into fast, stable and slow reaction periods in sequence.

[0054] Anomaly Detection and Re-verification Module: During the rapid reaction period, the module determines whether the hydrogen peroxide decomposition is abnormal based on the temperature and pressure data within the sealed space. If not, the module executes the phase switching correction module. If so, the module performs anomaly re-verification using the hydrogen peroxide concentration measured by infrared spectroscopy. If an anomaly is confirmed, the stacking is paused and the type of abnormal decomposition is reported. If no anomaly is confirmed, the module switches to the phase switching correction module.

[0055] Phase switching correction module: Obtain the measured hydrogen peroxide concentration change curve during the stable reaction period, compare it with the corresponding curve segment in the benchmark to evaluate the relative deviation ratio of the reaction rate, and correct the time point for entering the slow reaction period accordingly.

[0056] Endpoint determination and termination module: After entering the slow reaction period, the module captures the moment when the hydrogen peroxide decomposition rate reaches the preset target value and uses it as the end point of the stacking reaction, ending the stacking and proceeding to the next process.

[0057] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention, by attaching a flexible temperature sensor array and a pressure sensor array to the inside of the sealing film and a near-infrared probe to the outside, can collect temperature, pressure and hydrogen peroxide concentration data in the stacking environment in real time without damaging the seal integrity or contacting the working fluid. This enables remote, continuous and non-contact monitoring of the chemical reaction process within the sealed system, overcoming the shortcomings of existing technologies that cannot monitor the decomposition state of hydrogen peroxide online.

[0058] 2. This invention utilizes a pre-calibrated stacking reaction baseline under identical operating conditions. By comparing the measured hydrogen peroxide concentration change curve during the stable reaction period with the baseline curve, the relative deviation ratio of the reaction rate is calculated, and the timing of entering the slow reaction period is adjusted accordingly. Finally, the moment when the hydrogen peroxide decomposition rate reaches the preset target value during the slow reaction period is captured as the stacking endpoint. This dynamic control mechanism allows the stacking time to adaptively adjust with the actual reaction rate, avoiding over- or under-decomposition caused by a fixed time. This ensures both the pretreatment effect and prevents fiber damage.

[0059] 3. Based on the variation law of hydrogen peroxide decomposition rate, this invention divides the stacking reaction process into a rapid reaction period, a stable reaction period, and a slow reaction period, and adopts differentiated control strategies for each stage: During the rapid reaction period, anomalies are initially judged based on temperature and pressure data, and anomalies are re-verified using infrared spectroscopy to effectively distinguish between normal fluctuations and substantial anomalies; during the stable reaction period, the time point is corrected based on the consistency of the concentration curve and the relative deviation ratio; during the slow reaction period, the endpoint of the decomposition rate reaching the target value is accurately captured. This phased mechanism significantly improves the accuracy of anomaly identification and the level of precision in control.

[0060] 4. This invention, by comprehensively considering the deviations of the heating rate, pressure rise rate, and measured hydrogen peroxide concentration, can determine whether the abnormal decomposition is too rapid or too slow, and can pause the stacking process and provide feedback upon confirming the anomaly. This function not only helps to promptly prevent damage to the fibers from abnormal reactions but also provides data support for subsequent process parameter optimization and quality traceability. Attached Figure Description

[0061] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0062] Figure 1 This is a schematic diagram of the method flow of the present invention.

[0063] Figure 2 This is a system module connection diagram of the present invention. Detailed Implementation

[0064] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the automated control method and system for continuous knitted fabric processing proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0066] The following description, in conjunction with the accompanying drawings, details the specific scheme of the automated control method and system for continuous knitted fabric processing provided by the present invention.

[0067] This invention first rolls and seals the fabric after impregnation with the working solution, attaching sensors and near-infrared probes to the inside and outside of the sealing film to record the initial hydrogen peroxide concentration. Then, using a pre-calibrated stacking reaction benchmark under the same working conditions, the reaction process is divided into rapid, stable, and slow reaction periods based on the change in hydrogen peroxide decomposition rate. During the rapid reaction period, anomalies are initially judged based on temperature and pressure data, and verified by infrared spectroscopy. If an anomaly is confirmed, stacking is paused and the anomaly type is reported. During the stable reaction period, the entry point into the slow reaction period is adjusted based on the consistency and relative deviation ratio of the concentration curve. After entering the slow reaction period, the stacking endpoint where the decomposition rate reaches the target value is captured. This invention achieves non-contact online monitoring and dynamic duration control of the stacking reaction, improving the stability and consistency of the pretreatment effect.

[0068] Please see Figure 1 As shown, the first aspect of the present invention provides an automated control method for continuous processing of knitted fabrics, comprising the following steps S1-S5.

[0069] Step S1: Roll up and seal the fabric after impregnation with the working solution. Attach flexible temperature and pressure sensors and a near-infrared probe to the inside and outside of the sealing film, respectively, and record the initial concentration of hydrogen peroxide in the working solution.

[0070] In a preferred embodiment of the present invention, step S1 includes: The knitted fabric after being impregnated with the working fluid is flattened and rolled up, and then wrapped with a sealing film. A flexible temperature sensor array and a pressure sensor array are attached to the inside of the sealing film, and multiple near-infrared probes are attached to the outside of the sealing film.

[0071] The working solution was sampled multiple times, and the hydrogen peroxide concentration in each sample was measured. The average value of the multiple measurements was taken as the initial concentration of hydrogen peroxide in the working solution and recorded.

[0072] It should be noted that in the room temperature stacking stage of the flat-width cold pad-batch pretreatment process, the flat-width fabric impregnated with the working solution is rolled up, wrapped with a sealing film, and placed in a static stacking environment at room temperature. The purpose of this stage is to utilize the alkaline and humid environment maintained within the sealed system under mild conditions without external heating, allowing the hydrogen peroxide and auxiliary chemicals in the working solution to continuously oxidize, saponify, and swell with natural impurities on the fiber (such as pectin, waxes, and cottonseed hulls). This ensures a complete reaction, effectively degrading non-woven impurities and improving the fiber's hydrophilicity. Specifically, the stacking process relies on the self-decomposition reaction of hydrogen peroxide under alkaline conditions. The trace amounts of heat and moisture generated inside the sealing film create a stable reaction microclimate, preventing the volatilization of effective components or heat loss. This ensures that the chemical agents react uniformly and controllably with the fiber over a longer reaction time, resulting in a stable and uniform pretreatment effect.

[0073] It should be noted that the room temperature stacking process must be carried out in a closed environment. The purpose is to build a relatively closed and stable reaction system to prevent the working liquid on the fabric from evaporating, drying out, or migrating in concentration. This ensures that the chemical agents act on the fibers continuously and evenly under constant humidity and temperature conditions, thereby effectively avoiding uneven pretreatment effects and quality defects such as sizing spots caused by local water loss or insufficient reaction. It also ensures that components such as hydrogen peroxide can be decomposed in a controlled manner under mild conditions without external airflow interference.

