Production line automatic monitoring method for foam material production

Abstract

The invention relates to the technical field of production monitoring, in particular to a production line automatic monitoring method for foam material production. According to the method, in a low-speed mixing stage, a mixing index is calculated through rotation speed uniformity for monitoring, and a mixing non-uniform coefficient at the last moment is determined; in the high-speed shearing stage, rotating speed and current matching is analyzed to obtain a shearing deviation index, temperature and pressure deviation is evaluated in combination with historical data to obtain a thermal reaction deviation degree, a mixing non-uniform coefficient is obtained to obtain a thermal reaction index for monitoring, and a thermal reaction activity coefficient at the last moment is determined; in the temperature control stage, temperature control indexes are adjusted according to historical temperature deviation, instantaneous pressure and a thermal reaction activity coefficient for monitoring, and monitoring and early warning in each stage are achieved. By associating real-time abnormal analysis closing of each production stage and combining historical performance differences, full-process chain type influence tracking is carried out, the accuracy and reliability of production line monitoring are improved, and stable production quality of foaming materials is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of production monitoring technology, and specifically to an automated monitoring method for a production line used in the production of foamed materials. Background Technology

[0002] Foamed materials, such as polyurethane foam and polystyrene foam, are widely used in construction, home appliances, and packaging due to their lightweight, heat insulation, and cushioning properties. Their production process, with a mixing tank as the core equipment, involves a multi-stage continuous process: Feeding stage: Polyols, catalysts, foaming agents, flame retardants, and other raw materials are precisely added to the mixing tank according to the formula; the proportion of raw materials directly affects the performance of the finished product. Low-speed mixing stage: Low-speed stirring allows the raw materials to initially fuse, avoiding stratification caused by density differences, such as the separation of liquid raw materials from solid fillers. High-speed shearing stage: High-speed rotating blades disperse the raw materials into tiny particles, achieving molecular-level mixing; the shear strength in this stage determines the reactivity of the raw materials. Temperature-controlled reaction stage: At a specific temperature, the raw materials undergo polymerization, cross-linking, and other chemical reactions, accompanied by the decomposition of the foaming agent to produce gas, forming a foam structure. Temperature deviations may lead to uneven cell size or structural collapse.

[0003] To ensure production quality, existing production line monitoring technologies typically set thresholds for various monitoring indicators at different stages to identify equipment anomalies. However, significant correlations exist between different stages of actual foam material production. For example, abnormal paddle stirring speed during the low-speed mixing stage may cause raw material stratification, affecting the shearing efficiency of the subsequent high-speed shearing stage; unstable temperature may trigger premature decomposition of raw materials and form a chain reaction. Existing technologies ignore the correlations between different stages. When the threshold analysis for a single stage is inaccurate, subsequent identification will also drift, leading to errors in anomaly monitoring and affecting the production quality of foam materials and the stability of equipment operation. Summary of the Invention

[0004] To address the technical problems in the prior art, the purpose of this application is to provide an automated monitoring method for a production line used in the production of foamed materials. The specific technical solution adopted is as follows: This application provides an automated monitoring method for a production line used in the production of foamed materials, the method comprising: In the continuous production stage of the stirred tank, the stirring speed, temperature, pressure and current data of the low-speed mixing stage, the stirring speed, temperature, pressure and current of the high-speed shearing stage, and the temperature and pressure of the temperature-controlled reaction stage are obtained. During the low-speed mixing stage, the mixing index at each moment is obtained based on the uniformity and stability of the stirring speed before each moment; the degree of mixing at the last moment of the low-speed mixing stage is used as the mixing non-uniformity coefficient. During the high-speed shearing stage, the matching performance of rotational speed fluctuations and current data in the local time period before each moment is analyzed to obtain the shearing deviation index at each moment. In the local time period before each moment, the deviation of temperature and pressure changes in the same time period of the same production stage in history is used to obtain the thermal response deviation degree at each moment. Based on the shearing deviation index and thermal response deviation degree at each moment, as well as the mixing non-uniformity coefficient, the monitoring thermal response index at each moment is obtained. The monitoring thermal response index at the last moment of the high-speed shearing stage is used as the thermal response activity coefficient. During the temperature control reaction stage, the monitoring and temperature control indicators at each moment are obtained based on the historical deviation of the temperature at that moment and the instantaneous pressure change, combined with the adjustment of the thermal reaction activity coefficient. Monitoring and early warning are based on monitoring mixing indicators, thermal reaction indicators, and temperature control indicators during the production stage.

[0005] Furthermore, the method for obtaining the monitoring mixed indicators includes: In the low-speed mixing stage, the difference in stirring speed between each time step and the previous time step is calculated and normalized to obtain the shear change degree at each time step; the difference between the stirring speed at each time step and the preset speed is used as the fluctuation degree at each time step. The product of the cutting abruptness and volatility at each moment is used as the mixing deviation at each moment; combined with the mixing deviations of all moments before each moment in the low-speed mixing phase, the monitoring mixing index at each moment is obtained.

