A novel intelligent control method and system for an ink production process

Abstract

This application provides a novel intelligent control method and system for ink production processes. The method involves intelligent control of the ink production process by acquiring the operating power of the stirring motor, online viscometer readings, and the amount of gas entrained from the tank top. A physical correlation analysis is performed between the stirring motor operating power and the online viscometer readings to construct a conflict intensity index. When the conflict intensity index exceeds a threshold and the amount of gas entrained from the tank top is abnormal, the system can accurately determine that the online viscometer reading is malfunctioning due to bubble interference and immediately interrupt the original control strategy, initiating a preset interference suppression program. This application effectively solves the technical problem of erroneous control caused by bubble interference with online viscometer readings in existing water-based ink production processes, significantly improving the intelligence level of the production process and the consistency of product batches.

Description

Technical Field

[0001] This application relates to the field of intelligent control of ink production processes, and more specifically, to a novel intelligent control method and system for ink production processes. Background Technology

[0002] Currently, ensuring batch-to-batch consistency is a core objective for high-quality and high-efficiency factories in the production of water-based inks. Traditional production methods rely on experienced operators manually adjusting key parameters such as stirring speed, temperature, material flow rate, and pH value. This leads to unstable production efficiency, inconsistent product quality, and slow response to unexpected situations (such as changes in raw material properties). To address these issues, intelligent production control systems have been introduced. These systems collect data in real time through sensors and automatically adjust production parameters. While this improves efficiency and stability, it can still cause errors and even product scrap when faced with unusual interactions between new raw material characteristics and the system's automatic adjustment strategies. For example, in the production of high-grade water-based packaging inks, the intelligent control system uses online viscometers and temperature sensors to acquire real-time information such as viscosity, temperature, and pH value of the ink during mixing and grinding. Based on preset rules, it automatically adjusts the agitator speed, material feed rate, and heating / cooling device temperature to ensure product quality. However, when using a batch of novel water-based acrylic resin with a higher molecular weight, the system detected a viscosity higher than the target value during the pre-mixing stage. According to the control logic, the system automatically increases the speed of the main dispersing agitator and slightly increases the temperature of the mixing tank to enhance mechanical dispersion and reduce apparent viscosity. Initially, the viscosity readings appeared to decrease, leading the system to determine that the control strategy was effective. However, operators observed abnormal white foam appearing in the container, which thickened with high-intensity agitation. This was because trace amounts of residual emulsifier in the batch of resin were activated under high-speed, high-shear forces, causing a large amount of air to be entrained into the ink slurry, forming stable bubbles. These bubbles severely interfered with the accuracy of the online viscometer, causing its measured values ​​to be far lower than the true viscosity of the ink liquid phase. Based on this erroneous low viscosity information, the system made incorrect judgments, deeming the agitation intensity too high or the solvent ratio inappropriate, and subsequently performed reverse operations, reducing the amount of deionized water added and adding thickener. These actions resulted in a higher true liquid phase viscosity of the ink, making it even harder for the bubbles to escape, exacerbating the foaming problem, and ultimately leading to the scrapping of the entire batch of material. Summary of the Invention

[0003] This application provides a novel intelligent control method and system for ink production process, which aims to solve the problem that when the intelligent control system encounters unusual interactions with new raw material characteristics and the system's automatic adjustment strategy during the production of water-based inks, errors may occur, leading to product scrap. In a first aspect, this application discloses a novel intelligent control method for ink production processes, comprising the following steps: A novel intelligent control method for ink production process includes: The operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained from the top of the tank are obtained; wherein, the operating power of the stirring motor reflects the actual energy consumption of the stirrer in overcoming the resistance of the ink, the online viscometer reading reflects the apparent viscosity of the ink, and the amount of gas entrained from the top of the tank reflects the degree of air bubble mixing in the ink; A physical correlation analysis is performed on the operating power of the stirring motor and the online viscometer reading to construct a contradiction intensity index between the operating power of the stirring motor and the online viscometer reading. When the contradiction intensity index exceeds the threshold and the amount of gas entrained at the top of the tank is abnormal, the online viscometer reading is determined to be disturbed and invalid. When a failure is detected, the original control strategy is interrupted and a preset interference suppression program is started; The continuous decrease in the aforementioned contradiction intensity index is used as the criterion for determining the elimination of interference until the original control strategy is restored. Secondly, this application also discloses a novel intelligent control system for ink production processes, comprising: The parameter acquisition module acquires the operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained from the top of the tank; wherein, the operating power of the stirring motor reflects the actual energy consumption of the stirrer in overcoming the resistance of the ink, the online viscometer reading reflects the apparent viscosity of the ink, and the amount of gas entrained from the top of the tank reflects the degree of air bubble mixing in the ink; The correlation analysis module performs physical correlation analysis on the operating power of the stirring motor and the online viscometer reading, and constructs a contradiction intensity index between the operating power of the stirring motor and the online viscometer reading. When the contradiction intensity index exceeds the threshold and the amount of gas entrained at the top of the tank is abnormal, it is determined that the online viscometer reading is interfered with and fails. The intervention module interrupts the original control strategy and starts a preset interference suppression program when a failure is detected. The parameter limiting module uses the continuous decrease of the contradiction intensity index as the criterion for determining interference elimination until the original control strategy is restored. Beneficial effects This application discloses a novel intelligent control method for ink production processes. By acquiring the operating power of the stirring motor, online viscometer readings, and the amount of gas entrained at the top of the tank, and performing physical correlation analysis between the stirring motor operating power and the online viscometer readings, a contradiction intensity index is constructed. When the contradiction intensity index exceeds a threshold and the amount of gas entrained at the top of the tank is abnormal, the system can accurately determine that the online viscometer reading has failed due to bubble interference. Upon determining failure, the system immediately interrupts the original control strategy and initiates a preset interference suppression program, such as suspending material addition operations based on online viscometer readings, initiating foam suppression intervention, and limiting the automatic adjustment of material handling parameters. Subsequently, the continuous decrease in the contradiction intensity index is used as the criterion for interference elimination until the original control strategy is restored. This method effectively solves the technical problem in existing water-based ink production processes where intelligent control systems cannot accurately identify and take effective measures when faced with bubble interference in online viscometer readings caused by the characteristics of new raw materials, thus leading to erroneous control and product scrap. By introducing a physical correlation analysis between the operating power of the stirring motor and the online viscometer reading, and combining this with the amount of gas entrained from the tank top as an auxiliary judgment, this application can more sensitively and accurately identify viscometer failures caused by bubble interference, avoiding the limitations of traditional single viscometer reading judgment. Simultaneously, the preset interference suppression program can intervene in the production process in a timely and effective manner, preventing further deterioration of the problem and significantly reducing production risks and material scrap rates. Therefore, the method of this application can significantly improve the intelligence level of the ink production process and the consistency of product batches, providing a reliable technical guarantee for high-quality, high-efficiency ink production. Attached Figure Description

[0004] To illustrate this application more clearly, the accompanying drawings used in the embodiments will be briefly described below. Obviously, those skilled in the art can obtain other drawings based on these drawings without any creative effort. Figure 1 The diagram above illustrates a flow chart of a novel intelligent control method for ink production. Figure 2 The diagram above illustrates a structural schematic of a novel intelligent control system for ink production processes. Figure reference numerals: 100, Intelligent control system for new ink production process; 10, Parameter acquisition module; 20, Correlation analysis module; 30, Intervention measures module; 40, Parameter limitation module. Detailed Implementation