[0074] It should be noted that, in order to remotely, continuously, and non-contactly monitor the stacking reaction process without damaging the sealed environment or coming into contact with chemical agents, thereby identifying abnormal decomposition of hydrogen peroxide and dynamically adjusting the stacking time, this invention attaches a flexible temperature sensor array, a gas pressure sensor array, and multiple near-infrared probes to the inner and outer sides of the sealing film, respectively.

[0075] The flexible temperature and pressure sensor arrays employ a non-invasive mounting method, directly fixing them to the inner surface of the sealing film using medical-grade double-sided adhesive or a removable silicone adhesive layer. This eliminates the need for puncturing or cutting the film or introducing any through-hole structures, enabling real-time acquisition of internal temperature and pressure data without compromising the seal integrity or allowing the sensors to remain in direct contact with the working fluid. Each sensor has a built-in wireless transmission module, transmitting the collected temperature and pressure data in real-time to an external data receiving terminal via wireless communication protocols such as Bluetooth, ZigBee, or RFID. This eliminates the need for openings in the sealing film to allow cables to exit, further ensuring the long-term integrity of the sealing system. In one specific installation embodiment, multiple flexible temperature and pressure sensors are evenly distributed in a grid pattern inside the sealing film at predetermined spatial intervals. Each sensor is self-powered by a button cell battery or flexible film battery, continuously acquiring data during the stacking period and transmitting it wirelessly to the data terminal. The function of the aforementioned sensor array is as follows: the decomposition reaction of hydrogen peroxide under alkaline conditions is accompanied by regular changes in system temperature and pressure. By continuously collecting temperature and pressure data, characteristic parameters of the reaction process can be extracted, such as heating rate, pressure rise rate and their fluctuation characteristics, which can then be used to determine whether there is abnormal decomposition, such as local overheating, decomposition that is too fast or too slow.

[0076] Furthermore, multiple near-infrared probes also employ a non-contact mounting method, meaning they are attached to the outer surface of the sealing film. They detect the interior of the sealed space using transmission or reflection near-infrared spectroscopy, without needing to penetrate the film or come into contact with the working fluid, thus maintaining the integrity of the sealing system. As a specific installation embodiment, multiple near-infrared probes are arranged at equal intervals along the axial direction of the rolled fabric on the outer side of the sealing film, with the optical window of each probe facing the inner side of the film. Optical coupling gel is filled between the probe and the film to reduce interface reflection loss. The probes are connected to a near-infrared spectrometer via optical fiber or signal lines to achieve online detection of hydrogen peroxide concentration. The function of this near-infrared probe is as follows: Based on the principle of near-infrared spectroscopy, by collecting the spectral absorption characteristics of the working fluid at a specific wavelength, the real-time concentration of hydrogen peroxide in the sealed system during the stacking process can be indirectly and non-destructively measured. This measured concentration is used, on the one hand, to verify and confirm the abnormal decomposition indicated by temperature and pressure data, and on the other hand, to calculate the relative deviation ratio of the reaction rate during the stable reaction period, thereby correcting the time point of entering the slow reaction period. It can also be used to calculate the hydrogen peroxide decomposition rate and capture the moment when the decomposition rate reaches the preset target value during the slow reaction period, thereby identifying the end point of the stacking reaction.

[0077] Step S2: Call the pre-calibrated stacking reaction benchmark under the same working conditions, including the hydrogen peroxide concentration change curve and the total stacking time. Based on the hydrogen peroxide decomposition rate change law, divide the current stacking reaction process into fast, stable and slow reaction periods in sequence.

[0078] In a preferred embodiment of the present invention, step S2 includes: Extract the pre-calibrated stacking reaction baselines under different working conditions from the database. The baselines include the hydrogen peroxide concentration change curve over time and the total stacking time.

[0079] The temperature and humidity of the current stacking environment are collected, and combined with the fabric type and working fluid formula, a pre-calibrated stacking reaction benchmark under the same working conditions is selected to predict the hydrogen peroxide concentration change curve over time and the total stacking time of the current stacking reaction.

[0080] Based on the hydrogen peroxide concentration versus time curve, the hydrogen peroxide decomposition rate is calculated point by point, and a hydrogen peroxide decomposition rate versus time curve is generated, where the hydrogen peroxide decomposition rate is the ratio of the change in hydrogen peroxide concentration to the corresponding reaction time.

[0081] Calculate the absolute value of the slope of the tangent line at each point on the curve of hydrogen peroxide decomposition rate versus time, and obtain the rate of decrease of hydrogen peroxide decomposition rate at each point. Based on this rate of decrease, divide the curve into steeply decreasing segment, gently decreasing segment and horizontal segment in sequence.

[0082] The time periods corresponding to the steep descent, gradual descent, and horizontal phases are respectively defined as the rapid reaction period, stable reaction period, and slow reaction period in the current stacking reaction process.

[0083] In a preferred embodiment of the present invention, the method for pre-calibrating the stacked reaction baseline through experiments includes: By setting and adjusting the working parameters of room temperature stacking, a variety of different working conditions can be obtained. These working parameters include the type of fabric, the working fluid formula, and the temperature and humidity of the stacking environment.

[0084] Under each working condition, after the fabric rolls are sealed and stacked, samples are taken at designated locations on the fabric rolls at fixed time intervals, and the hydrogen peroxide concentration of each sample is measured. The time point of each sampling is recorded synchronously until the hydrogen peroxide decomposition rate measured at a certain sampling time point reaches the preset target value, thereby obtaining multiple sets of detection data on hydrogen peroxide concentration. The cumulative stacking time corresponding to the cessation of sampling and measurement is determined as the total stacking time under that working condition.

[0085] Plot the hydrogen peroxide concentration as time on the x-axis and the hydrogen peroxide concentration as the y-axis, and draw a curve showing the change of hydrogen peroxide concentration over time based on multiple sets of detection data.

[0086] By changing the fabric roll and the sampling location, the above steps are repeated to obtain multiple hydrogen peroxide concentration change curves over time and multiple total stacking times. Then, the final hydrogen peroxide concentration change curve over time and the total stacking time under this condition are determined, thereby constructing the stacking reaction benchmark under this condition.

[0087] The stacked reaction baselines under all operating conditions are compiled and stored in the database.

[0088] It should be noted that the method for obtaining the hydrogen peroxide decomposition rate measured at a certain sampling time point is as follows: subtract the initial concentration of hydrogen peroxide from the hydrogen peroxide concentration measured at the sampling time point, and the difference is the amount of decrease in hydrogen peroxide concentration; then calculate the ratio of the decrease in hydrogen peroxide concentration to the initial concentration of hydrogen peroxide, and the ratio is the hydrogen peroxide decomposition rate corresponding to that sampling time point.

