A method for monitoring the automation of a production line for the production of foamed materials

Abstract

The present application relates to the technical field of production monitoring, and in particular to a production line automation monitoring method for foaming material production. The method monitors the mixing index by calculating the rotational speed uniformity in the low-speed mixing stage and determines the mixing unevenness coefficient at the last moment. In the high-speed shearing stage, the shearing deviation index is analyzed by matching the rotational speed and the current, the thermal reaction deviation degree is evaluated by combining the historical data and the thermal reaction index obtained by the mixing unevenness coefficient, and the thermal reaction activity coefficient at the last moment is determined. In the temperature control stage, the temperature control index is adjusted for monitoring according to the temperature historical deviation, the instantaneous pressure and the thermal reaction activity coefficient, and the monitoring and early warning of each stage are realized. The present application combines the real-time abnormal analysis of each production stage with the historical performance difference, and performs the whole-process chain influence tracking, so as to improve the accuracy and reliability of the production line monitoring and ensure the stable production quality of the foaming material.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of production monitoring, and in particular to a production line automation monitoring method for foaming material production. BACKGROUND

[0002] Foaming materials, such as polyurethane foam, polystyrene foam, etc., are widely used in the fields of construction, household appliances, packaging, etc. due to their light weight, heat insulation, cushioning, etc. The production process takes the stirred tank as the core equipment and needs to go through multiple stages of continuous process: the feeding stage: according to the formula, the raw materials such as polyol, catalyst, blowing agent, flame retardant, etc. are accurately put into the stirred tank, and the proportion of the raw materials directly affects the performance of the finished product; the low-speed mixing stage: the raw materials are preliminarily fused through low-speed stirring to avoid stratification caused by density difference, such as separation of liquid raw materials and solid fillers; the high-speed shearing stage: the raw materials are dispersed into small particles by the high-speed rotating paddle to realize molecular-level mixing, and the shearing strength in this stage determines the reactivity of the raw materials; the temperature control reaction stage: at a specific temperature, the raw materials undergo chemical reactions such as polymerization and crosslinking, accompanied by the decomposition of blowing agents to produce gas, forming a foam structure, and temperature deviation may cause uneven cell size or structure collapse.

[0003] In order to ensure the production quality, the existing production line monitoring technology usually sets threshold values for various monitoring indicators in different stages to identify equipment abnormalities. However, there are also significant correlations between actual foaming material production stages, such as abnormal paddle stirring speed in the low-speed mixing stage, which may cause raw material stratification and affect the shearing efficiency in the subsequent high-speed shearing stage, and unstable temperature, which may trigger premature decomposition of raw materials and form a chain reaction. The existing technology ignores the correlation between different stages, and when a single stage threshold analysis is inaccurate, the subsequent identification will also drift, resulting in errors in abnormal monitoring, affecting the production quality of foaming materials and the stability of equipment operation. SUMMARY

[0004] In order to solve the above technical problems in the prior art, the purpose of the present application is to provide a production line automation monitoring method for foaming material production, and the technical solution adopted is as follows:

[0005] The present application provides a production line automation monitoring method for foaming material production, which comprises:

[0006] In the continuous production stage of the stirred tank, 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 control reaction stage are obtained;

[0007] In the low-speed mixing stage, the monitoring mixing index at each time is obtained according to the uniform and stable performance of the previous stirring speed at each time; and the monitoring mixing degree at the last time in the low-speed mixing stage is taken as the mixing unevenness coefficient;

[0008] In the high-speed shearing stage, the matching performance of the rotational speed fluctuation and the current data in the local period before each time is analyzed to obtain a shearing deviation index of the time; in the local period before each time, a thermal reaction deviation degree of each time is obtained according to the temperature and pressure changes deviating from the same period in the history of the same production stage; a monitoring thermal reaction index of the time is obtained according to the shearing deviation index and the thermal reaction deviation degree of each time and a mixing unevenness coefficient; and the monitoring thermal reaction index of the last time in the high-speed shearing stage is taken as a thermal reaction activity coefficient;

[0009] In the temperature control reaction stage, a monitoring temperature control index of the time is obtained according to the historical deviation degree of the temperature at the time and the instantaneous pressure change and combined with the thermal reaction activity coefficient adjustment;

[0010] The monitoring mixing index, the monitoring thermal reaction index and the monitoring temperature control index in the production stage are used for monitoring and early warning.

