Automated Electrochemical Liquid Medicine Adding System

Abstract

The present invention relates to the technical field of liquid medicine addition, specifically an automated electrochemistry liquid medicine addition system. The system includes a liquid addition behavior dynamic optimization module, which combines a first risk impact value and a second risk impact value to judge the optimization requirements of the liquid addition behavior at the current time; and when there are optimization requirements, generates different batch liquid addition behavior planning schemes, calculates the intervention interference values of each batch of liquid addition behavior planning schemes on the production line during the execution process respectively, and screens the batch liquid addition behavior planning scheme with the smallest corresponding intervention interference value as the liquid addition behavior dynamic optimization result. In the process of automated electrochemistry liquid medicine addition, the present invention not only realizes the automatic replenishment of the liquid medicine in the liquid medicine storage tank, but also takes into account the operating state of the current production equipment and the influence of the liquid medicine addition behavior on the produced products, realizes the dynamic optimization of the liquid medicine addition behavior, reduces the interference of the liquid addition behavior on the equipment operation, and realizes the effective control of the liquid medicine addition behavior.

Description

Technical Field

[0001] The present invention relates to the technical field of liquid medicine addition, and specifically to an automated electrochemical liquid medicine addition system. Background Art

[0002] With the continuous progress of automation technology, more and more industries have started to use automated equipment for production and management to improve production efficiency and product quality. In the field of electrochemistry, the introduction of automation technology has provided a new solution for liquid medicine addition, realizing the transformation from manual operation to automated control. Compared with manual addition, which is easily affected by human factors and leads to unstable liquid medicine ratios, the automated electrochemical liquid medicine addition system can achieve precise quantification of liquid medicine ratios and reduce the impact of the liquid medicine addition process on product quality to a certain extent.

[0003] Existing automated electrochemical liquid medicine addition systems often simply monitor the liquid level of the liquid medicine in the liquid medicine storage tank through sensors, automatically prepare the liquid medicine to be added when the monitoring result is abnormal, and automatically replenish the liquid medicine in the liquid medicine storage tank. However, this method does not consider the operating state of the current production equipment and the impact of the liquid medicine addition behavior on the produced products, fails to achieve dynamic optimization of the liquid medicine addition behavior, and reduces the interference of the medicine addition behavior on equipment operation. Therefore, there are significant defects in the prior art. Summary of the Invention

[0004] The purpose of the present invention is to provide an automated electrochemical liquid medicine addition system to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solution: an automated electrochemical liquid medicine addition system, the system includes:

[0006] A liquid addition behavior determination module, which obtains the liquid medicine data in each liquid medicine storage tank at the current time through sensors in real time, compares the obtained liquid medicine data with the standard parameters of the corresponding liquid medicine storage tank, and calculates the liquid medicine addition demand value of each liquid medicine storage tank;

[0007] An addition amount prediction module, which generates the liquid medicine addition characteristic parameters corresponding to the current time according to the obtained liquid medicine addition demand values of each liquid medicine storage tank and the current states of each liquid medicine storage tank;

[0008] Liquid addition behavior impact analysis module, the liquid addition behavior impact analysis module obtains the liquid addition amount corresponding to each liquid storage tank in the liquid addition characteristic parameters and the operation status of the production line to which the corresponding liquid storage tank belongs at the current time, combines the impacts of different liquid addition behaviors on the production line operation status in the historical data, predicts the impact of adding the corresponding liquid addition amount to the corresponding liquid storage tank at the current time on the corresponding production line, and obtains the first risk impact value; combines the operation data of the current production line, predicts the time delay of each liquid addition, and evaluates the impact of the corresponding liquid addition time delay on the corresponding production line, and obtains the second risk impact value;

[0009] Liquid addition behavior dynamic optimization module, the liquid addition behavior dynamic optimization module combines the first risk impact value and the second risk impact value to judge the optimization requirements of the liquid addition behavior at the current time; and when there are optimization requirements, generates different batch liquid addition behavior planning schemes, and respectively calculates the intervention interference values of each batch liquid addition behavior planning scheme on the production line during the execution process, and screens the batch liquid addition behavior planning scheme with the smallest corresponding intervention interference value as the liquid addition behavior dynamic optimization result;

[0010] Liquid addition behavior warning module, the liquid addition behavior warning module generates a liquid addition behavior warning report according to the optimization requirement determination result and the liquid addition behavior dynamic optimization result of the liquid addition behavior at the current time obtained by the liquid addition behavior dynamic optimization module, and feeds it back to the corresponding administrator for confirmation.

[0011] Furthermore, the liquid data includes the component composition of the liquid, the concentration of each component, and the total amount of the liquid;

[0012] When calculating the liquid addition demand value of each liquid storage tank in the liquid addition behavior determination module, the liquid addition demand value of the i-th liquid storage tank is denoted as Qi,

[0013] ,

[0014] where β is a demand conversion factor and β is a constant preset in the database;

[0015] Cik represents the absolute value of the difference between the concentration of the k-th component in the liquid data of the i-th liquid storage tank at the current time and the midpoint of the concentration interval corresponding to the component in the standard parameters of the corresponding liquid storage tank; ki represents the number of component types in the liquid data of the i-th liquid storage tank at the current time;

[0016] Lik represents the interval length of the k-th component in the liquid data of the i-th liquid storage tank in the corresponding concentration interval in the corresponding standard parameters;

[0017] Zi represents the opposite of the difference between the total amount of the liquid in the liquid data of the i-th liquid storage tank at the current time and the minimum value of the total amount of the liquid in the corresponding standard parameters;

[0018] Let \(P\{\}\) denote the demand determination function. When the value of the first parameter in the function is greater than or equal to the value of the second parameter, the corresponding function result is determined to be the value of the first parameter in the function; otherwise, the corresponding function result is determined to be 0.