[0089] It should be noted that if the hydrogen peroxide decomposition rate is too low, the effective active ingredients in the working solution will not be able to fully act on the fiber impurities, resulting in insufficient whiteness of the pretreated fabric. Conversely, if the hydrogen peroxide decomposition rate is too high, not only will the subsequent short steaming process lose its synergistic effect due to the low residual hydrogen peroxide content, but it may also damage the fibers due to excessive oxidation. Therefore, the hydrogen peroxide decomposition rate needs to be controlled within a reasonable range to balance the pretreatment effect and fiber safety. As a specific example, for conventional cotton knitted fabrics, the target value for the hydrogen peroxide decomposition rate can be set at 85%–95%, preferably 90%. For fabrics with high impurity content or a tight structure, it can be appropriately increased to 88%–95%, while for lightweight fabrics or fabrics with lower pretreatment requirements, it can be decreased to 80%–88%. In addition, the target value is dynamically adapted according to the actual needs of the fabric type, working solution formula and subsequent short steaming process: if the measured decomposition rate at the end of the stacking is low and the whiteness of the fabric does not meet the requirements, the target value of the decomposition rate is appropriately increased and the stacking time is extended; if the decomposition rate is high and the subsequent short steaming process affects the overall treatment effect due to insufficient hydrogen peroxide residue, or there are signs of decreased fiber strength, the target value of the decomposition rate is appropriately reduced and the stacking is terminated in advance.

[0090] It should be noted that the specific method for determining the final hydrogen peroxide concentration versus time curve under the operating conditions, based on multiple hydrogen peroxide concentration versus time curves, is as follows: Multiple hydrogen peroxide concentration-time variation curves were fitted. Specifically, with time as the x-axis and hydrogen peroxide concentration as the y-axis, the hydrogen peroxide concentration values ​​corresponding to the same time point on each curve were summarized, and the arithmetic mean or median of the concentration values ​​at each time point was calculated as the representative concentration value at that time point. Subsequently, the least squares method or local weighted regression method was used to fit the representative concentration values ​​at each time point to obtain a smooth characteristic curve that can reflect the overall trend of concentration change. This characteristic curve was determined as the final hydrogen peroxide concentration-time variation curve under this operating condition.

[0091] It should be noted that the specific method for determining the final total stacking time under the operating condition based on multiple values ​​of the total stacking time is as follows: Based on the multiple values ​​of the total stacking time obtained, the numerical range of the total stacking time is obtained; the numerical range is divided into multiple consecutive numerical intervals according to the principle of equal gradient; the number of numerical points falling into each numerical interval is counted, and the ratio of the number of numerical points to the total number of numerical points is calculated. This ratio is used as the confidence weight of the numerical interval; the median of each numerical interval is taken, and combined with the confidence weight of each interval, the final total stacking time under this working condition is calculated through linear weighted fusion analysis.

[0092] It should be noted that the specific method for screening items under the same working conditions is as follows: Obtain the operating parameters of the current room temperature stack and query the database to see if there is an operating condition record that is completely consistent with the current operating parameters.

[0093] If the query is successful, the record for that operating condition will be identified as the same operating condition.

[0094] If the query fails, the current working condition parameters are compared with the working condition parameters of each working condition stored in the database one by one. The matching degree of the current working condition parameters with each working condition in the database on each working condition parameter item is calculated. The matching degrees of each parameter item are accumulated to obtain the overall similarity between each working condition in the database and the current working condition. The working condition in the database with the highest similarity is taken as the same working condition.

[0095] The specific method for obtaining the matching degree of various working condition parameters is as follows: When the operating condition parameter is a numerical parameter, the relative deviation between the current operating condition parameter value and the operating condition parameter value in the library is calculated, and the matching degree of the operating condition parameter is determined according to the preset mapping relationship between the relative deviation and the matching degree.

[0096] When the operating condition parameter is a non-numerical parameter, according to the preset assignment rules, if the current operating condition parameter is the same as the operating condition parameter in the library, a first matching degree fixed value is assigned; if they are different, a second matching degree fixed value is assigned, thereby determining the matching degree of the operating condition parameter.

[0097] In a preferred embodiment of the present invention, the method for dividing the curve based on the rate of decrease of the hydrogen peroxide decomposition rate includes: Starting from the first data point on the curve of hydrogen peroxide decomposition rate versus time, identify data points where the rate of decrease in hydrogen peroxide decomposition rate falls within the range of the rate of decrease corresponding to the preset steep descent segment. The continuous curve segment formed by the data points that meet this condition is defined as the steep descent segment, and the end point of the steep descent segment is recorded as the inflection point between the steep descent segment and the gradual descent segment.

[0098] Starting from the inflection point between the steep descent segment and the gradual descent segment, identify data points whose rate of hydrogen peroxide decomposition falls within the descent rate range corresponding to the preset gradual descent segment. The continuous curve segment formed by the data points that meet this condition is determined as the gradual descent segment, and the end point of the gradual descent segment is recorded as the inflection point between the gradual descent segment and the horizontal segment.

[0099] The remaining curve segment after the inflection point between the descent segment and the horizontal segment is defined as the horizontal segment.

[0100] It should be noted that the decomposition reaction of hydrogen peroxide during room temperature stacking exhibits inherent kinetic laws. The hydrogen peroxide concentration versus time curve generally shows a decreasing trend of rapid initial decrease followed by a gradual slowdown; correspondingly, the hydrogen peroxide decomposition rate versus time curve shows a gradual decay from a relatively high initial value. Furthermore, the decay of the decomposition rate is not uniform; its rate of decay (i.e., the absolute value of the slope of the tangent line to the rate curve) exhibits a phased characteristic from fast to slow: in the initial stage of the reaction, the hydrogen peroxide concentration is high and effective collisions are frequent, resulting in a rapid decrease in the decomposition rate; as the reaction proceeds, the concentration decreases and byproducts accumulate, gradually slowing the rate of decay; in the later stage of the reaction, the system tends towards equilibrium, and the rate of decay approaches zero.

[0101] Based on the above characteristics, this invention uses the rate of decrease in decomposition rate as the dividing criterion: the stage where the rate of decrease falls into the preset steep decrease range is defined as the steep decrease range, corresponding to the rapid reaction period, where hydrogen peroxide rapidly decomposes and effectively acts on fiber impurities; the stage where the rate of decrease falls into the preset slow decrease range is defined as the slow decrease range, corresponding to the stable reaction period, where the decomposition reaction tends to slow down but still continues; the stage where the rate of decrease approaches zero and the curve is basically horizontal is defined as the horizontal range, corresponding to the slow reaction period, where the decomposition reaction is nearing completion. Through the above division method, the staged identification and refined control of the stacking reaction process can be achieved.

[0102] It should be noted that the range of decreasing rates corresponding to the steep descent phase and the range of decreasing rates corresponding to the gradual descent phase are defined based on the fact that the absolute value of the slope of the tangent line of the hydrogen peroxide decomposition rate versus time curve (i.e., the decreasing rate) can quantitatively characterize the rate of decay of the decomposition reaction. Through statistical analysis of a large amount of pre-calibration experimental data under the same operating conditions, the typical distribution range of decreasing rates at different reaction stages can be determined. Specifically, during the rapid reaction phase, the hydrogen peroxide concentration is high, the decomposition reaction is intense, the decomposition rate decreases rapidly, and the absolute value of its tangent line slope is usually large; as the reaction enters the steady phase, the rate of decrease in decomposition slows down significantly; in the slow reaction phase, the decomposition rate tends to stabilize, and the decreasing rate approaches zero. As a specific example, for the room temperature stacking process of conventional cotton knitted fabrics, when the rate of hydrogen peroxide decomposition decreases by more than or equal to 0.15 percentage points per minute (i.e., the decomposition rate decreases by more than 0.15% per minute), the interval into which it falls is set as the rate of decrease corresponding to the steep descent segment; when the rate of decrease is between 0.02 percentage points per minute and 0.15 percentage points per minute, it is set as the rate of decrease corresponding to the slow descent segment; when the rate of decrease is less than 0.02 percentage points per minute, it is determined to enter the horizontal segment.