[0011] Further, the monitoring mixing index acquisition method comprises:

[0012] In the low-speed mixing stage, the difference between the stirring rotational speed of each time and the stirring rotational speed of the previous time is calculated and normalized to obtain the cutting mutation degree of each time; and the difference between the stirring rotational speed of each time and the preset rotational speed is taken as the fluctuation degree of each time.

[0013] The product of the cutting mutation degree and the fluctuation degree of each time is taken as the mixing deviation degree of each time; and the monitoring mixing index of each time is obtained by combining the mixing deviation degrees of all times before each time in the low-speed mixing stage.

[0014] Further, the shearing deviation index acquisition method comprises:

[0015] For any time in the high-speed shearing stage, the difference between the stirring rotational speed of each time and the preset rotational speed is calculated in the preset local window before the time to obtain a difference sequence of the time.

[0016] In the preset local window before the time, the difference between the current data of each time and the average of all current data in the preset local window is calculated and normalized to obtain the current fluctuation degree of each time.

[0017] The difference sequence and the current data sequence in the preset local window before the time are matched by DTW to obtain a matching group; and the average of the current fluctuation degree in each matching group is taken as the output weight of each matching group.

[0018] The distance between the difference sequence and the current data sequence in each matching group is weighted and summed with the output weight of the matching group as the weight to obtain the shearing deviation index of the time.

[0019] Further, the method for obtaining the thermal reaction deviation degree comprises:

[0020] For any time point in the high-speed shearing stage, obtain the temperature range in the preset local window before the time point and the pressure average value;

[0021] Based on the temperature range fluctuation deviation of the preset local window before the time point and the same period in the historical production stage, obtain the temperature historical deviation index of the time point;

[0022] Based on the pressure average value deviation of the preset local window before the time point and the same period in the historical production stage, obtain the pressure historical deviation index of the time point;

[0023] Combine the temperature historical deviation index and the pressure historical deviation index of the time point to obtain the thermal reaction deviation degree of the time point.

[0024] Further, the method for obtaining the temperature historical deviation index comprises:

[0025] Obtain the historical temperature range of the preset local window before the time point in each historical production stage;

[0026] Calculate the standard deviation of all historical temperature ranges as the historical temperature fluctuation value, and calculate the average value of all historical temperature ranges as the historical temperature performance value;

[0027] The ratio of the difference between the temperature range of the time point and the historical temperature performance value to the historical temperature fluctuation value is taken as the temperature historical deviation index of the time point.

[0028] Further, the method for obtaining the pressure historical deviation index comprises:

[0029] Obtain the historical pressure average value of the preset local window before the time point in each historical production stage, and calculate the average value of all historical pressure average values as the historical pressure performance value;

[0030] The difference between the pressure average value at the time point and the historical pressure performance value is taken as the pressure historical deviation index of the time point.

[0031] Further, the method for obtaining the thermal reaction index comprises:

[0032] In the high-speed shearing stage, the product of the shearing deviation degree and the thermal reaction deviation degree of each time point is taken as the thermal reaction activity index of the time point.

[0033] For any one moment in the high-speed shearing stage, the average of the thermal reaction activity indexes of all moments in the preset local window before the moment is multiplied by the value after negative correlation mapping and normalization processing of the mixing unevenness coefficient to obtain the monitoring thermal reaction index of the moment.

[0034] Further, the method for obtaining the monitoring temperature control index comprises:

[0035] For any one moment in the temperature control reaction stage, the historical temperature at the same moment in each historical production stage is obtained; the standard deviation of all historical temperatures is taken as the historical fluctuation value; the ratio of the difference between the temperature at the moment and the preset temperature parameter value to the historical fluctuation value is taken as the instantaneous temperature deviation performance at the moment.

[0036] The ratio of the pressure difference between the moment and the previous moment to the time difference is taken as the instantaneous pressure change performance at the moment; the initial difference index at the moment is obtained by combining the instantaneous temperature deviation performance and the instantaneous pressure change performance at the moment.

[0037] The initial difference index at the moment is multiplied by the value after normalization processing of the thermal reaction activity coefficient to obtain the adjustment value at the moment; the sum of the initial difference index and the adjustment value at the moment is taken as the monitoring temperature control index at the moment.

[0038] Further, the monitoring and early warning based on the monitoring mixing index, the monitoring thermal reaction index and the monitoring temperature control index in the production stage comprises:

[0039] In the low-speed mixing stage, when the monitoring mixing degree is greater than the preset mixing threshold, early warning is performed.

[0040] In the high-speed shearing stage, when the monitoring thermal reaction index is greater than the preset shearing threshold, early warning is performed.

