A granulator control method for producing water dispersible granules

Abstract

The present application relates to the technical field of water dispersible granule, and particularly relates to a granulator granulation control method for water dispersible granule production. The method comprises the following steps: obtaining the outlet humidity of the main air duct of the drying system exhaust port in the water dispersible granule granulation process and the moisture content of the granules; evaluating the high humidity performance degree of each time according to the distribution of the outlet humidity within the preset time length before each time; determining the normal time according to the increment of the moisture content of the granules; determining the threshold reference confidence according to the growth of the high humidity performance degree of the normal time and the increment of the moisture content of the granules in the neighborhood after the standard lag time of the normal time; obtaining the moisture content factor of the normal time after the standard lag time based on the distribution characteristics of the moisture content of the granules after the standard lag time of the normal time, and then determining the humidity performance threshold; adjusting the spraying rate according to the deviation of the high humidity performance degree of the current time and the humidity performance threshold. The present application realizes the real-time adjustment of the spraying rate.

Description

Technical Field

[0001] This invention relates to the field of water-dispersible granules technology, and more specifically to a granulation control method for a granulation mechanism used in the production of water-dispersible granules. Background Technology

[0002] Water-dispersible granules are granular formulations that rapidly disintegrate and disperse in water to form a stable suspension. They are widely used in pesticides and pharmaceuticals, characterized by good dispersibility, safe use, and ease of storage and transportation. In the production process of water-dispersible granules, granulation is a core step. Fine powder material, after being pulverized by air jet milling, is fed into the granulation chamber under negative pressure. Moisture is quantitatively introduced through a spray system, causing the powder particles to agglomerate and knead, gradually forming uniformly sized and dense wet granules. Hot air drying technology is then used to rapidly remove moisture, ensuring uniform particle size, low moisture content, and good looseness. During this process, strict control of the spray volume, atomization uniformity, and granulation time is necessary to avoid problems such as agglomeration, adhesion to the walls, or moisture absorption and reabsorption in the finished product due to excessively wet granules, thus providing qualified intermediate granules for subsequent drying and sieving processes.

[0003] Water-dispersible granules are essentially hydrophilic materials that rapidly disintegrate and disperse in water. In current granulation techniques, due to their strong hydrophilicity, hygroscopic nature, and extremely low tolerance for humidity, water-dispersible granules allow for very low residual moisture compared to ordinary granules, which do not require such high water sensitivity and allow for a small amount of residual moisture after drying. If humidity is not properly controlled during the granulation process, the water-dispersible granules will swell, clump, and deform due to moisture absorption. Summary of the Invention

[0004] To address the problem of poor granulation quality caused by the inability to precisely control humidity during the production of water-dispersible granules using existing methods, the present invention aims to provide a granulation control method for a granulation machine used in the production of water-dispersible granules. The specific technical solution adopted is as follows:

[0005] This invention provides a granulation control method for granulation machines used in the production of water-dispersible granules, the method comprising the following steps:

[0006] To obtain the outlet air humidity and particle moisture content of the main air duct of the drying system during the granulation process of water-dispersible granules;

[0007] Based on the distribution of air humidity at the outlet within a preset time period before each time point in the current time period, evaluate the degree of high humidity performance at each time point; determine the normal time point based on the increase in particle moisture content; determine the threshold reference confidence level of the normal time point based on the increase in the degree of high humidity performance at the normal time point and the increase in particle moisture content in the time neighborhood after the standard lag time of the normal time point.

[0008] Based on the distribution characteristics of particle moisture content after the standard lag time at the normal time, the particle moisture content factor after the standard lag time at the normal time is obtained; the threshold optimization degree at the normal time is obtained by combining the threshold reference confidence and the particle moisture content factor; the humidity performance threshold is determined by the threshold optimization degree and the high humidity performance degree at the normal time.

[0009] Adjust the spray rate based on the deviation between the current level of high humidity and the humidity threshold.

[0010] Preferably, the step of evaluating the degree of high humidity performance at each moment based on the distribution of air outlet humidity within a preset time period prior to each moment in the current time period includes:

[0011] For any point in the current time period:

[0012] By using the minimum air outlet humidity between each time point within a preset time period prior to any given time point, the air outlet humidity at each time point within the preset time period prior to any given time point is weighted, and the summation is performed on all times within the preset time period prior to any given time point to obtain the degree of high humidity performance at any given time point.

[0013] Preferably, determining the normal time based on the increment of particle moisture content includes: taking the time when the increment of particle moisture content is less than or equal to a preset increment threshold as the normal time, and the process of obtaining the increment of particle moisture content is: taking the difference between the particle moisture content of the later time and the particle moisture content of the previous time as the increment of particle moisture content.