[0103] It should be noted that, to facilitate a more intuitive understanding of the stage division logic of this invention, a specific example is provided below. Taking the stacking treatment of conventional cotton knitted fabrics at room temperature (stacking environment temperature 25±2℃, relative humidity 65±5%) using a standard working solution (initial hydrogen peroxide concentration 8-10g / L, pH value 10.5-11.0) as an example, the stages of the stacking reaction process are divided as follows: The rapid reaction period corresponds to a time range of 0 to 4 hours. During this period, the hydrogen peroxide decomposition rate is high and decreases rapidly. The curve of the hydrogen peroxide decomposition rate over time shows a steep slope. The decomposition rate drops rapidly from the highest point, indicating a vigorous reaction and full interaction between the chemical reagents and fiber impurities. The end point of this stage (i.e., at 4 hours) is the inflection point where the rate begins to slow down significantly, marking the transition from the rapid reaction period to the stable reaction period.

[0104] The steady reaction period corresponds to a time range of 4 to 12 hours. During this period, the decomposition rate of hydrogen peroxide decreases slowly, and the curve of the hydrogen peroxide decomposition rate over time shows a gentle slope. The reaction tends to slow down but still continues. The end point of this stage (i.e., at 12 hours) is the inflection point where the rate drops to a very low level, marking the transition from the steady reaction period to the slow reaction period.

[0105] The slow reaction period corresponds to a time range of 12 to 24 hours. During this period, the hydrogen peroxide decomposition rate tends to stabilize and is at an extremely low level. The curve of the hydrogen peroxide decomposition rate over time shows a basically horizontal shape (flat slope), indicating that the reaction is nearing completion. When the plant is piled up for about 24 hours, the decomposition rate has almost stopped. Whether to terminate the piling can be determined by whether the hydrogen peroxide decomposition rate has reached the preset target value.

[0106] It should be understood that the above time range and inflection point values ​​(4 hours and 12 hours) are exemplary data for this specific working condition. In actual applications, they can be adjusted accordingly based on the type of fabric, the formula of the working fluid, and the temperature and humidity of the stacking environment, but this does not affect the stage division logic of the present invention.

[0107] Step S3: During the rapid reaction period, determine whether the hydrogen peroxide decomposition is abnormal based on the temperature and pressure data in the sealed space. If not, proceed to S4. If yes, retest the abnormality using the hydrogen peroxide concentration measured by infrared spectroscopy. If the abnormality is confirmed, suspend the stacking and report the type of abnormal decomposition. If the abnormality is not confirmed, proceed to S4.

[0108] In a preferred embodiment of the present invention, the method for anomaly detection and re-verification in step S3 includes: S31. During the rapid response period, multiple monitoring time points are set according to the first time interval.

[0109] Acquire the temperature data of each node in the temperature sensor array and the air pressure data of each node in the air pressure sensor array within the sealed space at the current time point.

[0110] Calculate the heating rate of each temperature sensor node and the pressure rise rate of each pressure sensor node, and construct heating rate sequence and pressure rise rate sequence respectively.

[0111] S32. Based on the temperature and pressure data during the rapid reaction period of the stacked reaction under the same historical operating conditions, determine the reference range of the heating rate and pressure rise rate at the current time point.

[0112] S33. If an abnormal value exceeding the corresponding reference range appears in the heating rate sequence or pressure rise rate sequence at the current time point, and the magnitude of the abnormal value exceeding the reference range is greater than the preset over-threshold, then it is determined that there is an abnormality in the decomposition of hydrogen peroxide, and S34 is executed.

[0113] Otherwise, if there is no abnormality, execute S35.

[0114] S34. Trigger multiple near-infrared probes to collect the spectrum of the working fluid on the fabric roll surface, measure the hydrogen peroxide concentration by infrared spectroscopy, and record the collection time.

[0115] Based on the stacking reaction baseline, the baseline value of hydrogen peroxide concentration corresponding to this collection time is extracted.

[0116] The hydrogen peroxide concentration measured by each near-infrared probe is compared with the benchmark value. If the deviation between the measured value and the benchmark value of hydrogen peroxide concentration is greater than the preset deviation threshold, and the number of near-infrared probes that meet the deviation condition reaches the preset number threshold, then an anomaly is confirmed and stacking is suspended.

[0117] Otherwise, it will be considered an unconfirmed anomaly and proceed to S35.

[0118] S35. Continue monitoring the hydrogen peroxide decomposition status at the next time point until the rapid reaction period ends.

[0119] It should be noted that, due to the vigorous decomposition of hydrogen peroxide during the rapid reaction period, the concentration and parameters such as temperature and pressure change rapidly. Therefore, to promptly detect abnormal decomposition signs, the monitoring time interval should be set relatively short. As a specific example, for the rapid reaction period (usually 0-4 hours after the start of stacking) of conventional cotton knitted fabrics in a room temperature stacking process, a monitoring time point can be set every 10-15 minutes, i.e., the interval between adjacent time points is 10-15 minutes. When the fabric has a high impurity content or the working solution is highly alkaline, the decomposition reaction is more active, and the time interval can be shortened to 5-10 minutes; while for relatively mild reaction conditions, it can be appropriately extended to 20-30 minutes. By setting the above time intervals, both monitoring sensitivity and data processing efficiency are ensured.

[0120] It should be noted that the reference ranges for heating rate and pressure rise rate were pre-calibrated using normal reaction data from the rapid reaction period during historical stacking reactions under the same operating conditions. Specifically, under the same fabric type, working fluid formulation, and ambient temperature and humidity conditions, stacking experiments were repeated multiple times, collecting temperature and pressure data at various time points during the rapid reaction period. The heating rate (i.e., the change in temperature per unit time) and pressure rise rate (i.e., the change in pressure per unit time) were calculated at each time point. Statistical analysis was performed on multiple sets of rate data at the same time point. After removing outliers, the mean and standard deviation were calculated. The interval formed by the mean ± k times the standard deviation (e.g., k=2 or 3) was determined as the reference range for the heating rate and pressure rise rate at that time point. For the interval values ​​between different time points, linear interpolation or curve fitting methods can be used to smooth the transition, thereby constructing a complete reference range curve.

