Automatic optimization method and system for flocculant dosage based on intelligent cup-pot coagulation

Abstract

The present invention discloses an automatic optimization method and system for flocculant dosage based on intelligent cup coagulation, the method comprising: obtaining the first post-settling turbidity after the i+1 round coagulation experiment based on the first flocculant dosage of the i+1 round; obtaining the first turbidity difference and the first post-settling turbidity difference of the i+1 round according to the first post-settling turbidity after the i+1 round coagulation experiment; executing a monotonicity judgment module when the first post-settling turbidity difference is greater than or equal to 0, and executing a binary search module when the first post-settling turbidity difference is less than 0, so as to determine the optimal flocculant dosage. The automatic optimization method proposed in the present invention can obtain a lower flocculant dosage to achieve the same post-settling turbidity, fully optimize the operating efficiency and accuracy of the coagulation process, thereby reducing and saving the experimental operation workload of water companies, and improving the work efficiency and economic benefits of water companies.

Description

Technical Field

[0001] The invention belongs to the technical field of combining automatic control with water treatment, and in particular relates to a method and system for automatically optimizing flocculant dosage based on intelligent cup-pot coagulation. Background Art

[0002] With the rapid development and popularization of urbanization and industrialization, water pollution and shortage have gradually become one of the important problems facing today's society. Therefore, water treatment technology is the key to solving water resource problems. Generally, the water treatment technology process mainly includes coagulation, sedimentation, filtration and disinfection, and the coagulation process is one of the most important links, which deeply affects the final effect of water treatment. Generally speaking, the coagulation process includes mixing and flocculation, and flocculation is the most important process in this process.

[0003] In the flocculation process, the flocculation effect of water quality is affected by multiple factors such as water temperature, pH value, type of flocculant, flocculant dosage and hydraulic conditions. However, in the actual production process of water companies within a certain period of time, the external water quality conditions such as water temperature, pH value and hydraulic conditions are usually basically fixed and unchanged, and have a limited impact on the real-time flocculation effect of water companies; in addition, in the daily flocculation process of water companies, flocculants must be purchased in advance, so the type of flocculant is also highly determined. In short, in a normally operating water company, compared with factors such as water temperature, pH value, and type of flocculant, the amount of flocculant added is the factor that has the greatest impact on the flocculation effect of water quality.

[0004] In the flocculation process, the amount of flocculant added directly determines the final flocculation effect of the water quality, which in turn affects the overall effluent quality of the water plant. This means that if less flocculant is added, the turbidity of the raw water after sedimentation will be higher, greatly reducing the effluent quality of the water company; on the contrary, if the amount of flocculant added is too much, the economic benefits and effluent quality of the water company will face varying degrees of decline. Therefore, in the flocculation process, how to determine the appropriate amount of flocculant added has always been the core issue of flocculation process research in water treatment technology. In order to solve this problem, domestic and foreign scholars have made a lot of attempts and efforts. However, so far, these attempts and efforts have not completely solved the problem of the optimal flocculant dosage for different raw water qualities. The reason is that, affected by factors such as water temperature, pH value, type of flocculant and hydraulic conditions, the relationship between the flocculant dosage and the flocculation effect of different raw water qualities shows the characteristics of nonlinearity, time lag and time variation. For example, in the flocculation process, the raw water needs to flow slowly through a very long horizontal flow sedimentation tank, and the water quality indicators can be obtained through the sensor at the tail of the horizontal flow sedimentation tank. Therefore, there is a time delay of 1 to 2 hours between the addition of flocculants and the coagulation results during coagulation. This phenomenon is also called the large time lag phenomenon.

[0005] In the daily production process, in order to determine the appropriate flocculant dosage, water companies use a common beaker experiment method. The specific steps of this method are as follows: First, researchers conduct a six-beaker experiment in the laboratory. This experiment treats six groups of the same raw water by adding different doses of flocculants; Second, after sufficient stirring, reaction and waiting, the researchers complete the flocculation and sedimentation process of the six beaker experiments; Third, the researchers accurately measure the turbidity of the supernatant of the water samples in all beakers, that is, the turbidity after sedimentation, and use these data to study the functional relationship between different flocculant dosages and the turbidity of the water samples after sedimentation; Fourth, based on the rich experience of technicians, the relationship data between the turbidity after sedimentation and the flocculant dosage is corrected to determine the optimal flocculant dosage corresponding to the current raw water quality. By executing all the steps described above, water companies provide a certain reference basis for the treatment of different raw water qualities.

[0006] However, the current method cannot achieve real-time adjustment and optimization of flocculant dosage. Summary of the invention

[0007] In order to solve the above problems existing in the prior art, the present invention provides a method and system for automatically optimizing the flocculant dosage based on intelligent cup-pot coagulation.

[0008] A method for automatically optimizing flocculant dosage based on intelligent cup coagulation, the method comprising:

[0009] Step 1, obtaining the first flocculant dosage of the i+1th round according to the flocculant dosage of the ith round and the difference of the flocculant dosage of the ith round;

[0010] Step 2: performing a coagulation experiment based on the first flocculant dosage of the (i+1) round to obtain a first post-sedimentation turbidity after the (i+1) round of coagulation experiment;

[0011] Step 3, obtaining the first turbidity difference of the i+1th round according to the first turbidity after sedimentation after the i+1th round of coagulation experiment and the target turbidity, and obtaining the first turbidity difference after sedimentation according to the difference between the first turbidity after sedimentation after the i-th round of coagulation experiment and the first turbidity after sedimentation after the i+1th round of coagulation experiment;

[0012] Step 4, judging whether the first turbidity difference of the i+1th round is less than 0, if the first turbidity difference of the i+1th round is greater than or equal to 0, executing step 5, if the first turbidity difference of the i+1th round is less than 0, taking the first flocculant dosage of the i+1th round as the preset flocculant dosage, and executing step 6;

[0013] Step 5: Based on the monotonicity judgment algorithm, the monotonicity of the functional relationship between the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round is obtained to obtain a monotonicity judgment result, a monotonicity Boolean value and an updated intermediate parameter are obtained according to the monotonicity judgment result, and the process is skipped to the step 2 to re-execute the step 2 according to the monotonicity Boolean value and the updated intermediate parameter until the preset flocculant dosage is obtained;

[0014] Step 6: Based on a binary search method, the optimal flocculant dosage is determined according to the updated intermediate value obtained from the flocculant dosage of the i-1th round, the flocculant dosage of the i-th round, and the preset flocculant dosage.