[0041] In the temperature control reaction stage, when the monitoring temperature control index is greater than the preset temperature control threshold, early warning is performed.

[0042] Further, the monitoring mixing index at each moment in the low-speed mixing stage is obtained by combining the mixing deviation degree of all moments before each moment, comprising:

[0043] For any one moment in the low-speed mixing stage, the sum of the mixing deviation degree of all moments before the moment and the moment is taken as the monitoring mixing index at the moment.

[0044] The present application has the following beneficial effects:

[0045] The present application acquires key data of each stage, ensures that monitoring analysis covers the whole production process, and facilitates subsequent correlation of the influence of different stages. In the low-speed mixing stage, the mixing index is calculated by the rotational speed uniformity, the initial mixing state of the raw materials is evaluated in real time, the stratification risk caused by unstable rotational speed is identified, the pre-sequencing abnormality at the last time of the stage is taken as the mixing unevenness coefficient, participates in the monitoring and adjustment of the subsequent shear effect, and the chain influence analysis is increased. Then, in the high-speed shear stage, the shear deviation index is analyzed by matching the rotational speed and the current, the abnormality of the device load caused by uneven material is identified, the thermal reaction deviation is evaluated by combining the historical data to evaluate the temperature and pressure deviation, the reaction abnormality is evaluated in a timely manner, the thermal reaction index is obtained by fusing the mixing unevenness coefficient, the dynamic monitoring of the reaction activity in the shear stage is realized, the accuracy and timeliness of abnormality identification are improved, and the thermal reaction index at the last time is determined to provide correlation influence basis for the temperature control stage. In the temperature control stage, the temperature control index is adjusted according to the temperature historical deviation, the instantaneous pressure and the thermal reaction activity coefficient, the reaction state is more accurately monitored, and the quality problem caused by temperature and pressure abnormality is avoided. Based on the index early warning of each stage, the timely intervention of the whole process risk is realized. The present application combines the real-time abnormality analysis of each production stage with the historical performance difference, traces the chain influence of the whole process, improves the accuracy and reliability of the production line monitoring, and guarantees the stable production quality of the foaming material. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0047] Figure 1 A flow chart of a production line automatic monitoring method for foaming material production provided by an embodiment of the present application;

[0048] Figure 2 A flow chart of a thermal reaction deviation acquisition method provided by an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following will combine the drawings and the preferred embodiments to specifically and clearly explain the specific implementation, structure, features and effects of the production line automatic monitoring method for foaming material production according to the present application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0050] 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 application belongs.

[0051] The application provides a production line automation monitoring method for foamed material production.

[0052] Please refer to Figure 1 , which shows a flow chart of a production line automation monitoring method for foamed material production according to an embodiment of the application, and the method comprises the following steps:

[0053] S1: In the continuous production stage of the stirred tank, 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 control reaction stage are obtained.

[0054] In the production of foamed material, the stirred tank production stage is the core process that determines the quality of the finished foamed material, and the stirred tank production bears the key processes of raw material mixing, shearing and reaction. The stirred tank production process includes: the feeding stage: receiving the raw materials such as polyols and catalysts delivered according to the formula; the low-speed mixing stage: preliminary mixing of the raw materials by low-speed stirring to prepare for subsequent processing; the high-speed shearing stage: high-speed stirring to generate shear force to disperse the raw materials uniformly; and the temperature control reaction stage: promoting the raw materials to react to form a foamed structure at a suitable temperature.

[0055] Due to the correlation between actual 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 stratify, affecting the uniformity of the subsequent process, and thus may cause the paddle to be blocked in the high-speed shearing stage, etc., or the temperature to be unstable and present small fluctuations, which may cause unexpected exothermic reactions between the raw materials, causing the foaming agent and other raw materials to decompose prematurely, thereby increasing the pressure in the stirred tank and forming a chain effect.

[0056] Therefore, monitoring data is collected for each stage for subsequent monitoring, adjustment and analysis. In the low-speed mixing stage, the stirring speed of the paddle at each time is collected. In the high-speed shearing stage, the stirring speed of the paddle, the temperature of the material in the stirred tank, the pressure inside the stirred tank and the current data are collected. In the temperature control reaction stage, the temperature and pressure at each time are collected.

[0057] It can be understood that the collected data is preprocessed, which can include data standardization and time scale normalization, so as to facilitate unified data analysis and remove dimensional effects. It should be noted that data preprocessing is a well-known technical means in the art, and the setting of the collection frequency can be controlled by the implementer, and therefore will not be described or limited here.