[0019] Through the analysis of the liquid medicine data, the present invention realizes the comprehensive quantification of the deviation of the liquid medicine storage tank situation compared with the corresponding standard parameters, and further realizes the accurate judgment of the liquid adding behavior of the liquid medicine storage tank.

[0020] Furthermore, the liquid adding characteristic parameters corresponding to the current time include the composition of the added liquid medicine corresponding to each liquid medicine storage tank, the concentrations corresponding to each component respectively, and the added amount of the liquid medicine.

[0021] When generating the liquid adding characteristic parameters corresponding to the current time in the added amount prediction module, the liquid adding demand value of each liquid medicine storage tank and the current state of each liquid medicine storage tank are obtained.

[0022] Arrange the medicine adding order corresponding to each liquid medicine storage tank in the liquid adding characteristic parameters corresponding to the current time in descending order according to the corresponding liquid adding demand value. The added amount of the liquid medicine corresponding to the \(i\)-th liquid medicine storage tank is the opposite of the difference between the total amount of the liquid medicine in the liquid medicine data of the \(i\)-th liquid medicine storage tank at the current time and the minimum value of the total amount of the liquid medicine in the corresponding standard parameters.

[0023] The concentrations corresponding to each component in the liquid adding characteristic parameters corresponding to the current time are obtained by querying the values corresponding to the corresponding data groups in the preset form in the database. The data groups corresponding to the corresponding components include the concentration of the corresponding component before adding medicine, the concentration interval corresponding to the corresponding component in the corresponding standard parameters, and the added amount of the liquid medicine.

[0024] Furthermore, the liquid adding behavior impact analysis module includes an added amount risk analysis unit and an added time delay risk analysis unit.

[0025] The added amount risk analysis unit obtains the added amount of the liquid medicine corresponding to each liquid medicine storage tank in the liquid adding characteristic parameters and the operating state of the production line to which the corresponding liquid medicine storage tank belongs at the current time, and combines the impacts of different liquid adding behaviors on the production line operating state in the historical data to predict the impact of adding the corresponding liquid adding amount to the corresponding liquid medicine storage tank at the current time on the corresponding production line, and obtains the first risk impact value.

[0026] The added time delay risk analysis unit combines the operating data of the current production line to predict the added time delay of each liquid adding, and evaluates the impact of the corresponding liquid adding time delay on the corresponding production line, and obtains the second risk impact value.

[0027] The present invention analyzes the interference of the addition amount of the liquid addition behavior on the production line operation and the interference of the corresponding addition delay on the production line operation when the production line stops through historical data analysis. By quantifying the risk impact degrees corresponding to the two situations respectively, an effective screening of the liquid addition method for the liquid medicine storage tank is realized, and data support is provided for the determination of the optimization requirement of the current-time liquid addition behavior and the screening of the optimization scheme in the subsequent steps.

[0028] Further, when the addition amount risk analysis unit obtains the first risk impact value,

[0029] obtain the liquid addition amount corresponding to each liquid medicine storage tank in the liquid addition characteristic parameters and the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time. The operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time includes the production product type corresponding to the production line to which the corresponding liquid medicine storage tank belongs at the current time, the remaining operation duration, the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition requirement value, the relationship function between the product abnormality rate corresponding to the corresponding product type and the mutation amount of the liquid addition requirement value, and the change function of the liquid addition requirement value corresponding to the corresponding product type with the operation duration;

[0030] in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time, when the remaining operation duration is equal to that in the historical data when the corresponding production line produces the corresponding product type, it is the quotient of the remaining product quantity to be produced at the current time and the average production speed of the corresponding product type in the historical data;

[0031] when obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition requirement value of the i-th liquid medicine storage tank, obtain each demand correlation data pair corresponding to the i-th liquid medicine storage tank in the historical data. In the demand correlation data pair, the first value is the liquid addition requirement value of the liquid medicine storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; according to the preset function model y = -x -a + b (where a and b are both constants, and through function fitting, the quantification and acquisition of the values of a and b can be realized), fit the obtained each demand correlation data pair, and calculate the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each correlation data pair respectively, obtain the data fitting deviation corresponding to each fitting result, and use the fitting function corresponding to the minimum value in the obtained data fitting deviations as the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition requirement value of the i-th liquid medicine storage tank, denoted as WQi(x);

[0032] When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change value of the liquid medicine addition requirement value of the i-th liquid medicine storage tank, obtain each demand mutation correlation data pair corresponding to the i-th liquid medicine storage tank in the historical data. The first value in the demand mutation correlation data pair is the sudden change value of the liquid medicine addition requirement of the liquid medicine storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type. The sudden change value of the liquid medicine addition requirement is equal to the maximum difference between the liquid medicine addition requirement values corresponding to different time points within the unit time after the medicine addition operation is executed; according to the preset function model y1=-x1 -a +b, fit each obtained demand mutation correlation data pair, and calculate the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each demand mutation correlation data pair respectively, to obtain the data fitting deviation corresponding to each fitting result. Take the fitting function corresponding to the minimum value among the obtained data fitting deviations as the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change value of the liquid medicine addition requirement value of the i-th liquid medicine storage tank, denoted as WTi(x1);

[0033] When obtaining the change function of the liquid medicine addition requirement value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the running duration, obtain each running demand correlation data pair corresponding to the i-th liquid medicine storage tank in the historical data. The first value in the running demand correlation data pair is the subsequent running duration based on the liquid medicine addition requirement value of the i-th liquid medicine storage tank corresponding to the corresponding product type, and the second value is the liquid medicine addition requirement value of the liquid medicine storage tank. Fit each obtained running demand correlation data pair according to the preset linear regression model, and take the obtained fitting function as the change function of the liquid medicine addition requirement value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the running duration, denoted as WYi(t);

[0034] Record the first risk impact value when adding the corresponding liquid medicine addition amount to the i-th liquid medicine storage tank at the current time as FOi,

[0035] where FOi = WTi(B),

[0036] where B represents the sudden change value of the liquid medicine addition requirement corresponding to adding the corresponding liquid medicine addition amount to the i-th liquid medicine storage tank at the current time; WTi(B) represents the function value of WTi(x1) when x1 is B;

[0037] The value of B is equal to the average value of the sudden change values of the liquid medicine addition requirements corresponding to each element in the reference array corresponding to Qi;

[0038] The reference array corresponding to Qi is obtained by querying all liquid medicine addition behaviors in the historical database where the corresponding liquid medicine addition requirement value is the same as Qi and the deviation between the liquid medicine addition amount and the liquid medicine addition amount added to the i-th liquid medicine storage tank at the current time is less than the preset value.