[0006] Furthermore, the method for obtaining the shear deviation index includes: For any moment in the high-speed shearing stage, within a preset local window before that moment, calculate the difference between the stirring speed and the preset speed at each moment to obtain the difference sequence at that moment. Within a preset local window before that moment, the difference between the current data at each moment and the mean of all current data in the preset local window is calculated and normalized to obtain the current fluctuation at each moment. The difference sequence in the preset local window before the given time is matched with the current data sequence using DTW to obtain matching groups; the mean current fluctuation at each time point in each matching group is used as the output weight of each matching group. Using the output weights of the matching groups as weights, the distances between the difference sequences and the current data sequences in each matching group are weighted and summed to obtain the shear deviation index at that moment.

[0007] Furthermore, the method for obtaining the thermal reaction deviation includes: For any moment in the high-speed shearing stage, obtain the temperature range and average pressure in a preset local window before that moment; Based on the temperature range fluctuation deviation between the preset local window before this moment and the same period in the same production stage in history, the historical temperature deviation index at this moment is obtained. Based on the deviation of the pressure average value between the preset local window before this moment and the same period in the same production stage in history, obtain the historical pressure deviation index at this moment. By combining the historical temperature deviation index and the historical pressure deviation index at that moment, the thermal response deviation at that moment can be obtained.

[0008] Furthermore, the method for obtaining the historical temperature deviation index includes: Obtain the historical temperature range of a preset local window at the same time in each historical and production stage before that moment; The standard deviation of all historical temperature ranges is used as the historical temperature fluctuation value; the average of all historical temperature ranges is calculated as the historical temperature performance value. The ratio of the difference between the temperature range at that moment and the historical temperature performance value to the historical temperature fluctuation value is used as the historical temperature deviation index at that moment.

[0009] Furthermore, the method for obtaining the historical pressure deviation index includes: Obtain the historical average pressure value of the same period in each historical production stage within the preset local window before this moment; calculate the average of all historical average pressure values ​​as the historical pressure performance value; The difference between the mean pressure at that moment and the historical pressure performance value is used as the historical deviation indicator of pressure at that moment.

[0010] Furthermore, the method for obtaining the monitored thermal reaction indicators includes: During the high-speed shearing phase, the product of the shear deviation and the thermal reaction deviation at each moment is used as the thermal reaction activity index at that moment. For any given moment in the high-speed shearing stage, the average value of the thermal reactivity index at all moments in the preset local window before that moment is multiplied by the value after negative correlation mapping and normalization of the mixing non-uniformity coefficient to obtain the monitored thermal reactivity index at that moment.

[0011] Furthermore, the method for obtaining the monitoring and temperature control indicators includes: For any moment in the temperature control reaction stage, obtain the historical temperature at that moment in each historical and production stage; take the standard deviation of all historical temperatures as the historical fluctuation value; take the ratio of the difference between the temperature at that moment and the preset temperature parameter value to the historical fluctuation value as the instantaneous temperature deviation performance at that moment. The ratio of the pressure difference between this moment and the previous moment to the time difference is used as the instantaneous pressure change performance at this moment; combined with the instantaneous temperature deviation performance and the instantaneous pressure change performance at this moment, the initial difference index at this moment is obtained. Multiply the initial difference index at that moment by the normalized value of the thermal reactivity coefficient to obtain the adjustment value at that moment; use the sum of the initial difference index and the adjustment value at that moment as the monitoring and temperature control index at that moment.

[0012] Furthermore, the monitoring and early warning system based on monitoring mixing indicators, thermal reaction indicators, and temperature control indicators during the production stage includes: During the low-speed mixing phase, an early warning is issued when the monitored mixing degree exceeds a preset mixing threshold. During the high-speed shearing stage, an early warning is issued when the monitored thermal reaction index exceeds the preset shear threshold. During the temperature control reaction phase, an early warning will be issued when the monitored temperature control index exceeds the preset temperature control threshold.

[0013] Furthermore, the mixing deviation of each moment preceding each moment in the low-speed mixing phase is combined to obtain the monitoring mixing index for each moment, including: For any given moment in the low-speed mixing phase, the sum of the mixing deviations of all moments prior to that moment and the mixing deviation at that moment is taken as the monitoring mixing index for that moment.

[0014] The present invention has the following beneficial effects: This invention specifically acquires key data at each stage, ensuring monitoring and analysis cover the entire production process and facilitating subsequent correlation of the impact of different stages. In the low-speed mixing stage, mixing indices are calculated based on rotational speed uniformity to assess the initial mixing state of raw materials in real time, identify stratification risks caused by unstable rotational speed, and use preceding anomalies analyzed at the end of the stage as a mixing non-uniformity coefficient to participate in the monitoring and adjustment of subsequent shearing effects, increasing chain effect analysis. Then, in the high-speed shearing stage, shear deviation indices are obtained by analyzing the matching of rotational speed and current, identifying abnormal equipment loads caused by material non-uniformity, and assessing thermal reaction deviations by combining historical data with temperature and pressure deviations to promptly evaluate reaction anomalies. The mixing non-uniformity coefficient is then integrated to obtain thermal reaction indices, achieving dynamic monitoring of reaction activity in the shearing stage, improving the accuracy and timeliness of anomaly identification, and providing a basis for correlation of impacts in the temperature control stage. In the temperature control stage, temperature control indices are adjusted based on historical temperature deviations, instantaneous pressure, and thermal reaction activity coefficients to more accurately monitor the reaction state and avoid quality problems caused by abnormal temperature and pressure. Based on early warnings of indices at each stage, timely intervention in risks throughout the entire process is achieved. This invention improves the accuracy and reliability of production line monitoring by linking real-time anomaly analysis of each production stage with historical performance differences, and conducts full-process chain impact tracking to ensure stable production quality of foamed materials. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart of an automated monitoring method for a production line used in the production of foamed materials, provided as an embodiment of the present invention; Figure 2 This is a flowchart illustrating a method for obtaining thermal reaction deviation according to an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an automated monitoring method for a production line used in the production of foamed materials according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details a specific scheme for an automated monitoring method for a production line used in the production of foamed materials, provided by the present invention.

