Method for detecting concentration of ammonium sulfate prepared based on sodium sulfate

Abstract

The invention discloses a method for detecting the concentration of ammonium sulfate prepared based on sodium sulfate, which comprises the following steps: dissolving sodium sulfate, performing double decomposition reaction on ammonium bicarbonate, filtering, washing and drying baking soda, and also comprises the following steps: performing cold separation on mother liquor, purifying and recycling sodium sulfate, performing vacuum evaporation, and performing vacuum cooling to obtain a byproduct ammonium sulfate. According to the method, the reaction time is divided into the detection time period and the control time, so that the reaction in the detection time period can be monitored in real time, the data of the time period is accurate data, the ammonium sulfate concentration prediction model is analyzed and constructed based on the data of the detection time period, the ammonium sulfate concentration at the end of the reaction is predicted, and the detection accuracy is improved based on the prediction result. Potential concentration deviation can be found in time, a basis is provided for adjustment and optimization in the production process, a control time period is reserved to adjust the influence parameter optimization reaction process, and the rejection rate and the rework rate caused by the concentration deviation are reduced, so that the production efficiency and the product quality are improved.

Description

Technical Field

[0001] The invention relates to the technical field of ammonium sulfate preparation, and in particular to a method for detecting the concentration of ammonium sulfate prepared based on sodium sulfate. Background Art

[0002] As an important nitrogen fertilizer, ammonium sulfate plays a vital role in agricultural production. The quality of its preparation process directly affects the quality and production cost of the product, which in turn has a profound impact on agricultural production and environmental protection. Traditional ammonium sulfate preparation methods mostly rely on multi-effect evaporation separation technology;

[0003] However, with the enhancement of environmental awareness and the improvement of energy efficiency requirements, new methods continue to emerge. Among them, the method of preparing ammonium sulfate from baking soda mother liquor through cold precipitation of Glauber's salt is more prominent. However, the concentration detection of the ammonium sulfate production process is often carried out at the end of the reaction, which makes it difficult to timely detect and warn of concentration deviations in the reaction process, thereby causing delays in adjustment measures, which in turn affects production efficiency and product quality. During adjustments, the identification of factors affecting ammonium sulfate concentration often relies on empirical judgment or simple statistical analysis, resulting in inaccurate identification of influencing factors and blind adjustment measures, which in turn affects adjustment effects and production efficiency. Summary of the invention

[0004] The object of the present invention is to provide a method for detecting the concentration of ammonium sulfate prepared from sodium sulfate to solve at least one of the above-mentioned problems of the prior art.

[0005] The invention provides a method for detecting the concentration of ammonium sulfate prepared from sodium sulfate, comprising the following steps: dissolving sodium sulfate, performing double decomposition reaction of ammonium bicarbonate, filtering, washing, and drying baking soda, and also comprising cold analysis of mother liquor, purification and recovery of sodium sulfate for reuse, vacuum evaporation, and vacuum cooling to produce by-product ammonium sulfate;

[0006] During the double decomposition reaction, the concentration of the ammonium sulfate solution is detected and analyzed, and the specific steps are as follows:

[0007] Step 1: Based on the double decomposition reaction time, the total reaction time is divided proportionally to obtain the detection period and the control period;

[0008] Step 2: Based on the detection period, obtain the sodium sulfate concentration data of the detection period, perform analysis and judgment, and obtain the ammonium sulfate concentration prediction model;

[0009] Step 3: Based on the ammonium sulfate concentration prediction model, determine whether the ammonium sulfate concentration can be within the standard concentration range at the end of the reaction time;

[0010] Step 4: Based on the abnormal signal, the relevant factors of the double decomposition reaction process are identified to determine the influencing factors to be optimized;

[0011] Step 5: Based on the determined influencing factors to be optimized, adjust and control the influencing factors during the control period.