[0039] Further, when the addition time-delay risk analysis unit obtains the second risk impact value,

[0040] the liquid addition time-delay corresponding to the i-th liquid storage tank is equal to the waiting operation duration in the operation state of the production line to which the corresponding liquid storage tank belongs at the current time;

[0041] The second risk impact value corresponding to the liquid addition time-delay of the i-th liquid storage tank is denoted as FTi,

[0042] FTi = WQi (WYi (tsi)),

[0043] where tsi represents the liquid addition time-delay corresponding to the i-th liquid storage tank; WYi (tsi) represents the function value corresponding to WYi (t) when t is tsi; WQi (WYi (tsi)) represents the function value corresponding to WQi (x) when x is WYi (tsi).

[0044] Further, when the liquid addition behavior dynamic optimization module determines the optimization requirement of the liquid addition behavior at the current time, if both the first risk impact value and the second risk impact value corresponding to the i-th liquid storage tank are greater than or equal to the preset product abnormality rate, it is determined that there is an optimization requirement for the liquid addition behavior at the current time; if both the first risk impact value and the second risk impact value corresponding to the i-th liquid storage tank are less than the preset product abnormality rate, it is determined that there is no optimization requirement for the liquid addition behavior at the current time.

[0045] If the first risk impact value corresponding to the i-th liquid storage tank is less than or equal to the second risk impact value, it is determined that the liquid addition behavior operation is performed according to the liquid addition characteristic parameters corresponding to the current time after the waiting operation duration in the operation state of the production line to which the i-th liquid storage tank belongs at the current time; otherwise, the liquid addition behavior operation is immediately performed according to the liquid addition characteristic parameters corresponding to the current time.

[0046] When the liquid addition behavior dynamic optimization module generates different batch liquid addition behavior planning schemes, the corresponding liquid addition amount of the i-th liquid storage tank at the current time is evenly divided into n parts and two batches. The liquid addition time corresponding to the first batch is the current time, and the liquid addition time corresponding to the second batch is the waiting operation duration in the operation state of the production line to which the i-th liquid storage tank belongs at the current time. The number of copies of the liquid addition amount corresponding to each liquid storage tank in the first batch and the second batch is adjusted respectively to generate different liquid addition behavior planning schemes corresponding to the corresponding liquid storage tanks. The liquid addition behavior planning schemes corresponding to each liquid storage tank are combined to generate different batch liquid addition behavior planning schemes. The sum of the number of copies of the liquid addition amounts corresponding to the first batch and the second batch corresponding to the corresponding liquid storage tank in each batch liquid addition behavior planning scheme is n, and n is a constant preset in the database.

[0047] When the liquid addition behavior dynamic optimization module calculates the intervention interference values of each batch of liquid addition behavior planning schemes on the production line during the execution process, the intervention interference value of the j-th batch of liquid addition behavior planning scheme on the production line during the execution process is denoted as GRj.

[0048] ,

[0049] where, ig represents the number of liquid medicine storage tanks; HOij represents the prediction result of the corresponding first risk impact value when the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme executes the corresponding first batch of liquid addition scheme; HTij represents the prediction result of the corresponding second risk impact value of the liquid medicine addition requirement value corresponding after the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme executes the corresponding first batch of liquid addition scheme.

[0050] The liquid medicine addition requirement value corresponding after the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme executes the corresponding first batch of liquid addition scheme is equal to the average value of the liquid medicine addition requirement values corresponding after each element in the reference set corresponding to the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme executes the corresponding liquid medicine addition behavior.

[0051] The reference set corresponding to the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme is obtained by querying all liquid medicine addition behaviors in the historical database where the corresponding liquid medicine addition requirement value is the same as Qi and the deviation between the liquid medicine addition amount and Mij is less than the preset value, and Mij represents the corresponding liquid medicine addition amount of the corresponding first batch of liquid addition scheme of the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme.

[0052] Furthermore, when the liquid addition behavior warning module generates a liquid addition behavior warning report, if there is no optimization requirement for the liquid addition behavior of each liquid medicine storage tank at the current time, then the set composed of the current time point, each liquid medicine addition characteristic parameter at the current time, and the corresponding execution time is used as the liquid addition behavior warning report corresponding to the current time;

[0053] if there is an optimization requirement for the liquid addition behavior of the liquid medicine storage tank at the current time, then the set composed of the current time point and the corresponding liquid addition behavior dynamic optimization result at the current time is used as the liquid addition behavior warning report corresponding to the current time;

[0054] After the generated liquid addition behavior warning report is fed back to the corresponding administrator for confirmation, when the corresponding administrator receives and approves the corresponding liquid addition behavior warning report or the corresponding administrator does not receive the corresponding liquid addition behavior warning report within the preset time, the liquid addition operation on the corresponding liquid medicine storage tank is automatically executed according to the liquid addition behavior planning scheme in the corresponding liquid addition behavior warning report; otherwise, the corresponding administrator is reminded to manually execute the liquid addition operation on the corresponding liquid medicine storage tank.