[0005] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance. In the production of water-based inks, traditional methods rely on manual experience to adjust parameters, leading to unstable production efficiency, inconsistent product quality, and slow response to unexpected situations. While the introduction of intelligent control systems has improved efficiency, it can still cause errors or even product scrap when faced with unusual interactions between new raw material characteristics and the system's automatic adjustment strategies. For example, when online viscometer readings are distorted due to bubble interference, the system may perform a reverse operation based on erroneous information, exacerbating the problem. like Figure 1 The diagram illustrates a flowchart of a novel intelligent control method for ink production. This application proposes a novel intelligent control method for ink production, comprising: S10, obtain the operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained at the top of the tank; wherein, the operating power of the stirring motor reflects the actual energy consumption of the stirrer to overcome the resistance of the ink, the online viscometer reading reflects the apparent viscosity of the ink, and the amount of gas entrained at the top of the tank reflects the degree of air bubble mixing in the ink. S20, perform physical correlation analysis on the operating power of the stirring motor and the online viscometer reading, and construct a contradiction intensity index between the operating power of the stirring motor and the online viscometer reading. When the contradiction intensity index exceeds the threshold and the amount of gas entrained from the top of the tank is abnormal, it is determined that the online viscometer reading is disturbed and fails. S30, when a failure is detected, the original control strategy is interrupted and a preset interference suppression program is started; S40 uses the continuous decline of the contradiction intensity index as the criterion for determining the elimination of interference until the original control strategy is restored. This application aims to effectively identify and suppress the distortion of online viscometer readings caused by factors such as bubbles during ink production by introducing multi-dimensional data correlation analysis and intelligent intervention mechanisms, thereby improving the robustness of the control system and the stability of the production process. To better understand this application, the key terms involved will first be explained. The operating power of the stirring motor reflects the actual load done by the stirrer in the ink, and is closely related to the physical properties of the ink, such as viscosity, density, and stirring speed. When the ink viscosity increases, the stirring resistance increases, and the operating power usually increases accordingly. Online viscometer readings refer to the apparent viscosity values ​​of ink measured in real time by a viscometer installed in the production pipeline or reaction vessel. This reading is one of the key parameters for controlling ink quality, directly affecting ink flowability, printability, and other properties. Gas entrainment at the top of the ink tank refers to the degree to which air or other gases are mixed into the ink paste during the ink production process due to stirring, mixing, and other operations. Gas entrainment forms bubbles, which not only affect the physical properties of the ink but may also interfere with the accuracy of online measurement equipment. The contradiction intensity index is a novel evaluation parameter proposed in this application, used to quantify the degree to which the operating power of the stirring motor deviates from the normal physical correlation with the online viscometer reading. Under normal circumstances, power and viscosity should show a certain positive or negative correlation. When this relationship deviates abnormally, it indicates that there may be interference. This application achieves intelligent control of the ink production process through the following methods: First, it is necessary to obtain the operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained from the top of the tank. In some embodiments, the steps of obtaining the stirring motor operating power, online viscometer reading, and the amount of gas entrained from the tank top may include: The voltage and current signals at the power input terminal of the stirring motor are collected by a power sensor, and the instantaneous active power is calculated as the operating power of the stirring motor. The damping signal of ink flowing through the probe is collected by a vibratory viscometer and converted into a viscosity value as an online viscometer reading. Furthermore, the rate of change of liquid level fluctuation is monitored by a non-contact ultrasonic level sensor, and the high-frequency energy density of the sound waves of bubble bursting is captured by an acoustic sensor. The degree of gas entrainment is then comprehensively judged as the amount of gas entrained at the top of the tank. The operating power of the agitator motor refers to the instantaneous active power consumed by the agitator to overcome the ink resistance during actual operation. This power is acquired in real time by a power sensor installed at the power input terminal of the agitator motor. The power sensor can accurately measure voltage and current signals and calculate the instantaneous active power based on these signals. This method can directly reflect the workload of the agitator and the flow characteristics of the ink, providing accurate physical quantities for subsequent correlation analysis. Online viscometer readings refer to the apparent viscosity of ink during the production process. This is achieved using a vibratory viscometer, where the probe is immersed in the ink. By measuring the damping signal experienced by the probe as it vibrates within the ink, this is converted into a specific viscosity value. Vibratory viscometers offer advantages such as fast response, high measurement accuracy, and minimal disturbance to the fluid, enabling them to accurately reflect changes in ink viscosity in real time. They are a key control parameter in the ink production process. The amount of gas entrainment at the top of the can refers to the degree to which air bubbles are incorporated into the ink during the agitation process. This parameter is obtained using a comprehensive judgment method. Specifically, a non-contact ultrasonic level sensor is used to monitor the rate of change of the ink surface fluctuation; significant surface fluctuations usually indicate the possibility of gas entrainment. Simultaneously, an acoustic sensor is positioned near the top of the can to capture the high-frequency sound energy density generated when bubbles burst. The high-frequency energy density of the bubble bursting sound wave is closely related to the formation and bursting intensity of the bubble. By comprehensively analyzing the rate of change of the ink surface fluctuation and the high-frequency energy density of the bubble bursting sound wave, the degree of gas entrainment in the ink can be determined more accurately, thus avoiding potential misjudgments from a single sensor. Secondly, a physical correlation analysis was performed on the operating power of the stirring motor and the online viscometer reading to construct a contradiction strength index between the stirring motor operating power and the online viscometer reading. When the contradiction strength index exceeds the threshold and the amount of gas entrainment at the top of the tank is abnormal, the online viscometer reading is determined to be disturbed and invalid. Constructing an index of contradiction intensity can be achieved by establishing a mathematical model of power and viscosity. For example, based on historical data, regression analysis can be used to establish a functional relationship between power and viscosity under normal operating conditions. When the real-time collected power and viscosity data deviate from the model's predicted values ​​to a certain extent, the contradiction intensity can be calculated. Another approach is to set normal operating ranges for power and viscosity; when power exceeds its upper limit and viscosity falls below its lower limit, the difference in the magnitude of deviation from the normal range is calculated as an index of contradiction intensity. Alternatively, machine learning algorithms can be used to train a model to identify abnormal correlation patterns between power and viscosity and output an index representing the degree of abnormality. Determining an abnormal amount of gas entrainment at the tank top can be achieved by setting a preset normal range. For example, when the amount of gas entrainment at the tank top exceeds a certain empirical threshold, it is considered abnormal. Another approach is to use statistical methods to calculate the historical average and standard deviation of the gas entrainment amount; when the real-time value deviates from the average by more than a certain multiple of the standard deviation, it is considered abnormal. Alternatively, a fuzzy logic system can be used to classify the gas entrainment amount into fuzzy sets such as "normal," "high," and "abnormally high," and the degree of abnormality can be determined based on a membership function. Furthermore, when a failure is detected, the original control strategy is interrupted, and a preset interference suppression program is activated. Interrupting the original control strategy can be achieved by sending a stop command to the control system. For example, when the online viscometer reading is determined to be invalid, the system immediately stops all automatic adjustment operations based on that reading, such as material addition and stirring speed adjustment. Another approach is to switch the control system to manual mode, allowing the operator to take over control. Alternatively, a preset "safety mode" can be activated, in which all parameters are maintained at safe and stable values, awaiting the elimination of interference. Activating a preset interference suppression program can be achieved by executing a series of pre-programmed actions. For example, the defoamer addition device can be activated immediately to spray defoamer into the ink to eliminate bubbles. Another approach is to reduce the speed of the stirring motor to decrease gas entrapment and bubble formation. Bubble suppression can also be achieved by adjusting the ink temperature, thereby altering the solubility of gases or the stability of bubbles. Finally, the continuous decline in the intensity of the conflict is used as the criterion for determining whether the interference has been eliminated, until the original control strategy is restored. Using a sustained decrease in the conflict intensity index as the criterion for determining interference elimination can be achieved by monitoring the index's trend in real time. For example, when the conflict intensity index shows a downward trend for several consecutive sampling periods and eventually falls below a preset normal threshold, the interference can be considered eliminated. Another approach is to combine this with other parameters, such as the amount of gas entrained at the tank top. When both the conflict intensity index decreases and the gas entrainment returns to normal, the interference can be considered eliminated. Alternatively, a time window can be set; if the conflict intensity index continues to decrease and stabilizes at a low level within this window, the interference is considered eliminated. Restoring the original control strategy can be achieved by sending a restore command to the control system. For example, once the disturbance is determined to be eliminated, the system automatically lifts the interruption and reactivates the automatic adjustment loop based on online viscometer readings. Another approach is to gradually increase the stirring speed and resume material addition operations to smoothly transition to normal production. Alternatively, the original control strategy can be manually restored by the operator after manual confirmation. The overall working principle of this application lies in effectively solving the problem of control failure caused by air bubble interference in the online viscometer reading during traditional ink production processes through multi-dimensional data fusion and intelligent judgment. During ink production, the system continuously acquires the operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained from the tank top. Under normal circumstances, there is a certain physical correlation between the operating power of the stirring motor and the online viscometer reading; for example, increased viscosity usually leads to increased stirring power. However, when a large number of air bubbles are entrained in the ink, the online viscometer reading may be lower due to the presence of air bubbles. At this time, the stirring motor, in overcoming the resistance of the air bubbles, may actually increase its operating power or maintain a higher level, resulting in an abnormal "contradiction" between the power and the viscosity reading. This application constructs a "contradiction intensity index" to quantify such abnormal deviations by performing physical correlation analysis on the operating power of the stirring motor and the online viscometer reading. Simultaneously, the system also monitors the amount of gas entrained at the tank top as direct evidence of bubble interference. When the contradiction intensity index exceeds a preset threshold and the amount of gas entrained at the tank top also shows an anomaly, the system can intelligently determine that the online viscometer reading has failed due to bubble interference. This judgment mechanism avoids the blind spots of traditional systems that rely solely on a single viscometer reading for control. Once a viscometer reading is determined to be faulty, the system immediately interrupts its existing control strategy, such as pausing material addition or stirring speed adjustments based on the erroneous viscosity reading, and instead activates a preset interference suppression program. This program may include measures such as reducing the stirring speed to decrease gas entrainment and adding defoamers to eliminate existing bubbles. These interventions aim to eliminate or mitigate bubble interference at its source, ensuring that the true viscosity of the ink can be accurately measured. During the interference suppression program, the system continuously monitors the interference intensity index. As bubbles are eliminated and interference weakens, the physical correlation between the stirring motor's operating power and the online viscometer reading gradually returns to normal, manifested as a continuous decrease in the interference intensity index. When this index drops to a preset safety level, indicating that the interference has been largely eliminated, the system restores its original control strategy, bringing the production process back to normal. In this way, this application can promptly detect and effectively address measurement distortion caused by bubble interference, avoiding the risk of product quality degradation or even scrap due to control based on erroneous data, and significantly improving the intelligence and stability of the ink production process. The core innovation of this application lies in the introduction of a "contradiction intensity index" and a multi-dimensional data fusion judgment mechanism to intelligently identify situations where online viscometer readings fail due to bubble interference. Traditional methods often rely on single sensor data for control. When the online viscometer reading is distorted due to bubble interference, the system will make incorrect control decisions based on erroneous information. For example, when the viscosity actually increases, the system may reduce the addition of thickener because the reading is too low due to bubbles, thus exacerbating the problem. Compared to the closest existing technology, the advantages of this application are: First, by performing a physical correlation analysis on the operating power of the stirring motor and the online viscometer readings, a contradiction intensity index is constructed, which can reveal the abnormal relationships between the data at a deeper level. This allows the system not only to detect anomalies but also to understand their nature, i.e., whether they are caused by bubble interference. Secondly, combining the amount of gas entrained from the tank top with direct evidence further enhances the accuracy and reliability of the judgment. This multi-sensor data fusion approach avoids the risk of misjudgment from a single sensor. Furthermore, upon determining a failure, immediately interrupting the original control strategy and activating the preset interference suppression program can promptly mitigate losses and prevent further deterioration of erroneous control decisions. Finally, using the continuous decline of the contradiction intensity index as the criterion for determining the elimination of interference provides an objective and quantitative recovery standard, ensuring that the system only returns to normal control after the interference is truly eliminated, thereby improving the stability and safety of the production process. In summary, this application effectively solves the problem of air bubble interference in online viscometer readings during ink production through an innovative intelligent judgment and intervention mechanism, significantly improving the level of intelligence in the production process and the stability of product quality, and has important technological advancement significance. In some embodiments, when it is determined that the online viscometer reading is affected by interference, the original control strategy is interrupted and a preset interference suppression program is initiated. This program includes pausing the material addition operation based on the online viscometer reading, initiating foam suppression intervention, and restricting the automatic adjustment