[0015] An embodiment of the present invention further provides a flocculant dosage automatic optimization system based on intelligent cup-pot coagulation, and the flocculant dosage automatic optimization system comprises:

[0016] A first dosage generating module, used for obtaining a first flocculant dosage of the (i+1)th round according to the flocculant dosage of the i-th round and the difference of the flocculant dosage of the i-th round;

[0017] A post-settling turbidity generation module, used for obtaining a first post-settling turbidity after the i+1th round of coagulation experiment based on the coagulation experiment performed with the first flocculant dosage in the i+1th round;

[0018] A post-settling turbidity difference generation module is used to obtain the first turbidity difference of the i+1th round according to the first post-settling turbidity after the i+1th round of coagulation experiment and the target turbidity, and to obtain the first post-settling turbidity difference according to the difference between the first post-settling turbidity after the i-th round of coagulation experiment and the first post-settling turbidity after the i+1th round of coagulation experiment;

[0019] A judgment module, judging whether the first turbidity difference of the i+1th round is less than 0, if the first turbidity difference of the i+1th round is greater than or equal to 0, executing the method of the second dosage generation module, if the first turbidity difference of the i+1th round is less than 0, taking the first flocculant dosage of the i+1th round as the preset flocculant dosage, and executing the optimal dosage generation module method;

[0020] A second dosage generation module is used to obtain the monotonicity of the functional relationship between the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round based on a monotonicity judgment algorithm to obtain a monotonicity judgment result, obtain a monotonic Boolean value and update intermediate parameters according to the monotonicity judgment result, and jump to the method of the post-settling turbidity generation module to re-execute the method of the post-settling turbidity generation module according to the monotonic Boolean value and the updated intermediate parameters until a preset flocculant dosage is obtained;

[0021] The optimal dosage generation module is used to determine the optimal flocculant dosage according to the updated intermediate value obtained from the flocculant dosage of the i-1th round, the flocculant dosage of the i-th round and the preset flocculant dosage.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The automatic optimization method proposed in the present invention can quickly obtain the optimal flocculant dosage for the current raw water quality with the assistance of the intelligent cup coagulation device. Compared with the classic six-beaker test method, the automatic optimization method proposed in the present invention can obtain a lower flocculant dosage to achieve the same turbidity after sedimentation, fully optimize the operating efficiency and accuracy of the coagulation process, thereby reducing the experimental operation workload of water companies and improving the work efficiency and economic benefits of water companies.

[0024] The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a schematic diagram of a fitting curve between turbidity after sedimentation and flocculant dosage provided by an embodiment of the present invention;

[0026] Figure 2 It is a flow chart of a method for automatically optimizing the dosage of flocculant based on intelligent cup-pot coagulation provided by an embodiment of the present invention;

[0027] Figure 3 It is a flow chart of another method for automatically optimizing the dosage of flocculant based on intelligent cup-pot coagulation provided by an embodiment of the present invention;

[0028] Figure 4 It is a schematic diagram of an execution flow of monotonicity judgment provided by an embodiment of the present invention;

[0029] Figure 5 It is a schematic diagram of an execution flow of a binary search provided by an embodiment of the present invention;

[0030] Figure 6 This is a schematic diagram of an execution flow of a verification strategy provided by an embodiment of the present invention.

[0031] Figure 7 It is a schematic diagram of an automatic optimization system for flocculant dosage based on intelligent cup-pot coagulation provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0033] Embodiment 1

[0034] At present, the six-beaker experiment can obtain the dosage of flocculants suitable for different raw water qualities, which basically meets the daily water treatment needs of water treatment companies. However, this method still has the following disadvantages:

[0035] First, the dosage of flocculants in the flocculation process is often excessive. This is because the adjustment of the dosage of flocculants often cannot match the changes in the incoming water in real time. In order to ensure that the effluent quality meets the standards, water companies usually need to add excessive flocculants. This practice has brought many negative effects to water companies. (1) Excessive flocculants seriously increase the cost of purchasing chemicals for water companies; (2) Excessive flocculants interact with the added chemicals of other processes, which directly leads to a corresponding increase in the cost of subsequent treatment. For example, excessive PAC (polyaluminium oxide) added to water leads to excessive residual aluminum ions in the water, which increases the treatment cost of water companies.

[0036] Second, the results of the flocculant dosage are heavily dependent on the operator's experience and judgment, which reduces the accuracy and reliability of the beaker experiment. This is because, in the beaker experiment, the adjustment of water temperature, the initial humidity of the beaker, the mixing and stirring speed of the solution, the addition time and specific amount of flocculants and other operating details may have a certain impact on the flocculation effect of water quality, which leads to different operators being likely to obtain very different experimental results. At this time, the flocculant dosage depends on the operator's experimental habits, experience or judgment, which greatly reduces the accuracy and reliability of the beaker experiment.

[0037] Third, the six-beaker test cannot cope with the problem of sudden changes in raw water quality, and it is difficult to ensure that the effluent quality of water companies meets the standards. This is mainly reflected in the reservoir discharge caused by sudden heavy rains, the overflow of reservoirs caused by insufficient water, and the adjustment or change of the output and process of sewage discharge enterprises, which can cause the raw water turbidity to soar from a few NTU (Nephelometric Turbidity Unit) to hundreds to thousands of NTU in a short period of time. These sudden changes require water companies to adjust the dosage of flocculants in a timely and accurate manner. However, affected by the details of artificial experimental operations, it is difficult for the six-beaker test to accurately and efficiently determine the optimal dosage of flocculants, which is likely to reduce the effluent quality of water companies and make it difficult to meet national or local standards, thereby increasing the administrative fines costs of water companies.

[0038] In view of the above reasons, there is an urgent need for an automatic optimization method for flocculant dosage to achieve real-time adjustment and optimization of flocculant dosage.

[0039] According to multiple rounds of verification of intelligent cup coagulation experiments, for the same raw water quality, there is a regularity in the relationship between the coagulation effect parameters represented by the post-settlement turbidity and the flocculant dosage. In the process of gradually increasing the flocculant dosage, the post-settlement turbidity first shows a trend of significant decrease. At this time, a small amount of flocculant reacts chemically with some suspended matter, organic matter, heavy metal particles and other impurities in the water to form a large number of flocs. When the flocculant dosage continues to increase, the post-settlement turbidity first decreases to a smaller value, and then continues to increase slowly. In this process, an appropriate amount of flocculant forms more flocs with most of the impurities to be treated in the water, which fully reduces the post-settlement turbidity of the water quality. However, when too much flocculant is added, the excess flocculant gradually becomes an impurity component in the water, while increasing the post-settlement turbidity of the water quality, causing the deterioration of the water quality coagulation effect and the waste of flocculant. In short, in order to formulate a search strategy for the flocculant dosage, the present invention provides a fitting curve of the relationship between the post-settlement turbidity and the flocculant dosage as the basic assumption for the subsequent automatic optimization strategy, such as Figure 1 As shown, according to Figure 1 It can be seen that when the turbidity after sedimentation reaches the target turbidity for the first time, the amount of flocculant added to the raw water quality is small, which is the optimal flocculant dosage corresponding to the current water quality, corresponding to Figure 1 Point A marked in the figure.

[0040] Therefore, see Figure 2 and Figure 3 The present invention proposes an automatic optimization method for flocculant dosage based on intelligent cup coagulation, and the automatic optimization method for flocculant dosage includes:

[0041] Step 1: Obtain the first flocculant dosage of the i+1th round according to the flocculant dosage of the i-th round and the difference of the flocculant dosage of the i-th round, wherein i represents the number of running rounds of the intelligent cup coagulation experiment in the automatic optimization algorithm.