[0020] Please see Figure 1 The diagram illustrates a flowchart of an automated monitoring method for a production line used in the production of foamed materials, according to an embodiment of the present invention. The method includes the following steps: S1: In the continuous production stage of the stirred tank, obtain the stirring speed in the low-speed mixing stage, the stirring speed, temperature, pressure and current data in the high-speed shearing stage, and the temperature and pressure in the temperature-controlled reaction stage.

[0021] In the production of foamed materials, the stirred tank production stage is the core process that determines the quality of the finished foamed material. The stirred tank production stage is responsible for the key processes of raw material mixing, shearing, and reaction. The stirred tank production process includes: feeding stage: receiving raw materials such as polyols and catalysts according to the formula; low-speed mixing stage: initially mixing the raw materials through low-speed stirring to prepare for subsequent processing; high-speed shearing stage: generating shearing force through high-speed stirring to disperse the raw materials evenly; temperature-controlled reaction stage: promoting the reaction of raw materials at a suitable temperature to form a foam structure.

[0022] Because there are interrelated effects between different stages, for example, in the low-speed mixing stage, if the paddle stirring speed is lower than the preset speed, it may cause the raw materials to separate, affecting the uniformity of the subsequent process. This may lead to greater resistance on the paddles in the high-speed shearing stage, or the temperature may be unstable and fluctuate slightly, which may cause unexpected exothermic reactions between the raw materials, resulting in the premature decomposition of raw materials such as foaming agents, thereby increasing the pressure in the mixing vessel and forming a chain reaction.

[0023] Therefore, monitoring data is acquired separately for each stage for subsequent monitoring, adjustment, and analysis. In this embodiment of the invention, during the low-speed mixing stage, the stirring speed of the impeller is collected at each moment. During the high-speed shearing stage, the stirring speed of the impeller, the temperature of the material inside the mixing vessel, the pressure inside the mixing vessel, and the current data are collected at each moment. During the temperature-controlled reaction stage, the temperature and pressure are collected at each moment.

[0024] It is understandable that monitoring data undergoes preprocessing, which may include data standardization and time-scale normalization to facilitate unified data analysis and remove the influence of units. It should be noted that data preprocessing is a well-known technique in the field, and the implementation of the data collection frequency setting can be adjusted by the implementer, and will not be elaborated upon or restricted here.

[0025] Furthermore, during the continuous production stage in the mixing tank, foaming materials typically have a production plan. Therefore, when multiple batches of foaming materials are produced continuously, the performance of the products corresponding to the historically produced products in the production plan is the same. To facilitate subsequent analysis based on historical production conditions, data on the production stages where the feeding ratio and preset equipment parameters for each production stage are identical, obtained from the production records, are used to provide data support for historical data comparison and analysis. The number of historical production stages can be adjusted by the implementer; in this embodiment, it can be 10, but no limitation is imposed here.

[0026] S2: During the low-speed mixing stage, based on the uniformity and stability of the stirring speed before each moment, the monitoring mixing index at each moment is obtained; the monitoring mixing degree at the last moment of the low-speed mixing stage is used as the mixing non-uniformity coefficient.

[0027] In the low-speed mixing stage, the main problem may be the separation of raw materials due to the unstable speed of the mixer. Therefore, the monitoring can reflect the initial mixing of raw materials based on the uniformity of the mixing speed. The more stable the mixer speed is in this stage, the more uniform the initial mixing of raw materials, the lower the degree of abnormality, and the lower the impact on subsequent processes.

[0028] Preferably, in this embodiment of the invention, the method for obtaining the monitoring mixing index by observing the uniformity of the stirring speed before a given time step includes: Considering that the raw materials of foaming materials contain solid fillers, such as flame retardant particles, if the speed suddenly changes during low-speed mixing, such as blade jamming or belt slippage, resulting in some raw materials not being mixed, it is easier to form a "dead zone", that is, to generate the risk of stratification. Therefore, in the low-speed mixing stage, the difference in stirring speed between each moment and the previous moment is calculated and normalized to obtain the cutting change degree at each moment, which reflects the degree of speed change at each moment.

[0029] It should be noted that normalization is a technique well-known to those skilled in the art, and the choice of normalization can be linear normalization or standard normalization, etc., and the specific normalization method is not limited here. In particular, for initial moments without a previous moment, the impact of mutation analysis is not performed.

[0030] Furthermore, the difference between the stirring speed at each moment and the preset speed is used as the fluctuation degree at each moment, reflecting the speed fluctuation at that moment. In this embodiment of the invention, the preset speed can be set by the implementer according to the specific implementation scenario, such as a preset of 30 r / min, which is not limited here. During the entire stirring process, since the raw materials are to be initially sheared and crushed, changes in speed are inevitable due to the resistance of the raw materials. However, when the speed change is large, the impact on the uniformity of mixing is greater.