[0012] Beneficial effects of the present invention:

[0013] 1. The present invention divides the reaction time into a detection period and a control time, so that the reaction in the detection period can be monitored in real time. The data of the period is real-time data. An ammonium sulfate concentration prediction model is constructed based on the analysis of the data in the detection period to predict the ammonium sulfate concentration at the end of the reaction. Based on the prediction result, potential concentration deviations can be discovered in time, providing a basis for adjustment and optimization in the production process. A control period is reserved to adjust its influencing parameters to optimize the reaction process, reduce the scrap rate and rework rate caused by concentration deviation, thereby improving production efficiency and product quality;

[0014] 2. The present invention can more accurately identify the key factors that have a significant impact on the concentration of ammonium sulfate by comprehensively considering the synchronicity and discreteness of the change in the concentration of ammonium sulfate and the change in related factors, thereby improving the accuracy and reliability of the detection. After determining the influencing factors to be optimized, targeted adjustments and optimizations can be made. When determining the influencing factors, the proportion of subsequent adjustments can be determined by the change relationship between the change in the concentration of ammonium sulfate and the change in related factors, which adds data support to the adjustment control, makes the adjustment process more refined, and thus improves production efficiency and reduces production costs, and also helps to improve product quality and stability;

[0015] 3. The present invention calculates the control value of the influencing factor, and adjusts the influencing factor to be optimized according to the control value within the control period, thereby optimizing the reaction process. The mother liquor is regulated at a pH value of 5-5.5 to eliminate HCO 3 , increasing the possibility of ammonium sulfate concentration reaching the standard concentration range. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a flow chart of a method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to the present invention;

[0018] Figure 2 This is a process flow chart of preparing ammonium sulfate based on sodium sulfate of the present invention;

[0019] Figure 3It is a schematic structural diagram of a device for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to the present invention.

[0020] In the figure: 3. Computer equipment; 301. Processor; 302. Memory; 303. Computer program; Detailed implementation manners

[0021] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] Embodiment 1

[0023] Figure 1 It is a flowchart of a method for detecting the concentration of ammonium sulfate prepared from sodium sulfate provided in Embodiment 1 of the present invention. The embodiment of the present invention is applicable to detecting the concentration of the generated ammonium sulfate solution during the double decomposition reaction. This method for detecting the concentration of ammonium sulfate prepared from sodium sulfate can be executed by a detection system for the concentration of ammonium sulfate prepared from sodium sulfate. This detection system for the concentration of ammonium sulfate prepared from sodium sulfate can be implemented by software and / or hardware, and this detection system for the concentration of ammonium sulfate prepared from sodium sulfate can be configured in a detection device for the concentration of ammonium sulfate prepared from sodium sulfate. Optionally, a detection device for the concentration of ammonium sulfate prepared from sodium sulfate can be an electronic device, and this electronic device can be a notebook, a desktop computer, a smart tablet, etc. The embodiment of the present invention does not limit this.

[0024] As Figure 2 shown, a method for detecting the concentration of ammonium sulfate prepared from sodium sulfate provided in the embodiment of the present invention specifically includes the following steps:

[0025] It includes the dissolution of sodium sulfate, the double decomposition reaction of ammonium bicarbonate, filtration, washing, and drying of baking soda, and also includes the cold crystallization of mother liquor, the purification and recycling of sodium sulfate for reuse, vacuum evaporation, and vacuum cooling to by-product ammonium sulfate;

[0026] In this embodiment, specifically, the double decomposition reaction uses Na 2 SO 4 to control the concentration at 350 - 450 g / L and the temperature at 40 - 45 °C, and add NH 4 HCO 3 with a concentration of 350 - 450 g / L, and the reaction time is 90 min;

[0027] Reaction formula: Na 2 SO4 +2NH 4 HCO 3 =2NaHCO 3 +(NH 4 ) 2 SO 4 ;

[0028] Filtration is to separate the baking soda generated by the reaction from the mother liquor solid-liquid separation, and the washing is to use NaHCO 3 Half-saturated water, calculated according to the amount of ammonium carbonate 1:1.2 (350+400 / 2*1.2=450mL) is used for spray washing, mainly to wash away NH 4 Root SO 4 root;

[0029] Drying is to further dry the surface water of the wet baking soda after centrifugal dehydration at 45-50℃ for 3-5h, so that the baking soda meets the national standards;

[0030] The mother liquor is cold-precipitated to produce ammonium sulfate, and the process of purifying the filtered mother liquor from which the baking soda is filtered out is as follows:

[0031] The first step is to adjust the pH to 5-5.5 with sulfuric acid to eliminate HCO 3 The root is as follows:

[0032] XNaHCO 3 .XNH 4 HCO 3 +XH 2 SO 4 =X(NH 4 ) 2 SO 4 .NaSO 4 +XCO 2 ↑+H 2 O;