[0042] Specifically, we first initialize the number of iterations i = 0, and let T tar It represents the target turbidity of the raw water quality. According to the requirements of water quality treatment, the initial value D(0) of the flocculant dosage of the automatic optimization method of flocculant dosage is set to 0, the initial turbidity T(0) (i.e., the turbidity after sedimentation of the raw water quality), the target turbidity T of the raw water quality tar , the difference in flocculant dosage between adjacent iteration rounds d(0), the initial value of the difference in turbidity after sedimentation between adjacent rounds is 0 and the intermediate parameter P of flocculant dosage (its initial value is set to 100%), the calculation coefficient Q of the difference in flocculant dosage between adjacent rounds (its initial value is set to 0), the minimum flocculant dosage d allowed by the intelligent cup coagulation device min , the initial value of the Boolean value (indicating turbidity after sedimentation and flocculant dosage) is set to 0 and other algorithm parameters.

[0043] For the (i+1)th round, the flocculant dosage of the (i)th round and the flocculant dosage difference of the (i)th round are first obtained, so as to obtain the first flocculant dosage of the (i+1)th round.

[0044] In a specific embodiment, step 1 may include:

[0045] The first flocculant dosage of the i+1th round is obtained according to the sum of the flocculant dosage of the i-th round and the difference between the flocculant dosage of the i-th round.

[0046] Here, the difference in flocculant dosage in the i-th round is the difference between the flocculant dosage in the i+1th round and the flocculant dosage in the i-th round. The difference in flocculant dosage in the i-th round can be calculated using the following formula:

[0047] d(i)=d(i-1)*Q

[0048] Wherein, d(i) is the difference in flocculant dosage in the i-th round, d(i-1) is the difference in flocculant dosage in the i-1th round, d(i-1)=D(i)-D(i-1), D(i) is the flocculant dosage in the i-th round, D(i-1) is the flocculant dosage in the i-1th round, because the initial d(0) and D(0) are known, the flocculant dosage D(1) of the first round can be determined by D(0)+d(0)=D(1), and because d(0) and the initial calculation coefficient are known, d(1) can be obtained, and so on, d(i-1), d(i), D(i-1) and D(i) can be obtained, and Q is the calculation coefficient of the difference in flocculant dosage between adjacent rounds, where Q=M1(i)*P*r / T dis0 , r is the proportional coefficient in the process of selecting the detection value, optional, r is equal to 1.2, the value of P is 100%, M1(i) = T1(i) - T tar , T1(i) is the first post-sedimentation turbidity after the i-th round of coagulation experiment, specifically, the post-sedimentation turbidity after the coagulation experiment obtained by performing the intelligent cup coagulation experiment using the i-th round of flocculant dosage, T dis0 =T1(i-1)-T1(i), T1(i-1) is the first post-sedimentation turbidity after the i-1th round of coagulation experiment, specifically, the post-sedimentation turbidity after the coagulation experiment obtained by conducting an intelligent cup coagulation experiment using the i-1th round of flocculant dosage, thereby obtaining the post-sedimentation turbidity after the coagulation experiment.

[0049] Therefore, the first flocculant dosage in the i+1th round is D1(i+1)=D(i)+d(i), and D1(i+1) is the first flocculant dosage in the i+1th round.

[0050] Step 2: Based on the first flocculant dosage of the (i+1) round, a coagulation experiment is performed to obtain the first post-sedimentation turbidity after the (i+1) round of coagulation experiment.

[0051] Specifically, the first flocculant dosage of the i+1th round obtained in step 1 is used to carry out the intelligent cup coagulation experiment, thereby obtaining the turbidity after sedimentation after the coagulation experiment, that is, the first turbidity after sedimentation after the i+1th round of coagulation experiment, which is recorded as T1(i+1).

[0052] Step 3, obtain the first turbidity difference of the i+1th round according to the first post-sedimentation turbidity after the i+1th round of coagulation experiment and the target turbidity, and obtain the first post-sedimentation turbidity difference according to the difference between the first post-sedimentation turbidity after the i-th round of coagulation experiment and the first post-sedimentation turbidity after the i+1th round of coagulation experiment.

[0053] In a specific embodiment, step 3 may include:

[0054] Step 3.1: The first turbidity difference of the i+1th round is obtained according to the difference between the first post-sedimentation turbidity after the i+1th round of coagulation experiment and the target turbidity. The first turbidity difference of the i+1th round is expressed as:

[0055] M1(i+1)=T1(i+1)-T tar

[0056] Wherein, M1(i+1) is the first turbidity difference of the i+1th round.

[0057] Step 3.2: Obtain the first post-sedimentation turbidity difference according to the difference between the first post-sedimentation turbidity after the i-th round of coagulation experiment and the first post-sedimentation turbidity after the i+1-th round of coagulation experiment. The first post-sedimentation turbidity difference is expressed as:

[0058] T dis1 =T1(i)-T1(i+1)

[0059] Among them, T dis1 It is the turbidity difference after the first sedimentation.

[0060] Step 4, determine whether the first turbidity difference of the i+1th round is less than 0. If the first turbidity difference of the i+1th round is greater than or equal to 0, execute step 5. If the first turbidity difference of the i+1th round is less than 0, use the first flocculant dosage of the i+1th round as the preset flocculant dosage, and execute step 6.

[0061] Step 5. Based on the monotonicity judgment algorithm, the monotonicity of the functional relationship between the first post-sedimentation turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round is obtained to obtain a monotonicity judgment result, and a monotonicity Boolean value and updated intermediate parameters are obtained according to the monotonicity judgment result, and then jump to step 2 to re-execute step 2 according to the monotonicity Boolean value and the updated intermediate parameters until the preset flocculant dosage is obtained.

[0062] In the process of searching for the optimal flocculant dosage, the automatic optimization method needs to judge the monotonicity of the function between the turbidity after sedimentation and the flocculant dosage of the current round according to the results of the intelligent cup coagulation experiment of the adjacent rounds. Among them, according to the numerical value of the turbidity after sedimentation between adjacent rounds, the automatic optimization method can judge the monotonicity between the turbidity after sedimentation and the flocculant dosage of the current round, that is, determine whether the flocculant dosage of the current round is within Figure 1 Point A and point B correspond to the left or right of the flocculant dosage value. During the search process, if the current round of dosage is Figure 1 To the left of point A, the automatic optimization method increases the value of the difference in flocculant dosage between adjacent rounds and continues the next round of dosage experiment. Otherwise, the current round of dosage is Figure 1 To the right of point B, the algorithm needs to return to the flocculant dosage of the previous iteration, reduce the flocculant dosage difference, and continue the next round of search.

[0063] In a specific embodiment, see Figure 4 , step 5 may include:

[0064] Step 5.1, assigning the minimum flocculant dosage to the first flocculant dosage difference of the i+1th round to obtain the second flocculant dosage difference of the i+1th round.

[0065] Specifically, the first flocculant dosage D1(i+1) of the i+1th round, the first post-settling turbidity T1(i+1) after the i+1th round of coagulation experiment, and the minimum flocculant dosage d min . Set the minimum flocculant dosage d min The first flocculant dosage difference d1(i+1) of the i+1th round is assigned, and the first flocculant dosage difference d1(i+1) of the i+1th round after the assignment is used as the second flocculant dosage difference d2(i+1) of the i+1th round, that is, d2(i+1)=d min .