[0031] Compared to slow speed fluctuations, such as normal load changes, sudden changes have a greater impact on mixing uniformity. Therefore, the degree of abrupt change in cutting is given higher weight in fluctuation analysis. Consequently, the product of the degree of abrupt change in cutting and the degree of fluctuation at each time step is taken as the mixing deviation at each time step, reflecting the degree of mixing fluctuation at each time step.

[0032] Finally, by combining the mixing deviations of all previous moments in the low-speed mixing stage, a monitoring mixing index is obtained for each moment. A larger monitoring mixing index indicates a higher likelihood of feed pulses causing stratification, suggesting a potentially more severe anomaly. In this embodiment of the invention, for any given moment in the low-speed mixing stage, the sum of the mixing deviations of all previous moments and the current moment is used as the monitoring mixing index for that moment. By comprehensively considering the degree of abnormal deviations before each moment, the degree of uneven mixing currently observed can be reflected, allowing for anomaly monitoring in the current stage based on the monitoring mixing index.

[0033] Until the very end of the low-speed mixing stage, the greater the overall mixing deviation, the worse the initial mixing effect, which may directly affect the shearing efficiency of the subsequent high-speed shearing stage. Therefore, the mixing degree monitored at the last moment is used as the mixing non-uniformity coefficient and is used in the analysis of the subsequent high-speed shearing stage.

[0034] S3: During the high-speed shearing stage, analyze the matching performance of rotational speed fluctuations and current data in the local time period before each moment to obtain the shearing deviation index at that moment; within the local time period before each moment, based on the deviation of temperature and pressure changes in the same time period of the same production stage in history, obtain the thermal response deviation degree at each moment; based on the shearing deviation index and thermal response deviation degree at each moment, as well as the mixing non-uniformity coefficient, obtain the monitoring thermal response index at that moment; use the monitoring thermal response index at the last moment of the high-speed shearing stage as the thermal response activity coefficient.

[0035] The high-speed shearing stage is relatively more important than the low-speed mixing stage. During the shearing process within the high-speed shearing stage, inappropriate shear strength often leads to premature decomposition of raw materials. It is also affected by the processing quality of the low-speed mixing stage. Therefore, the mixing non-uniformity coefficient of the previous stage can be combined with the shearing analysis of the stage itself to monitor the current high-speed shearing stage with different sensitivities.

[0036] When the mixing quality is low during the low-speed mixing stage, the uneven material distribution during shearing creates a large viscosity gradient, leading to increased instantaneous resistance during shearing and consequently, instability in the output current. Therefore, uneven mixing at low speeds can cause localized material aggregation, resulting in unstable blade resistance, manifested as asynchronous fluctuations in speed and motor current.

[0037] Therefore, the first step is to analyze the shear resistance deviation based on the speed and current fluctuations during local time periods. Preferably, in this embodiment of the invention, the method for obtaining the shear deviation index includes: For any given moment in the high-speed shearing stage, within a preset local window preceding that moment, the difference between the stirring speed and the preset speed is calculated to obtain a difference sequence for that moment, characterizing the speed fluctuation features over a local time period. In this embodiment of the invention, the preset local window is set to a window spanning 10 seconds prior to each moment. By analyzing the local data fluctuation performance through this local time period, the specific window size can be adjusted by the implementer according to the specific implementation scenario, and is not limited here.

[0038] Furthermore, within a preset local window prior to that moment, the difference between the current data at each moment and the mean of all current data within the preset local window is calculated and normalized to obtain the current fluctuation at each moment. During high-speed shearing, the motor current directly corresponds to the blade load. If the material is uniform and the load is stable, the current should fluctuate slightly around the window mean, meaning the current fluctuation is small. However, if the material is uneven, such as agglomeration or stratification, the blade resistance will change suddenly, causing the current to deviate from the mean by a larger margin, meaning the current fluctuation is large. Therefore, the current fluctuation can amplify the parts most likely to cause abnormal fluctuations.

[0039] Furthermore, the difference sequence in the preset local window before that moment is matched with the current data sequence using DTW to obtain a matching group. It should be noted that the Dynamic Time Warping (DTW) algorithm matching is a well-known technique in the art and will not be described in detail here.

[0040] Each matching group reflects the situation where the fluctuation trends of the two sequences are most matched. Therefore, the mean current fluctuation at each time step in each matching group is used as the output weight of each matching group. Using the output weight of the matching group as the weight, the distances between the difference sequence and the current data sequence in each matching group are weighted and summed to obtain the shear deviation index at that time step.

[0041] The distance in each matching group refers to the difference between the data points at corresponding time points of the speed difference sequence and the current sequence in the matching group. In one specific embodiment of the present invention, the difference can be obtained by Euclidean distance, and in other embodiments, it can also be obtained by absolute difference, which is used to quantify the difference between the two sequences at the position of the matching group.

[0042] The smaller the distance, the higher the matching degree, the better the synchronization between speed fluctuation and current fluctuation, and the more the material is in normal shearing behavior. The current operating status of the equipment can be more accurately assessed by weighting the current fluctuation degree.