[0033] The second step is to eliminate excess HCO 3 The root solution was frozen to 0°C and Na 2 SO 4 .10H 2 O solubility is as low as 3-4 g / 100 mL water and (NH 4)2 SO 4 The difference in dissolution of 75g / 100mL water, Na precipitates at low temperature 2 SO 4 .10H 2 O, grow crystals for 4-6 hours, and remove the mother liquor (NH 4 ) 2 SO 4 ), the solid sodium sulfate is returned to the reaction process for continued reuse in the production of baking soda;

[0034] The process of preparing ammonium sulfate by vacuum evaporation and vacuum cooling is:

[0035] The first step is to remove the mother liquor from the centrifuge and perform vacuum evaporation to further increase (NH 4)2 SO 4 concentration and precipitation of sodium sulfate (NaSO 4) , after the centrifuge removes the sodium sulfate, the mother liquor is separated and evaporated by vacuum to increase (NH 4)2 SO 4 concentration, and then the high temperature liquid is vacuum flashed and cooled to 45-50°C to precipitate (NH 4)2 SO 4 Crystals, using a centrifuge to remove water to obtain ammonium sulfate;

[0036] In the second step, the dehydrated mother liquor is combined with NaSO 4 .Na 2 SO 4 .10H 2 O is heated to 45-50℃ and dissolved in the reaction process to mix with NH 4 HCO 3 The reaction produces baking soda;

[0037] The technical solution of this embodiment is to produce sodium sulfate from baking soda mother liquor and obtain ammonium sulfate by cold precipitation of mirabilite. Compared with the existing multi-effect evaporation to separate sodium sulfate from the mother liquor and then flash distilling ammonium sulfate, the new method has the advantages of energy saving, environmental protection, and stable quality of ammonium sulfate.

[0038] Embodiment 2

[0039] Based on the above embodiments, Figure 1 As shown, a method for detecting the concentration of ammonium sulfate prepared from sodium sulfate provided in an embodiment of the present invention, in the double decomposition reaction process, in order to ensure that the reaction conditions meet the process requirements, it is necessary to detect the concentration of the generated ammonium sulfate solution. Monitoring the concentration of the ammonium sulfate solution is an important link to ensure product quality and improve production efficiency, and specifically includes the following steps:

[0040] Step 1: Based on the double decomposition reaction time, the total reaction time is divided proportionally to obtain the detection period and the control period;

[0041] The split ratios include but are not limited to: 7:3, 8:2;

[0042] In this embodiment, the reaction time of double decomposition is 90min. If the time is divided according to the split ratio of 7:3, the detection period is 0-63min and the control period is 63-90min. If the time is divided according to the split ratio of 8:2, the detection period is 0-72min and the control period is 72-90min.

[0043] By dividing the reaction time into a detection period and a control time, the reaction in the detection period can be monitored in real time. The data in this period is real-time data. Analysis and prediction are performed based on the data in the detection period. Based on the prediction results, a control period is reserved to adjust its influencing parameters to optimize the reaction process and reduce the scrap rate and rework rate caused by concentration deviation.

[0044] Step 2: Based on the detection period, obtain the sodium sulfate concentration data of the detection period, perform analysis and judgment, and obtain the ammonium sulfate concentration prediction model;

[0045] In some embodiments, based on the detection period, the detection period is divided into a number of detection time points, wherein the time difference between any two adjacent time points is the same;

[0046] Obtaining the concentration of ammonium sulfate at each detection time point, wherein the detection method of the ammonium sulfate concentration includes but is not limited to: titration method, titration method, conductivity method, and online monitoring instrument;

[0047] In this embodiment, practitioners in the art may select a dedicated ammonium sulfate concentration sensor (such as DERACE online ammonium sulfate concentration meter) in an online monitoring instrument, which has a high degree of automation and can provide faster data feedback;

[0048] Integrate the ammonium sulfate concentrations during the detection period into an ammonium sulfate concentration data set in chronological order;

[0049] Assuming that the change of ammonium sulfate concentration over time is linear, the least squares method is used to obtain the linear regression fitting model;

[0050] Based on the linear regression fitting model, the mean square error and standard deviation are calculated to analyze whether the ammonium sulfate concentration data set conforms to the linear change. The specific process is as follows:

[0051] The calculation formula for mean square error MSE is: Where n is the number of detection time points, y i is the actual value of the ammonium sulfate concentration corresponding to the i-th detection time point (i.e., the value in the ammonium sulfate concentration data set), is the predicted value of ammonium sulfate concentration corresponding to the i-th detection time point;