[0066] Step 5.2: Calculate the first flocculant dosage of the i+2th round based on the difference between the first flocculant dosage of the i+1th round and the second flocculant dosage of the i+1th round.

[0067] Specifically, the first flocculant dosage of the i+2 round is obtained according to the sum of the difference between the first flocculant dosage of the i+1 round and the second flocculant dosage of the i+1 round. The first flocculant dosage of the i+2 round is expressed as:

[0068] D1(i+2)=D1(i+1)+d2(i+1)

[0069] Wherein, D1(i+2) is the first flocculant dosage in the i+2th round.

[0070] Step 5.3: Based on the first flocculant dosage of the (i+2) round of coagulation experiment, a first post-sedimentation turbidity after the (i+2) round of coagulation experiment is obtained.

[0071] Specifically, the first flocculant dosage of the i+2th round obtained in step 5.2 is used to carry out the intelligent cup coagulation experiment, thereby obtaining the post-sedimentation turbidity after the coagulation experiment, that is, the first post-sedimentation turbidity after the i+2th round of coagulation experiment, which is recorded as T1(i+2).

[0072] Step 5.4, determine the relationship between the first turbidity after sedimentation after the i+1th round of coagulation experiment and the first turbidity after sedimentation after the i+2th round of coagulation experiment. If the first turbidity after sedimentation after the i+1th round of coagulation experiment is less than the first turbidity after sedimentation after the i+2th round of coagulation experiment, jump to step 5.5, otherwise jump to step 5.6.

[0073] Step 5.5: If the first post-sedimentation turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round show an increasing trend, the monotonic Boolean value t=0, and the intermediate parameters are updated to obtain the first intermediate parameter P1, and jump to step 5.7.

[0074] Optional, P1 = P 未 *85%, P 未 It is the intermediate parameter before updating.

[0075] Step 5.6: If the first post-sedimentation turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round show a decreasing trend, the monotonic Boolean value t=1, and the intermediate parameter is updated to obtain the second intermediate parameter P2, and jump to step 5.7.

[0076] Optional, P2 = P 未 *100%.

[0077] Step 5.7, jump to step 2, and re-execute step 2 according to the monotonic Boolean value and the first intermediate parameter obtained in step 5.5 or according to the monotonic Boolean value and the second intermediate parameter obtained in step 5.6.

[0078] Specifically, when the monotonic Boolean value t=0, step 2 can be re-executed according to the monotonic Boolean value and the first intermediate parameter obtained in step 5.5. When the monotonic Boolean value t=1, step 2 can be re-executed according to the monotonic Boolean value and the second intermediate parameter obtained in step 5.6 until the corresponding turbidity difference is less than 0, and the flocculant dosage obtained by the turbidity difference is used as the preset flocculant dosage.

[0079] In a specific embodiment, re-executing step 2 according to the monotonic Boolean value obtained in step 5.5 and the first intermediate parameter can be performed according to the following steps A11-A13, wherein:

[0080] A11. If the monotonicity Boolean value t=0, update the calculation coefficient according to the first intermediate parameter to obtain the first calculation coefficient.

[0081] Specifically, according to Q1 = M1(i+1)*P1*r / T dis1 , r=1.2, Q1 is the first calculation coefficient.

[0082] A12. The first flocculant dosage difference of the i+2th round is obtained according to the first calculation coefficient and the flocculant dosage difference of the i-th round. The first flocculant dosage difference of the i+2th round is expressed as:

[0083] d1(i+2)=d(i)*Q1

[0084] Wherein, d1(i+2) is the difference in the dosage of the first flocculant in the i+2th round.

[0085] A13. Calculate the first flocculant dosage of the i+3th round according to the difference between the first flocculant dosage of the i+1th round and the first flocculant dosage of the i+2th round, and jump to step 2, and execute step 2 according to the first flocculant dosage of the i+3th round.

[0086] Specifically, the first flocculant dosage D1(i+3) of the i+3th round is the sum of the difference between the first flocculant dosage of the i+1th round and the first flocculant dosage of the i+2th round, that is, D1(i+3)=D1(i+1)+d1(i+2). After obtaining D1(i+3)=D1(i+1)+d1(i+2), it jumps to step 2 and adds the first flocculant dosage D1(i+3) of the i+3th round according to Re-execute the steps of step 2 until the corresponding turbidity difference is less than 0, and use the flocculant dosage obtained for the turbidity difference as the preset flocculant dosage, that is, if the turbidity difference corresponding to the first flocculant dosage D1(i+3) of the i+3 round is less than 0, then use the first flocculant dosage D1(i+3) of the i+3 round as the preset flocculant dosage to execute step 6, otherwise continue to search for the preset flocculant dosage.

[0087] In another specific embodiment, re-executing step 2 according to the monotonic Boolean value and the second intermediate parameter obtained in step 5.6 can be specifically performed according to the following steps A21-A22, wherein:

[0088] A21. If the monotonicity Boolean value t=1, the calculation coefficient is updated according to the second intermediate parameter to obtain a second calculation coefficient.

[0089] Specifically, according to Q2 = M1(i+1)*P2*r / T dis1 , Q2 is the second calculation coefficient.

[0090] A22. Determine whether the third flocculant dosage difference of the i+1th round is equal to the minimum flocculant dosage (it should be noted that when the monotonic Boolean value t=1 is determined, the third flocculant dosage difference of the i+1th round is the minimum flocculant dosage, that is, d3(i+1)=d min , d3(i+1) is the difference in dosage of the third flocculant in the i+1th round);

[0091] If so, the second flocculant dosage difference of the i+2 round is obtained according to the flocculant dosage difference of the i+3 round and the second calculation coefficient, that is, the second flocculant dosage difference of the i+2 round is d2(i+2)=d(i)*Q2, and then the second flocculant dosage of the i+3 round is obtained according to the first flocculant dosage of the i+1 round and the second flocculant dosage difference of the i+2 round, and the process jumps to step 2, and step 2 is performed according to the second flocculant dosage of the i+3 round until the corresponding turbidity difference is less than 0, and the flocculant dosage obtained by the turbidity difference is used as the preset flocculant dosage, that is, if the turbidity difference corresponding to the second flocculant dosage of the i+3 round is less than 0, the second flocculant dosage of the i+3 round is used as the preset flocculant dosage to perform step 6, otherwise continue to search for the preset flocculant dosage;

[0092] If not, the third flocculant dosage difference of the i+2th round is obtained according to the second calculation coefficient and the third flocculant dosage difference of the i+1th round, that is, the third flocculant dosage difference of the i+2th round d3(i+2)=d3(i+1)*Q2, and then the third flocculant dosage of the i+3th round is obtained according to the first flocculant dosage of the i+2th round and the third flocculant dosage difference of the i+2th round, and jump to step 2, according to the i+ The third flocculant dosage of the 3rd round executes step 2 until the corresponding turbidity difference is less than 0, and the flocculant dosage obtained by the turbidity difference is used as the preset flocculant dosage, that is, if the turbidity difference corresponding to the third flocculant dosage D3(i+3) of the i+3th round is less than 0, then the third flocculant dosage D3(i+3) of the i+3th round is used as the preset flocculant dosage to execute step 6, otherwise continue to look for the preset flocculant dosage.