[0043] During the high-speed shearing stage, the increased shearing force of the mixer causes the material to heat up. The uneven distribution of material during high-speed shearing further contributes to this heat generation, resulting in a temperature rise in the initial shearing phase. The combined frictional heat and exothermic chemical reaction during shearing, along with any deviation from historical temperature and pressure patterns (such as excessively rapid temperature increases and sudden pressure rises), strongly suggests premature reaction of the raw materials, potentially indicating abnormalities like foaming agent decomposition.

[0044] Therefore, analyzing the deviation of current temperature and pressure based on historical production data facilitates anomaly monitoring at the current stage. Preferably, in this embodiment of the invention, the method for obtaining the thermal reaction deviation is described in [reference needed]. Figure 2 The diagram illustrates a flowchart of a method for obtaining thermal reaction deviation according to an embodiment of the present invention, the method comprising the following steps: S311: For any moment in the high-speed shearing stage, obtain the temperature range and average pressure in the preset local window before that moment.

[0045] The temperature range is calculated by taking the difference between the maximum and minimum temperatures in a preset local window before a given time point. This range reflects the temperature change. At the same time, the average pressure is obtained to reflect the degree of material reaction during the time period. The fluctuations in temperature and the magnitude of pressure distribution reflect the potential impact of premature heating during this stage.

[0046] S312: Based on the temperature range fluctuation deviation between the preset local window before this moment and the same period in the same production stage in history, obtain the historical temperature deviation index at this moment.

[0047] First, consider the degree of temperature deviation. If the current temperature range deviates significantly from historical values, it indicates a higher degree of potential anomaly in temperature analysis at this stage. In this embodiment of the invention, the historical temperature range of a preset local window prior to this moment is obtained within the same historical production stage. Due to the consistency of historical batches, data within the same time frame in terms of production sequence can be selected for each historical production stage to obtain the historical temperature range during the synchronous production period.

[0048] The standard deviation of all historical temperature ranges is used as the historical temperature fluctuation value, reflecting the degree of fluctuation in temperature range under normal historical conditions. The average of all historical temperature ranges is calculated as the historical temperature performance value, reflecting the basic distribution of historical temperature ranges within the same time period.

[0049] Finally, the ratio of the difference between the temperature range at that moment and the historical temperature performance value to the historical temperature fluctuation value is used as the historical temperature deviation index at that moment. The greater the difference between the temperature range at that moment and the historical temperature performance value, and the smaller the historical temperature fluctuation value, the higher the degree of temperature deviation at that moment.

[0050] It is understandable that due to the fluctuations in actual production, it is impossible for all temperature ranges to be equal. Therefore, the historical temperature fluctuation value cannot be zero. In other embodiments of the present invention, in order to ensure the reliability of parameter acquisition, the difference between the temperature range at this moment and the historical temperature performance value is used as the numerator, and the sum of the historical temperature fluctuation value and the preset parameter threshold is used as the denominator. The preset parameter threshold is set to 0.001 to ensure that the denominator is not zero. Further details are not provided here.

[0051] S313: Based on the deviation of the pressure average value in the preset local window before this moment from the pressure average value in the same period of the same production stage in history, obtain the historical pressure deviation index at this moment.

[0052] Secondly, the degree of pressure deviation is considered. Pressure reflects the intensity of the reaction within the reactor and the state of the materials. If the current average pressure deviates significantly from historical values, it indicates a higher degree of potential anomaly in the material reaction analysis at this stage. In this embodiment of the invention, the historical average pressure value of a preset local window before this moment is obtained for each historical production stage. The average of all historical average pressure values ​​is calculated as the historical pressure representation, reflecting the basic distribution of historical average pressure values ​​within the same time period.

[0053] Finally, the difference between the average pressure at that moment and the historical pressure performance value is used as the pressure historical deviation index at that moment. The difference is the absolute value of the difference between the average pressure and the historical pressure performance value. The larger the pressure historical deviation index, the greater the degree of deviation of the material reaction history.

[0054] In other embodiments of the present invention, the ratio of the average pressure at that moment to the historical pressure performance value can also be used as the historical pressure deviation index at that moment. The average pressure will be higher when a chemical-thermal reaction occurs, so the deviation index will be larger, which will not be elaborated here.

[0055] S314: Combine the historical temperature deviation index and historical pressure deviation index at this moment to obtain the thermal response deviation at this moment.

[0056] By comprehensively reflecting the degree of deviation from both temperature and pressure, in this embodiment of the invention, the product of the historical temperature deviation index and the historical pressure deviation index at that moment is taken as the thermal response deviation at that moment. The greater the thermal response deviation, the greater the possibility of thermal response anomaly at that moment.

[0057] In other embodiments of the present invention, the sum of the historical temperature deviation index and the historical pressure deviation index at that moment can also be used as the thermal response deviation at that moment, and there is no limitation on this.

[0058] The temperature inside the mixing vessel gradually stabilizes as the shear uniformity of the material increases. At this point, the mixing unevenness observed during the low-speed mixing stage indicates the degree of increase in heat generation by the mixer when performing the same work. For example, poor mixing uniformity indicates that the initial shear-induced heat generation of the material is relatively higher within the same timeframe. Therefore, a faster temperature increase compared to previous batches is normal.