of material handling parameters. When a failure is detected, the original control strategy is interrupted and a preset interference suppression program is initiated, including: pausing the material addition operation based on the online viscometer reading, initiating foam suppression intervention, and restricting the automatic adjustment of material processing parameters. Suspending material addition operations based on online viscometer readings means immediately stopping or freezing all material addition commands (such as solvents, thickeners, etc.) that rely on that reading once the online viscometer reading is determined to be malfunctioning due to interference. The purpose is to prevent excessive or insufficient material addition due to erroneous viscosity readings, which could further deteriorate ink quality or production process stability. Furthermore, initiating foam suppression intervention refers to the system proactively taking measures to reduce or eliminate air bubbles in the ink when interference with the online viscometer reading is detected and an abnormal amount of gas entrainment from the top of the container is observed. This may include, but is not limited to, reducing the stirring speed to reduce gas entrainment, or using chemical means such as adding defoamers to break up the foam. The aim is to directly solve the problem of viscosity measurement distortion caused by air bubble intrusion and restore the true apparent viscosity of the ink. Furthermore, limiting the automatic adjustment of material handling parameters refers to the function of freezing or limiting the automatic adjustment of certain key material handling parameters (such as stirring speed, temperature, etc.) during disturbance suppression. Its purpose is to prevent the system from making inappropriate parameter adjustments under erroneous readings or unstable conditions, thereby avoiding the introduction of new disturbances or exacerbation of existing problems, and ensuring that the production process remains in a relatively stable and controlled state until the disturbance is eliminated. The technical solution of this application avoids material ratio imbalance caused by erroneous data by immediately suspending material addition operations based on the online viscometer reading when it is determined to be malfunctioning due to interference. Simultaneously, it initiates foam suppression intervention, directly addressing the main cause of viscosity reading distortion—air bubble intrusion—and fundamentally eliminating the source of interference. Furthermore, limiting the automatic adjustment of material handling parameters effectively prevents the system from making erroneous self-adjustments in unstable states, thus avoiding further escalation of the problem. These three synergistic measures form a comprehensive and effective interference suppression mechanism, ensuring proper control of the production process until the interference is eliminated. Through the above technical solution, when the online viscometer reading fails due to interference, the interference suppression program can be quickly and comprehensively activated. Suspending material addition effectively avoids material waste and product quality degradation caused by erroneous viscosity data. Activating foam suppression intervention directly addresses the impact of air bubbles on viscosity measurement, helping to quickly restore accurate viscosity measurements. Limiting the automatic adjustment of material handling parameters ensures the stability of the production process during interference, preventing negative impacts from improper adjustments. Therefore, this solution significantly improves the robustness and reliability of the ink production process, reduces production interruptions and product defects caused by sensor failure, thereby improving overall production efficiency and product quality. In some embodiments described above in this application, when the online viscometer reading is determined to be affected by interference, the original control strategy needs to be interrupted and a preset interference suppression program needs to be activated. Specifically, the interference suppression program includes suspending material addition operations based on the online viscometer reading, activating foam suppression intervention, and limiting the automatic adjustment of material handling parameters. To more effectively implement these intervention measures, this application further proposes specific implementation steps. In response, this application further proposes the following method for interrupting the original control strategy and activating a preset interference suppression procedure when a failure is detected: Pause the material addition control loop based on the online viscometer reading to interrupt the solvent or thickener addition command. Simultaneously reduce the stirring motor speed to a preset low speed value to reduce gas entrainment, and start the defoamer adding device to spray defoamer onto the foam layer; Additionally, freeze the material handling parameters, including stirring speed and temperature, to maintain the current foam suppression settings. Specifically, suspending the material addition control loop based on online viscometer readings means immediately stopping or blocking any solvent or thickener addition commands triggered by that viscometer reading when interference with the online viscometer reading is detected. The purpose is to prevent material imbalances caused by erroneous viscosity readings, which could affect ink product quality. For example, when the viscometer incorrectly displays a viscosity that is too low, the system might incorrectly add thickener, resulting in an actual viscosity that is too high; and vice versa. Disrupting this control loop can prevent such misoperations. The simultaneous reduction of the stirring motor speed to a preset low speed can be understood as adjusting the stirring equipment speed from its normal operating state to a lower, pre-set speed while activating the interference suppression program. The purpose is to significantly reduce the degree to which gas is entrained into the ink during stirring, thereby reducing the generation and accumulation of bubbles. In practical applications, the preset low speed value can be optimized based on the ink characteristics, the geometry of the mixing tank, and historical production data to minimize gas entrainment while ensuring basic mixing. Simultaneously, activating the defoamer addition device to spray defoamer onto the foam layer refers to activating equipment specifically designed for eliminating foam, precisely spraying chemical defoamer onto the foam layer formed on the ink surface. The purpose is to quickly break up the formed foam through physical or chemical action, further reducing the amount of gas entrained at the top of the tank, thereby eliminating the source of interference to the online viscometer reading. The type and amount of defoamer can be selected and adjusted according to the chemical composition of the ink and the severity of the foam. Furthermore, freezing material handling parameters, including stirring speed and temperature, and maintaining the current foam suppression settings means that during interference suppression, key material handling parameters such as stirring speed and ink temperature are fixed at their current state or preset optimized foam suppression values, and the automatic control system is no longer allowed to adjust them according to conventional strategies. The purpose is to ensure the stability of production environment parameters during interference suppression, avoiding the introduction of new interference or impact on foam suppression effectiveness due to parameter fluctuations, thereby creating stable conditions for the system to resume normal operation. The technical solution of this application, by refining and coordinating key operations in the interference suppression process, can more accurately and effectively address the problem of online viscometer readings failing due to bubble interference. Specifically, pausing the material addition control loop directly cuts off the potential source of material ratio errors caused by erroneous viscosity readings, fundamentally preventing further deterioration of product quality. Simultaneously reducing the stirring motor speed and starting the defoamer addition device reduces the amount of gas entrained and foam content in the ink from both the source and existing bubbles, directly intervening in the physical interference factors that cause viscometer failure. Freezing the material handling parameters ensures the stability and controllability of the production environment during interference suppression, avoiding negative impacts on the suppression effect due to parameter fluctuations, thus providing a stable foundation for the system to resume normal operation. These synergistic measures together ensure the effectiveness of interference suppression and the stability of the production process. Through the above technical solutions, this application can achieve precise and multi-dimensional suppression of online viscometer reading failure due to bubble interference during ink production. Specifically, by refining the pause mechanism for material addition, material waste and product quality issues caused by misjudgment are effectively avoided. By synchronously adjusting the stirring speed and introducing defoamers, the bubble content in the ink can be quickly and effectively reduced, directly eliminating physical interference to the viscometer reading and significantly improving the efficiency and success rate of interference suppression. In addition, by freezing key material handling parameters, the stability of the production environment is ensured during interference suppression, avoiding the generation of secondary interference. This makes the entire interference suppression process more controllable and reliable, ultimately ensuring the continuity of the ink production process and the stability of product quality. In some embodiments described above in this application, a method is proposed to determine whether the online viscometer reading is affected by interference by analyzing the operating power of the stirring motor and the online viscometer reading through physical correlation analysis, combined with the amount of gas entrained from the tank top. However, in actual production processes, the complex rheological properties of ink and the dynamic changes in the production environment may lead to insufficient accuracy in simple threshold judgments or abnormal state identification, thereby affecting the accuracy and robustness of interference judgment and potentially resulting in misjudgments or missed judgments. In this regard, this application further proposes that the step of performing physical correlation analysis on the operating power of the stirring motor and the online viscometer reading to construct a contradiction intensity index between the operating power of the stirring motor and the online viscometer reading, and determining that the online viscometer reading is interfered with and fails when the contradiction intensity index exceeds a threshold and the amount of gas entrained at the top of the tank is abnormal, includes: Construct an index to assess the degree of discrepancy between the operating power of the stirring motor and the reading of the online viscometer; The amount of gas entrained at the top of the tank is fuzzy to generate a gas interference confidence level; Based on the increase in the intensity of the conflict, the weight ratio of the stirring motor operating power and the online viscometer reading in the risk assessment is dynamically adjusted. By integrating the aforementioned contradiction intensity index with the confidence level of gas interference, a comprehensive risk assessment is obtained; Based on the comprehensive risk assessment, it was determined that the online viscometer reading was malfunctioning due to interference. Specifically, constructing a contradiction strength index between the operating power of the stirring motor and the online viscometer reading involves quantifying the degree of deviation by analyzing the expected correlation between the two under specific operating conditions. For example, when the operating power of the stirring motor increases while the online viscometer reading decreases unreasonably, it indicates a physical contradiction between the two, and this contradiction strength index aims to capture this inconsistency. The fuzzy processing of the gas entrainment amount at the tank top to generate a gas interference confidence score can be understood as transforming discrete or fuzzy data on the gas entrainment amount at the tank top into a continuous confidence value representing the probability of gas interference. This aims to more precisely quantify the impact of gas entrainment on the viscometer reading, rather than simply judging whether it is "abnormal." For example, a fuzzy logic system can be used to divide the gas entrainment amount into fuzzy sets such as "low," "medium," and "high," and output a confidence score between 0 and 1 based on a preset membership function and fuzzy rules. In practical applications, the weight ratio of the operating power of the stirring motor and the online viscometer reading in risk assessment is dynamically adjusted according to the increase in the contradiction strength index, with the aim of making risk assessment more adaptable. When the contradiction intensity index rises sharply, it indicates a potential serious deviation in the sensor reading. In this case, a higher weight can be assigned to it to accelerate interference identification. Conversely, when the contradiction intensity index changes gradually, the weight can be appropriately reduced to avoid oversensitivity. Furthermore, fusing the contradiction intensity index with the gas interference confidence level to obtain a comprehensive risk judgment involves combining these two key indicators using an algorithm to form a more comprehensive and reliable risk assessment result. For example, weighted summation, fuzzy inference, or neural networks can be used for fusion. Therefore, based on the comprehensive risk judgment, the online viscometer reading is determined to be malfunctioning due to interference. The purpose is to leverage the advantages of multi-source information fusion to improve the accuracy and reliability of interference judgment and reduce the occurrence of misjudgments and omissions. The technical solution of this application significantly improves the accuracy and robustness of online viscometer reading failure judgment due to interference by introducing fuzzy processing of the amount of gas entrained at the tank top and dynamic weight adjustment of the contradiction intensity index. Specifically, traditional simple threshold judgment may not be able to fully capture the complex physical phenomena in the ink production process. For example, when the amount of gas entrained at the tank top is at a critical state, simply marking it as "abnormal" or "normal" may lead to judgment errors. Through fuzzy processing, the amount of gas entrained is transformed into a continuous gas interference confidence level, enabling the system to more finely assess the potential impact of gas on the viscometer reading and avoid the limitations of binary judgment. At the same time, the increase in the contradiction intensity index between the stirring motor operating power and the online viscometer reading can reflect the severity and urgency of the potential interference. By dynamically adjusting the weight ratio of the two in risk judgment according to this increase, the system can adaptively adjust the judgment strategy according to the actual situation. For example, when the contradiction increases sharply, the contradiction intensity index is given higher priority, thereby achieving a faster and more accurate response. Finally, by integrating the contradiction intensity index with the gas interference confidence level after dynamic weight adjustment, a more comprehensive and reliable integrated risk assessment can be formed by taking into account multiple factors, thereby effectively avoiding the bias that may be caused by a single indicator. Through the above technical solution, this application overcomes the problem of insufficient accuracy in interference judgment under complex working conditions caused by traditional methods. Specifically, by fuzzy processing of the amount of gas entrained at the tank top, the system can more precisely quantify the degree of gas interference, avoiding misjudgments that may be caused by simple threshold judgment. Simultaneously, by dynamically adjusting the weights according to the increase in the contradiction intensity index, the system can adaptively adjust the judgment strategy according to the severity of the interference, improving the sensitivity and accuracy of the judgment. Therefore, the comprehensive risk judgment obtained by integrating multi-source information significantly improves the reliability and robustness of online viscometer reading failure judgment due to interference, effectively reducing false alarms and missed alarms, providing a more stable and reliable data foundation for intelligent control of the ink production process, thereby ensuring product quality and production efficiency. For example, suppose that during the ink production process, the system continuously monitors the operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained from the tank top. First, the system continuously constructs a contradiction strength index between the stirring motor's operating power and the online viscometer reading. For instance, if at a certain moment the stirring motor's operating power suddenly increases while the online viscometer reading shows an unreasonable decrease, the calculated contradiction strength index will increase significantly. Simultaneously, the data on the amount of gas entrained from the tank top is input into a fuzzy logic system for processing. This system generates a gas interference confidence level between 0 and 1 based on a preset