[0093] Here, the calculation formula for the second flocculant dosage D2(i+3) of the i+3th round is: D2(i+3)=D1(i+1)+d2(i+2).

[0094] Here, the calculation formula for the third flocculant dosage in the i+3th round is: D3(i+3)=D1(i+2)+d3(i+2).

[0095] Step 6: Based on the binary search method, the optimal flocculant dosage is determined according to the updated intermediate value obtained from the flocculant dosage of the i-1th round, the flocculant dosage of the i-th round, and the preset flocculant dosage.

[0096] According to the design of the overall process, when the algorithm completes the first stage of search, that is, M≤0, the amount of flocculant added in the current round is Figure 1 Between point A and point B, and the amount of flocculant added in the previous round is between Figure 1 In order to approach point A with the optimal flocculant dosage, step 6 adopts a binary search method with high search efficiency, and uses the flocculant dosage of two adjacent rounds as input parameters to execute the search process in step 6.

[0097] In a specific embodiment, see Figure 5 , step 6 may include:

[0098] Step 6.1, determine whether the difference between the preset flocculant dosage and the flocculant dosage of the i-th round is equal to the minimum flocculant dosage. If so, set the flocculant dosage of the i-1th round to the first end value of the binary search method, and set the preset flocculant dosage to the second end value of the binary search method. If not, set the flocculant dosage of the i-th round to the first end value of the binary search method, and set the preset flocculant dosage to the second end value of the binary search method.

[0099] Here, the preset flocculant dosage is recorded as D(l), l is the number of rounds of the current iteration, and the first end value is the left end value, recorded as D l , the second end value is the right end value, recorded as D r .

[0100] Step 6.2: Obtain an intermediate value according to the first end value and the second end value, and assign the intermediate value to the preset flocculant dosage to obtain the assigned preset flocculant dosage.

[0101] Here, the middle value D m =(D l +D r ) / 2, therefore, the preset flocculant dosage after assignment is D1(l)=D m .

[0102] Step 6.3: Conduct a coagulation experiment based on the preset flocculant dosage after the assignment to obtain the preset post-sedimentation turbidity after the coagulation experiment.

[0103] Specifically, the intelligent cup coagulation experiment is carried out using the preset flocculant dosage after the assignment obtained in step 6.2, so as to obtain the turbidity after sedimentation after the coagulation experiment, that is, the preset turbidity after sedimentation after the coagulation experiment is obtained, which is recorded as T1(l).

[0104] Step 6.4: Obtain a preset turbidity difference value according to the difference between the preset post-sedimentation turbidity and the target turbidity after the coagulation experiment.

[0105] Here, the calculation formula of the preset turbidity difference M1(l) is: M1(l)=T1(l)-T tar .

[0106] Step 6.5: Determine whether the preset turbidity difference is greater than -0.1. If so, use the intermediate value to update the first end value. If not, use the intermediate value to update the second end value.

[0107] That is, if M1(l)≥-0.1, then the current intermediate value D m Assign value D to the left side l , that is, D l =D m , to update the left value D l , otherwise, the current intermediate value D m Assign value D to the right side l , that is, D r =D m , to update the right value D l .

[0108] Step 6.6: Determine whether the preset turbidity difference is equal to -0.1 or 0. If so, update the intermediate value according to the updated first end value or the updated second end value obtained in step 6.5 to obtain the updated intermediate value, and execute step 6.7. If not, jump to step 6.2 and execute step 6.2 according to the updated first end value or the updated second end value obtained in step 6.5, that is, recalculate the intermediate value until the corresponding turbidity difference is equal to -0.1 or 0, and obtain the final intermediate value. The updated intermediate value is recorded as D m1 .

[0109] Step 6.7, determine the optimal flocculant dosage based on the updated intermediate value.

[0110] After binary search, under normal circumstances, the automatic optimization method has reached the optimal flocculant dosage at point A. However, if the value of d(i) is set too large in the first stage, there is a certain possibility that d(i) will be Figure 1 The dosage at point D is mistakenly regarded as the optimal dosage. In order to avoid this error in d(i), this embodiment uses different proportional coefficients, selects four specific dosage values ​​that are smaller than the current dosage, and uses a certain strategy to detect and verify the optimal flocculant dosage.

[0111] In a specific embodiment, see Figure 6 , step 6.7 may include:

[0112] Step 6.71, set the current iteration round number to round number j, and assign round number j to sampling sequence number s.

[0113] That is, the current iteration round number is set equal to j, and the sampling sequence number s is set equal to the round number j.

[0114] Step 6.72: Utilize the first proportional coefficient and the updated intermediate value to obtain the j-th flocculant dosage, and record the j-th round of flocculant dosage as the detection value.

[0115] Specifically, the updated intermediate value D is calculated m1 The product of the first proportional coefficient is taken as the flocculant dosage of the jth round, denoted as D(s).

[0116] Optionally, the first proportionality coefficient c1=80%.

[0117] Step 6.73: Conduct a coagulation experiment based on the flocculant dosage of the j-th round to obtain the post-settling turbidity T(s) after the j-th round of coagulation experiment.

[0118] Specifically, the j-th round of flocculant dosage obtained in step 6.72 is used to carry out the intelligent cup coagulation experiment, so as to obtain the post-sedimentation turbidity after the coagulation experiment, that is, the post-sedimentation turbidity T(s) after the j-th round of coagulation experiment.

[0119] Step 6.74, update the round number to j+1, and reduce the first proportional coefficient to obtain the second proportional coefficient.

[0120] Optionally, the second proportional coefficient is obtained by subtracting 20% ​​from the first proportional coefficient c1.

[0121] Step 6.75, determine whether the difference between j+1 and sampling number s is less than 5. If so, jump to step 6.72 and continue to collect test values. If not, the final flocculant dosage of the j+1th round, the j+2th round and the j+3th round are obtained, all of which are recorded as test values, and the corresponding turbidity after sedimentation T(s+1) after the j+1th round of coagulation experiment, the turbidity after sedimentation T(s+2) after the j+2th round of coagulation experiment, the turbidity after sedimentation T(s+3) after the j+3th round of coagulation experiment and the turbidity after sedimentation T(s+4) after the j+4th round of coagulation experiment are obtained.

[0122] That is to say, when the difference between j+1 and the sampling number s is less than 5, return to step 6.72, use the product of the second proportional coefficient and the updated intermediate value to obtain the flocculant dosage of the j+1th round, and record the flocculant dosage of the j+1th round as the detection value, and then carry out coagulation experiment with the flocculant dosage of the j+1th round to obtain the turbidity after sedimentation T(s+1) after the j+1th round of coagulation experiment, then update the number of rounds to j+2, and reduce the second proportional coefficient (such as subtracting 20% ​​from the second proportional coefficient c2 to obtain the third proportional coefficient), and then judge whether the difference between j+2 and the sampling number s is less than 5, until the obtained number of rounds is greater than or equal to 5, if the difference between j+5 and the sampling number s is equal to 5, stop the iteration, and finally The obtained flocculant dosage D(s) of the j-th round, the flocculant dosage D(s+1) of the j+1-th round, the flocculant dosage D(s+2) of the j+2-th round, the flocculant dosage D(s+3) of the j+3-th round and the flocculant dosage D(s+4) of the j+4-th round are all recorded as detection values, and the flocculant dosage of the j-th round is recorded as the detection value when n=0, the flocculant dosage of the j+1-th round is recorded as the detection value when n=1, the flocculant dosage of the j+2-th round is recorded as the detection value when n=2, the flocculant dosage of the j+3-th round is recorded as the detection value when n=3, and the flocculant dosage of the j+4-th round is recorded as the detection value when n+1 (here n=3), wherein n is the detection value serial number, and the value of n is 0, 1, 2 or 3.