[0055] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: In the automated electrochemical liquid medicine adding process of the present invention, not only the liquid level of the liquid medicine in the liquid medicine storage tank is monitored through sensors to realize the automatic replenishment of the liquid medicine in the liquid medicine storage tank, but also the operating state of the current production equipment and the influence of the liquid medicine adding behavior on the produced products are considered, and the dynamic optimization of the liquid medicine adding behavior is realized, so as to reduce the interference of the liquid medicine adding behavior on the equipment operation and realize the effective control of the liquid medicine adding behavior. Description of the Drawings

[0056] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0057] Figure 1 is a schematic structural diagram of the automated electrochemical liquid medicine adding system of the present invention. Detailed Embodiments

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the 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.

[0059] Please refer to Figure 1 , the present invention provides a technical solution: an automated electrochemical liquid medicine adding system, the system includes:

[0060] A liquid adding behavior determination module, which obtains the liquid medicine data in each liquid medicine storage tank at the current time through sensors in real time, compares the obtained liquid medicine data with the standard parameters of the corresponding liquid medicine storage tank, and calculates the liquid medicine adding demand value of each liquid medicine storage tank;

[0061] The liquid medicine data includes the composition of the liquid medicine, the concentration of each component, and the total amount of the liquid medicine;

[0062] When calculating the liquid medicine adding demand value of each liquid medicine storage tank in the liquid adding behavior determination module, the liquid medicine adding demand value of the i-th liquid medicine storage tank is denoted as Qi,

[0063] ,

[0064] where β is a demand conversion factor and β is a constant preset in the database;

[0065] $C_{ik}$ represents the absolute value of the difference between the concentration of the $k$-th component in the liquid medicine data of the $i$-th liquid medicine storage tank at the current time and the midpoint of the concentration interval corresponding to the corresponding component in the standard parameters of the corresponding liquid medicine storage tank; $k_i$ represents the number of component types in the liquid medicine data of the $i$-th liquid medicine storage tank at the current time;

[0066] $L_{ik}$ represents the interval length of the $k$-th component in the concentration interval corresponding to the standard parameters in the liquid medicine data of the $i$-th liquid medicine storage tank;

[0067] $Z_i$ represents the opposite of the difference between the total amount of the liquid medicine in the liquid medicine data of the $i$-th liquid medicine storage tank at the current time and the minimum value of the total amount of the liquid medicine in the corresponding standard parameters;

[0068] $P\{,\}$ represents a demand determination function. When the value of the first parameter in the function is greater than or equal to the value of the second parameter, the corresponding function result is determined to be the value of the first parameter in the function; otherwise, the corresponding function result is determined to be 0.

[0069] An addition amount prediction module, which generates a liquid medicine addition characteristic parameter corresponding to the current time according to the obtained liquid medicine addition demand values of each liquid medicine storage tank and the current states of each liquid medicine storage tank;

[0070] The liquid medicine addition characteristic parameter corresponding to the current time includes the component composition of the added liquid medicine corresponding to each liquid medicine storage tank, the concentration corresponding to each component respectively, and the addition amount of the liquid medicine;

[0071] When generating the liquid medicine addition characteristic parameter corresponding to the current time in the addition amount prediction module, the liquid medicine addition demand value of each liquid medicine storage tank and the current states of each liquid medicine storage tank are obtained;

[0072] Arrange the medicine addition order corresponding to each liquid medicine storage tank in the liquid medicine addition characteristic parameter corresponding to the current time in descending order according to the corresponding liquid medicine addition demand value. The addition amount of the liquid medicine corresponding to the $i$-th liquid medicine storage tank is the opposite of the difference between the total amount of the liquid medicine in the liquid medicine data of the $i$-th liquid medicine storage tank at the current time and the minimum value of the total amount of the liquid medicine in the corresponding standard parameters;

[0073] The concentration corresponding to each component in the liquid medicine addition characteristic parameter corresponding to the current time is obtained by querying the value corresponding to the corresponding data group in the preset form in the database. The data group corresponding to the corresponding component includes the concentration of the corresponding component before adding medicine, the concentration interval corresponding to the corresponding component in the corresponding standard parameters, and the addition amount of the liquid medicine.

[0074] Liquid addition behavior impact analysis module, the liquid addition behavior impact analysis module obtains the liquid addition amount corresponding to each liquid storage tank in the liquid addition characteristic parameters and the operating state of the production line to which the liquid storage tank belongs at the current time, combines the impacts of different liquid addition behaviors on the production line operating state in historical data, predicts the impact of adding the corresponding liquid addition amount to the corresponding liquid storage tank at the current time on the corresponding production line, and obtains the first risk impact value; combines the operating data of the current production line, predicts the time delay of each liquid addition, and evaluates the impact of the corresponding liquid addition time delay on the corresponding production line, and obtains the second risk impact value;

[0075] The liquid addition behavior impact analysis module includes a liquid addition amount risk analysis unit and a liquid addition time delay risk analysis unit,

[0076] The liquid addition amount risk analysis unit obtains the liquid addition amount corresponding to each liquid storage tank in the liquid addition characteristic parameters and the operating state of the production line to which the liquid storage tank belongs at the current time, combines the impacts of different liquid addition behaviors on the production line operating state in historical data, predicts the impact of adding the corresponding liquid addition amount to the corresponding liquid storage tank at the current time on the corresponding production line, and obtains the first risk impact value;

[0077] When the liquid addition amount risk analysis unit obtains the first risk impact value,

[0078] Obtain the liquid addition amount corresponding to each liquid storage tank in the liquid addition characteristic parameters and the operating state of the production line to which the liquid storage tank belongs at the current time, and the operating state of the production line to which the liquid storage tank belongs at the current time includes the production product type corresponding to the production line to which the liquid storage tank belongs at the current time, the remaining operation time, the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value, the relationship function between the product abnormality rate corresponding to the corresponding product type and the mutation amount of the liquid addition demand value, and the change function of the liquid addition demand value corresponding to the corresponding product type with the operation time;