membership function (e.g., dividing the gas entrainment into three fuzzy sets: "low," "medium," and "high") and fuzzy rules (e.g., "if the gas entrainment is high, then the gas interference confidence level is high"). For example, when the gas entrainment from the tank top is at a moderately high level, a gas interference confidence level of 0.6 is generated. Then, the system dynamically adjusts the weight of the contradiction strength index and the gas interference confidence level in the final risk assessment based on the increase in the current contradiction strength index. For example, if the inconsistency intensity index rises sharply from 0.1 to 0.8 within a short period, it indicates a potential serious sensor problem. In this case, the weight of the inconsistency intensity index might be dynamically adjusted to 0.7, while the weight of the gas interference confidence score would be 0.3. The system then fuses the adjusted inconsistency intensity index (e.g., 0.8 * 0.7 = 0.56) with the gas interference confidence score (e.g., 0.6 * 0.3 = 0.18), obtaining a comprehensive risk value (0.56 + 0.18 = 0.74) through simple weighted summation. Finally, this comprehensive risk value is compared with a preset comprehensive threshold. If the preset comprehensive threshold is 0.7, then since 0.74 exceeds the threshold, the system will determine that the online viscometer reading is affected by interference and immediately trigger subsequent interference suppression procedures. In this way, even if the anomaly of a single indicator is insufficient to trigger an alarm, multi-indicator fusion judgment can identify potential sensor interference problems earlier and more accurately. In some embodiments, the step of constructing a strength index of the discrepancy between the operating power of the stirring motor and the online viscometer reading may include the following: Within a preset time period, when the average operating power of the stirring motor exceeds the upper limit of the first historical normal operating range and the average reading of the online viscometer is lower than the lower limit of the second historical normal operating range, the absolute value of the difference between the power increase and the viscosity decrease is calculated, and this absolute value of the difference is used as an indicator of the degree of contradiction between the operating power of the stirring motor and the online viscometer reading. The preset time period refers to a time window set to smooth out instantaneous data fluctuations, such as a rolling average period. Its purpose is to obtain a more representative average parameter value to avoid misjudgments caused by short-term instantaneous disturbances. Within the preset time period, the average operating power of the agitator motor is obtained by statistically averaging the continuously collected data. The first historical normal operating range upper limit refers to the upper limit of normal fluctuation in the operating power of the agitator motor, determined based on historical production data and process experience. When the average power exceeds this upper limit, it usually indicates an abnormal increase in the resistance experienced by the agitator. The average value of the online viscometer reading is the value obtained by statistically averaging the continuously collected online viscometer reading data within the preset time period. The second historical normal operating range lower limit refers to the lower limit of normal fluctuation in the online viscometer reading, determined based on historical production data and process experience. When the average viscosity reading is below this lower limit, it usually indicates an abnormal decrease in the apparent viscosity of the ink. Furthermore, the power increase refers to the amount by which the average operating power of the stirring motor exceeds the upper limit of the first historical normal operating range, while the viscosity decrease refers to the amount by which the average online viscometer reading decreases relative to the lower limit of the second historical normal operating range. Calculating the absolute value of the difference between the power increase and viscosity decrease aims to quantify the degree to which the stirring motor operating power and the online viscometer reading deviate from the normal physical correlation. When the stirring motor operating power increases while the online viscometer reading decreases, this anomalous trend indicates a significant contradiction between the two; the absolute value of this difference is used as an indicator of the intensity of this contradiction to visually reflect its severity. The technical solution of this application monitors whether the average operating power of the stirring motor exceeds its normal upper limit and whether the average reading of the online viscometer falls below its normal lower limit within a preset time period, and calculates the absolute value of the difference between the two deviations from the normal range as a contradiction intensity index. This effectively identifies potential interferences in the ink production process. Under normal circumstances, increased ink viscosity leads to increased stirring resistance, resulting in increased stirring motor power; conversely, decreased viscosity leads to decreased power. However, when a large amount of gas is entrained in the ink, forming bubbles, these bubbles reduce the apparent viscosity of the ink, causing an abnormal drop in the online viscometer reading. Simultaneously, when the stirrer is stirring in a fluid containing bubbles, due to the damping effect of the bubbles and the interaction between the stirrer and the bubble interface, the stirring motor may need to consume more power to maintain the stirring effect, or the non-Newtonian fluid characteristics of the bubbles may cause abnormal fluctuations or even increases in stirring power. Therefore, when a contradictory phenomenon occurs where the stirring motor power increases while the online viscometer reading decreases, this contradiction intensity index can accurately capture this abnormal physical correlation, indicating that the online viscometer reading may be affected by interference such as bubbles and thus malfunction. By introducing the average value within a preset time period, instantaneous noise and short-term fluctuations can be effectively filtered out, making the calculation of the contradiction intensity index more stable and reliable, and avoiding misjudgments caused by occasional data jumps. Through the above technical solution, this application provides a more accurate and robust method for constructing an inconsistency strength index. This method effectively quantifies the abnormal physical correlation between the operating power of the stirring motor and the average value of the online viscometer readings over a preset time period, as well as their deviation from historical normal operating ranges. This significantly improves the accuracy and sensitivity of determining online viscometer readings affected by interference, especially in complex operating conditions where air bubble entrainment leads to a decrease in apparent viscosity but an increase in actual stirring load. This index can more reliably reveal anomalies in sensor readings, providing a solid data foundation for subsequent interference suppression and control strategy adjustments, and avoiding production efficiency losses or product quality problems caused by misjudgments. In some embodiments described above, this application proposes a scheme to dynamically adjust the weighting of the stirring motor's operating power and the online viscometer reading in risk assessment based on the increase in the contradiction intensity index. However, in actual ink production, different ink formulations exhibit varying sensitivities to air bubbles, which can affect the physical correlation between the stirring motor's operating power and the online viscometer reading. Failure to fully consider the characteristics of the ink formulation itself and its sensitivity to air bubbles may result in inaccurate weighting adjustments, thereby affecting the accuracy of determining the failure of the online viscometer reading due to interference. In response, this application further proposes the following steps for adjusting the weights of the stirring motor operating power and the online viscometer reading in risk assessment based on the increase in the contradiction intensity index: Obtain ink formulation information; Based on the ink formulation information, obtain the ink's sensitivity to air bubbles; Based on the ink formulation information and the sensitivity information, a weight adjustment factor is determined; The contradiction intensity index is corrected according to the weight adjustment factor to obtain the corrected contradiction intensity index. Specifically, obtaining ink formulation information includes acquiring detailed composition and proportion data for the current production batch of ink. This information is typically stored in the production management system or formulation database and can be accessed in real time by the intelligent control system. Obtaining the ink formulation's sensitivity to bubbles refers to querying or calculating, based on known ink formulations, the ease with which the formulation generates, stabilizes, or dissipates bubbles during stirring. For example, some high-viscosity inks or those containing specific surfactants may be more prone to bubble entrapment or have more difficult-to-eliminate bubbles, thus exhibiting higher sensitivity. This sensitivity information can be pre-modeled based on historical data, experimental results, or expert experience, with the aim of quantifying the inherent response characteristics of different ink formulations to bubble interference. Determining the weighting adjustment factor involves calculating a multiplicative or additive factor to correct the inconsistency intensity index based on the ink formulation information and its bubble sensitivity information. For example, for inks with high bubble sensitivity, a larger adjustment of the weights may be needed when the inconsistency intensity index increases to respond more quickly to potential interference. Correcting the contradiction intensity index means performing a calculation, such as multiplying or adding, the originally calculated contradiction intensity index with a determined weight adjustment factor to obtain a corrected contradiction intensity index that better reflects the current actual situation of the ink. The technical solution of this application introduces ink formulation information and its sensitivity to bubbles, so that the weight adjustment of the contradiction intensity index is no longer based solely on its increase rate, but combines the physicochemical properties of the ink itself. Specifically, after obtaining the ink formulation information of the current production, the system can identify the inherent sensitivity of the formulation to bubbles. For example, for inks that are prone to foaming or whose bubbles are difficult to eliminate, even if the increase rate of the contradiction intensity index is the same, the possibility of viscometer reading failure caused by bubble interference is higher. By determining a weight adjustment factor and using it to correct the contradiction intensity index, the risk assessment can be made more consistent with actual working conditions. It is precisely because of this refined consideration of ink characteristics that the determination of online viscometer reading failure due to interference is more accurate and robust. Through the above technical solution, this application can dynamically and intelligently adjust the weight of the contradiction intensity index in risk assessment based on the characteristics of different ink formulations and their sensitivity to bubbles, thereby improving the accuracy and adaptability of online viscometer reading failure judgment due to interference. Compared with the solution that adjusts the weight solely based on the increase in contradiction intensity index, the technical solution of this application can effectively avoid misjudgment or omission caused by differences in ink formulations, enabling the intelligent control system to maintain high-precision interference identification capability when processing diverse ink products, further improving the stability and control efficiency of the ink production process. For example, suppose an ink production line is producing two ink formulations with different formulas: Formula A (low bubble sensitivity) and Formula B (high bubble sensitivity). When the system detects an increase in the inconsistency intensity index between the stirring motor's operating power and the online viscometer reading, if Formula A is used, the system will acquire its low bubble sensitivity information and determine a small weighting adjustment factor to slightly correct the inconsistency intensity index. However, when Formula B is used, the system will acquire its high bubble sensitivity information and determine a larger weighting adjustment factor to more significantly correct the inconsistency intensity index. For instance, even if the absolute value of the inconsistency intensity index is the same for Formula B as for Formula A, its higher bubble sensitivity will result in a higher corrected index, allowing the system to more quickly and accurately determine that the online viscometer reading may be affected by bubble interference and promptly initiate the interference suppression procedure. Specifically, ink formulation information may include the ink's solid content, solvent type, and additive types; bubble sensitivity information can be a preset value, such as a scale from 1 to 10, or an output value from a mathematical model based on experimental data. The weighting adjustment factor can be a multiplier greater than 1, such as 1.1 or 1.2, or a function related to the sensitivity level. In this way, the system can personalize the processing based on the characteristics of different inks, ensuring the accuracy of the judgment. In some embodiments of this application, the determination of online viscometer reading failure due to interference relies on whether the amount of gas entrained from the tank top is abnormal. However, in actual ink production, the measurement data of the amount of gas entrained from the tank top is often affected by environmental noise, sensor fluctuations, and transient changes in the production process, making direct judgment of "abnormality" potentially inaccurate or unrobust, and prone to misjudgment or missed judgment. If the above problems are not addressed, the judgment of online viscometer reading failure may be inaccurate, thereby affecting subsequent control strategies and causing a decrease in production efficiency or fluctuations in product quality. To address this, this application further proposes to perform fuzzy processing on the amount of gas entrained from the tank top to generate a more reliable confidence level for gas interference, thereby improving the accuracy and robustness of failure determination. The steps described above for fuzzing the amount of gas entrainment at the tank top to generate a confidence level for gas interference include: Based on the amount of gas entrained from the tank top, identify the noise components present in the amount of gas entrained from the tank top; The noise components are filtered to obtain the amount of gas entrained from the tank top after filtration. Based on the filtered amount of gas entrainment at the top of the tank, adjust the membership function of the gas entrainment signal in the amount of gas entrainment at the top of the tank. Based on the filtered amount of gas entrainment at the top of the tank, adjust the fuzzy rules of the gas entrainment signal in the amount of gas entrainment at the top of the tank. Based on the adjusted membership function and the adjusted fuzzy rules, the filtered gas entrainment at the top of the tank is processed to generate a gas interference confidence score. Specifically, identifying noise components in the gas entrainment data from the tank top refers to using signal analysis techniques, such as Fourier transform, wavelet analysis, or statistical methods, to detect and distinguish high-frequency fluctuations, random disturbances, or abnormal spikes in the raw data of the gas entrainment data from the tank top, which are not caused by the production process itself. The purpose is to provide cleaner input data for subsequent fuzzy processing. Filtering noise components can be understood as using digital filters, such as low-pass filters, median filters, or Kalman filters, to suppress or remove the identified noise components, thereby obtaining a smoother and more accurate filtered gas entrainment data from the tank top. The purpose is to eliminate the influence of measurement errors and environmental interference on the gas entrainment assessment. In practical applications, adjusting the membership function of the gas entrainment signal based on the filtered gas entrainment data refers to dynamically modifying the boundaries and shape of the fuzzy set (e.g., "low," "medium," "high" gas entrainment data) based on the distribution characteristics of the current filtered gas entrainment data. For example, when a system is in a state of gas entrainment for an extended period, the center or width of the membership function can be adaptively adjusted to better reflect the degree of gas entrainment under the current operating conditions. The aim is to enable the fuzzy system to more accurately map actual physical quantities to fuzzy concepts. Furthermore, adjusting the fuzzy rules for the gas entrainment signal based on the filtered tank top gas entrainment amount refers to dynamically modifying the fuzzy inference rule base based on actual production experience, expert knowledge, or machine learning algorithms. For example, when a specific gas entrainment range is found to be highly correlated with a certain interference pattern, the corresponding fuzzy rules can be strengthened or weakened to improve the accuracy of interference determination. The