[0123] Step 6.76, determine the optimal flocculant dosage based on the post-sedimentation turbidity T(s) after the j-th round of coagulation experiment, the post-sedimentation turbidity T(s+1) after the j+1-th round of coagulation experiment, the post-sedimentation turbidity T(s+2) after the j+2-th round of coagulation experiment, the post-sedimentation turbidity T(s+3) after the j+3-th round of coagulation experiment, and the post-sedimentation turbidity T(s+4) after the j+4-th round of coagulation experiment.

[0124] In one specific embodiment, step 6.76 includes:

[0125] Determine whether the turbidity after sedimentation T(s+n) after the j+nth round of coagulation experiment is greater than the turbidity after sedimentation T(s+n+1) after the j+nth round of coagulation experiment, where the value of n is 0, 1, 2 or 3;

[0126] If T(s+n)>T(s+n+1) is never true, the flocculant dosage of the jth round is taken as the optimal flocculant dosage. Otherwise, it is determined whether the turbidity after sedimentation T(s+n) after the j+nth round of coagulation experiment is greater than the turbidity after sedimentation T(s) after the jth round of coagulation experiment.

[0127] If the turbidity after sedimentation T(s+n) after the j+nth round of coagulation experiment is less than or equal to the turbidity after sedimentation T(s) after the jth round of coagulation experiment, then when the value of n is 0, if T(s)>T(s+1), then update the first end value to 0, update the second end value to the jth round of flocculant dosage, and jump to step 6.2, and continue to run according to step 6.2 until the optimal flocculant dosage is obtained;

[0128] If the turbidity after sedimentation T(s+n) after the j+nth round of coagulation experiment is greater than the turbidity after sedimentation T(s) after the jth round of coagulation experiment, then when the value of n is 1, 2 or 3, if any one of the first condition, the second condition or the third condition is met, the intermediate parameter is updated to the third intermediate parameter. Here, the third intermediate parameter P3 = P 当 *90%(P 当 is the current intermediate parameter), and jumps to step 5 (specifically jumps to step A21-A22 in step 5.6 in step 5), updates the calculation coefficient according to the third intermediate parameter (specifically updates the second calculation coefficient Q2 according to the third intermediate parameter) to continue running (when executing steps A21-A22 here, the difference in the third flocculant dosage of the i+1th round is taken as the first flocculant dosage of the i+1th round), until the optimal flocculant dosage is obtained, wherein the first condition is T(s+1)>T(s+2)≥T(s), the second condition is T(s+2)>T(s+3) and T(s)≤T(s+1)≤T(s+2), and the third condition is T(s+3)>T(s+4) and T(s)≤T(s+1)≤T(s+2)≤T(s+3).

[0129] That is to say, it is determined whether the turbidity after sedimentation T(s+n) is greater than the turbidity after the next round of sedimentation T(s+n+1), that is, T(s+n)>T(s+n+1). If T(s+n)>T(s+n+1) is never true, that is, T(s)≤T(s+1)≤T(s+2)≤T(s+3)≤T(s+4), then the flocculant dosage D(s) of the jth round is output as the optimal flocculant dosage; otherwise, it is continued to determine whether the turbidity after sedimentation T(s+n) is greater than the turbidity after sedimentation T(s). If not, when n=0, if T(s)>T(s+1), let the parameter D l =0 and Dr=D(s), and jump to step 6.2 to continue running; if so, when the value of n is 1, 2 or 3, the three logical relations are T(s+1)>T(s+2)≥T(s), T(s+2)>T(s+3) and T(s)≤T(s+1)≤T(s+2), T(s+3)>T(s+4) and T(s)≤T(s+1)≤T(s+2)≤T(s+3). If any of them is true, update the intermediate parameter P3=P 当 *90%, and jump to step 5, update the calculation coefficient, and continue running to finally confirm the optimal flocculant dosage.

[0130] First, in the detection value verification stage, if T(s+1) to T(s+4) is a gradually increasing turbidity value sequence, then D(s) corresponding to T(s) is the optimal flocculant dosage and can be directly output; second, for n∈[0,3], if there is a decrease in value from T(s+1) to T(s+4) and T(s+n)>T(s), then D(s) is not the optimal flocculant dosage, and the optimal flocculant dosage D(s) exceeds Figure 1 Point D in the figure needs to reduce the intermediate parameter P and the calculation coefficient Q, turn to step 5 in the overall process, and search for the optimal flocculant dosage again; third, if there is a decrease in value from T(s+1) to T(s+4) and T(s+n)≤T(s), then the optimal flocculant dosage is Figure 1 Between point M and point B, 0 and D(s) need to be assigned to the left value D respectively. l and the right value D r , as the input parameter for binary search, continue to find the optimal flocculant dosage at point A.

[0131] The automatic optimization method proposed in the present invention can quickly obtain the optimal flocculant dosage for the current raw water quality with the assistance of the intelligent cup coagulation device. Compared with the classic six-beaker experiment method, the automatic optimization method proposed in the present invention can not only save the experimental operation workload of water companies, but also obtain the flocculant dosage that achieves the same post-settling turbidity, fully improve the operating efficiency and accuracy of the coagulation process, thereby improving the work efficiency and economic benefits of water companies.

[0132] The automatic optimization method for flocculant dosage proposed in the present invention is based on the intelligent cup-jar coagulation device. According to the fitting curve relationship between the dosage and the coagulation effect, by executing different dosage search strategies, the optimal flocculant dosage suitable for the current water quality and with the best coagulation effect is obtained, thereby improving the operating efficiency and accuracy of the coagulation process.

[0133] Embodiment 2

[0134] This embodiment provides a specific example of determining the optimal flocculant dosage using the automatic optimization method of the first embodiment, wherein the initial turbidity of the water quality T(0)=5NTU):

[0135] 1. Obtain the initial turbidity T(0)=5NTU of the raw water quality from the water plant control end.

[0136] 2. Initialization: initial turbidity T(0) = 5NTU, initial dosage D(0) = 5, target turbidity T tar =2.0, number of running rounds i=0, difference between adjacent rounds d(0)=5, intermediate parameter P=100%, minimum flocculant dosage d min =0.2, the left value D l =0, right value D r =0, intermediate value D m =0.

[0137] according to Figure 2 The overall process shown, based on the intelligent cup tank coagulation device, respectively executes the processes of monotonicity judgment, binary search and verification strategy.

[0138] The algorithm is executed for about 10 minutes, then stops and outputs the optimal flocculant dosage data D(8)=15.2. For details, see Table 1.