[0014] Preferably, the acquisition of the standard lag time includes:

[0015] The moment when the increase in particle moisture content exceeds a preset threshold is considered an abnormal moment.

[0016] For any abnormal moment:

[0017] The degree of high temperature abnormality at each time before any abnormal moment is obtained by considering the difference between the degree of high temperature performance at any abnormal moment and each time before it, and the difference between the increment of the degree of high temperature performance at each time before the abnormal moment and the maximum value of the increment of the degree of high temperature performance between each time before the abnormal moment and the abnormal moment.

[0018] The moment corresponding to the maximum value of the high temperature anomaly degree of all moments before any abnormal moment is recorded as the air outlet performance moment of any abnormal moment; the time interval between any abnormal moment and its air outlet performance moment is recorded as the particle performance lag time of any abnormal moment.

[0019] The standard lag time is determined by rounding up the mean of the lag times of particle performance at all abnormal moments.

[0020] Preferably, determining the threshold reference confidence level for the normal time based on the increase in the degree of high humidity at the normal time and the increase in particle moisture content within the time neighborhood after the standard lag time at the normal time includes:

[0021] For any normal moment:

[0022] The threshold reference confidence level for any normal moment is obtained based on the increment of the high humidity performance at any given normal moment, the difference between the duration of each moment in the time neighborhood of any normal moment and the standard lag duration, and the increment of the particle moisture content at each moment in the time neighborhood of the first moment after the standard lag duration of any normal moment.

[0023] Preferably, the process of obtaining the particle moisture content factor after the standard lag time based on the distribution characteristics of particle moisture content at the normal time includes:

[0024] For any normal moment:

[0025] The moment when the particle moisture content first reaches its maximum value after a certain period following the standard of any normal moment is recorded as the candidate moment; the time period between the first moment after the standard of any normal moment and the candidate moment is recorded as the reference time period of any normal moment.

[0026] By using the negative correlation normalization results of the particle moisture content increments at all times within the reference time period, the particle moisture content is weighted and summed to obtain the particle moisture factor at any normal time after the standard lag time.

[0027] Preferably, the step of combining the threshold reference confidence level and the particle moisture content factor to obtain the optimal threshold at normal times includes:

[0028] For any normal moment:

[0029] Calculate the first difference between the preset water content threshold and the particle water content factor at any normal time, and record the maximum value between the first difference and 0 as the first feature value;

[0030] Based on the first feature value and the threshold reference confidence level at any normal time, the threshold preference degree at any normal time is obtained. The first feature value is negatively correlated with the threshold preference degree, and the threshold reference confidence level is positively correlated with the threshold preference degree.

[0031] Preferably, determining the humidity performance threshold by the degree of threshold preference and the degree of high humidity performance at normal times includes:

[0032] For any normal moment: the product of the normalized value of the threshold optimization degree of the any normal moment and the high humidity performance degree of the any normal moment is recorded as the second feature value of the any normal moment;

[0033] The average value of the second characteristic value at all normal times is used as the humidity performance threshold.

[0034] Preferably, adjusting the spray rate based on the deviation between the current level of high humidity and the humidity threshold includes:

[0035] Calculate the second difference between the current level of high humidity and the humidity threshold, and record the maximum value between the second difference and 0 as the third feature value;

[0036] The ratio between the third characteristic value and the humidity performance threshold is determined as the degree of humidity deviation at the current moment;

[0037] The spray rate is adjusted based on the degree of humidity deviation.

[0038] Preferably, adjusting the spray rate using the degree of humidity deviation includes:

[0039] Calculate the third difference between the current spray rate and the preset minimum spray rate, and the fourth difference between the constant 1 and the degree of humidity deviation at the current moment;

[0040] Calculate the first product between the third and fourth differences, and use the sum of the first product and the spray rate at the current moment as the adjusted spray rate, and then make the adjustment.

[0041] The present invention has at least the following beneficial effects:

[0042] This invention takes into account the extremely low tolerance for humidity control in water-dispersible granules, thus requiring strict control of the humidity in the granulator. First, based on the distribution of outlet air humidity over a preset time period prior to each moment in the current timeframe, the degree of high humidity at each moment is evaluated. Then, normal times are selected from the perspective of the increase in particle moisture content, as these normal times have greater reference value. Since the expression of particle moisture content has a lag, this invention, based on the increase in the degree of high humidity at normal times and the increase in particle moisture content within the time neighborhood after the standard lag time of the normal times, evaluates the humidity of the granulator at the current time. The lag relationship between the increase in outlet humidity and particle moisture content was evaluated, and the threshold reference confidence level at normal time was determined. Based on the distribution characteristics of particle moisture content after the standard lag time at normal time, the particle moisture content after the standard lag time at normal time was evaluated, and the particle moisture content factor after the standard lag time at normal time was obtained. The humidity performance threshold was determined. Finally, the spray rate was adjusted according to the deviation between the current high humidity performance and the humidity performance threshold, realizing real-time adjustment of the spray rate of the spray granulator and ensuring the production quality of water-dispersible granules. Attached Figure Description

[0043] 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.