[0059] At the same time, the impact of rotational speed performance on abnormalities should be considered. When the shear deviation index value is large, it means that the rotational speed performance is worse in a local period, and the possibility of abnormal heating is higher. Therefore, it is necessary to amplify the abnormal sensitivity contribution of the current deviation.

[0060] Therefore, the sensitivity to different data anomalies during this stage is adjusted by combining the shear deviation index and the mixing non-uniformity coefficient. Preferably, in this embodiment of the invention, the method for obtaining the monitoring thermal reaction index includes: During the high-speed shearing phase, the product of the shear deviation and the thermal reaction deviation at each moment is used as the thermal reaction activity index at that moment. The tolerance for thermal reaction deviation is adjusted from the perspective of rotational speed by adjusting the shear deviation. The larger the shear deviation, the higher the possibility of anomaly, and therefore the larger the thermal reaction activity index.

[0061] Finally, for any moment in the high-speed shearing stage, the mean value of the thermal reactivity index of all moments in the preset local window before that moment is multiplied by the value after negative correlation mapping and normalization of the mixing non-uniformity coefficient to obtain the monitoring thermal reactivity index at that moment. By monitoring the thermal reactivity index, anomalies in the high-speed shearing stage can be monitored.

[0062] Because this change in thermal conditions is somewhat continuous, the average value of the thermal reactivity index at each local time point is used to reflect the comprehensive anomaly estimate. When the overall average value of the thermal reactivity index is high, it indicates that decomposition or other phenomena are very likely to occur prematurely at this time. In this case, the larger the mixing non-uniformity coefficient, the higher the level of preceding mixing, and the higher the possibility of generating additional heat. Therefore, when the mixing non-uniformity coefficient is large, the anomaly judgment can be appropriately suppressed.

[0063] It should be noted that negative correlation mapping is a technique well known to those skilled in the art, such as using negative exponential form or inverse proportional form, etc., and will not be limited or elaborated here.

[0064] By monitoring the thermal reaction indicators at the final moment of the high-speed shearing stage after stabilization, the final heat impact of this stage can be reflected, which may affect the reaction intensity of the next temperature control stage. Therefore, the thermal reaction indicators at the final moment of the high-speed shearing stage are used as thermal reaction activity coefficients to participate in the anomaly monitoring of the temperature control reaction stage.

[0065] S4: During the temperature control reaction stage, based on the historical deviation of the temperature at a given time and the instantaneous pressure change, combined with the adjustment of the thermal reaction activity coefficient, the monitoring and temperature control indicators at that time are obtained.

[0066] In the temperature-controlled reaction stage of foaming materials, temperature is the core driving factor of the chemical reaction. However, chemical reactions, such as the decomposition of foaming agents and polymer crosslinking, directly lead to changes in pressure inside the reactor. For example, when the temperature is too high, foaming agents such as HCFCs will decompose rapidly, releasing a large amount of gas and causing a sudden increase in pressure. Conversely, if the temperature is too low, the reaction is incomplete, gas release is slow, and the pressure change rate is low. Therefore, instantaneous pressure change is used as an indirect indicator to quantify the intensity of the chemical reaction at any given moment during the temperature-controlled reaction stage.

[0067] The thermal reactivity coefficient reflects the degree of shear heat accumulation during the high-speed shearing stage and affects the initial reactivity during the temperature control stage. If the thermal reactivity coefficient is high, such as large temperature fluctuations and violent material reactions during the high-speed shearing stage, it indicates that the raw material is already in a highly active state. The tolerance for temperature and pressure fluctuations during the temperature control stage is even lower. That is, even a small temperature deviation or pressure change may trigger a chain reaction, such as local overheating leading to cell rupture.

[0068] Therefore, preferably, in this embodiment of the invention, the method for obtaining the detection temperature control index by combining the adjustment of the thermal reactivity coefficient includes: First, for any given moment in the temperature-controlled reaction phase, obtain the historical temperature at that moment in each historical production phase. The deviation is reflected by the historical temperature fluctuation at that moment. The standard deviation of all historical temperatures is used as the historical fluctuation value, representing the degree of temperature fluctuation range at the corresponding moment in historical production.

[0069] Furthermore, the ratio of the difference between the temperature at this moment and the preset temperature parameter value to the historical fluctuation value is used as the instantaneous temperature deviation performance at that moment. The greater the difference between the temperature at this moment and the preset temperature parameter value, and the smaller the historical fluctuation value, the more severe the current temperature fluctuation is, and the more significant the instantaneous temperature abnormality is. It should be noted that the implementer can set the preset temperature parameter value according to the specific implementation scenario, and no specific restrictions are imposed here.

[0070] Furthermore, the ratio of the pressure difference between this moment and the previous moment to the time difference is used as the instantaneous pressure change performance at this moment. The instantaneous change rate is reflected by the ratio of the change in value between moments to the time difference. The larger the ratio, the greater the instantaneous change and the more significant the abnormal situation.

[0071] Therefore, by combining the instantaneous temperature deviation performance and the instantaneous pressure change performance at that moment, the initial difference index at that moment is obtained. In this embodiment of the invention, the sum of the instantaneous temperature deviation performance and the instantaneous pressure change performance at that moment is used as the initial difference index at that moment. The larger the initial difference index, the more significant the anomaly in temperature and pressure changes.