[0058] In addition, in the stirred tank continuous production stage, the foamed material usually has a production plan, so when multiple batches of foamed material are continuously produced, the product performance of the historically produced product on the production plan is the same. To facilitate subsequent analysis based on historical production conditions, the data on the production stage with the same historical production stage and the current feeding production stage are obtained from the production record, the feeding ratio of the historical production stage and the current feeding production stage, and the preset parameters of the equipment of each production stage are the same. The data on the production stage are provided for historical data comparison and analysis. The number of historical production stages can be controlled by the implementer, and in the embodiment of the present application, it can be 10, which is not limited here.

[0059] S2: In the low-speed mixing stage, a monitoring mixing index is obtained according to the uniform performance stability of the stirring speed at each time; and the monitoring mixing degree at the last time of the low-speed mixing stage is taken as a mixing unevenness coefficient.

[0060] In the low-speed mixing stage, the main problem that may exist is the stratification of raw materials due to unstable stirring speed, so the monitoring can be based on the uniform performance of the stirring speed to reflect the initial mixing of the raw materials. The better the performance stability of the stirring speed in this stage, the more uniform the initial mixing of the raw materials, the lower the abnormality of the raw materials, and the relatively lower the subsequent influence.

[0061] Preferably, in the embodiment of the present application, the method for obtaining the monitoring mixing index by the uniform performance of the stirring speed at each time comprises:

[0062] Considering that the foamed material raw materials contain solid fillers such as flame retardant particles, if the speed suddenly jumps during low-speed stirring, such as paddle jamming or belt slipping, the local raw materials are not stirred, and then the "dead zone" is more likely to be formed, that is, the stratification risk is generated. Therefore, in the low-speed mixing stage, the difference between the stirring speed at each time and the stirring speed at the previous time is calculated and normalized to obtain the cutting mutation degree at each time, which reflects the mutation degree of the speed at the time.

[0063] It should be noted that normalization is a technical means familiar to those skilled in the art, and the selection of normalization can be linear normalization or standard normalization, and the specific normalization method is not limited here. In particular, for the initial time without the previous time, the mutation analysis is not affected.

[0064] Further, the difference between the stirring speed at each time and the preset speed is taken as the fluctuation at each time, reflecting the speed fluctuation at the time itself, and in the embodiment of the present application, the preset speed can be set according to the specific implementation scene, such as 30 r / min, which is not limited herein. In the whole stirring process, since the raw materials need to be preliminarily sheared and crushed, the speed will inevitably change due to the obstruction of the raw materials, but when the speed changes greatly, the influence on the uniform mixing is higher.

[0065] Compared with slow speed fluctuation, such as normal load change, the sudden change has greater damage to the uniformity of mixing, so the cutting mutation degree is given higher weight in the fluctuation analysis. Therefore, further, the product of the cutting mutation degree at each time and the fluctuation degree is taken as the mixing deviation degree at each time, reflecting the mixing fluctuation degree at each time.

[0066] Finally, the monitoring mixing index at each time is obtained by combining the mixing deviation degrees of all previous times in the low-speed mixing stage, and the greater the monitoring mixing index, the more likely the layered phenomenon caused by the feed pulse occurs, and the higher the current abnormal situation may be. In the embodiment of the present application, for any time in the low-speed mixing stage, the sum of the mixing deviation degrees of all previous times and the time is taken as the monitoring mixing index of the time, which comprehensively reflects the mixing unevenness influence degree shown at the current time based on the monitoring mixing index, and the current stage can be monitored based on the monitoring mixing index.

[0067] Until the last time of the low-speed mixing stage, the greater the comprehensive mixing deviation degree, the worse the initial mixing effect, and the more likely the shearing efficiency of the subsequent high-speed shearing stage is affected, so the monitoring mixing degree of the last time is taken as the mixing unevenness coefficient to participate in the analysis of the subsequent high-speed shearing stage.

[0068] S3: In the high-speed shearing stage, the matching performance of the speed fluctuation and the current data in the local period before each time is analyzed to obtain the shearing deviation index of the time; in the local period before each time, the thermal reaction deviation degree of each time is obtained according to the deviation of the temperature and pressure changes from the same period in the historical production stage; the monitoring thermal reaction index of the time is obtained according to the shearing deviation index and the thermal reaction deviation degree of each time, and the mixing unevenness coefficient; the monitoring thermal reaction index of the last time of the high-speed shearing stage is taken as the thermal reaction activity coefficient.