[0052] The calculation process of the predicted value of ammonium sulfate concentration is as follows: outputting the detection time point to the independent variable of the linear regression fitting model, and outputting the predicted value of ammonium sulfate concentration;

[0053] The calculation formula for standard deviation SD is: in, is the residual at the i-th detection time point, represents the average value of all residuals, and n is the number of detection time points;

[0054] Substitute the mean square error MSE and standard deviation SD into the formula PD = s1*MSE+s2*SD 2 , the judgment value PD is calculated, where s1 and s2 are preset proportional coefficients, the value of s1 is 0.524, and the value of s2 is 0.476;

[0055] A judgment threshold is set, and the judgment value is compared with the judgment threshold. If the judgment value is less than the judgment threshold, the ammonium sulfate concentration data set conforms to the linear regression model, and a conforming signal is generated. If the judgment value is greater than or equal to the judgment threshold, the ammonium sulfate concentration data set does not conform to the linear regression model, and a non-conforming signal is generated.

[0056] The specific value of the judgment threshold is set by the implementer according to the specific implementation situation and is not limited here;

[0057] Based on the generated coincident signal, the linear regression model is the ammonium sulfate concentration prediction model;

[0058] Based on the generation of non-compliance signals, other models are used to train the ammonium sulfate concentration dataset, wherein the other models include but are not limited to: decision trees, random forests, support vector machines (SVMs), neural networks (including recursive neural networks such as LSTM or GRU), or gradient boosted tree (GBDT) models;

[0059] In this embodiment, the LSTM (Long Short-Term Memory Network) model is selected to train the ammonium sulfate concentration data set. The reason for selecting the LSTM (Long Short-Term Memory Network) model is that the LSTM model has better ability to process data with time series characteristics;

[0060] The specific process is:

[0061] Normalize the ammonium sulfate concentration data set to eliminate the impact of different dimensions on model training. The normalization formula can use min-max normalization to scale the data to the [0,1] interval. At the same time, convert the time data into a format suitable for model input, such as a time step sequence.

[0062] The preprocessed ammonium sulfate concentration data set is divided according to a certain ratio (e.g., 80% training set, 20% test set);

[0063] Set the input dimensions based on the time step and number of features (in this case, a single feature of ammonium sulfate concentration, but the time step will be determined by the time interval and total duration);

[0064] Select an appropriate number of LSTM units (such as 50, 100, etc.), and set the activation functions of the forget gate, input gate, and output gate (usually sigmoid), as well as the activation function of the cell state (usually tanh). Multiple layers of LSTM can be stacked to enhance the learning ability of the model.

[0065] After the LSTM layer, add one or more fully connected layers to extract features and output predicted values. The number of output units in the last layer should match the predicted target (in this case, 1, i.e., ammonium sulfate concentration).

[0066] Use a linear activation function to output the predicted ammonium sulfate concentration value;

[0067] Set the number of training rounds and the batch size in each round, then run the model for training. During the training process, monitor the loss value and performance indicators on the validation set, adjust the learning rate or use early stopping to prevent overfitting;

[0068] Evaluate the trained LSTM model on the test set, calculate and compare the difference between the predicted value and the true value, and evaluate the generalization ability of the model;

[0069] Depending on the evaluation results, you may need to adjust the model structure (such as increasing the number of LSTM layers, changing the number of units), optimizer parameters, or data preprocessing methods, and then retrain the model;

[0070] The LSTM (Long Short-Term Memory Network) model obtained through training is the ammonium sulfate concentration prediction model;

[0071] Step 3: Based on the ammonium sulfate concentration prediction model, determine whether the ammonium sulfate concentration can be within the standard concentration range at the end of the reaction time;

[0072] Among them, the standard concentration range is set by practitioners in this field based on historical experimental data and production process standards;

[0073] In some embodiments, based on the obtained ammonium sulfate concentration prediction model, the end time of the double decomposition reaction is used as an input value, and the ammonium sulfate concentration prediction model outputs a corresponding ammonium sulfate concentration prediction value;

[0074] Comparison of predicted ammonium sulfate concentrations with the standard concentration range

[0075] If the predicted value of ammonium sulfate concentration is within the standard concentration range, it means that at the end of the reaction, the ammonium sulfate concentration meets the production process standard and generates a normal signal;

[0076] If the predicted value of the ammonium sulfate concentration is not within the standard concentration range, it means that at the end of the reaction, the ammonium sulfate concentration does not meet the production process standard, and an abnormal signal is generated;