[0079] In the operating state of the production line to which the liquid storage tank belongs at the current time, the remaining operation time is equal to the quotient of the remaining product quantity to be produced at the current time and the average production speed of the corresponding product type in historical data when the corresponding production line produces the corresponding product type in historical data;

[0080] When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, obtain each demand correlation data pair corresponding to the i-th liquid storage tank in historical data, and the first value in the demand correlation data pair is the liquid addition demand value of the liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; according to the preset function model y=-x -a+b (where a and b are both constants, and through function fitting, the quantification and acquisition of the values of a and b can be achieved), fit the obtained various demand correlation data pairs, and calculate the sum of the shortest distances between the function curves corresponding to each fitting result and the coordinates corresponding to each correlation data pair respectively, to obtain the data fitting deviation corresponding to each fitting result. Take the fitting function corresponding to the minimum value among the obtained data fitting deviations as the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid medicine addition demand value of the i-th liquid medicine storage tank, denoted as WQi(x);

[0081] In this embodiment, when obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid medicine addition demand value of the i-th liquid medicine storage tank, the function model y = -x -a +b is used for function fitting. Quantified into a specific coordinate system, the parameter corresponding to the x-axis is the liquid medicine addition demand value of the liquid medicine storage tank, and the parameter corresponding to the y-axis is the product abnormality rate corresponding to the corresponding product type; the fitting result is actually the quantification and acquisition of the values of a and b.

[0082] When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the change amount of the liquid medicine addition demand value of the i-th liquid medicine storage tank, obtain each demand mutation correlation data pair corresponding to the i-th liquid medicine storage tank in the historical data. The first value in the demand mutation correlation data pair is the change amount of the liquid medicine addition demand of the liquid medicine storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; the change amount of the liquid medicine addition demand is equal to the maximum difference between the liquid medicine addition demand values corresponding to different time points within the unit time after the medicine addition operation is executed. According to the preset function model y1 = -x1 -a +b, fit the obtained various demand mutation correlation data pairs, and calculate the sum of the shortest distances between the function curves corresponding to each fitting result and the coordinates corresponding to each demand mutation correlation data pair respectively, to obtain the data fitting deviation corresponding to each fitting result. Take the fitting function corresponding to the minimum value among the obtained data fitting deviations as the relationship function between the product abnormality rate corresponding to the corresponding product type and the change amount of the liquid medicine addition demand value of the i-th liquid medicine storage tank, denoted as WTi(x1);

[0083] When obtaining the variation function of the liquid medicine addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation duration, obtain each operation demand correlation data pair corresponding to the i-th liquid medicine storage tank in the historical data. The first value in the operation demand correlation data pair is the subsequent operation duration based on the liquid medicine addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type, and the second value is the liquid medicine addition demand value of the liquid medicine storage tank. Fit each obtained operation demand correlation data pair according to the preset linear regression model, and use the obtained fitting function as the variation function of the liquid medicine addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation duration, denoted as WYi(t);

[0084] Denote the first risk impact value corresponding to adding the corresponding liquid medicine addition amount to the i-th liquid medicine storage tank at the current time as FOi,

[0085] The FOi = WTi(B),

[0086] where B represents the sudden change amount of the liquid medicine addition demand corresponding to adding the corresponding liquid medicine addition amount to the i-th liquid medicine storage tank at the current time; WTi(B) represents the function value corresponding to WTi(x1) when x1 is B;

[0087] The value of B is equal to the average value of the sudden change values of the liquid medicine addition demand corresponding to each element in the reference array corresponding to Qi;

[0088] The reference array corresponding to Qi is obtained by querying all liquid medicine addition behaviors in the historical database where the corresponding liquid medicine addition demand value is the same as Qi and the deviation between the liquid medicine addition amount and the liquid medicine addition amount added to the i-th liquid medicine storage tank at the current time is less than the preset value.

[0089] The addition time delay risk analysis unit combines the operation data of the current production line, predicts the time delay of each liquid medicine addition, and evaluates the impact of the corresponding liquid medicine addition time delay on the corresponding production line to obtain the second risk impact value;

[0090] When the addition time delay risk analysis unit obtains the second risk impact value,

[0091] The liquid medicine addition time delay corresponding to the i-th liquid medicine storage tank is equal to the waiting operation duration in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time;

[0092] Denote the second risk impact value corresponding to the liquid medicine addition time delay corresponding to the i-th liquid medicine storage tank as FTi,

[0093] FTi = WQi(WYi(tsi)),

[0094] where, tsi represents the liquid addition time delay corresponding to the i-th liquid storage tank; WYi(tsi) represents the function value corresponding to WYi(t) when t is tsi; WQi(WYi(tsi)) represents the function value corresponding to WQi(x) when x is WYi(tsi).

[0095] The liquid addition behavior dynamic optimization module combines the first risk impact value and the second risk impact value to judge the optimization requirement of the liquid addition behavior at the current time; and when there is an optimization requirement, generates different batch liquid addition behavior planning schemes, and respectively calculates the intervention interference values of each batch of liquid addition behavior planning schemes on the production line during the execution process, and screens the batch liquid addition behavior planning scheme with the smallest corresponding intervention interference value as the liquid addition behavior dynamic optimization result;

[0096] When the liquid addition behavior dynamic optimization module judges the optimization requirement of the liquid addition behavior at the current time, if both the first risk impact value and the second risk impact value corresponding to the i-th liquid storage tank are greater than or equal to the preset product abnormality rate, it is determined that there is an optimization requirement for the liquid addition behavior at the current time; if both the first risk impact value and the second risk impact value corresponding to the i-th liquid storage tank are less than the preset product abnormality rate, it is determined that there is no optimization requirement for the liquid addition behavior at the current time.