[0069] The high-speed shearing stage is relatively more important than the low-speed mixing stage, and the internal shearing process often causes the premature decomposition of raw materials due to the unsuitable shearing strength, and is also affected by the processing quality of the low-speed mixing stage, so the mixing unevenness coefficient of the previous stage can be combined with the shearing analysis of the current stage to monitor the current high-speed shearing stage with different sensitivities.

[0070] When the low-speed mixing stage mixes the material with a low quality, the material viscosity gradient is large due to uneven material during shearing, resulting in an increase in the instantaneous resistance to shearing, and further causing the output current of the current to be unstable. Therefore, if the low-speed mixing is uneven, the material will appear to be locally aggregated, resulting in unstable blade resistance, which is manifested as the rotation speed and motor current fluctuation being out of sync.

[0071] Therefore, first, the resistance deviation of shearing is analyzed with respect to the rotation speed fluctuation and current fluctuation in a local period, and preferably, in the embodiments of the present application, the method for obtaining the shearing deviation index comprises:

[0072] For any moment in the high-speed shearing stage, in a preset local window before the moment, the difference between the stirring rotation speed at each moment and the preset rotation speed is calculated to obtain a difference sequence at the moment, which represents the rotation speed fluctuation characteristics in a local period. In the embodiments of the present application, the preset local window is set to a window of 10 seconds before each moment, and the local data fluctuation performance is analyzed through the local period. The specific window size can be adjusted by the implementer according to the specific implementation scenario, which is not limited here.

[0073] Further, in the preset local window before the 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 degree at each moment. In high-speed shearing, the motor current directly corresponds to the blade load. If the material is uniform, the load is stable, and the current should fluctuate around the window mean with a small amplitude, that is, the current fluctuation degree is small. However, if the material is uneven, such as clumping, stratification, etc., the blade resistance will suddenly change, resulting in an increase in the deviation of the current from the mean, that is, the current fluctuation degree is large. Therefore, the current fluctuation degree can amplify the part that is more likely to produce abnormal fluctuations.

[0074] Further, the difference sequence and the current data sequence in the preset local window before the moment are matched by DTW to obtain a matching group. It should be noted that the dynamic time warping (DTW) algorithm matching is a well-known technical means to those skilled in the art, which will not be described here.

[0075] Each matching group reflects the most matched situation of the fluctuation change trend of the two sequences, so the mean of the current fluctuation degree in each matching group is taken as the output weight of each matching group. The distance between the difference sequence and the current data sequence in each matching group is weighted and summed with the output weight of the matching group as the weight to obtain the shearing deviation index at the moment.

[0076] The distance in each matching group refers to a difference measure between data points of the rotational speed difference value sequence and the current sequence at corresponding time points in the matching group. In one specific embodiment of the present application, the difference measure can be obtained by using the Euclidean distance, and in other embodiments, the absolute value difference can also be used to quantify the difference between the two sequences at the position of the matching group.

[0077] The smaller the distance and are, the higher the matching degree is, and the better the synchronization of the rotational speed fluctuation and the current fluctuation is, which reflects that the material is in normal shearing performance, and the current equipment operating state is more accurately evaluated after weighting the current fluctuation degree.

[0078] In the high-speed shearing stage, the corresponding shearing force of the mixer is significantly increased, which causes the material to heat up. Due to the unevenness of the material during high-speed shearing, the material itself also heats up significantly, and thus the temperature rises in the initial shearing stage. The frictional heat and the chemical reaction heat are superimposed in the shearing process, and if the temperature and pressure change deviate from the historical normal state, such as rapid temperature rise and pressure surge, it is more likely that the raw materials react in advance, such as foaming agent decomposition and other abnormalities.

[0079] Therefore, by analyzing the deviation degree of the current temperature and pressure in combination with the historical production situation, the abnormality in the current stage can be monitored, and preferably, in the embodiment of the present application, the method for obtaining the thermal reaction deviation degree is as follows: Figure 2 which shows a flow chart of a method for obtaining a thermal reaction deviation degree according to one embodiment of the present application. The method comprises the following steps:

[0080] S311: For any time point in the high-speed shearing stage, obtain the temperature range and the pressure average in a preset local window before the time point.

[0081] The difference between the maximum temperature and the minimum temperature in the preset local window before the time point is taken as the temperature range, which reflects the temperature change value, and the pressure average is also obtained to reflect the reaction degree of the material in the period. According to the temperature change fluctuation and the pressure distribution, the influence of the possible early heating in this stage is reflected.