[0077] The technical solution of this embodiment is: by dividing the reaction time to obtain the detection period and the control period, the prediction model is constructed using the ammonium sulfate concentration data in the detection period, and according to the linear regression fitting of the data set, a suitable model (such as LSTM) is selected for training to obtain an ammonium sulfate concentration prediction model, and the ammonium sulfate concentration at the end of the reaction is predicted by the model, and compared with the standard concentration range to determine whether the product quality meets the production process standards;

[0078] By building an ammonium sulfate concentration prediction model, the ammonium sulfate concentration at the end of the reaction can be predicted more accurately, providing strong support for product quality control. At the same time, models such as LSTM can be flexibly selected according to the linear regression fitting of the data set to meet the needs of different data characteristics and improve the generalization ability of the model.

[0079] By predicting the ammonium sulfate concentration at the end of the reaction, potential concentration deviations can be discovered in a timely manner, providing a basis for adjustment and optimization in the production process, thereby improving production efficiency and product quality, and reducing the scrap rate and rework rate caused by concentration deviations, thereby reducing production costs and improving the economic benefits of the enterprise.

[0080] Embodiment 3

[0081] Based on the above embodiments, Figure 1 As shown, a method for detecting the concentration of ammonium sulfate prepared from sodium sulfate provided in an embodiment of the present invention specifically comprises the following steps:

[0082] Step 4: Based on the abnormal signal, the relevant factors of the double decomposition reaction process are identified to determine the influencing factors to be optimized;

[0083] Among them, the relevant factors in the metathesis reaction process include but are not limited to: reaction temperature, reaction pressure, stirring rate;

[0084] In some embodiments, based on the ammonium sulfate concentration data of the detection period, the relevant factor parameter value corresponding to the detection period is obtained;

[0085] In the detection period, the time period between two adjacent detection time points is marked as the analysis period;

[0086] In each analysis period, the difference between the ammonium sulfate concentration value at the end time point of the analysis period and the ammonium sulfate concentration value at the start time point of the analysis period is calculated to obtain the ammonium sulfate concentration change value, and the difference between the relevant factor parameter value at the end time point of the analysis period and the relevant factor parameter value at the start time point of the analysis period is calculated to obtain the relevant factor change value;

[0087] The change values ​​of ammonium sulfate concentration and related factor changes in the same analysis period are marked as the same group of data;

[0088] If the change value of ammonium sulfate concentration and the change value of related factors in the same group of data have the same sign, they are marked as same-direction change; if the change value of ammonium sulfate concentration and the change value of related factors in the same group of data have different signs, they are marked as different-direction change;

[0089] It should be explained that the same sign of the change value of ammonium sulfate concentration and the change value of related factors means that the change value of ammonium sulfate concentration and the change value of related factors are both positive or both negative;

[0090] Count the number of changes in the same direction and the number of changes in different directions, and sum them up to get the total number. Calculate the ratio of the number of changes in the same direction to the total number to get the same direction ratio, marked as TS.

[0091] Extract the data groups corresponding to the same-direction changes, calculate the ratio of the change value of the ammonium sulfate concentration in each data group to the change value of the relevant factors, and obtain the change ratio;

[0092] Arrange the change ratios in chronological order and calculate the discrete representation value BZ of the change ratio data. The calculation formula is: Where n is the number of change ratios, S k represents the kth change ratio, represents the average value of all adjacent change ratios of the kth change ratio, JC represents the difference between the maximum and minimum values ​​in the change ratio data, and JZ represents the average value of all change ratios;

[0093] Normalizing the discrete representation values ​​to eliminate the influence of the dimension, wherein the normalization is a processing method well known to practitioners in the art, such as linear function normalization;

[0094] Substitute the same direction quantity ratio TS and the discrete characterization value BZ into the formula XG = p1*ln(TS+1.003)+p2*BZ -2 , and obtain the relevant value, where p1 and p2 are preset proportional coefficients, the value of p1 is 1.524, and the value of p2 is 1.476;

[0095] It should be noted that the same direction quantity ratio is proportional to the correlation value, that is, the larger the same direction quantity ratio is, the larger the correlation value is, and the greater the correlation between the ammonium sulfate concentration and the corresponding related factors is, and the discrete representation value is inversely proportional to the correlation value, that is, the smaller the discrete representation value is, the larger the correlation value is, and the greater the correlation between the ammonium sulfate concentration and the corresponding related factors is;