[0121] It should be noted that the over-amplitude threshold is used to determine whether the abnormal value of the heating rate or pressure rise rate reaches a severity level that requires triggering a retest, distinguishing between normal fluctuations and significant anomalies. During a normal reaction, due to sensor measurement errors or local micro-environmental fluctuations, the monitoring data may slightly exceed the reference range, but such slight exceedances do not indicate substantial abnormal decomposition of hydrogen peroxide. Only when the exceedance exceeds a certain threshold does it indicate a potential risk of localized severe decomposition or runaway. As a specific value example, the over-amplitude threshold can be set to 20%–30% of the reference range width. For example, if the upper limit of the reference range is a certain value, and the exceedance exceeds 10% of that upper limit value, it is considered an over-amplitude. Furthermore, the over-amplitude threshold can be adaptively adjusted. If frequent retests are found in actual production but all are verified to be normal reactions, the over-amplitude threshold can be appropriately increased to avoid false alarms; conversely, if missed alarms occur, resulting in abnormal decomposition not being identified in time, the over-amplitude threshold can be appropriately decreased to improve sensitivity.

[0122] It should be noted that the specific process for calculating the hydrogen peroxide concentration based on the spectrum of the working fluid on the fabric roll surface is as follows: A quantitative relationship model between hydrogen peroxide concentration and near-infrared spectral characteristic absorption is established experimentally beforehand. Specifically, a series of hydrogen peroxide standard solutions of known concentrations are prepared, and the absorption spectra of each standard solution in the near-infrared band (e.g., wavelengths of 1100–1300 nm or 1400–1600 nm, with the characteristic absorption peak of the OH group in the hydrogen peroxide molecule located around 1420 nm) are collected under room temperature stacking conditions. The absorbance values ​​at the characteristic wavelengths are extracted, and a calibration model between absorbance and hydrogen peroxide concentration is established using partial least squares or multiple linear regression. During actual monitoring, multiple near-infrared probes are triggered to collect the spectrum of the working fluid on the fabric roll surface, obtaining the absorbance values ​​at the corresponding characteristic wavelengths. These values ​​are then substituted into the pre-established quantitative relationship model to calculate the real-time concentration of hydrogen peroxide in the sealed space at that moment.

[0123] It should be noted that the preset deviation threshold is used to determine whether the difference between the measured hydrogen peroxide concentration obtained by the near-infrared probe and the baseline value at the corresponding moment in the stacked reaction baseline reaches the level required to confirm abnormal decomposition. Under normal reaction conditions, a certain deviation between the measured value and the baseline value is permissible due to the microscopic non-uniformity of the working fluid distribution or random errors in spectral measurement; however, when the deviation is too large, it indicates that the hydrogen peroxide consumption rate in a local area deviates significantly from the normal level, and there is a possibility of abnormal decomposition. As a specific example, the deviation threshold can be set to ±15% to ±25% of the baseline value, for example, preferably ±20%. In addition, the deviation threshold can be dynamically adjusted. If the deviation exceeds the threshold in actual monitoring but no substantial abnormality is found in subsequent verification, the deviation threshold can be appropriately relaxed to reduce the false alarm rate; if abnormal decomposition fails to be identified in time, the deviation threshold can be appropriately tightened to improve monitoring sensitivity.

[0124] It should be noted that the preset quantity threshold is used to confirm the authenticity of abnormal decomposition and avoid false alarms triggered by occasional measurement errors of individual near-infrared probes. Since the distribution of working fluid at different locations along the fabric roll axis may have slight differences, the concentration deviation measured by a single probe may not be representative; only when multiple probes distributed along the axis detect significant deviations is it sufficient to prove the existence of a genuine abnormal decomposition, either locally or globally. As a specific example, when the total number of near-infrared probes is 5 to 7, the quantity threshold can be set to 3 to 4, meaning that at least 3 or 4 probes simultaneously detect deviations exceeding the deviation threshold before an anomaly is confirmed. Furthermore, the quantity threshold can be adaptively adjusted. If false alarms from individual probes occur frequently during production, but multiple probes fail to confirm the anomaly, the quantity threshold can be appropriately increased to reduce the frequency of erroneous shutdowns; conversely, if abnormal decomposition is detected but not confirmed in a timely manner, the quantity threshold can be appropriately decreased to improve the overall sensitivity of anomaly identification.

[0125] In a preferred embodiment of the present invention, the method for obtaining the abnormal decomposition type in step S3 includes: If the abnormal values ​​in the heating rate sequence or pressure rise rate sequence exceed the upper limit of the corresponding reference range, and the measured value of hydrogen peroxide concentration is lower than the benchmark value, then the abnormal decomposition type is determined to be decomposition too fast.

[0126] If the abnormal value in the heating rate sequence or pressure rise rate sequence is lower than the lower limit of the corresponding reference range, and the measured value of hydrogen peroxide concentration is higher than the benchmark value, then the abnormal decomposition type is determined to be decomposition too slow.

[0127] It should be noted that in actual production applications, there is a possibility that different axial or radial positions of the same fabric roll may simultaneously exhibit localized characteristics of excessively rapid and excessively slow decomposition. The main reasons for this include: differences in the liquid content of the fabric roll caused by uneven roller pressure, temperature gradients formed by different radial heat dissipation conditions of the fabric roll, changes in the reaction environment caused by incomplete sealing of the sealing film, and the inherent dispersion of the detection results from different position sensors.

[0128] To address the situation where two types of abnormal manifestations coexist, the present invention employs the following processing strategy: First, calculate the deviation distribution between the measured hydrogen peroxide concentration values ​​obtained by all near-infrared probes and the corresponding benchmark values ​​in the stacked reaction baseline, and then statistically analyze the proportions of regions exhibiting characteristics of excessively fast decomposition and excessively slow decomposition. If the proportion of a certain type of region (excessively fast decomposition or excessively slow decomposition) exceeds a preset region proportion threshold (as a specific example, this threshold can be set to 60%), then this type is determined as an overall anomaly.

[0129] If the proportions of the two types of areas are roughly equal and it is difficult to determine the main cause, then considering that excessively rapid decomposition may lead to irreversible fiber damage, while excessively slow decomposition can be compensated for by subsequent short steaming processes, the abnormal handling logic should be executed first according to the type of excessively rapid decomposition, that is, the stacking should be suspended and retested to ensure the safety of fiber quality to the greatest extent.

[0130] Step S4: Obtain the measured hydrogen peroxide concentration change curve during the stable reaction period, and compare it with the corresponding curve segment in the benchmark to evaluate the relative deviation ratio of the reaction rate, and correct the time point for entering the slow reaction period accordingly.

[0131] In a preferred embodiment of the present invention, step S4 includes: S41. During the stable reaction period, set several monitoring time points according to the second time interval, obtain the hydrogen peroxide concentration measured by each near-infrared probe at each monitoring time point, and plot the measured hydrogen peroxide concentration change curve during the stable reaction period accordingly.

[0132] S42. Extract the curve segment corresponding to the stable reaction period from the pile reaction baseline as the baseline hydrogen peroxide concentration change curve.

[0133] S43. Calculate the degree of agreement between the measured concentration change curve and the reference concentration change curve.

[0134] If the degree of agreement reaches the preset threshold, there is no need to adjust the time point for entering the slow reaction period.

[0135] Otherwise, corrections are required, and S44 should be executed.

[0136] S44. Take the first derivative of the measured concentration change curve and the reference concentration change curve to obtain the measured decomposition rate change curve and the reference decomposition rate change curve, and align the two in time sequence.