[0082] S312: Based on the temperature range fluctuation deviation in the preset local window before the time point and the historical temperature range in the same period in the historical production stage, obtain the temperature historical deviation index of the time point.

[0083] First, consider the deviation degree of the temperature difference. If the current temperature range deviates from the historical situation more, the possible abnormality degree of this stage in the temperature analysis is higher. In the embodiment of the present application, the historical temperature range of the preset local window before the time point in each historical production stage in the same period is obtained. Due to the consistency of the historical batches, in each historical production stage, the data within the same period in the production time sequence can be selected to obtain the historical temperature range in the same production period.

[0084] The standard deviation of all historical temperature ranges is taken as a historical temperature fluctuation value, which reflects the range of temperature range fluctuations under normal historical conditions by using the standard deviation. The average value of all historical temperature ranges is taken as a historical temperature performance value, which reflects the basic distribution size of the historical temperature range in the same period range.

[0085] Finally, the ratio of the difference between the temperature range at this moment and the historical temperature performance value to the historical temperature fluctuation value is taken as the temperature historical deviation index at this moment. The greater the difference between the temperature range at this moment and the historical temperature performance value, and the smaller the historical temperature fluctuation value, the higher the temperature deviation degree at this moment.

[0086] It can be understood that due to the fluctuation changes in actual production, all temperature ranges may not be equal, so the historical temperature fluctuation value cannot be zero. In other embodiments of the present application, to ensure the reliability of parameter acquisition, the sum of the historical temperature fluctuation value and a preset parameter threshold value is taken as the denominator after the difference between the temperature range at this moment and the historical temperature performance value as the numerator. The preset parameter threshold value is set to 0.001 to ensure that the denominator is not zero, which will not be described further herein.

[0087] S313: Based on the deviation of the pressure mean value in the same period in the historical production stage before the preset local window from the present moment, a pressure historical deviation index at this moment is obtained.

[0088] Secondly, the deviation degree of the pressure is considered. The pressure is used to reflect the reaction intensity and material state in the kettle. If the current pressure mean value deviates from the historical condition more, the higher the abnormal degree of this stage in the material reaction analysis. In the embodiments of the present application, the historical pressure mean value of the preset local window before the present moment in the same period in each historical production stage is obtained, and the average value of all historical pressure mean values is taken as a historical pressure performance, which reflects the basic distribution size of the historical pressure mean value in the same period range.

[0089] Finally, the difference between the pressure mean value at this moment and the historical pressure performance value is taken as the pressure historical deviation index at this moment, and the difference is the absolute value of the difference between the pressure mean value and the historical pressure performance value. The greater the pressure historical deviation index, the greater the deviation degree of the material reaction.

[0090] In other embodiments of the present application, the ratio of the pressure mean value at this moment to the historical pressure performance value can also be taken as the pressure historical deviation index at this moment. When chemical heat reaction occurs, the pressure mean value will be higher, so the deviation index will be larger, which will not be described further herein.

[0091] S314: The heat reaction deviation degree at this moment is obtained by combining the temperature historical deviation index and the pressure historical deviation index at this moment.

[0092] By comprehensively reflecting the deviation degree from two aspects of temperature and pressure, in the embodiment of the present application, the product of the temperature history deviation index and the pressure history deviation index at this moment is taken as the thermal reaction deviation degree at this moment, and the greater the thermal reaction deviation degree, the more likely the thermal reaction abnormality at this moment is.

[0093] In other embodiments of the present application, the sum of the temperature history deviation index and the pressure history deviation index at this moment can also be taken as the thermal reaction deviation degree at this moment, which is not limited herein.

[0094] The temperature in the stirred tank gradually tends to be stable with the increase of the uniformity of material shearing, and at this time, the mixing unevenness obtained through the low-speed mixing stage can represent the increase of the corresponding heat generation performance of the stirrer under the condition of doing the same work. For example, when the mixing uniformity is poor, it represents that the heat generation caused by the initial shearing of the material is relatively higher under the same time, and at this time, it is normal that the temperature increases relatively fast compared with the stirring process of the historical batch.

[0095] Meanwhile, the speed performance is considered for the abnormality, and when the shearing deviation index value is large, it means that the speed performance of the local period is worse, and the possibility of abnormal heat generation is higher, so the abnormal sensitive contribution of the current deviation needs to be amplified.