[0044] Figure 1 A flowchart of a granulation control method for producing water-dispersible granules provided in an embodiment of the present invention;

[0045] Figure 2 This is a structural block diagram of a granulation control system for a granulation machine used in the production of water-dispersible granules, provided in an embodiment of the present invention. Detailed Implementation

[0046] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description, in conjunction with the accompanying drawings and preferred embodiments, describes a granulation control method for a granulation machine used in the production of water-dispersible granules according to the present invention.

[0047] 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.

[0048] The following describes in detail, with reference to the accompanying drawings, a specific scheme for the granulation control method of a granulation mechanism for the production of water-dispersible granules provided by the present invention.

[0049] An example of a granulation control method for a granulator used in the production of water-dispersible granules:

[0050] This embodiment proposes a granulation control method for granulation machines used in the production of water-dispersible granules, such as... Figure 1 As shown, a granulation control method for a granulator used in the production of water-dispersible granules according to this embodiment includes the following steps:

[0051] Step S1: Obtain the outlet humidity and particle moisture content of the main air duct of the drying system during the granulation process of water-dispersible granules.

[0052] During the granulation process of water-dispersible granules, a humidity sensor is installed near the end of the drying section in the main air duct of the drying system exhaust port to monitor the water vapor concentration in the drying exhaust gas in real time. The water vapor concentration can reflect the moisture content of the particles, so in this embodiment, the collected water vapor concentration value is used as the moisture content of the particles. An online near-infrared moisture meter is installed at the conveyor belt at the dryer outlet to determine the moisture content on the surface and inside of the particles using the absorption characteristics of the near-infrared band. In this embodiment, the data collection frequency of water vapor concentration and exhaust humidity is once every 1 second. In specific applications, the implementer can set it according to the specific situation.

[0053] Thus, using the above method, this embodiment has collected the outlet air humidity and particulate moisture content at various times within the current time period. The current time period is the set consisting of all historical times with a time interval less than or equal to a preset first duration, plus the current time. The current time is the last moment within the current time period. In this embodiment, the preset first duration is one week. In specific applications, the implementer can set it according to specific circumstances.

[0054] Step S2: Evaluate the degree of high humidity performance at each time point based on the distribution of air humidity in the air outlet within a preset time period before each time point in the current time period; determine the normal time point based on the increase in particle moisture content; determine the threshold reference confidence level of the normal time point based on the increase in the degree of high humidity performance at the normal time point and the increase in particle moisture content in the time neighborhood after the standard lag time of the normal time point.

[0055] When controlling the production humidity of a granulator, real-time monitoring of the humidity status is necessary. However, monitoring the moisture content of the discharged particles has a significant lag, as it can only be measured after the drying process is complete, failing to reflect the current drying status of the system in real time. Therefore, it is unsuitable as a basis for process adjustment. In contrast, outlet air humidity reflects the balance between the evaporation load and the hot air drying capacity within the drying system, serving as a preliminary indicator for judging drying efficiency and adjusting drying parameters. This makes it more suitable for process control and anomaly early warning. However, to ensure the effectiveness of anomaly detection, it is necessary to analyze the characteristics of outlet air humidity changes prior to the high moisture content of the discharged particles.

[0056] During the drying process of water-dispersible granules, the moisture in the system does not evaporate sufficiently, and the drying capacity tends to be saturated. At this time, the moisture in the material cannot be removed in a timely and effective manner, which eventually leads to an increase in the moisture content of the discharged granules. During this process, the humidity at the air outlet rises and remains high. Therefore, the degree of high humidity at each moment can be judged based on this.

[0057] This embodiment will use one moment as an example for illustration. The method provided in this embodiment can be used to process other moments.

[0058] Specifically, for any moment within the current time period:

[0059] The minimum outlet humidity is used to calculate the humidity level at each time point within a preset time period before the current time. The humidity levels at each time point within that preset time period are then weighted and summed to obtain the overall humidity level at that time. In this embodiment, the preset time period is 12 hours; however, in specific applications, the implementer can adjust this setting according to the specific circumstances.

[0060] As a specific example, a formula for calculating the degree of high humidity is given, which is the first time period within the current time frame. The degree of high humidity at any given time can be expressed as:

[0061]

[0062] in, For the current period The degree of high humidity at any given time For the first Within the preset time period before the [time]th moment The moment to the Minimum airflow humidity between time points; For the first Within the preset time period before the [time]th moment The humidity of the air outlet at that moment; For the first The number of moments within a preset duration prior to the given moment. This represents the normalization function.