[0137] S45. Obtain the cumulative area of ​​the region enclosed by the curve segments located above and below the reference rate curve in the measured rate curve, and further calculate the ratio of the cumulative area of ​​the upper region to the cumulative area of ​​the lower region to obtain the relative deviation ratio of the reaction rate.

[0138] S46. Based on the relative deviation ratio, determine the correction direction and correction duration for the time point entering the slow reaction period: If the relative deviation ratio is greater than 1, it indicates that the measured rate is greater than the reference rate. The time point for entering the slow reaction period needs to be advanced, and the advance delay time should be calculated: subtract 1 from the relative deviation ratio and multiply the difference by the total duration of the original steady reaction period.

[0139] If the relative deviation ratio is less than 1, it indicates that the measured rate is less than the reference rate. The time point for entering the slow reaction period needs to be delayed, and the delay time is calculated: subtract the difference between 1 and the relative deviation ratio, and multiply it by the total duration of the original steady reaction period.

[0140] It should be noted that, because the hydrogen peroxide decomposition reaction tends to be slower during the stable reaction period, and the rate of concentration change is significantly lower than during the rapid reaction period, the monitoring interval can be appropriately extended to reduce the burden of data acquisition and processing, while avoiding redundant data due to excessive sampling. As a specific example, for the stable reaction period (usually 4–12 hours after the start of stacking) of conventional cotton knitted fabrics in a room temperature stacking process, the monitoring interval can be set to 30–60 minutes, preferably 45 minutes. In contrast, the monitoring interval during the rapid reaction period (0–4 hours) is typically 10–15 minutes, and the interval during the stable reaction period is approximately 3–5 times longer than that during the rapid reaction period. By setting the time intervals differently in each stage, data acquisition efficiency is optimized while ensuring monitoring accuracy.

[0141] It should be noted that the specific method for obtaining the measured hydrogen peroxide concentration change curves during the stable reaction period is as follows: Based on the hydrogen peroxide concentration data measured by each near-infrared probe at each monitoring time point, multiple curves showing the change of measured hydrogen peroxide concentration over time are plotted. Then, each curve is fitted (e.g., using local weighted regression or spline interpolation) to eliminate local measurement noise and spatial distribution differences. Finally, the characteristic curve obtained after fitting is determined as the measured hydrogen peroxide concentration change curve during the stable reaction period. Through the above processing, the representativeness and stability of the measured curves can be effectively improved, providing a reliable basis for subsequent comparison and analysis with the benchmark curve.

[0142] It should be noted that the consistency threshold is used to determine the degree of consistency between the measured hydrogen peroxide concentration change curve and the benchmark hydrogen peroxide concentration change curve during the stable reaction period, thereby determining whether the time point for entering the slow reaction period needs to be corrected. When the two curves are highly consistent, it indicates that the current stacking reaction process is basically consistent with the pre-calibrated benchmark reaction process, and no adjustment of the time points of subsequent stages is required; conversely, when the two curves deviate significantly, it indicates that there is a systematic deviation in the current reaction rate, which needs to be compensated for through time point correction. As a specific value example, when the correlation coefficient is used as the consistency index, the consistency threshold can be set to 0.85, that is, when the correlation coefficient between the measured curve and the benchmark curve is greater than or equal to 0.85, the consistency is considered to be up to standard and no correction is required; when the correlation coefficient is lower than 0.85, the consistency is considered insufficient and correction is required.

[0143] It should be noted that this invention chooses to correct the decomposition rate during the stable reaction period, rather than based on the rapid reaction period or a combination of both stages. This is primarily based on the following considerations: During the rapid reaction period, the decomposition rate fluctuates significantly, influenced by factors such as initial liquid content and coil tightness, resulting in poor data stability. Furthermore, this stage is short, with a limited control window, making precise correction difficult. In contrast, the stable reaction period lasts longer, with a gradual change in the decomposition rate. The measured data exhibits good stability and repeatability, more accurately reflecting the systematic deviation between the current reaction and the baseline. Completing the correction during this stage allows for sufficient adjustment space for determining the endpoint of the slow reaction period. If correction is performed using data from both stages, the data fluctuations during the rapid reaction period dilute the systematic deviation reflected in the stable reaction period, thus reducing the accuracy of the correction. In summary, correction based on a single stage of the stable reaction period offers technical advantages such as good data stability, a sufficient control window, a simple calculation model, and strong engineering adaptability.

[0144] It should be noted that when correcting the decomposition rate from the steady reaction period to the point where the slow reaction period begins, the temperature and pressure sensor data are checked again before the correction. If the data is normal, the time point correction is performed; if the data is abnormal, the stacking is paused and an alarm is issued.

[0145] Step S5: After entering the slow reaction period, capture the moment when the hydrogen peroxide decomposition rate reaches the preset target value and take it as the end point of the stacking reaction, end the stacking and proceed to the next process.

[0146] In a preferred embodiment of the present invention, step S5 includes: After entering the slow reaction period, the hydrogen peroxide concentration is continuously monitored at preset time intervals, and the current hydrogen peroxide decomposition rate is calculated in combination with the initial hydrogen peroxide concentration.

[0147] Once the hydrogen peroxide decomposition rate calculated at a certain monitoring time point reaches the preset target value, that time point is determined as the end point of the stacking reaction, the stacking ends, and the process proceeds to the next step.

[0148] It should be noted that after entering the slow reaction period, the hydrogen peroxide decomposition reaction is nearly complete, and the decomposition rate is at an extremely low level and changes slowly. Therefore, the monitoring interval can be further extended based on the stable reaction period to minimize the data acquisition and processing load while ensuring accurate capture of the decomposition rate reaching the preset target value. As a specific example, for the slow reaction period (usually 12–24 hours after the start of stacking) of conventional cotton knitted fabrics in a room temperature stacking process, the monitoring interval can be set to 60–120 minutes, preferably 90 minutes. Compared with the fast reaction period (10–15 minutes) and the stable reaction period (30–60 minutes), the time interval of the slow reaction period shows a differentiated configuration with progressively increasing intervals.

[0149] It should be noted that, in another specific embodiment, the monitoring time interval during the slow reaction period can be dynamically adjusted in addition to the aforementioned fixed setting. Specifically, as the stacking reaction progresses and the rate of change of hydrogen peroxide decomposition gradually slows down, in order to more accurately capture the moment when the decomposition rate reaches the preset target value, the monitoring time interval should be reduced accordingly. That is, the sampling frequency should be increased as the decomposition rate approaches the target value to reduce the risk of missing the endpoint due to sparse sampling.

[0150] In this embodiment, the present invention constructs a stacking reaction benchmark library under multiple working conditions and matches it with the current working condition parameters, so that the control strategy can adapt to changes in fabric type, working solution formula and ambient temperature and humidity, effectively avoiding quality defects caused by local water loss, uneven reaction or poor sealing, and significantly improving the stability and batch consistency of the pretreatment effect.

[0151] See Figure 2 As shown, the second aspect of the present invention provides an automated control system for continuous processing of knitted fabrics, including an initial data acquisition module, a reaction stage division module, an anomaly detection and verification module, a stage switching correction module, and an endpoint determination and termination module.