[0096] Therefore, the shearing deviation index and the mixing unevenness coefficient are combined to adjust the sensitivity of the abnormal performance of different data in this stage. Preferably, in the embodiment of the present application, the method for obtaining the monitoring thermal reaction index comprises:

[0097] In the high-speed shearing stage, the product of the shearing deviation degree and the thermal reaction deviation degree at each moment is taken as the thermal reaction activity index at this moment, and the tolerance degree of the thermal reaction deviation is adjusted from the speed angle by the shearing deviation degree, and when the shearing deviation degree is larger, it means that the abnormality itself is higher, so the thermal reaction activity index is larger.

[0098] Finally, for any moment in the high-speed shearing stage, the mean value of the thermal reaction activity index of all moments in the preset local window before this moment is multiplied by the value after the negative correlation mapping and the normalization processing of the mixing unevenness coefficient, to obtain the monitoring thermal reaction index at this moment, and the high-speed shearing stage can be monitored by the monitoring thermal reaction index.

[0099] Since the heat condition change has certain persistence, the average of the thermal reaction activity index in the local period of each time reflects the comprehensive abnormal estimation, when the average of the thermal reaction activity index is overall high, it is very likely to produce decomposition and the like at this time. When the mixing unevenness coefficient is larger, it indicates that the previous mixing condition is higher, and the possibility of generating some extra heat is higher, so when the mixing unevenness coefficient is larger, the abnormal judgment can be appropriately inhibited.

[0100] It should be noted that the negative correlation mapping is a technical means familiar to those skilled in the art, such as using a negative exponential power form or an inverse proportion form, and the like, which is not limited and elaborated here.

[0101] By monitoring the thermal reaction index at the last moment of the stable high-speed shearing stage, the final heat influence of this stage is reflected, which can affect the reaction intensity of the next temperature control stage, so the monitoring thermal reaction index at the last moment of the high-speed shearing stage is taken as a thermal reaction activity coefficient, and is used in the abnormal monitoring of the temperature control reaction stage.

[0102] S4: In the temperature control reaction stage, the monitoring temperature control index of the time is obtained according to the historical deviation degree of the temperature at the time and the instantaneous pressure change, combined with the thermal reaction activity coefficient adjustment.

[0103] In the temperature control reaction stage of the foaming material, the temperature is the core driving factor of the chemical reaction, but the chemical reaction, such as decomposition of the foaming agent and polymer crosslinking, can directly cause the pressure change in the kettle. For example, when the temperature is too high, the foaming agent such as HCFCs can accelerate the decomposition and release a large amount of gas, so that the pressure rises suddenly, and vice versa, if the temperature is too low, the reaction is incomplete, the gas is released slowly, and the pressure change rate is low. Therefore, the instantaneous pressure change is used as an indirect index for quantifying the severity of the chemical reaction at the time in the temperature control reaction stage.

[0104] The thermal reaction activity coefficient reflects the shearing heat accumulation degree of the high-speed shearing stage, and affects the initial reaction activity of the temperature control stage. If the thermal reaction activity coefficient value is high, such as large temperature fluctuation in the high-speed shearing stage and violent reaction of the material, it indicates that the raw material is in a high activity state, and the temperature control stage has a lower fault tolerance rate to the temperature and pressure fluctuation change, that is, a small temperature deviation or pressure change can trigger a chain reaction, such as local overheating leading to cell rupture.

[0105] Therefore, preferably, in the embodiment of the present application, the method for obtaining the detection temperature control index in combination with the thermal reaction activity coefficient adjustment comprises:

[0106] Firstly, for any time in the temperature control reaction stage, the historical temperature of the time at the same time in each historical same production stage is obtained, and the deviation is reflected by the historical temperature fluctuation deviation at the time. The standard deviation of all historical temperatures is taken as the historical fluctuation value, which is the temperature fluctuation range degree of the corresponding time in the historical production.

[0107] Further, the ratio of the difference between the temperature at the moment and the preset temperature parameter value and the historical fluctuation value is taken as the instantaneous temperature deviation performance at the moment. When the difference between the temperature at the moment and the preset temperature parameter value is greater and the historical fluctuation value is smaller, it indicates that the relative degree of the current temperature fluctuation is relatively severe, and the instantaneous temperature performance is more significant. It should be noted that the implementer of the preset temperature parameter value can set it according to the specific implementation scene, which is not specifically limited here.

[0108] Further, the ratio of the pressure difference between the moment and the previous moment and the time difference is taken as the instantaneous pressure change performance at the moment. The instantaneous change rate is reflected by the ratio of the numerical change between the moments and the time difference. When the ratio is greater, it indicates that the instantaneous change degree is greater, and the abnormal situation is more significant.