[0139] Table 1 Operation data of automatic optimization algorithm when the initial turbidity is 5NTU

[0140]

[0141] Embodiment 2

[0142] This embodiment provides a specific example of determining the optimal flocculant dosage using the automatic optimization method of the first embodiment, wherein the initial turbidity of the water quality T(0)=800NTU):

[0143] 1. Obtain the initial turbidity T(0)=800NTU of the raw water quality from the water plant control end.

[0144] 2. Initialization: initial turbidity T(0) = 800 NTU, initial dosage D(0) = 5, target turbidity Ttar =4.0, number of running rounds i=0, difference between adjacent rounds d(0)=5, middle parameter P=100%, minimum flocculant dosage dmin=0.2, left end value D l =0, right value D r =0, intermediate value D m =0.

[0145] according to Figure 2 The overall process shown, based on the intelligent cup tank coagulation device, respectively executes the processes of monotonicity judgment, binary search and verification strategy.

[0146] The algorithm is executed for about 10 minutes, then stops and outputs the optimal flocculant dosage data D(9)=24.1. For details, see Table 2.

[0147] Table 2 Operation data of automatic optimization algorithm when the initial turbidity is 800 NTU

[0148]

[0149] Embodiment 4

[0150] See also Figure 7 , Figure 7 Schematic diagram of an automatic optimization system for flocculant dosage based on intelligent cup-pot coagulation provided by an embodiment of the present invention. The present invention further provides an automatic optimization system for flocculant dosage based on intelligent cup-pot coagulation on the basis of the above embodiment. The automatic optimization system for flocculant dosage based on intelligent cup-pot coagulation includes:

[0151] A first dosage generating module, used for obtaining a first flocculant dosage of the (i+1)th round according to the flocculant dosage of the i-th round and the difference of the flocculant dosage of the i-th round;

[0152] A post-settling turbidity generation module, used for obtaining a first post-settling turbidity after the i+1th round of coagulation experiment based on the coagulation experiment performed with the first flocculant dosage in the i+1th round;

[0153] A post-settling turbidity difference generation module is used to obtain the first turbidity difference of the i+1th round according to the first post-settling turbidity after the i+1th round of coagulation experiment and the target turbidity, and to obtain the first post-settling turbidity difference according to the difference between the first post-settling turbidity after the i-th round of coagulation experiment and the first post-settling turbidity after the i+1th round of coagulation experiment;

[0154] A judgment module, judging whether the first turbidity difference of the i+1th round is less than 0, if the first turbidity difference of the i+1th round is greater than or equal to 0, executing the method of the second dosage generation module, if the first turbidity difference of the i+1th round is less than 0, taking the first flocculant dosage of the i+1th round as the preset flocculant dosage, and executing the optimal dosage generation module method;

[0155] A second dosage generation module is used to obtain the monotonicity of the functional relationship between the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round based on a monotonicity judgment algorithm to obtain a monotonicity judgment result, obtain a monotonic Boolean value and update intermediate parameters according to the monotonicity judgment result, and jump to the method of the post-settling turbidity generation module to re-execute the method of the post-settling turbidity generation module according to the monotonic Boolean value and the updated intermediate parameters until a preset flocculant dosage is obtained;

[0156] The optimal dosage generation module is used to determine the optimal flocculant dosage according to the updated intermediate value obtained from the flocculant dosage of the i-1th round, the flocculant dosage of the i-th round and the preset flocculant dosage.

[0157] The automatic optimization system for flocculant dosage provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0158] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0159] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification.

[0160] Although the present invention is described herein in conjunction with various embodiments, in the process of implementing the claimed invention, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings and the disclosure. In the specification, the word "comprising" does not exclude other components or steps, and "one" or "a" does not exclude multiple situations. Certain measures are recorded in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0161] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A method for automatically optimizing flocculant dosage based on intelligent cup coagulation, characterized in that: The method for automatically optimizing the flocculant dosage comprises: Step 1, obtaining the first flocculant dosage of the i+1th round according to the flocculant dosage of the ith round and the difference of the flocculant dosage of the ith round; Step 2: performing a coagulation experiment based on the first flocculant dosage of the (i+1) round to obtain a first post-sedimentation turbidity after the (i+1) round of coagulation experiment; Step 3, obtaining the first turbidity difference of the i+1th round according to the first turbidity after sedimentation after the i+1th round of coagulation experiment and the target turbidity, and obtaining the first turbidity difference after sedimentation according to the difference between the first turbidity after sedimentation after the i-th round of coagulation experiment and the first turbidity after sedimentation after the i+1th round of coagulation experiment; Step 4, judging whether the first turbidity difference of the i+1th round is less than 0, if the first turbidity difference of the i+1th round is greater than or equal to 0, executing step 5, if the first turbidity difference of the i+1th round is less than 0, taking the first flocculant dosage of the i+1th round as the preset flocculant dosage, and executing step 6; Step 5, based on the monotonicity judgment algorithm, obtain the monotonicity of the functional relationship between the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round to obtain a monotonicity judgment result, obtain a monotonicity Boolean value and update the intermediate parameter according to the monotonicity judgment result, and jump to the step 2 to re-execute the step 2 according to the monotonicity Boolean value and the updated intermediate parameter until the preset flocculant dosage is obtained; wherein, if the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round show an increasing trend, the monotonicity Boolean value t=0, and the intermediate parameter is updated to obtain the first intermediate parameter; if the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round show a decreasing trend, the monotonicity Boolean value t=1, and the intermediate parameter is updated to obtain the second intermediate parameter; The relationship between the intermediate parameter of the flocculant dosage and the difference in flocculant dosage between adjacent rounds is: Q = M1(i)*P*r / T dis0 , where Q is the calculation coefficient of the difference in flocculant dosage between adjacent rounds, Q = M1(i)*P*r / T dis0 , r is the proportional coefficient in the process of selecting the detection value, M1(i)=T1(i)-T tar , T1(i) is the first sedimentation turbidity after the i-th round of coagulation experiment, T dis0 =T1(i-1)-T1(i), T1(i-1) is the first sedimentation turbidity after the i-1th round of coagulation experiment, T tar Indicates the target turbidity of raw water quality; Step 6: Based on a binary search method, the optimal flocculant dosage is determined according to the updated intermediate value obtained from the flocculant dosage of the i-1th round, the flocculant dosage of the i-th round, and the preset flocculant dosage.

2. The method for automatically optimizing the flocculant dosage according to claim 1, characterized in that: The step 1 comprises: The first flocculant dosage of the i+1th round is obtained according to the sum of the flocculant dosage of the i-th round and the difference of the flocculant dosage of the i-th round. The difference of the flocculant dosage of the i-th round is expressed as: d(i)=d(i-1)*Q Wherein, d(i) is the difference in flocculant dosage in the i-th round, d(i-1) is the difference in flocculant dosage in the i-1th round, and Q is the calculation coefficient.