[0063] Indicates the first Within the preset time period before the [time]th moment The moment to the The minimum outlet humidity between time points is normalized, and this normalization result is used as the weight for weighting the outlet humidity. Low humidity ranges are given low weight, while the most recent period of sustained high humidity is given high weight, thus focusing on the actual humidity during periods of sustained high humidity. When the first... Within the preset time period prior to the specified time, each time up to the specified time... The higher the minimum air humidity between the two moments, and the higher the humidity of the first moment... When the humidity of the air outlet is higher at each time point within the preset time period prior to the current time point, the humidity of the air outlet at each time point is higher. The higher the humidity level at any given moment, the better.

[0064] Historical data shows that there are times when the particle moisture content exceeds the standard, resulting in product defects. In order to determine the threshold of high humidity performance before the particle moisture content does not meet the standard, it is necessary to combine historical data to determine the threshold of high humidity performance.

[0065] First, the time when the increase in particle moisture content is less than or equal to a preset threshold is defined as a normal time. The process for obtaining the increase in particle moisture content is as follows: the difference between the particle moisture content of the later time and the particle moisture content of the previous time is taken as the increase in particle moisture content. For any given time, the increase in particle moisture content at that time is the difference between the particle moisture content at that time and the particle moisture content of the previous time.

[0066] The moment when the increase in particle moisture content is less than or equal to the preset increment threshold is considered an abnormal moment, and the moment when the increase in particle moisture content is greater than the preset increment threshold is also considered an abnormal moment. The preset increment threshold is set by the implementer according to the specific situation, and will not be elaborated on here.

[0067] For any abnormal moment, when the particle moisture content has exceeded the threshold, and the change in the moisture content of the discharged particles has a significant lag, the outlet humidity has already shown an abnormality at this time. The moment when the outlet humidity shows an abnormality will be earlier than the moment of the abnormality. When the outlet humidity shows an abnormality, it is manifested as a significant increase in the degree of high humidity and continuous high humidity. Therefore, the lag time shown at each abnormal moment will be analyzed next.

[0068] For any abnormal moment:

[0069] The degree of high temperature anomaly at each time before the abnormal moment is obtained by considering the difference between the degree of high temperature performance at the abnormal moment and each time before the abnormal moment, and the difference between the increment of the degree of high temperature performance at each time before the abnormal moment and the maximum value of the increment of the degree of high temperature performance between each time before the abnormal moment and the abnormal moment. The time corresponding to the maximum value of the degree of high temperature anomaly at all times before the abnormal moment is recorded as the air outlet performance time of the abnormal moment; the time interval between the abnormal moment and the air outlet performance time is recorded as the particulate matter performance lag time of the abnormal moment.

[0070] As a specific example, the formula for calculating the degree of high temperature anomaly is given, the first... Before the first abnormal moment The degree of high humidity anomaly at any given time can be expressed as:

[0071]

[0072] in, Indicates the first Before the first abnormal moment The degree of abnormal high humidity at a given time Indicates the first Before the first abnormal moment The degree of high humidity at any given time For the first The degree of high humidity at an abnormal moment For the first Before the first abnormal moment The increase in the degree of high humidity at each moment For the first The time from the start of the anomaly to its preceding time The maximum value of the increase in the degree of high humidity within a time interval. This represents an exponential function with the natural constant as its base.

[0073] For any given moment, the specific method for obtaining the increment of the high humidity performance at that moment is as follows: the difference between the high humidity performance at that moment and the high humidity performance at the previous moment is used as the increment of the high humidity performance at that moment. The larger the value, the more significant the [value]. Before the first abnormal moment The closer the degree of high humidity at a given moment is to the subsequent particle moisture content, the more it reflects the degree of high humidity during abnormal conditions. Before the first abnormal moment The greater the likelihood of abnormal air humidity at a given moment; The larger the value, the more likely it is to be from the first... Before the first abnormal moment The moment to the Within the interval of the nth abnormal moment, the nth The first abnormal start time before the The degree of high humidity varied most at the [time point], and [time point]... The more abnormal the moment, the more likely it is to be related to the first. The first abnormal start time before the The abnormal air humidity at any given time was caused by the same factor.

[0074] Using the above method, the particle performance lag time at each abnormal moment can be obtained, and the average of the particle performance lag times at all abnormal moments, rounded up, is determined as the standard lag time.

[0075] This embodiment requires anomaly detection of the current real-time outlet humidity. Therefore, it is necessary to obtain the threshold of high humidity performance of the outlet humidity based on historical data. However, at abnormal times, the particle moisture content has already become abnormal, so it cannot be used to determine the threshold of high humidity performance of the outlet humidity. The threshold needs to be determined based on normal production data.