[0096] A correlation threshold is set, and the correlation value is compared with the correlation threshold. If the correlation value is greater than the correlation threshold, a correlation signal is generated; if the correlation value is less than or equal to the correlation threshold, an irrelevant signal is generated;

[0097] Extract the relevant factors and relevant values ​​corresponding to the generated relevant signals, arrange the relevant values ​​in descending order to obtain a relevant value ranking table, and extract the relevant factors corresponding to the first relevant value in the ranking table as the influencing factors to be optimized;

[0098] It should be noted that if there is a tie for the first place in the sorting table, the relevant factors with a relatively large number of the same direction will be extracted as the influencing factors to be optimized. If the ratio of the number of the same direction is also the same, the implementer will select the influencing factors to be optimized based on historical experience;

[0099] The technical solution of this embodiment is: by monitoring the changes in the concentration of ammonium sulfate and related factors (such as reaction temperature, reaction pressure, stirring rate) during the double decomposition reaction, the number and ratio of the same-direction and different-direction changes in the change value of the ammonium sulfate concentration and the change value of the related factors are calculated, and the discrete characterization value of the change ratio is further calculated, and the correlation value is calculated in combination with the same-direction quantity ratio and the discrete characterization value, and finally the influencing factors to be optimized are determined according to the comparison between the correlation value and the related threshold value;

[0100] Therefore, by comprehensively considering the synchronization and discreteness of the changes in ammonium sulfate concentration and related factors, the key factors that have a significant impact on the ammonium sulfate concentration can be more accurately identified, thereby improving the accuracy and reliability of the detection. After determining the influencing factors to be optimized, targeted adjustments and optimizations can be made. When determining the influencing factors, the proportion of subsequent adjustments can be determined through the changing relationship between the changes in ammonium sulfate concentration and the changes in related factors, which adds data support to the adjustment control and makes the adjustment process more refined, thereby improving production efficiency and reducing production costs. It also helps to improve product quality and stability.

[0101] Embodiment 4

[0102] Based on the above embodiments, Figure 1 As shown, a method for detecting the concentration of ammonium sulfate prepared from sodium sulfate provided in an embodiment of the present invention specifically comprises the following steps:

[0103] Step 5: Based on the determined influencing factors to be optimized, adjust and control the influencing factors during the control period;

[0104] In some embodiments, based on the determined influencing factors to be optimized, a parameter value of the influencing factor to be optimized in the detection period is obtained and marked as a current parameter value of the influencing factor;

[0105] Obtain the average value of the change ratio corresponding to the influencing factors to be optimized;

[0106] The predicted value of ammonium sulfate concentration is calculated by difference with the standard concentration value to obtain the ammonium sulfate concentration deviation value, wherein the standard concentration value is the median value of the standard concentration range;

[0107] The deviation value of the ammonium sulfate concentration is processed with the average value of the change ratio corresponding to the influencing factor to be optimized to obtain the adjustment value of the influencing factor parameter;

[0108] It should be noted that the adjustment value of the influencing factor parameter may be positive or negative;

[0109] The current influencing factor parameter value and the influencing factor parameter adjustment value are summed up to obtain the influencing factor adjustment value;

[0110] During the control period, the parameter adjustment value of the influencing factor to be optimized is adjusted to the influencing factor control value, thereby optimizing the reaction process and increasing the possibility that the ammonium sulfate concentration meets the standard concentration range;

[0111] The technical solution of this embodiment is: by obtaining the parameter value of the influencing factor to be optimized in the detection period as the current value, and calculating the corresponding average value of the change ratio, by comparing the predicted value of the ammonium sulfate concentration with the median value of the standard concentration range, the concentration deviation value is obtained, and the deviation value is ratio-processed with the average value of the change ratio, so as to obtain the parameter adjustment value of the influencing factor. Whether it is a positive value or a negative value, the adjustment value will be added to the current parameter value of the influencing factor to obtain the influencing factor adjustment value. In the control period, the influencing factor to be optimized is adjusted according to the adjustment value, so as to optimize the reaction process. The mother liquor is adjusted to a pH value of 5-5.5 as the adjustment value to eliminate HCO 3 , increasing the possibility of ammonium sulfate concentration reaching the standard concentration range.