[0097] If the first risk impact value corresponding to the i-th liquid storage tank is less than or equal to the second risk impact value, it is determined that the liquid addition behavior operation is performed according to the liquid addition characteristic parameters corresponding to the current time after the waiting operation duration in the running state of the production line to which the i-th liquid storage tank belongs at the current time; otherwise, the liquid addition behavior operation is immediately performed according to the liquid addition characteristic parameters corresponding to the current time;

[0098] When the liquid addition behavior dynamic optimization module generates different batch liquid addition behavior planning schemes, the corresponding liquid addition amount of the i-th liquid storage tank at the current time is evenly divided into n parts and two batches. The liquid addition time corresponding to the first batch is the current time, and the liquid addition time corresponding to the second batch is the waiting operation duration in the running state of the production line to which the i-th liquid storage tank belongs at the current time; the number of parts of the liquid addition amount corresponding to each liquid storage tank in the first batch and the second batch is respectively adjusted to generate different liquid addition behavior planning schemes corresponding to the corresponding liquid storage tanks, and the liquid addition behavior planning schemes corresponding to each liquid storage tank are combined to generate different batch liquid addition behavior planning schemes. The sum of the number of parts of the liquid addition amount corresponding to the first batch and the second batch corresponding to the corresponding liquid storage tank in each batch liquid addition behavior planning scheme is n, and the n is a constant preset in the database;

[0099] When the liquid addition behavior dynamic optimization module calculates the intervention interference values of each batch of liquid addition behavior planning schemes on the production line during the execution process, the intervention interference value of the j-th batch of liquid addition behavior planning scheme on the production line during the execution process is denoted as GRj.

[0100] ,

[0101] where ig represents the number of liquid medicine storage tanks; HOij represents the prediction result of the corresponding first risk impact value when the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme executes the corresponding first batch of liquid addition scheme; HTij represents the prediction result of the corresponding second risk impact value of the liquid addition requirement value corresponding after the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme executes the corresponding first batch of liquid addition scheme.

[0102] The liquid addition requirement value corresponding after the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme executes the corresponding first batch of liquid addition scheme is equal to the average value of the liquid addition requirement values corresponding after each element in the reference set corresponding to the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme executes the corresponding liquid addition behavior.

[0103] The reference set corresponding to the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme is obtained by querying all liquid addition behaviors in the historical database where the corresponding liquid addition requirement value is the same as Qi and the deviation between the liquid addition amount and Mij is less than the preset value, and Mij represents the corresponding liquid addition amount of the corresponding first batch of liquid addition scheme of the i-th liquid medicine storage tank in the j-th batch of liquid addition behavior planning scheme.

[0104] Liquid addition behavior warning module, which generates a liquid addition behavior warning report according to the optimization requirement determination result and the liquid addition behavior dynamic optimization result of the current time liquid addition behavior obtained by the liquid addition behavior dynamic optimization module, and feeds it back to the corresponding administrator for confirmation.

[0105] When the liquid addition behavior warning module generates a liquid addition behavior warning report, if there is no optimization requirement for the liquid addition behavior of each liquid medicine storage tank at the current time, then the set composed of the current time point, each liquid addition characteristic parameter at the current time and the corresponding execution time is used as the liquid addition behavior warning report corresponding to the current time.

[0106] If there is an optimization requirement for the liquid addition behavior of the liquid medicine storage tank at the current time, then the set composed of the current time point and the liquid addition behavior dynamic optimization result corresponding to the current time is used as the liquid addition behavior warning report corresponding to the current time.

[0107] After the generated liquid addition behavior warning report is fed back to the corresponding administrator for confirmation, when the corresponding administrator receives and approves the corresponding liquid addition behavior warning report or the corresponding administrator does not receive the corresponding liquid addition behavior warning report within the preset time, the liquid addition operation for the corresponding liquid storage tank is automatically executed according to the liquid addition behavior planning scheme in the corresponding liquid addition behavior warning report; otherwise, the corresponding administrator is reminded to manually execute the liquid addition operation for the corresponding liquid storage tank.

[0108] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0109] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. Automated electrochemical solution adding system, characterized in that: The system comprises: A liquid adding behavior determination module, which obtains the liquid data in each liquid storage tank at the current time in real time through a sensor, and compares the obtained liquid data with the standard parameters of the corresponding liquid storage tank, and calculates the liquid adding demand value of each liquid storage tank; The drug solution data includes the composition of the drug solution, the concentration of each component and the total amount of the drug solution; When calculating the liquid addition requirement value of each liquid storage tank in the liquid addition behavior determination module, the liquid addition requirement value of the i-th liquid storage tank is recorded as Qi, ， Among them, β is the demand conversion factor and β is a constant preset in the database; Cik represents the absolute value of the difference between the concentration of the kth component in the liquid data of the i-th liquid storage tank at the current time and the midpoint of the concentration interval corresponding to the corresponding component in the standard parameters of the corresponding liquid storage tank; ki represents the number of component types in the liquid data of the i-th liquid storage tank at the current time; Lik represents the interval length of the concentration interval corresponding to the kth component in the liquid data of the i-th liquid storage tank in the corresponding standard parameter; Zi represents the inverse of the difference between the total amount of liquid medicine in the liquid medicine data of the i-th liquid medicine storage tank at the current time and the minimum value of the total amount of liquid medicine in the corresponding standard parameter; P{,} represents the demand judgment function. When the value of the first parameter in the function is greater than or equal to the value of the second parameter, the corresponding function result is judged to be the value of the first parameter in the function; otherwise, the corresponding function result is judged to be 0; An addition amount prediction module, wherein the addition amount prediction module generates a characteristic parameter of the drug liquid addition corresponding to the current time according to the obtained drug liquid addition demand value of each drug liquid storage tank and the current state of each drug liquid storage tank; A liquid addition behavior impact analysis module, wherein the liquid addition behavior impact analysis module obtains the amount of liquid added corresponding to each liquid storage tank in the liquid addition characteristic parameters and the operating status of the production line to which the corresponding liquid storage tank belongs at the current time, and combines the impact of different liquid addition behaviors on the production line operating status in historical data to predict the impact of the corresponding liquid addition amount added to the corresponding liquid storage tank at the current time on the corresponding production line to obtain a first risk impact value; combines the operating data of the current production line to predict the delay of each liquid addition, and evaluates the impact of the corresponding liquid addition delay on the corresponding production line to obtain a second risk impact value; A liquid-adding behavior dynamic optimization module, wherein the liquid-adding behavior dynamic optimization module combines the first risk impact value and the second risk impact value to determine the optimization requirements of the liquid-adding behavior at the current time; and when there is an optimization requirement, generates different batch liquid-adding behavior planning schemes, and respectively calculates the intervention interference value of each batch liquid-adding behavior planning scheme on the production line during the execution process, and selects the batch liquid-adding behavior planning scheme with the smallest corresponding intervention interference value as the liquid-adding behavior dynamic optimization result; The liquid adding behavior warning module generates a liquid adding behavior warning report based on the optimization demand judgment result of the liquid adding behavior at the current time and the liquid adding behavior dynamic optimization result obtained by the liquid adding behavior dynamic optimization module, and feeds it back to the corresponding administrator for confirmation.