[0109] Therefore, the initial difference index at the moment is obtained by combining the instantaneous temperature deviation performance at the moment and the instantaneous pressure change performance at the moment. In the embodiment of the present application, the sum of the instantaneous temperature deviation performance at the moment and the instantaneous pressure change performance at the moment is taken as the initial difference index at the moment. The greater the initial difference index, the more significant the abnormality in temperature and pressure change.

[0110] In other embodiments of the present application, the product of the instantaneous temperature deviation performance at the moment and the instantaneous pressure change performance at the moment can also be taken as the initial difference index at the moment, which is not described and limited here.

[0111] Finally, the initial difference index at the moment is multiplied by the value after normalization processing of the thermal reaction activity coefficient to obtain the adjustment value at the moment. The degree of risk transmission in the previous stage is measured by the thermal reaction activity coefficient adjustment. The sum of the initial difference index at the moment and the adjustment value at the moment is taken as the monitoring temperature control index at the moment, which can be monitored based on the monitoring temperature control index.

[0112] S5: monitoring and early warning based on the monitoring mixing index, the monitoring thermal reaction index and the monitoring temperature control index in the production stage.

[0113] After the production evaluation of each stage, different early warning strategies are performed through the indexes at the moment in the stage. In the embodiment of the present application, in the low-speed mixing stage, when the monitoring mixing degree is greater than the preset mixing threshold, it indicates that the mixing fluctuation at the moment is greater, and the initial mixing cutting may be abnormal, which needs to be warned. In one specific embodiment of the present application, after the warning, the measures of suspending feeding and checking the mechanical state of the mixer can be taken.

[0114] In the high-speed shearing stage, when the monitored thermal reaction index is greater than the preset shearing threshold value, it indicates that the thermal reaction activity is too high at this moment, and the heat release leads to a higher possibility of abnormal production, and a warning is needed. In one specific embodiment of the present application, the shearing speed can be reduced by 10%-15% after the warning, or the cooling system can be started.

[0115] In the temperature control reaction stage, when the monitored temperature control index is greater than the preset shearing threshold value, it indicates that the abnormal degree of deviation of the strain chemical reaction is large, and a warning is needed. In one specific embodiment of the present application, emergency pressure relief or termination of the reaction is taken after the warning.

[0116] In the embodiments of the present application, the preset mixing threshold value can be set to 0.7, the preset shearing threshold value can be set to 0.8, and the preset shearing threshold value can be set to 0.8. The specific values can be adjusted by the implementer, and are not limited herein.

[0117] In summary, the present application acquires key data of each stage, ensures that the monitoring and analysis covers the whole production process, and facilitates subsequent correlation of the influence of different stages. In the low-speed mixing stage, the mixing index is calculated by the rotational speed uniformity, the initial mixing state of the raw materials is evaluated in real time, the stratification risk caused by unstable rotational speed is identified, the pre-sequence abnormality analyzed at the last moment of the stage is used as the mixing unevenness coefficient, participates in the monitoring and adjustment of the subsequent shearing effect, and the chain influence analysis is increased. Then, in the high-speed shearing stage, the shearing deviation index is analyzed by matching the rotational speed and the current, the abnormality of the equipment load caused by uneven material is identified, the thermal reaction deviation is evaluated by combining the historical data and the temperature and pressure deviation, the reaction abnormality is evaluated in a timely manner, the thermal reaction index is obtained by fusing the mixing unevenness coefficient, the dynamic monitoring of the reaction activity in the shearing stage is realized, the accuracy and timeliness of abnormal identification are improved, and the thermal reaction index at the last moment is determined to provide correlation influence basis for the temperature control stage. In the temperature control stage, the temperature control index is adjusted according to the temperature historical deviation, the instantaneous pressure and the thermal reaction activity coefficient, the reaction state is more accurately monitored, and the quality problem caused by temperature and pressure abnormality is avoided. Based on the index warning of each stage, timely intervention of the whole process risk is realized. The present application combines the real-time abnormality analysis of each production stage with the historical performance difference, traces the chain influence of the whole process, improves the accuracy and reliability of the production line monitoring, and ensures the stable production quality of the foaming material.

[0118] It should be noted that the above-mentioned order of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0119] The various embodiments described in this specification are presented by way of example, and each embodiment is not inherently more important than any other embodiment.

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 monitoring mixing index at each moment is obtained based on the uniformity and stability of the stirring speed before each moment; the monitoring mixing index 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 average 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 index exceeds the 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 prior to that moment and the mixing deviation at that moment is taken as the monitoring mixing index for that moment.

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