[0072] In other embodiments of the present invention, the product of the instantaneous temperature deviation performance and the instantaneous pressure change performance at that moment can also be used as the initial difference index at that moment, which will not be elaborated or limited here.

[0073] Finally, the initial difference index at that moment is multiplied by the normalized value of the thermal reactivity coefficient to obtain the adjusted value at that moment. The degree of risk transmission in the previous stage is measured by adjusting the thermal reactivity coefficient. The sum of the initial difference index and the adjusted value at that moment is used as the monitoring and temperature control index for that moment, allowing for monitoring based on the detected temperature control index.

[0074] S5: Monitoring and early warning are based on monitoring mixing indicators, thermal reaction indicators, and temperature control indicators during the production stage.

[0075] After evaluating production at each stage, different early warning strategies are implemented based on the indicators at each stage. In this embodiment of the invention, during the low-speed mixing stage, when the monitored mixing degree exceeds a preset mixing threshold, it indicates that the mixing fluctuation at this moment is large, and the initial mixing and cutting may be abnormal, requiring an early warning. In one specific embodiment of the invention, after the early warning, measures such as suspending feeding and checking the mechanical status of the mixer can be taken.

[0076] During the high-speed shearing stage, when the monitored thermal reaction index is greater than the preset shearing threshold, it indicates that the thermal reaction activity is too high at this moment, and the heat release is likely to cause production abnormalities, requiring an early warning. In a specific embodiment of the present invention, after the early warning, the shearing speed can be reduced by 10%-15%, or the cooling system can be activated.

[0077] During the temperature-controlled reaction stage, if the monitored temperature control index exceeds the preset shear threshold, it indicates a significant deviation from the normal chemical reaction, requiring an early warning. In one specific embodiment of the invention, an emergency depressurization or reaction termination is initiated after the early warning.

[0078] In this embodiment of the invention, the preset mixing threshold can be set to 0.7, the preset shearing threshold can be set to 0.8, and the specific values ​​can be adjusted by the implementer himself, without any limitation.

[0079] In summary, this invention specifically acquires key data at each stage, ensuring monitoring and analysis cover the entire production process and facilitating subsequent correlation of the impact of different stages. In the low-speed mixing stage, mixing indicators are calculated based on rotational speed uniformity to assess the initial mixing state of raw materials in real time, identify the risk of stratification caused by unstable rotational speed, and use the preceding anomalies analyzed at the end of the stage as a mixing non-uniformity coefficient to participate in the monitoring and adjustment of subsequent shearing effects, increasing chain effect analysis. Furthermore, in the high-speed shearing stage, the shearing deviation index is obtained by analyzing the matching of rotational speed and current, identifying abnormal equipment loads caused by material non-uniformity, and assessing the thermal reaction deviation by combining historical data with temperature and pressure deviations to promptly assess reaction anomalies. The mixing non-uniformity coefficient is then integrated to obtain the thermal reaction index, achieving dynamic monitoring of the reaction activity in the shearing stage, improving the accuracy and timeliness of anomaly identification, and simultaneously providing a basis for correlation of impacts in the temperature control stage. In the temperature control stage, the temperature control index is adjusted based on historical temperature deviations, instantaneous pressure, and the thermal reaction activity coefficient, more accurately monitoring the reaction state and avoiding quality problems caused by abnormal temperature and pressure. Based on early warnings of indicators at each stage, timely intervention in risks throughout the entire process is achieved. This invention improves the accuracy and reliability of production line monitoring by linking real-time anomaly analysis of each production stage with historical performance differences, and conducts full-process chain impact tracking to ensure stable production quality of foamed materials.

[0080] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0081] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. An automated monitoring method for a production line used in the production of foamed materials, characterized in that, The method includes: In the continuous production stage of the stirred tank, the stirring speed, temperature, pressure and current data of the low-speed mixing stage, the stirring speed, temperature, pressure and current of the high-speed shearing stage, and the temperature and pressure of the temperature-controlled reaction stage are obtained. During the low-speed mixing stage, the mixing index at each moment is obtained based on the uniformity and stability of the stirring speed before each moment; the degree of mixing at the last moment of the low-speed mixing stage is used as the mixing non-uniformity coefficient. During the high-speed shearing stage, the matching performance of rotational speed fluctuations and current data in the local time period before each moment is analyzed to obtain the shearing deviation index at each moment. In the local time period before each moment, the deviation of temperature and pressure changes in the same time period of the same production stage in history is used to obtain the thermal response deviation degree at each moment. Based on the shearing deviation index and thermal response deviation degree at each moment, as well as the mixing non-uniformity coefficient, the monitoring thermal response index at each moment is obtained. The monitoring thermal response index at the last moment of the high-speed shearing stage is used as the thermal response activity coefficient. During the temperature control reaction stage, the monitoring and temperature control indicators at each moment are obtained based on the historical deviation of the temperature at that moment and the instantaneous pressure change, combined with the adjustment of the thermal reaction activity coefficient. Monitoring and early warning are based on monitoring mixing indicators, thermal reaction indicators, and temperature control indicators during the production stage.