aim is to optimize the fuzzy inference process to better reflect the complexity of the actual production environment. Therefore, processing the filtered tank top gas entrainment amount and generating a gas interference confidence score based on the adjusted membership function and adjusted fuzzy rules involves using the filtered tank top gas entrainment amount as input to the fuzzy system, combining the dynamically adjusted membership function and fuzzy rules for fuzzy inference, and finally outputting a value between 0 and 1, representing the probability or degree to which the current gas entrainment interferes with the online viscometer reading. Its purpose is to provide a quantitative and continuous indicator for evaluating interference, rather than a simple binary judgment. The technical solution of this application effectively solves the data noise and uncertainty problems faced by directly judging "abnormalities" in traditional methods by introducing a fuzzy processing mechanism for the amount of gas entrained at the tank top. Specifically, firstly, noise components in the original gas entrainment data are identified and filtered out, ensuring higher reliability of the input data for subsequent fuzzy processing. Secondly, by dynamically adjusting the membership function and fuzzy rules based on the filtered data, the fuzzy system can adaptively adapt to the complex changes and uncertainties in gas entrainment during ink production, thereby more accurately capturing the true degree of interference of gas entrainment on viscometer readings. This dynamic adjustment mechanism allows the system to flexibly adjust the evaluation criteria for gas interference according to changes in actual operating conditions, avoiding misjudgments or omissions that may be caused by fixed threshold judgments. Finally, the gas interference confidence level generated by fuzzy inference is a continuous and quantitative indicator that can more meticulously reflect the potential risks of gas interference, providing a more refined and robust input for comprehensive risk assessment. Through the above technical solution, this application can significantly improve the accuracy and robustness of judging abnormal gas entrainment at the tank top. Compared with simply setting a threshold to judge whether the gas entrainment is abnormal, the fuzzy processing mechanism can effectively cope with sensor noise and uncertainties in the production process, reducing false alarms or missed alarms caused by data fluctuations. As a result, the generated gas interference confidence score more accurately reflects the actual degree of interference of bubbles on the online viscometer reading, thus making the comprehensive risk judgment of online viscometer reading failure due to interference more reliable, avoiding erroneous control decisions caused by inaccurate interference judgment, and further ensuring the stability of the ink production process and product quality. For example, suppose that during the ink production process, the amount of gas entrained at the top of the tank is monitored in real time using ultrasonic level sensors and acoustic sensors. The raw gas entrainment data may contain high-frequency noise caused by equipment vibration, ambient airflow, or occasional operational events. First, the system uses a wavelet denoising algorithm to identify and filter out these noise components, resulting in a smoother, filtered gas entrainment curve. Next, based on this filtered data, the system dynamically adjusts the preset fuzzy membership function. For instance, initially, the membership functions for "low," "medium," and "high" gas entrainment may be set to fixed intervals. However, in actual operation, if the filtered gas entrainment is found to fluctuate within a specific interval for a long period, the system will adaptively adjust the shape of the membership function for that interval to more accurately reflect the actual distribution of gas entrainment under the current operating conditions. Simultaneously, the fuzzy rules are also dynamically adjusted. For example, an initial rule might be "If the gas entrainment is high, then the confidence level for gas interference is high." However, if historical data analysis reveals that, under specific ink formulations and stirring speeds, even with high gas entrainment levels, the actual interference with viscometer readings is not significant, then the weight of this rule or its output confidence value will be reduced accordingly. Ultimately, the filtered gas entrainment level from the tank top is input into a dynamically adjusted fuzzy inference system, such as using a Mamdani or Sugeno fuzzy inference model, and calculated using the adjusted membership function and fuzzy rules to output an accurate gas interference confidence score. For example, when the gas entrainment level is moderately high, and historical data indicates a high risk of interference at this level, the system might output a gas interference confidence score of 0.75, rather than a simple binary judgment of "abnormal" or "normal." This continuous confidence score is then used to fuse with a contradiction strength index to obtain a more comprehensive overall risk assessment. In some embodiments described above in this application, a scheme is proposed to integrate the contradiction intensity index and the gas interference confidence level to obtain a comprehensive risk assessment. Specifically, the steps for integrating the contradiction intensity index and the gas interference confidence level to obtain a comprehensive risk assessment include: The adjusted weighting percentage of the contradiction intensity index is multiplied by the value of the contradiction intensity index, and then the weighting percentage of the gas interference confidence level is multiplied by the value of the gas interference confidence level to obtain the comprehensive risk value. When the overall risk value exceeds the preset overall threshold, the overall risk is determined to be that the online viscometer reading is interfered with and fails. Specifically, the adjusted weighting of the aforementioned contradiction intensity index refers to the proportion of the contradiction intensity index in risk assessment. This proportion can be dynamically adjusted based on actual production experience, ink formulation characteristics, and historical data analysis results. For example, when the ink is highly sensitive to bubbles, the weighting of the gas interference confidence level may be appropriately increased, while the weighting of the contradiction intensity index will be adjusted accordingly. The value of the contradiction intensity index is a specific value calculated based on the physical correlation analysis between the operating power of the stirring motor and the online viscometer reading, reflecting the degree of deviation from the normal correlation between the two. The value of the gas interference confidence level is a quantitative indicator reflecting the abnormal degree of gas entrainment at the tank top after fuzzy processing. Multiplying the respective weightings of both by their values ​​aims to quantify the contribution of different risk sources to the final judgment. The comprehensive risk value is a single quantitative indicator that integrates the contradiction intensity index and the gas interference confidence level. It comprehensively reflects the overall risk level of online viscometer reading failure due to interference. The preset comprehensive threshold is a critical value used to determine whether the online viscometer reading has failed due to interference. This threshold can be set according to the process requirements of ink production, product quality standards, and risk tolerance. When the comprehensive risk value exceeds the preset comprehensive threshold, it indicates that the possibility of the online viscometer reading failing due to interference is extremely high, and immediate intervention measures are required. The technical solution of this application achieves a more comprehensive and accurate assessment of whether online viscometer readings are affected by bubble interference by weighted fusion of a contradiction intensity index reflecting physical correlation anomalies and a gas interference confidence level reflecting gas entrainment anomalies. This fusion mechanism considers two different but related interference sources, avoiding potential misjudgments or omissions that may occur with a single index. By setting a preset comprehensive threshold, the system can promptly and reliably determine whether online viscometer readings are affected by interference based on the overall risk level, thereby providing an accurate trigger signal for subsequent interference suppression procedures. The above technical solution effectively improves the accuracy and robustness of online viscometer reading failure detection. Compared to relying on a single indicator, this solution reduces false alarm and false negative rates through multi-source information fusion, enabling the intelligent control system of the ink production process to more accurately identify and address bubble interference. This avoids problems such as incorrect material addition and product quality fluctuations caused by viscometer reading failure, ensuring the stability of the ink production process and the consistency of product quality. like Figure 2 The diagram illustrates a novel intelligent control system for ink production processes. Further embodiments of this application disclose a novel intelligent control system 100 for ink production processes, comprising: The parameter acquisition module 10 acquires the operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained from the top of the tank; wherein, the operating power of the stirring motor reflects the actual energy consumption of the stirrer in overcoming the resistance of the ink, the online viscometer reading reflects the apparent viscosity of the ink, and the amount of gas entrained from the top of the tank reflects the degree of air bubble mixing in the ink; The correlation analysis module 20 performs physical correlation analysis on the operating power of the stirring motor and the online viscometer reading, and constructs a contradiction intensity index between the operating power of the stirring motor and the online viscometer reading. When the contradiction intensity index exceeds the threshold and the amount of gas entrained at the top of the tank is abnormal, it is determined that the online viscometer reading is interfered with and fails. Intervention module 30 interrupts the original control strategy and starts a preset interference suppression program when a failure is detected. The parameter limiting module 40 uses the continuous decrease of the contradiction intensity index as the criterion for determining interference elimination until the original control strategy is restored. This system aims to achieve intelligent acquisition, analysis, and decision-making of multi-dimensional data during the ink production process through modular design, thereby effectively identifying and suppressing online viscometer reading distortion caused by factors such as air bubbles. Through a parameter acquisition module that monitors key production data in real time, a correlation analysis module that intelligently identifies abnormal correlations between data, an intervention module that promptly activates a corrective mechanism, and a parameter limitation module that continuously evaluates the intervention effect, this system can significantly improve the robustness and stability of the ink production process, ensuring consistent product quality. To better understand the system architecture of this application, each module is described in detail below. The parameter acquisition module is responsible for collecting key operational data during the ink production process in real time. The specific methods for acquiring the stirring motor's operating power, online viscometer readings, and the amount of gas entrained at the top of the tank have already been described in the above embodiments and will not be repeated here. It is important to emphasize that the parameter acquisition module can integrate various sensors and data interfaces. For example, it can communicate with power sensors, viscometers, level sensors, and acoustic sensors via industrial Ethernet or fieldbus protocols to ensure the real-time performance and accuracy of the data. This module can be configured to collect data periodically or in an event-driven manner and perform preliminary processing on the collected raw data, such as filtering and unit conversion, for use by subsequent modules. The correlation analysis module is responsible for performing in-depth analysis of the data provided by the parameter acquisition module to identify potential interference. The above implementation has already described the specific logic for performing physical correlation analysis on the stirring motor operating power and online viscometer readings, constructing a contradiction intensity index, and determining the failure of the online viscometer readings due to interference in conjunction with abnormal gas entrainment at the tank top; this will not be repeated here. It is important to emphasize that the correlation analysis module can be implemented as an independent computing unit, such as an industrial PC or embedded controller, running a preset algorithm model internally. This module can be configured to continuously monitor the data stream; once it detects that the contradiction intensity index exceeds a threshold and the gas entrainment at the tank top is abnormal, it will trigger a failure determination signal and transmit this signal to the intervention measures module. The intervention module is responsible for immediately taking preset corrective actions when the online viscometer reading is determined to be faulty. The specific operation of interrupting the original control strategy and activating the preset interference suppression program has already been described in the above embodiments and will not be repeated here. It is important to emphasize that the intervention module can be designed to communicate directly or indirectly with actuators on the production line (such as the stirrer motor frequency converter, solvent pump, defoamer dosing device, etc.). For example, when a failure determination signal is received, the module can send a speed reduction command to the stirrer motor controller, a pause command to the solvent dosing pump, and activate the defoamer spraying device. The response speed and execution accuracy of this module are crucial for timely loss mitigation; therefore, highly reliable control logic and hardware interfaces are typically employed. The parameter limiting module is responsible for continuously evaluating the intervention effect during the interference suppression program and restoring normal production after the interference is eliminated. The specific logic of using a continuous decrease in the contradiction intensity index as the criterion for interference elimination, until the original control strategy is restored, has already been described in the above implementation and will not be repeated here. It is important to emphasize that the parameter limiting module can be configured to continuously receive the contradiction intensity index output by the correlation analysis module and perform trend analysis on it. When the index continuously decreases and stabilizes within the normal range, the module will issue an interference elimination signal. Subsequently, the module can gradually lift the restrictions on material handling parameters, for example, by slowly increasing the speed of the stirring motor or reactivating the material addition control loop based on the viscometer reading, to ensure a smooth transition of the production process to a normal state. The intelligent control system of this application effectively solves the problem of control failure caused by air bubble interference in the online viscometer readings during traditional ink production processes by introducing a modular architecture and a multi-dimensional data fusion judgment mechanism. Traditional systems often rely on single sensor data for control. When the online viscometer reading is distorted due to air bubble interference, the system will make incorrect control decisions based on erroneous information. For example, when the viscosity actually increases, the system may reduce the addition of thickener because the reading is too low due to air bubbles, thus exacerbating the problem. In summary, the system of this application achieves refined and intelligent control of the ink production process through innovative intelligent judgment and intervention mechanisms, which is of significant technological advancement. The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A novel intelligent control method for ink production process, characterized in that, include: The operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained from the top of the tank are obtained; wherein, the operating power of the stirring motor reflects the actual energy consumption of the stirrer in overcoming the resistance of the ink, the online viscometer reading reflects the apparent viscosity of the ink, and the amount of gas entrained from the top of the tank reflects the degree of air bubble mixing in the ink; A physical correlation analysis is performed on the operating power of the stirring motor and the online viscometer reading to construct a contradiction intensity index between the operating power of the stirring motor and the online viscometer reading. When the contradiction intensity index exceeds the threshold and the amount of gas entrained at the top of the tank is abnormal, the online viscometer reading is determined to be disturbed and invalid. When a failure is detected, the original control strategy is interrupted and a preset interference suppression program is started; The continuous decrease in the aforementioned contradiction intensity index is used as the criterion for determining the elimination of interference until the original control strategy is restored.