2. The automated electrochemical solution adding system according to claim 1, characterized in that: The characteristic parameters of the liquid medicine addition corresponding to the current time include the composition of the liquid medicine added corresponding to each liquid medicine storage tank, the concentration of each component and the amount of liquid medicine added; When the addition amount prediction module generates the characteristic parameters of the drug liquid addition corresponding to the current time, the drug liquid addition demand value of each drug liquid storage tank and the current state of each drug liquid storage tank are obtained; Arrange the order of adding medicines corresponding to each medicine storage tank in the medicine addition characteristic parameter corresponding to the current time according to the corresponding medicine addition demand value from large to small, and the medicine addition amount corresponding to the i-th medicine storage tank is the inverse number of the difference between the total amount of medicine in the medicine data of the i-th medicine storage tank at the current time and the minimum value of the total amount of medicine in the corresponding standard parameter; The concentrations corresponding to the various components in the characteristic parameters of the liquid medicine addition corresponding to the current time are obtained by querying the values ​​corresponding to the corresponding data groups in the preset forms in the database. The data groups corresponding to the corresponding components include the concentrations of the corresponding components before adding the medicine, the concentration ranges corresponding to the corresponding components in the corresponding standard parameters, and the amount of liquid medicine added.

3. The automated electrochemical solution adding system according to claim 1, characterized in that: The liquid addition behavior impact analysis module includes an addition amount risk analysis unit and an addition delay risk analysis unit. The addition amount risk analysis unit obtains the amount of medicine added corresponding to each medicine storage tank in the medicine addition characteristic parameter and the operating status of the production line to which the corresponding medicine storage tank belongs at the current time, and combines the impact of different medicine addition behaviors on the production line operating status in the historical data to predict the impact of the corresponding medicine addition amount added to the corresponding medicine storage tank at the current time on the corresponding production line to obtain a first risk impact value; The addition delay risk analysis unit predicts the delay of adding each drug solution in combination with the operation data of the current production line, and evaluates the impact of the corresponding drug solution addition delay on the corresponding production line to obtain a second risk impact value.

4. The automated electrochemical solution adding system according to claim 3, characterized in that: When the additive amount risk analysis unit obtains the first risk impact value, Obtain the amount of liquid medicine added corresponding to each liquid medicine storage tank in the liquid medicine addition characteristic parameters and the operating status of the production line to which the corresponding liquid medicine storage tank belongs at the current time, wherein the operating status of the production line to which the corresponding liquid medicine storage tank belongs at the current time includes the type of production product corresponding to the production line to which the corresponding liquid medicine storage tank belongs at the current time, the waiting time, the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid medicine addition demand value, the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change amount of the liquid medicine addition demand value, and the change function of the liquid medicine addition demand value corresponding to the corresponding product type with the running time; When the waiting time in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time is equal to the corresponding product type produced by the corresponding production line in the historical data, the quotient of the remaining product quantity to be produced at the current time and the average production speed of the corresponding product type in the historical data; When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, obtain each demand-related data pair corresponding to the i-th liquid storage tank in the historical data, wherein the first value of the demand-related data pair is the liquid addition demand value of the liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; according to the preset function model y=-x -a +b fits each demand-related data pair obtained, and calculates the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each associated data pair, and obtains the data fitting deviation corresponding to each fitting result. The fitting function corresponding to the minimum value of the obtained data fitting deviation is used as the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, which is recorded as WQi (x); When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change in the demand value of the medicine liquid addition of the ith medicine liquid storage tank, obtain each demand mutation associated data pair corresponding to the ith medicine liquid storage tank in the historical data, wherein the first value of the demand mutation associated data pair is the sudden change in the demand for medicine liquid addition of the medicine liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; the sudden change in the demand for medicine liquid addition is equal to the maximum difference between the corresponding values ​​of the demand for medicine liquid addition at different time points per unit time after the medicine adding operation is performed; according to the preset function model y1=-x1 -a +b fits each demand mutation associated data pair obtained, and calculates the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each demand mutation associated data pair, and obtains the data fitting deviation corresponding to each fitting result. The fitting function corresponding to the minimum value of the obtained data fitting deviation is used as the relationship function between the product abnormality rate corresponding to the corresponding product type and the mutation amount of the liquid addition demand value of the i-th liquid storage tank, recorded as WTi (x1); When obtaining the function of the change of the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation time, obtain each operation demand associated data pair corresponding to the i-th liquid medicine storage tank in the historical data, the first value of the operation demand associated data pair is the subsequent operation time based on the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type, and the second value is the liquid addition demand value of the liquid medicine storage tank; fit each obtained operation demand associated data pair according to the preset linear regression model, and use the obtained fitting function as the change function of the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation time, recorded as WYi(t); The first risk impact value corresponding to the addition of the corresponding amount of liquid medicine to the i-th liquid medicine storage tank at the current time is recorded as FOi, The FOi=WTi(B), Among them, B represents the sudden change in the demand for adding liquid medicine corresponding to the amount of liquid medicine added to the i-th liquid medicine storage tank at the current time; WTi (B) represents the function value corresponding to WTi (x1) when x1 is B; The reference array corresponding to Qi is obtained by querying the historical database for all the liquid addition behaviors whose corresponding liquid addition demand value is the same as Qi and whose deviation between the liquid addition amount and the corresponding liquid addition amount added in the i-th liquid storage tank at the current time is less than a preset value.