[0152] The reaction stage division module is connected to the initial data acquisition module and the anomaly detection and verification module, respectively, and the stage switching correction module is connected to the anomaly detection and verification module and the endpoint determination and termination module, respectively.

[0153] The initial data acquisition module is used to roll and seal the fabric after impregnation with the working fluid. Flexible temperature and pressure sensors and near-infrared probes are attached to the inside and outside of the sealing film, respectively, and the initial concentration of hydrogen peroxide in the working fluid is recorded.

[0154] The reaction stage division module is used to call the pre-calibrated stacking reaction benchmark under the same working conditions, including the hydrogen peroxide concentration change curve and the total stacking time. Based on the change law of hydrogen peroxide decomposition rate, the current stacking reaction process is divided into fast, stable and slow reaction periods in sequence.

[0155] The anomaly detection and retest module is used to determine whether the hydrogen peroxide decomposition is abnormal during the rapid reaction period based on the temperature and pressure data in the sealed space. If not, the phase switching correction module is executed. If so, the anomaly is retested using the hydrogen peroxide concentration measured by infrared spectroscopy. If an anomaly is confirmed, the stacking is paused and the type of abnormal decomposition is reported. If no anomaly is confirmed, the process is switched to the phase switching correction module.

[0156] The phase switching correction module is used to obtain the measured hydrogen peroxide concentration change curve during the stable reaction period, compare it with the corresponding curve segment in the benchmark to evaluate the relative deviation ratio of the reaction rate, and correct the time point for entering the slow reaction period accordingly.

[0157] The endpoint determination and termination module is used to capture the moment when the hydrogen peroxide decomposition rate reaches the preset target value after entering the slow reaction period and use it as the endpoint of the stacking reaction, ending the stacking and entering the next process.

[0158] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0159] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. The focus of each embodiment is on its differences from other embodiments. In particular, the apparatus embodiments are described simply because they are fundamentally based on the method embodiments; relevant details can be found in the descriptions of the method embodiments.

[0160] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0161] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0162] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0163] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0164] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0165] Secondly, the accompanying drawings of the embodiments disclosed in this invention only involve structures related to the embodiments disclosed in this invention. Other structures can refer to general designs. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other.

[0166] Finally, the above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An automated control method for continuous processing of knitted fabrics, characterized in that, Includes the following steps: S1. Roll up and seal the fabric after impregnation with the working fluid. Install flexible temperature and pressure sensors and near-infrared probes on the inside and outside of the sealing film, respectively, and record the initial concentration of hydrogen peroxide in the working fluid. S2. Call the pre-calibrated stacking reaction benchmark under the same working conditions, including the hydrogen peroxide concentration change curve and the total stacking time. According to the hydrogen peroxide decomposition rate change law, divide the current stacking reaction process into fast, stable and slow reaction periods in sequence. S3. During the rapid reaction period, determine whether the hydrogen peroxide decomposition is abnormal based on the temperature and pressure data in the sealed space. If not, proceed to S4. If yes, retest the abnormality by measuring the hydrogen peroxide concentration using infrared spectroscopy. If the abnormality is confirmed, suspend the stacking and report the type of abnormal decomposition. If the abnormality is not confirmed, proceed to S4. S4. Obtain the measured hydrogen peroxide concentration change curve during the stable reaction period, and compare it with the corresponding curve segment in the benchmark to evaluate the relative deviation of the reaction rate, and correct the time point of entering the slow reaction period accordingly. S5. After entering the slow reaction period, capture the moment when the hydrogen peroxide decomposition rate reaches the preset target value and take it as the end point of the stacking reaction, end the stacking and enter the next process.

2. The automated control method for continuous processing of knitted fabrics according to claim 1, characterized in that, Step S1 includes: The knitted fabric after being impregnated with the working fluid is flattened and rolled up, and then wrapped with a sealing film. A flexible temperature sensor array and a pressure sensor array are attached to the inside of the sealing film, and multiple near-infrared probes are attached to the outside of the sealing film. The working solution was sampled multiple times, and the hydrogen peroxide concentration in each sample was measured. The average value of the multiple measurements was taken as the initial concentration of hydrogen peroxide in the working solution and recorded.

3. The automated control method for continuous processing of knitted fabrics according to claim 1, characterized in that, Step S2 includes: Extract the pre-calibrated stacking reaction baselines under different working conditions from the database. The baselines include the hydrogen peroxide concentration change curve over time and the total stacking time. The temperature and humidity of the current stacking environment are collected, and combined with the fabric type and working fluid formula, the pre-calibrated stacking reaction benchmark under the same working conditions is screened to predict the hydrogen peroxide concentration change curve over time and the total stacking time of the current stacking reaction. Based on the hydrogen peroxide concentration change curve over time, the hydrogen peroxide decomposition rate is calculated point by point, and the hydrogen peroxide decomposition rate change curve over time is generated. The hydrogen peroxide decomposition rate is the ratio of the change in hydrogen peroxide concentration to the corresponding reaction time. Calculate the absolute value of the slope of the tangent line at each point on the curve of hydrogen peroxide decomposition rate versus time, and obtain the rate of decrease of hydrogen peroxide decomposition rate at each point. Based on the rate of decrease, divide the curve into steeply decreasing segment, gently decreasing segment and horizontal segment in sequence. The time periods corresponding to the steep descent, gradual descent, and horizontal phases are respectively defined as the rapid reaction period, stable reaction period, and slow reaction period in the current stacking reaction process.

4. The automated control method for continuous processing of knitted fabrics according to claim 3, characterized in that, Methods for pre-calibrating the stacked reaction baseline through experiments include: By setting and adjusting the working parameters of room temperature stacking, a variety of different working conditions can be obtained. These working parameters include the type of greige fabric, the formula of the working fluid, and the temperature and humidity of the stacking environment. Under each working condition, after the fabric rolls are sealed and stacked, samples are taken at designated locations on the fabric rolls at fixed time intervals, and the hydrogen peroxide concentration of each sample is measured. The time point of each sampling is recorded synchronously until the hydrogen peroxide decomposition rate measured at a certain sampling time point reaches the preset target value, thereby obtaining multiple sets of detection data on hydrogen peroxide concentration. The cumulative stacking time corresponding to the time when sampling and measurement stop is determined as the total stacking time under that working condition. Plot the hydrogen peroxide concentration as time on the x-axis and hydrogen peroxide concentration on the y-axis, and draw a curve of hydrogen peroxide concentration versus time based on multiple sets of detection data. By changing the cloth roll and the sampling position, the above steps were repeated to obtain multiple hydrogen peroxide concentration change curves over time and multiple total stacking time values. Then, the final hydrogen peroxide concentration change curve over time and total stacking time under this working condition were determined, thereby constructing the stacking reaction benchmark under this working condition. The stacked reaction baselines under all operating conditions are compiled and stored in the database.