2. The method according to claim 1, characterized in that, The steps for obtaining the operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained at the top of the tank include: The voltage and current signals at the power input terminal of the stirring motor are collected by a power sensor, and the instantaneous active power is calculated as the operating power of the stirring motor. The damping signal of ink flowing through the probe is collected by a vibratory viscometer and converted into a viscosity value as the reading of the online viscometer. Furthermore, the rate of change of liquid level fluctuation is monitored by a non-contact ultrasonic liquid level sensor, and the high-frequency energy density of the sound wave of bubble bursting is captured by an acoustic sensor. The degree of gas entrainment is then comprehensively judged as the amount of gas entrainment at the top of the tank.

3. The method according to claim 2, characterized in that, When a failure is detected, the original control strategy is interrupted, and a preset interference suppression program is activated, including: Pause the material addition operation based on the online viscometer reading, initiate foam suppression intervention, and restrict the automatic adjustment of material handling parameters.

4. The method according to claim 3, characterized in that, The steps of pausing the material addition operation based on the online viscometer reading, initiating foam suppression intervention, and limiting the automatic adjustment of material handling parameters include: Pause the material addition control loop based on the online viscometer reading to interrupt the solvent or thickener addition command. Simultaneously reduce the stirring motor speed to a preset low speed value to reduce gas entrainment, and start the defoamer adding device to spray defoamer onto the foam layer; Additionally, freeze the material handling parameters, including stirring speed and temperature, to maintain the current foam suppression settings.