[0076] At a certain normal moment, if the particle moisture content increases and gets closer to the particle moisture content threshold, it indicates that the high humidity of the outlet air will have an upward trend before the standard lag time at that moment. Therefore, the threshold reference confidence level at the normal moment is determined, and it is judged whether the particle moisture content has increased synchronously after the standard lag time after that moment.

[0077] The following explanation uses a normal moment as an example. The method provided in this embodiment can be used to process other normal moments.

[0078] Specifically, for any normal moment:

[0079] The threshold reference confidence level for the normal moment is obtained based on the increment of the high humidity performance at the normal moment, the difference between the duration of each moment in the time neighborhood of the normal moment and the first moment after its standard lag duration and the standard lag duration, and the increment of particle moisture content at each moment in the time neighborhood of the first moment after the standard lag duration of the normal moment.

[0080] As a specific example, the detailed formula for calculating the threshold reference confidence level is given. The threshold reference confidence level at a normal time point can be expressed as:

[0081]

[0082] in, Indicates the first Threshold reference confidence level at a normal time point, Indicates the first The increase in the degree of high humidity at a normal time. Indicates the first The number of times within the time neighborhood of a normal time point to the first time point after its standard lag. Indicates the first Within the time neighborhood of the first time after the standard lag time from the first normal time, the i-th The duration of each moment, Indicates the standard lag time. Indicates the first Within the time neighborhood of the first time after the standard lag time of a normal time, the i-th The increase in particle moisture content at each moment. This represents the normalization function.

[0083] In this embodiment, for any given moment, the process of obtaining the moments within its preset neighborhood is as follows: taking that moment as the center moment, obtain a time window of a preset second duration, and take all moments within that time window as moments within the preset neighborhood of that moment; in this embodiment, the preset second duration is 21 seconds, but in specific applications, the implementer can set it according to the specific situation.

[0084] Used to indicate the first Within the time neighborhood of the first time after the standard lag time from the first normal time, the i-th The difference between the duration of a given moment and the standard lag duration; the larger the value, the greater the duration difference between the two time periods. The greater the increase in the degree of high humidity at a normal time, the more it indicates that the first... The greater the increase in the degree of high humidity at a normal time, the greater the increase in the degree of high humidity. The larger the value, the more likely it is to be the first. At the first moment, the particle moisture content increased after the standard lag time. The greater the increase in the degree of high humidity at a normal time, and The larger the value, the more likely the increase in particle moisture content is due to changes in the degree of high humidity in the outlet air, which is more helpful in obtaining the threshold, i.e., the first... The higher the threshold reference confidence level at a normal time, the better.

[0085] Using the above method, the threshold reference confidence level can be obtained for each normal time point.

[0086] Step S3: Based on the distribution characteristics of particle moisture content after the standard lag time at the normal time, obtain the particle moisture content factor after the standard lag time at the normal time; combine the threshold reference confidence and the particle moisture content factor to obtain the threshold optimization degree at the normal time; determine the humidity performance threshold by the threshold optimization degree and the high humidity performance degree at the normal time.

[0087] Since the standard lag time is obtained based on the abnormal moment, that is, the moment when the particle moisture content exceeds the threshold, but since the particle moisture content may further increase after exceeding the threshold, for any moment when the degree of high humidity increases, the particle moisture content can only be regarded as the degree of increase in particle moisture content caused by the increase in the degree of high humidity after the particle moisture content stabilizes after the standard lag time. Therefore, this embodiment will combine the distribution characteristics of particle moisture content after the standard lag time at normal time to evaluate the particle moisture content at normal time after the standard lag time.

[0088] Specifically, for any normal moment:

[0089] The moment when the particle moisture content first reaches its maximum value after a certain time lag from the normal moment is designated as the candidate moment. The time interval between the first moment after the standard lag from the normal moment and the candidate moment is designated as the reference time interval for the normal moment. Using the negative correlation normalization result of the particle moisture content increments at all moments within the reference time interval, the particle moisture content is weighted and summed to obtain the particle moisture factor for the normal moment after the standard lag time.

[0090] In this embodiment, a specific calculation formula for the particle moisture content factor is given. The particle moisture content factor at a normal moment after the standard lag time can be expressed as:

[0091]

[0092] in, Indicates the first The particle water content factor at a normal time after the standard lag time Indicates the first The number of moments within a reference time period at a normal moment. Indicates the first Within the reference time period of the first normal moment The increase in particle moisture content at each moment. Indicates the first Within the reference time period of the first normal moment Moisture content of particles at a given time.