5. The automated electrochemical solution adding system according to claim 4, characterized in that: When the delay risk analysis unit is added to obtain the second risk impact value, The liquid medicine addition delay corresponding to the i-th liquid medicine storage tank is equal to the waiting time in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time; The second risk impact value corresponding to the delay in adding the liquid medicine corresponding to the i-th liquid medicine storage tank is recorded as FTi, FTi = WQi (WYi (tsi)), Among them, tsi represents the delay of adding liquid medicine corresponding to the i-th liquid medicine storage tank; WYi(tsi) represents the function value corresponding to WYi(t) when t is tsi; WQi(WYi(tsi)) represents the function value corresponding to WQi(x) when x is WYi(tsi).

6. The automated electrochemical solution adding system according to claim 5, characterized in that: When the dynamic optimization module for liquid adding behavior determines the optimization demand for liquid adding behavior at the current time, when the first risk impact value and the second risk impact value corresponding to the i-th liquid medicine storage tank are both greater than or equal to the preset product abnormality rate, it is determined that there is an optimization demand for liquid adding behavior at the current time; when the first risk impact value and the second risk impact value corresponding to the i-th liquid medicine storage tank are both less than the preset product abnormality rate, it is determined that there is no optimization demand for liquid adding behavior at the current time. If the first risk impact value corresponding to the i-th drug liquid storage tank is less than or equal to the second risk impact value, it is determined that after the waiting time in the operation state of the production line to which the i-th drug liquid storage tank belongs at the current time, the liquid adding behavior operation is performed according to the drug liquid adding characteristic parameters corresponding to the current time; otherwise, the liquid adding behavior operation is immediately performed according to the drug liquid adding characteristic parameters corresponding to the current time; When the liquid adding behavior dynamic optimization module generates different batch liquid adding behavior planning schemes, the corresponding liquid addition amount added to the i-th liquid storage tank at the current time is divided into n parts and two batches. The liquid addition time corresponding to the first batch is the current time, and the liquid addition time corresponding to the second batch is the waiting time in the operation state of the production line to which the i-th liquid storage tank belongs at the current time; The number of portions of the added liquid corresponding to each liquid storage tank in the first batch and the second batch is adjusted respectively, and different liquid adding behavior planning schemes corresponding to the corresponding liquid storage tanks are generated, and the liquid adding behavior planning schemes corresponding to the various liquid storage tanks are combined to generate different batch liquid adding behavior planning schemes, and the sum of the number of portions of the added liquid corresponding to the first batch and the second batch respectively corresponding to the corresponding liquid storage tanks in each batch liquid adding behavior planning scheme is n, and n is a constant preset in the database; When the dynamic optimization module for liquid adding behavior respectively calculates the intervention interference value of each batch of liquid adding behavior planning scheme on the production line during the execution process, the intervention interference value of the j-th batch of liquid adding behavior planning scheme on the production line during the execution process is recorded as GRj. ， Among them, ig represents the number of liquid medicine storage tanks; HOij represents the prediction result of the first risk impact value corresponding to the i-th liquid medicine storage tank in the j-th batch liquid filling behavior planning scheme when the corresponding first batch liquid filling scheme is executed; HTij represents the prediction result of the second risk impact value corresponding to the liquid addition demand value after the i-th liquid medicine storage tank in the j-th batch liquid filling behavior planning scheme executes the corresponding first batch liquid filling scheme; The liquid addition demand value corresponding to the i-th liquid storage tank in the j-th batch liquid addition behavior planning scheme after executing the corresponding first batch liquid addition scheme is equal to the average value of the liquid addition demand values ​​corresponding to each element in the reference set corresponding to the i-th liquid storage tank in the j-th batch liquid addition behavior planning scheme after executing the corresponding liquid addition behavior; The reference set corresponding to the i-th liquid storage tank in the j-th batch liquid adding behavior planning scheme is obtained by querying the historical database for all liquid adding behaviors whose corresponding liquid addition demand value is the same as Qi and whose deviation between the liquid addition amount and Mij is less than a preset value. The Mij represents the corresponding liquid addition amount corresponding to the first batch liquid adding plan corresponding to the i-th liquid storage tank in the j-th batch liquid adding behavior planning scheme.

7. The automated electrochemical solution adding system according to claim 1, characterized in that: When the liquid adding behavior warning module generates a liquid adding behavior warning report, if there is no optimization demand for liquid adding behavior in each liquid storage tank at the current time, a set consisting of the current time point, each liquid adding characteristic parameter at the current time and the corresponding execution time is used as the liquid adding behavior warning report corresponding to the current time; If there is a need to optimize the liquid filling behavior of the liquid storage tank at the current time, the set consisting of the current time point and the dynamic optimization results of the liquid filling behavior corresponding to the current time is used as the liquid filling behavior warning report corresponding to the current time; After the generated liquid adding behavior warning report is fed back to the corresponding administrator for confirmation, when the corresponding administrator receives and approves the corresponding liquid adding behavior warning report or the corresponding administrator does not receive the corresponding liquid adding behavior warning report within the preset time, the liquid adding operation on the corresponding medicine liquid storage tank is automatically executed according to the liquid adding behavior planning plan in the corresponding liquid adding behavior warning report; otherwise, the corresponding administrator is reminded to manually perform the liquid adding operation on the corresponding medicine liquid storage tank.

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