[0112] Embodiment 5

[0113] Based on the above embodiments, the present invention provides a system for detecting the concentration of ammonium sulfate prepared from sodium sulfate, which specifically includes:

[0114] Time division module: based on the double decomposition reaction time, the total reaction time is divided proportionally to obtain the detection period and the control period;

[0115] The split ratios include but are not limited to: 7:3, 8:2;

[0116] Prediction model acquisition module: based on the detection period, obtain the sodium sulfate concentration data of the detection period, perform analysis and judgment, and obtain the ammonium sulfate concentration prediction model;

[0117] Concentration standard judgment module: Based on the ammonium sulfate concentration prediction model, it is judged whether the ammonium sulfate concentration can be within the standard concentration range at the end of the reaction time;

[0118] Module for determining the influence to be optimized: Based on the abnormal signal, the module identifies the relevant factors of the double decomposition reaction process and determines the influence factors to be optimized;

[0119] Optimization control module: Based on the determined influencing factors to be optimized, the influencing factors are adjusted and controlled during the control period.

[0120] Embodiment 6

[0121] like Figure 3 As shown, an embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, a method for detecting the concentration of ammonium sulfate produced from sodium sulfate as described in any one of the above methods is implemented.

[0122] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that

[0123] Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0124] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0125] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit of the computer device 3 and an external storage device. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0126] Embodiment 7

[0127] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, a method for detecting the concentration of ammonium sulfate produced by sodium sulfate as described in any one of the above methods is implemented.

[0128] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0129] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0130] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0131] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0132] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0133] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0134] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate, characterized in that: The following steps are involved: It includes dissolving sodium sulfate, double decomposition reaction of ammonium bicarbonate, filtering, washing, and drying baking soda, and also includes cooling mother liquor, purifying and recovering sodium sulfate for reuse, vacuum evaporation, and vacuum cooling to produce by-product ammonium sulfate; During the double decomposition reaction, the concentration of the ammonium sulfate solution is detected and analyzed, and the specific steps are as follows: Step 1: Based on the double decomposition reaction time, the total reaction time is divided proportionally to obtain the detection period and the control period; Step 2: Based on the detection period, obtain the sodium sulfate concentration data of the detection period, perform analysis and judgment, and obtain the ammonium sulfate concentration prediction model; Step 3: Based on the ammonium sulfate concentration prediction model, determine whether the ammonium sulfate concentration can be within the standard concentration range at the end of the reaction time, and identify and output abnormal signals; Step 4: Based on the abnormal signal, the relevant factors of the double decomposition reaction process are identified to determine the influencing factors to be optimized; Step 5: Based on the determined influencing factors to be optimized, adjust and control the influencing factors during the control period.

2. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 1, characterized in that: The acquisition process of the ammonium sulfate concentration prediction model is as follows: Based on the detection period, the detection period is divided into several detection time points; Obtain the concentration of ammonium sulfate at each detection time point; Integrate the ammonium sulfate concentrations during the detection period into an ammonium sulfate concentration data set in chronological order; The least square method was used to obtain the linear regression fitting model; Based on the linear regression fitting model, the judgment value is calculated; A judgment threshold is set, and the judgment value is compared with the judgment threshold. If the judgment value is less than the judgment threshold, the ammonium sulfate concentration data set conforms to the linear regression model, and a conforming signal is generated. If the judgment value is greater than or equal to the judgment threshold, the ammonium sulfate concentration data set does not conform to the linear regression model, and a non-conforming signal is generated. Based on the generated coincident signal, the linear regression model is the ammonium sulfate concentration prediction model; Based on the generation of non-compliant signals, other models are used to train the ammonium sulfate concentration data set, and the trained model is the ammonium sulfate concentration prediction model.

3. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 2, characterized in that: The process of obtaining the judgment value is as follows: Get the mean square error MSE and standard deviation SD; Substitute the mean square error MSE and standard deviation SD into the formula PD = s1*MSE+s2*SD 2 , the judgment value PD is calculated, where s1 and s2 are preset proportional coefficients.

4. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 3, characterized in that: The process of obtaining the mean square error MSE and the standard deviation SD is as follows: The calculation formula for mean square error MSE is: Where n is the number of detection time points, y i is the actual value of the ammonium sulfate concentration corresponding to the i-th detection time point (i.e., the value in the ammonium sulfate concentration data set), is the predicted value of ammonium sulfate concentration corresponding to the i-th detection time point; The calculation process of the predicted value of ammonium sulfate concentration is as follows: outputting the detection time point to the independent variable of the linear regression fitting model, and outputting the predicted value of ammonium sulfate concentration; The calculation formula for standard deviation SD is: in, is the residual at the i-th detection time point, represents the average value of all residuals, and n is the number of detection time points.

5. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 1, characterized in that: The specific process of step three is: Based on the obtained ammonium sulfate concentration prediction model, the end time of the double decomposition reaction is used as an input value, and the ammonium sulfate concentration prediction model outputs a corresponding ammonium sulfate concentration prediction value; Comparison of predicted ammonium sulfate concentrations with the standard concentration range If the predicted value of the ammonium sulfate concentration is not within the standard concentration range, an abnormal signal is generated.

6. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 1, characterized in that: The process of the influencing factors to be optimized is: Obtaining a correlation value, setting a correlation threshold, comparing the correlation value with the correlation threshold, generating a correlation signal if the correlation value is greater than the correlation threshold, and generating an uncorrelated signal if the correlation value is less than or equal to the correlation threshold; The relevant factors and relevant values ​​corresponding to the generated relevant signals are extracted, and the relevant values ​​are arranged in order from large to small to obtain a correlation value sorting table. The relevant factors corresponding to the first correlation value in the sorting table are extracted as the influencing factors to be optimized.

7. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 6, characterized in that: The process of obtaining the related value is as follows: Obtain the same direction quantity ratio TS and the discrete characterization value BZ; Substitute the same direction quantity ratio TS and the discrete characterization value BZ into the formula XG = p1*ln(TS+1.003)+p2*BZ -2 , and obtain the relevant value, where p1 and p2 are preset proportional coefficients.

8. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 7, characterized in that: The process of obtaining the same direction quantity ratio TS is as follows: Based on the ammonium sulfate concentration data of the detection period, obtain the relevant factor parameter value corresponding to the detection period; In the detection period, the time period between two adjacent detection time points is marked as the analysis period; In each analysis period, the difference between the ammonium sulfate concentration value at the end time point of the analysis period and the ammonium sulfate concentration value at the start time point of the analysis period is calculated to obtain the ammonium sulfate concentration change value, and the difference between the relevant factor parameter value at the end time point of the analysis period and the relevant factor parameter value at the start time point of the analysis period is calculated to obtain the relevant factor change value; The change values ​​of ammonium sulfate concentration and related factor changes in the same analysis period are marked as the same group of data; If the change value of ammonium sulfate concentration and the change value of related factors in the same group of data have the same sign, they are marked as same-direction change; if the change value of ammonium sulfate concentration and the change value of related factors in the same group of data have different signs, they are marked as different-direction change; The numbers marked as changes in the same direction and changes in different directions are counted and summed up to get the total number. The ratio of the number of changes in the same direction to the total number is calculated to get the same direction ratio, which is marked as TS.

9. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 7, characterized in that: The process of obtaining the discrete characterization value BZ is as follows: Extract the data groups corresponding to the same-direction changes, calculate the ratio of the change value of the ammonium sulfate concentration in each data group to the change value of the relevant factors, and obtain the change ratio; Arrange the change ratios in chronological order and calculate the discrete representation value BZ of the change ratio data. The calculation formula is: Where n is the number of change ratios, S k represents the kth change ratio, represents the average value of all adjacent change ratios of the kth change ratio, JC represents the difference between the maximum and minimum values ​​in the change ratio data, and JZ represents the average value of all change ratios.

10. A method for detecting the concentration of ammonium sulfate prepared from sodium sulfate according to claim 9, characterized in that: The process of adjusting and controlling the influencing factors during the control period is as follows: Based on the determined influencing factors to be optimized, obtaining parameter values ​​of the influencing factors to be optimized during the detection period, and marking them as current parameter values ​​of the influencing factors; Obtain the average value of the change ratio corresponding to the influencing factors to be optimized; The predicted value of ammonium sulfate concentration is calculated by difference with the standard concentration value to obtain the ammonium sulfate concentration deviation value, wherein the standard concentration value is the median value of the standard concentration range; The deviation value of the ammonium sulfate concentration is processed with the average value of the change ratio corresponding to the influencing factor to be optimized to obtain the adjustment value of the influencing factor parameter; It should be noted that the adjustment value of the influencing factor parameter may be positive or negative; The current influencing factor parameter value and the influencing factor parameter adjustment value are summed up to obtain the influencing factor adjustment value; During the control period, the parameters of the influencing factors to be optimized are adjusted to the influencing factor control values.

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