[0093] The larger the value, the less the increase in particle moisture content. This indicates that the increase in particle moisture content caused by the increased degree of high humidity has tended to stabilize, and it can be used as the particle moisture content result value after the particle moisture content has stabilized. Indicates the first Within the reference time period of the first normal moment The negative correlation normalization result of the increment of particle moisture content at each time point is used as the weight of the particle moisture content. The particle moisture content is then weighted and summed to obtain the particle moisture content factor.

[0094] At a normal moment within the current time period, assuming a relatively high threshold reference confidence level, the closer the particle moisture content factor is to the particle moisture content threshold, but does not exceed the moisture content threshold, the more suitable that moment is as a threshold for the degree of high humidity performance.

[0095] For any normal moment:

[0096] Calculate the difference between the preset water content threshold and the particle water content factor at the normal time, and record this difference as the first difference. Record the maximum value between the first difference and 0 as the first feature value. Based on the first feature value and the threshold reference confidence level at the normal time, obtain the threshold optimization degree at the normal time. The first feature value is negatively correlated with the threshold optimization degree, and the threshold reference confidence level is positively correlated with the threshold optimization degree.

[0097] Among them, a positive correlation means that the dependent variable increases as the independent variable increases, and the dependent variable decreases as the independent variable decreases. It can be an additive relationship, a multiplicative relationship, etc., which is determined by practical application. A negative correlation means that the dependent variable decreases as the independent variable increases, and the dependent variable increases as the independent variable decreases. It can be a subtractive relationship, a division relationship, etc., which is determined by practical application.

[0098] In this embodiment, a specific calculation formula for the degree of threshold preference is given, the first... The optimality of the threshold at a normal time point can be expressed as:

[0099]

[0100] in, Indicates the first The optimal threshold for a normal time period Indicates the first Threshold reference confidence level at a normal time point, This indicates the preset water content threshold. Indicates the first The particle water content factor at a normal time after the standard lag time This represents the function that takes the maximum value. This represents an exponential function with the natural constant as its base.

[0101] Indicates the first The first difference corresponding to each normal moment. This represents the first characteristic value. The preset water content threshold is set by the implementer according to the specific circumstances, and will not be elaborated further here.

[0102] For any normal time: the product of the normalized value of the threshold optimization degree at that normal time and the high humidity performance degree at that normal time is recorded as the second characteristic value of that normal time. Using the above method, the second characteristic value for each normal time can be obtained, and the average of the second characteristic values ​​for all normal times is taken as the humidity performance threshold. In this embodiment, when normalizing the threshold optimization degree, maximum and minimum values ​​are used for normalization processing. The maximum and minimum value normalization method is existing technology and will not be elaborated further here.

[0103] Thus, this embodiment has obtained the humidity performance threshold.

[0104] Step S4: Adjust the spray rate based on the deviation between the current level of high humidity and the humidity threshold.

[0105] After obtaining the humidity performance threshold, the real-time high humidity performance can be judged to determine the degree of humidity deviation, and the spray rate can be adjusted based on the degree of deviation.

[0106] Specifically, the difference between the current level of high humidity and the humidity threshold is calculated and recorded as the second difference. The maximum value between the second difference and 0 is recorded as the third characteristic value. The ratio between the third characteristic value and the humidity threshold is determined as the humidity deviation at the current moment. The humidity deviation at the current moment can be expressed as:

[0107]

[0108] in, The degree of humidity deviation at the current moment. The current level of high humidity. The humidity performance threshold, This represents the function that takes the maximum value.

[0109] The third characteristic value is represented by the ratio between the third characteristic value and the humidity performance threshold. The larger the ratio, the greater the deviation of the humidity from the humidity performance threshold at the current moment, that is, the greater the degree of humidity deviation at the current moment.

[0110] Next, the spray rate will be adjusted based on the current humidity deviation.

[0111] Specifically, firstly, the difference between the current spray rate and the preset minimum spray rate is calculated, and this difference is recorded as the third difference. Then, the difference between the constant 1 and the humidity deviation at the current time is calculated, and this difference is recorded as the fourth difference. The product of the third difference and the fourth difference is recorded as the first product. The sum of the first product and the spray rate at the current time is used as the adjusted spray rate, and then the adjustment is performed.

[0112] In this embodiment, a specific calculation formula for the adjusted spray rate is given, and the adjusted spray rate can be expressed as:

[0113]

[0114] In the formula, The adjusted spray rate, The spray rate at the current moment; Set the minimum spray rate; This represents the degree of humidity deviation at the current moment.

[0115] This represents the third difference. This represents the fourth difference. This indicates the first product. The preset minimum spray rate is the minimum spray rate of the equipment, which is determined based on the specific conditions of the equipment.