5. The method according to claim 1, characterized in that, The step of performing physical correlation analysis on the operating power of the stirring motor and the online viscometer reading to construct a contradiction intensity index between the operating power of the stirring motor and the online viscometer reading, and determining that the online viscometer reading is interfered with and fails when the contradiction intensity index exceeds a threshold and the amount of gas entrainment at the top of the tank is abnormal, includes: Construct an index to assess the degree of discrepancy between the operating power of the stirring motor and the reading of the online viscometer; The amount of gas entrained at the top of the tank is fuzzy to generate a gas interference confidence level; Based on the increase in the intensity of the conflict, the weight ratio of the stirring motor operating power and the online viscometer reading in the risk assessment is dynamically adjusted. By integrating the aforementioned contradiction intensity index with the confidence level of gas interference, a comprehensive risk assessment is obtained; Based on the comprehensive risk assessment, it was determined that the online viscometer reading was malfunctioning due to interference.

6. The method according to claim 5, characterized in that, The steps for constructing the index of the degree of contradiction between the operating power of the stirring motor and the online viscometer reading include: Within a preset time period, when the average operating power of the stirring motor exceeds the upper limit of the first historical normal operating range and the average reading of the online viscometer is lower than the lower limit of the second historical normal operating range, the absolute value of the difference between the power increase and the viscosity decrease is calculated, and this absolute value of the difference is used as an indicator of the degree of contradiction between the operating power of the stirring motor and the online viscometer reading.