2. The automated monitoring method for a production line used in the production of foamed materials according to claim 1, characterized in that, The method for obtaining the monitoring mixed indicators includes: In the low-speed mixing stage, the difference in stirring speed between each time step and the previous time step is calculated and normalized to obtain the shear change degree at each time step; the difference between the stirring speed at each time step and the preset speed is used as the fluctuation degree at each time step. The product of the cutting abruptness and volatility at each moment is used as the mixing deviation at each moment; combined with the mixing deviations of all moments before each moment in the low-speed mixing phase, the monitoring mixing index at each moment is obtained.

3. The automated monitoring method for a production line used in the production of foamed materials according to claim 1, characterized in that, The method for obtaining the shear deviation index includes: For any moment in the high-speed shearing stage, within a preset local window before that moment, calculate the difference between the stirring speed and the preset speed at each moment to obtain the difference sequence at that moment. Within a preset local window before that moment, the difference between the current data at each moment and the mean of all current data in the preset local window is calculated and normalized to obtain the current fluctuation at each moment. The difference sequence in the preset local window before the given time is matched with the current data sequence using DTW to obtain matching groups; the mean current fluctuation at each time point in each matching group is used as the output weight of each matching group. Using the output weights of the matching groups as weights, the distances between the difference sequences and the current data sequences in each matching group are weighted and summed to obtain the shear deviation index at that moment.

4. The automated monitoring method for a production line used in the production of foamed materials according to claim 1, characterized in that, The method for obtaining the thermal reaction deviation includes: For any moment in the high-speed shearing stage, obtain the temperature range and average pressure in a preset local window before that moment; Based on the temperature range fluctuation deviation between the preset local window before this moment and the same period in the same production stage in history, the historical temperature deviation index at this moment is obtained. Based on the deviation of the pressure average value between the preset local window before this moment and the same period in the same production stage in history, obtain the historical pressure deviation index at this moment. By combining the historical temperature deviation index and the historical pressure deviation index at that moment, the thermal response deviation at that moment can be obtained.

5. The automated monitoring method for a production line used in the production of foamed materials according to claim 4, characterized in that, The method for obtaining the historical temperature deviation index includes: Obtain the historical temperature range of a preset local window at the same time in each historical and production stage before that moment; The standard deviation of all historical temperature ranges is used as the historical temperature fluctuation value; the average of all historical temperature ranges is calculated as the historical temperature performance value. The ratio of the difference between the temperature range at that moment and the historical temperature performance value to the historical temperature fluctuation value is used as the historical temperature deviation index at that moment.

6. The automated monitoring method for a production line used in the production of foamed materials according to claim 4, characterized in that, The method for obtaining the historical pressure deviation index includes: Obtain the historical average pressure value of the same period in each historical production stage within the preset local window before this moment; calculate the average of all historical average pressure values ​​as the historical pressure performance value; The difference between the mean pressure at that moment and the historical pressure performance value is used as the historical deviation indicator of pressure at that moment.

7. The automated monitoring method for a production line used in the production of foamed materials according to claim 1, characterized in that, The method for obtaining the monitoring thermal reaction indicators includes: During the high-speed shearing phase, the product of the shear deviation and the thermal reaction deviation at each moment is used as the thermal reaction activity index at that moment. For any given moment in the high-speed shearing stage, the average value of the thermal reactivity index at all moments in the preset local window before that moment is multiplied by the value after negative correlation mapping and normalization of the mixing non-uniformity coefficient to obtain the monitored thermal reactivity index at that moment.

8. The automated monitoring method for a production line used in the production of foamed materials according to claim 1, characterized in that, The methods for obtaining the monitoring and temperature control indicators include: For any moment in the temperature control reaction stage, obtain the historical temperature at that moment in each historical and production stage; take the standard deviation of all historical temperatures as the historical fluctuation value; take the ratio of the difference between the temperature at that moment and the preset temperature parameter value to the historical fluctuation value as the instantaneous temperature deviation performance at that moment. The ratio of the pressure difference between this moment and the previous moment to the time difference is used as the instantaneous pressure change performance at this moment; combined with the instantaneous temperature deviation performance and the instantaneous pressure change performance at this moment, the initial difference index at this moment is obtained. Multiply the initial difference index at that moment by the normalized value of the thermal reactivity coefficient to obtain the adjustment value at that moment; use the sum of the initial difference index and the adjustment value at that moment as the monitoring and temperature control index at that moment.

9. The automated monitoring method for a production line used in the production of foamed materials according to claim 1, characterized in that, The monitoring and early warning system based on monitoring mixing indicators, thermal reaction indicators, and temperature control indicators during the production stage includes: During the low-speed mixing phase, an early warning is issued when the monitored mixing degree exceeds a preset mixing threshold. During the high-speed shearing stage, an early warning is issued when the monitored thermal reaction index exceeds the preset shear threshold. During the temperature control reaction phase, an early warning will be issued when the monitored temperature control index exceeds the preset temperature control threshold.

10. The automated monitoring method for a production line used in the production of foamed materials according to claim 2, characterized in that, The mixing index for each moment is obtained by combining the mixing deviation of all moments prior to each moment in the low-speed mixing phase, including: For any given moment in the low-speed mixing phase, the sum of the mixing deviations of all moments preceding that moment and the moment at that moment is taken as the monitoring mixing index for that moment.

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