[0116] After determining the adjusted spray rate based on the current humidity deviation, the spray rate of the spray granulator is adjusted to the adjusted spray rate to complete the subsequent production work.

[0117] The method provided in this embodiment is used to adjust the spray rate in real time, thereby ensuring the production qualification rate of water-dispersible granules.

[0118] This embodiment takes into account the extremely low tolerance for humidity control inherent in water-dispersible granules, thus requiring strict control of the granulator's humidity. First, based on the distribution of outlet air humidity over a preset time period prior to each moment in the current timeframe, the degree of high humidity at each moment was evaluated. Then, normal times were selected from the perspective of the increase in particle moisture content, as these normal times have greater reference value. Since the particle moisture content exhibits a lag, this embodiment uses the increase in high humidity at normal times and the increase in particle moisture content within the time neighborhood after the standard lag time at normal times to evaluate the current... The lag relationship between the increase in outlet humidity and particle moisture content during different time periods was evaluated, and the threshold reference confidence level for normal time was determined. Based on the distribution characteristics of particle moisture content after the standard lag time at normal time, the particle moisture content after the standard lag time at normal time was evaluated, and the particle moisture content factor after the standard lag time at normal time was obtained. The humidity performance threshold was determined. Finally, the spray rate was adjusted according to the deviation between the current high humidity performance level and the humidity performance threshold, realizing real-time adjustment of the spray granulator spray rate and ensuring the production quality of water-dispersible granules.

[0119] An example of a granulation control system for a granulation machine used in the production of water-dispersible granules:

[0120] See Figure 2 The diagram illustrates a structural block diagram of a granulation control system for producing water-dispersible granules according to an embodiment of the present invention. The system may include a data acquisition module, a confidence level determination module, a threshold determination module, and a control module.

[0121] The data acquisition module is used to obtain the air humidity and particle moisture content of the main air duct of the drying system during the granulation process of water-dispersible granules.

[0122] The confidence level determination module is used to evaluate the degree of high humidity performance at each moment based on the distribution of air humidity in the air outlet within a preset time period before each moment in the current time period; determine the normal moment based on the increase in particle moisture content; and determine the threshold reference confidence level of the normal moment based on the increase in the degree of high humidity performance at the normal moment and the increase in particle moisture content in the time neighborhood after the standard lag time of the normal moment.

[0123] The threshold determination module is used to obtain the particle moisture content factor after the standard lag time at the normal time based on the distribution characteristics of particle moisture content after the standard lag time at the normal time; combine the threshold reference confidence and the particle moisture content factor to obtain the threshold optimization degree at the normal time; and determine the humidity performance threshold by combining the threshold optimization degree and the high humidity performance degree at the normal time.

[0124] The control module is used to adjust the spray rate based on the deviation between the current level of high humidity and the humidity threshold.

[0125] It should be understood that Figure 2 The structural block diagram and modules of the granulation control system for water-dispersible granule production shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated hardware. Those skilled in the art will understand that the above-described methods and systems can be implemented using computer-executable instructions and / or included in processor control code, for example, on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and modules of this specification can be implemented not only by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, or by a combination of the above-described hardware circuits and software (e.g., firmware).

[0126] For more details about the above modules, please refer to other parts of this manual; they will not be repeated here.

[0127] In other embodiments, a granulation control device for producing water-dispersible granules is also provided, including a memory and a processor. The memory stores executable program code, and the processor calls and runs the executable program code from the memory, causing the device to execute the granulation control method for producing water-dispersible granules described above. Specifically, the device may be a chip, component, or module. The chip may include a connected processor and memory; wherein the memory stores instructions, and when the processor calls and executes the instructions, the chip can execute the granulation control method for producing water-dispersible granules provided in the above embodiments.

[0128] In other embodiments, a computer program product is also provided, which, when run on a computer, causes the computer to perform the aforementioned steps to implement the granulation control method for producing water-dispersible granules provided in the above embodiments.

[0129] In other embodiments, a computer-readable storage medium is also provided, which stores computer program code. When the computer program code is run on a computer, it causes the computer to perform the above-described method steps to implement the granulation control method for producing water-dispersible granules provided in the above embodiments.