7. The method according to claim 5, characterized in that, The weighting of the stirring motor operating power and the online viscometer reading in risk assessment is dynamically adjusted based on the increase in the contradiction intensity index. The steps include: Obtain ink formulation information; Based on the ink formulation information, obtain the ink's sensitivity to air bubbles; Based on the ink formulation information and the sensitivity information, a weight adjustment factor is determined; The contradiction intensity index is corrected according to the weight adjustment factor to obtain the corrected contradiction intensity index.

8. The method according to claim 5, characterized in that, The step of fuzzing the amount of gas entrainment at the top of the tank to generate a gas interference confidence level includes: Based on the amount of gas entrained from the tank top, identify the noise components present in the amount of gas entrained from the tank top; The noise components are filtered to obtain the amount of gas entrained from the tank top after filtration. Based on the filtered amount of gas entrainment at the top of the tank, adjust the membership function of the gas entrainment signal in the amount of gas entrainment at the top of the tank. Based on the filtered amount of gas entrainment at the top of the tank, adjust the fuzzy rules of the gas entrainment signal in the amount of gas entrainment at the top of the tank. Based on the adjusted membership function and the adjusted fuzzy rules, the filtered gas entrainment at the top of the tank is processed to generate a gas interference confidence score.

9. The method according to claim 5, characterized in that, The step of integrating the contradiction intensity index and the gas interference confidence level to obtain a comprehensive risk assessment specifically includes: The adjusted weighting percentage of the contradiction intensity index is multiplied by the value of the contradiction intensity index, and then the weighting percentage of the gas interference confidence level is multiplied by the value of the gas interference confidence level to obtain the comprehensive risk value. When the overall risk value exceeds the preset overall threshold, the overall risk is determined to be that the online viscometer reading is interfered with and fails.

10. A novel intelligent control system for ink production process, characterized in that, The system includes: The parameter acquisition module acquires the operating power of the stirring motor, the online viscometer reading, and the amount of gas entrained from the top of the tank; wherein, the operating power of the stirring motor reflects the actual energy consumption of the stirrer in overcoming the resistance of the ink, the online viscometer reading reflects the apparent viscosity of the ink, and the amount of gas entrained from the top of the tank reflects the degree of air bubble mixing in the ink; The correlation analysis module performs physical correlation analysis on the operating power of the stirring motor and the online viscometer reading, and constructs a contradiction intensity index between the operating power of the stirring motor and the online viscometer reading. When the contradiction intensity index exceeds the threshold and the amount of gas entrained at the top of the tank is abnormal, it is determined that the online viscometer reading is interfered with and fails. The intervention module interrupts the original control strategy and starts a preset interference suppression program when a failure is detected. The parameter limiting module uses the continuous decrease of the contradiction intensity index as the criterion for determining interference elimination until the original control strategy is restored.

Images