5. The automated control method for continuous processing of knitted fabrics according to claim 3, characterized in that, Methods for dividing curves based on the rate of decrease in the hydrogen peroxide decomposition rate include: Starting from the first data point of the hydrogen peroxide decomposition rate versus time curve, identify data points where the rate of decrease of hydrogen peroxide decomposition rate falls within the range of the rate of decrease corresponding to the preset steep drop segment. The continuous curve segment formed by the data points that meet this condition is defined as the steep drop segment, and the end point of the steep drop segment is recorded as the inflection point between the steep drop segment and the gradual drop segment. Starting from the inflection point between the steep descent section and the gradual descent section, identify data points whose rate of decrease in hydrogen peroxide decomposition falls within the range of the rate of decrease corresponding to the preset gradual descent section. The continuous curve segment formed by the data points that meet this condition is identified as the gradual descent section, and the end point of the gradual descent section is recorded as the inflection point between the gradual descent section and the horizontal section. The remaining curve segment after the inflection point between the descent segment and the horizontal segment is defined as the horizontal segment.

6. The automated control method for continuous processing of knitted fabrics according to claim 2, characterized in that, The methods for anomaly detection and re-verification in step S3 include: S31. Set multiple monitoring time points according to the first time interval during the rapid response period; Acquire the temperature data of each node in the temperature sensor array and the air pressure data of each node in the air pressure sensor array within the sealed space at the current time point; Calculate the heating rate of each temperature sensor node and the pressure rise rate of each pressure sensor node, and construct heating rate sequence and pressure rise rate sequence respectively; S32. Based on the temperature and pressure data during the rapid reaction period in the stacking reaction under the same historical operating conditions, determine the reference range of the heating rate and pressure rise rate at the current time point. S33. If an abnormal value exceeding the corresponding reference range appears in the heating rate sequence or pressure rise rate sequence at the current time point, and the magnitude of the abnormal value exceeding the reference range is greater than the preset over-threshold, then it is determined that there is an abnormality in the decomposition of hydrogen peroxide, and S34 is executed. Otherwise, determine that there is no abnormality and execute S35; S34. Trigger multiple near-infrared probes to collect the spectrum of the working fluid on the fabric roll surface, measure the hydrogen peroxide concentration by infrared spectroscopy, and record the collection time. Based on the pile reaction baseline, extract the baseline value of hydrogen peroxide concentration corresponding to the acquisition time; Compare the hydrogen peroxide concentration measured by each near-infrared probe with the benchmark value. If the deviation between the measured value of hydrogen peroxide concentration and the benchmark value is greater than the preset deviation threshold, and the number of near-infrared probes that meet the deviation condition reaches the preset number threshold, then an anomaly is confirmed and stacking is suspended. Otherwise, it will be considered an unconfirmed anomaly and proceed to S35; S35. Continue monitoring the hydrogen peroxide decomposition status at the next time point until the rapid reaction period ends.

7. The automated control method for continuous processing of knitted fabrics according to claim 6, characterized in that, The methods for obtaining the anomaly decomposition type in step S3 include: If the abnormal value in the heating rate sequence or pressure rise rate sequence exceeds the upper limit of the corresponding reference range, and the measured value of hydrogen peroxide concentration is lower than the benchmark value, then the abnormal decomposition type is determined to be decomposition too fast. If the abnormal value in the heating rate sequence or pressure rise rate sequence is lower than the lower limit of the corresponding reference range, and the measured value of hydrogen peroxide concentration is higher than the benchmark value, then the abnormal decomposition type is determined to be decomposition too slow.

8. The automated control method for continuous processing of knitted fabrics according to claim 1, characterized in that, Step S4 includes: S41. During the stable reaction period, set several monitoring time points according to the second time interval, obtain the hydrogen peroxide concentration measured by each near-infrared probe at each monitoring time point, and draw the measured hydrogen peroxide concentration change curve during the stable reaction period accordingly. S42. Extract the curve segment corresponding to the stable reaction period from the pile reaction baseline as the baseline hydrogen peroxide concentration change curve; S43. Calculate the degree of agreement between the measured concentration change curve and the reference concentration change curve; If the degree of agreement reaches the preset threshold, there is no need to adjust the time point for entering the slow reaction period; Otherwise, corrections are required, and S44 should be executed; S44. Take the first derivative of the measured concentration change curve and the reference concentration change curve to obtain the measured decomposition rate change curve and the reference decomposition rate change curve, and align the two in time sequence. S45. Obtain the cumulative area of ​​the region enclosed by the curve segments located above and below the reference rate curve in the measured rate curve, and further calculate the ratio of the cumulative area of ​​the upper region to the cumulative area of ​​the lower region to obtain the relative deviation ratio of the reaction rate. S46. Based on the relative deviation ratio, determine the correction direction and correction duration for the time point entering the slow reaction period: If the relative deviation ratio is greater than 1, it indicates that the measured rate is greater than the reference rate. The time point for entering the slow reaction period needs to be advanced, and the advance delay time should be calculated: multiply the difference obtained by subtracting 1 from the relative deviation ratio by the total duration of the original steady reaction period. If the relative deviation ratio is less than 1, it indicates that the measured rate is less than the reference rate. The time point for entering the slow reaction period needs to be delayed, and the delay time is calculated: subtract the difference between 1 and the relative deviation ratio, and multiply it by the total duration of the original steady reaction period.

9. The automated control method for continuous processing of knitted fabrics according to claim 1, characterized in that, Step S5 includes: After entering the slow reaction period, the hydrogen peroxide concentration is continuously monitored at preset time intervals, and the current hydrogen peroxide decomposition rate is calculated in combination with the initial hydrogen peroxide concentration. Once the hydrogen peroxide decomposition rate calculated at a certain monitoring time point reaches the preset target value, that time point is determined as the end point of the stacking reaction, the stacking ends, and the process proceeds to the next step.

10. An automated control system for continuous processing of knitted fabrics, characterized in that, include: Initial data acquisition module: The fabric after impregnation with working fluid is rolled and sealed. Flexible temperature and pressure sensors and near-infrared probes are attached to the inside and outside of the sealing film, respectively, and the initial concentration of hydrogen peroxide in the working fluid is recorded. Reaction stage division module: Calls the pre-calibrated stacking reaction benchmark under the same working conditions, including the hydrogen peroxide concentration change curve and the total stacking time. Based on the hydrogen peroxide decomposition rate change law, the current stacking reaction process is divided into fast, stable and slow reaction periods in sequence. Anomaly Detection and Re-verification Module: During the rapid reaction period, the module determines whether the hydrogen peroxide decomposition is abnormal based on the temperature and pressure data in the sealed space. If not, the module executes the stage switching correction module. If so, the module performs anomaly re-verification using the hydrogen peroxide concentration measured by infrared spectroscopy. If an anomaly is confirmed, the stacking is paused and the type of abnormal decomposition is reported. If an anomaly is not confirmed, the module switches to the stage switching correction module. Stage switching correction module: Obtain the measured hydrogen peroxide concentration change curve during the stable reaction period, compare it with the corresponding curve segment in the benchmark to evaluate the relative deviation of the reaction rate, and correct the time point for entering the slow reaction period accordingly. Endpoint determination and termination module: After entering the slow reaction period, the module captures the moment when the hydrogen peroxide decomposition rate reaches the preset target value and uses it as the end point of the stacking reaction, ending the stacking and proceeding to the next process.

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