[0130] The systems, electronic devices, computer program products, and computer-readable storage media provided are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0131] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A granulation control method for a granulation machine used in the production of water-dispersible granules, characterized in that, The method includes the following steps: To obtain the outlet air humidity and particle moisture content of the main air duct of the drying system during the granulation process of water-dispersible granules; Based on the distribution of air humidity at the outlet within a preset time period before each time point in the current time period, evaluate the degree of high humidity performance at each time point; determine the normal time point based on the increase in particle moisture content; determine the threshold reference confidence level of the normal time point based on the increase in the degree of high humidity performance at the normal time point and the increase in particle moisture content in the time neighborhood after the standard lag time of the normal time point. Based on the distribution characteristics of particle moisture content after the standard lag time at the normal time, the particle moisture content factor after the standard lag time at the normal time is obtained; the threshold optimization degree at the normal time is obtained by combining the threshold reference confidence and the particle moisture content factor; the humidity performance threshold is determined by the threshold optimization degree and the high humidity performance degree at the normal time. Adjust the spray rate based on the deviation between the current level of high humidity and the humidity threshold. The evaluation of the high humidity performance at each moment, based on the distribution of air humidity within a preset time period prior to each moment in the current time period, includes: For any point in the current time period: By using the minimum outlet humidity between each time point within a preset time period prior to any given time point, the outlet humidity at each time point within the preset time period prior to any given time point is weighted, and the summation is performed on all times within the preset time period prior to any given time point to obtain the degree of high humidity performance at any given time point. The method of determining the normal time based on the increment of particle moisture content includes: taking the time when the increment of particle moisture content is less than or equal to a preset increment threshold as the normal time; the process of obtaining the increment of particle moisture content is: taking the difference between the particle moisture content of the later time and the particle moisture content of the previous time as the increment of particle moisture content. Obtaining the standard lag duration includes: The moment when the increase in particle moisture content exceeds a preset threshold is considered an abnormal moment. For any abnormal moment: The degree of high humidity abnormality at each time before any abnormal moment is obtained by considering the difference between the degree of high humidity at any abnormal moment and each time before it, and the difference between the increment of the degree of high humidity at each time before the abnormal moment and the maximum value of the increment of the degree of high humidity between each time before the abnormal moment and the abnormal moment. The moment corresponding to the maximum value of the high humidity anomaly level of all moments before any abnormal moment is recorded as the air outlet performance moment of any abnormal moment; the time interval between any abnormal moment and its air outlet performance moment is recorded as the particle performance lag time of any abnormal moment. The standard lag time is determined by rounding up the mean of the lag times of particle performance at all abnormal moments. The determination of the threshold reference confidence level for the normal time period based on the increase in the degree of high humidity at the normal time and the increase in particle moisture content in the time neighborhood after the standard lag time at the normal time includes: For any normal moment: The threshold reference confidence level for any normal moment is obtained based on the increment of the high humidity performance at any normal moment, the difference between the duration of each moment in the time neighborhood of any normal moment and the standard lag duration, and the increment of particle moisture content at each moment in the time neighborhood of the first moment after the standard lag duration of any normal moment. The distribution characteristics of particle moisture content after the standard lag time based on the normal time are used to obtain the particle moisture content factor after the standard lag time at the normal time, including: For any normal moment: The moment when the particle moisture content first reaches its maximum value after the standard lag time of any normal moment is recorded as the candidate moment; the time period between the first moment after the standard lag time of any normal moment and the candidate moment is recorded as the reference time period of any normal moment. Using the negative correlation normalization results of the particle moisture content increments at all times within the reference time period, the particle moisture content is weighted and summed to obtain the particle moisture content factor at any normal time after the standard lag time. The method of combining threshold reference confidence and particle moisture content factor to obtain the optimal threshold at normal times includes: For any normal moment: Calculate the first difference between the preset water content threshold and the particle water content factor at any normal time, and record the maximum value between the first difference and 0 as the first feature value; Based on the first feature value and the threshold reference confidence level at any normal time, the threshold preference degree at any normal time is obtained. The first feature value is negatively correlated with the threshold preference degree, and the threshold reference confidence level is positively correlated with the threshold preference degree. The determination of the humidity performance threshold by the degree of threshold optimization and the degree of high humidity performance at normal times includes: For any normal moment: the product of the normalized value of the threshold optimization degree of the any normal moment and the high humidity performance degree of the any normal moment is recorded as the second feature value of the any normal moment; The average value of the second characteristic value at all normal times is used as the humidity performance threshold. The adjustment of the spray rate based on the deviation between the current level of high humidity and the humidity threshold includes: Calculate the second difference between the current level of high humidity and the humidity threshold, and record the maximum value between the second difference and 0 as the third feature value; The ratio between the third characteristic value and the humidity performance threshold is determined as the degree of humidity deviation at the current moment; The spray rate is adjusted based on the degree of humidity deviation. The adjustment of the spray rate based on the degree of humidity deviation includes: Calculate the third difference between the current spray rate and the preset minimum spray rate, and the fourth difference between the constant 1 and the degree of humidity deviation at the current moment; Calculate the first product between the third and fourth differences, and use the sum of the first product and the spray rate at the current moment as the adjusted spray rate, and then make the adjustment.

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