3. The method for automatically optimizing the flocculant dosage according to claim 1, characterized in that: The step 3 comprises: The first turbidity difference of the i+1th round is obtained according to the difference between the first post-sedimentation turbidity after the i+1th round of coagulation experiment and the target turbidity. The first turbidity difference of the i+1th round is expressed as: M1(i+1)=T1(i+1)-T tar Among them, M1(i+1) is the first turbidity difference of the i+1th round, T1(i+1) is the first turbidity after sedimentation of the i+1th round of coagulation experiment, T tar is the target turbidity; The first turbidity difference after sedimentation is obtained according to the difference between the first turbidity after sedimentation after the i-th round of coagulation experiment and the first turbidity after sedimentation after the i+1-th round of coagulation experiment. The first turbidity difference after sedimentation is expressed as: T dis1 =T1(i)-T1(i+1) Among them, T dis1 is the turbidity difference after the first sedimentation, and T1(i) is the turbidity after the first sedimentation after the i-th round of cup coagulation experiment.

4. The method for automatically optimizing the flocculant dosage according to claim 1, characterized in that: The step 5 comprises: Step 5.1, assigning the minimum flocculant dosage to the first flocculant dosage difference of the i+1th round to obtain the second flocculant dosage difference of the i+1th round; Step 5.2, obtaining the first flocculant dosage of the i+2th round based on the difference between the first flocculant dosage of the i+1th round and the second flocculant dosage of the i+1th round; Step 5.3, performing a coagulation experiment based on the first flocculant dosage of the (i+2) round, obtaining a first post-sedimentation turbidity after the (i+2) round of coagulation experiment; Step 5.4, judging the relationship between the first turbidity after sedimentation after the i+1th round of coagulation experiment and the first turbidity after sedimentation after the i+2th round of coagulation experiment, if the first turbidity after sedimentation after the i+1th round of coagulation experiment is less than the first turbidity after sedimentation after the i+2th round of coagulation experiment, jumping to step 5.5, otherwise jumping to step 5.6; Step 5.5, if the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round show an increasing trend, the monotonic Boolean value t=0, and the intermediate parameter is updated to obtain the first intermediate parameter, and jump to step 5.7; Step 5.6: If the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round show a decreasing trend, the monotonic Boolean value t=1, and the initial intermediate parameter is updated to obtain the second intermediate parameter, and jump to step 5.7; Step 5.7, jump to the step 2, and re-execute the step 2 according to the monotonic Boolean value and the first intermediate parameter obtained in the step 5.5 or according to the monotonic Boolean value and the second intermediate parameter obtained in the step 5.6, until the preset flocculant dosage is obtained.

5. The method for automatically optimizing the flocculant dosage according to claim 4, characterized in that: Re-performing step 2 according to the monotonic Boolean value obtained in step 5.5 and the first intermediate parameter until the preset flocculant dosage is obtained, including: If the monotonicity Boolean value t=0, then updating the calculation coefficient according to the first intermediate parameter to obtain a first calculation coefficient; Obtain the first flocculant dosage difference of the (i+2) round according to the first calculation coefficient and the flocculant dosage difference of the i-th round; The first flocculant dosage of the i+3th round is obtained according to the difference between the first flocculant dosage of the i+1th round and the first flocculant dosage of the i+2th round, and the process jumps to step 2, and step 2 is performed according to the first flocculant dosage of the i+3th round.

6. The method for automatically optimizing the flocculant dosage according to claim 4, characterized in that: According to the monotonicity Boolean value obtained in step 5.6 and the second intermediate parameter, step 2 is re-executed, including: If the monotonicity Boolean value t=1, the calculation coefficient is updated according to the second intermediate parameter to obtain a second calculation coefficient; Determine whether the third flocculant dosage difference of the i+1th round is equal to the minimum flocculant dosage; If yes, then the second flocculant dosage difference of the i+2th round is obtained according to the flocculant dosage difference of the i+1th round and the second calculation coefficient, and then the second flocculant dosage of the i+3th round is obtained according to the first flocculant dosage of the i+1th round and the second flocculant dosage difference of the i+2th round, and the process jumps to step 2, and step 2 is executed according to the second flocculant dosage of the i+3th round until the corresponding turbidity difference is less than 0, and the flocculant dosage obtained by the turbidity difference is used as the preset flocculant dosage; If not, the third flocculant dosage difference of the i+2th round is obtained according to the second calculation coefficient and the third flocculant dosage difference of the i+1th round, and then the third flocculant dosage of the i+3th round is obtained according to the first flocculant dosage of the i+2th round and the third flocculant dosage difference of the i+2th round, and jump to step 2, and execute step 2 according to the third flocculant dosage of the i+3th round until the corresponding turbidity difference is less than 0, and the flocculant dosage obtained by the turbidity difference is used as the preset flocculant dosage.

7. The method for automatically optimizing the flocculant dosage according to claim 1, characterized in that: The step 6 comprises: Step 6.1, determine whether the difference between the preset flocculant dosage and the flocculant dosage of the i-th round is equal to the minimum flocculant dosage, if so, set the flocculant dosage of the i-1th round as the first end value of the binary search method, and set the preset flocculant dosage as the second end value of the binary search method; if not, set the flocculant dosage of the i-th round as the first end value of the binary search method, and set the preset flocculant dosage as the second end value of the binary search method; Step 6.2, obtaining an intermediate value according to the first end value and the second end value, and assigning the intermediate value to the preset flocculant dosage to obtain the assigned preset flocculant dosage; Step 6.3, performing a coagulation experiment based on the preset flocculant dosage after the assignment, and obtaining a preset post-settling turbidity after the coagulation experiment; Step 6.4, obtaining a preset turbidity difference according to the difference between the preset post-sedimentation turbidity and the target turbidity after the coagulation experiment; Step 6.5, determining whether the preset turbidity difference is greater than or equal to -0.1, if so, using the intermediate value to update the first end value, if not, using the intermediate value to update the second end value; Step 6.6, determine whether the preset turbidity difference is equal to -0.1 or 0. If so, update the intermediate value according to the updated first end value or the updated second end value obtained in step 6.5 to obtain an updated intermediate value, and execute step 6.

7. If not, jump to step 6.2, and execute step 6.2 according to the updated first end value or the updated second end value obtained in step 6.5; Step 6.7: Determine the optimal flocculant dosage according to the updated intermediate value.

8. The method for automatically optimizing the flocculant dosage according to claim 7, characterized in that: The step 6.7 comprises: Step 6.71, set the current iteration round number to round number j, and assign round number j to sampling sequence number s; Step 6.72, using the first proportionality coefficient and the updated intermediate value to obtain the flocculant dosage of the j-th round, and recording the flocculant dosage of the j-th round as the detection value; Step 6.73, performing a coagulation experiment based on the dosage of the flocculant in the j-th round, and obtaining the post-settling turbidity T(s) after the j-th round of coagulation experiment; Step 6.74, update the round number to j+1, and reduce the first proportional coefficient to obtain a second proportional coefficient; Step 6.75, determine whether the difference between j+1 and the sampling number s is less than 5. If so, jump to step 6.72 and continue to collect test values. If not, finally obtain the flocculant dosage of the j+1th round, the flocculant dosage of the j+2th round, the flocculant dosage of the j+3th round and the flocculant dosage of the j+4th round, all of which are recorded as test values, and the corresponding turbidity after sedimentation T(s+1) after the j+1th round of coagulation experiment, the turbidity after sedimentation T(s+2) after the j+2th round of coagulation experiment, the turbidity after sedimentation T(s+3) after the j+3th round of coagulation experiment and the turbidity after sedimentation T(s+4) after the j+4th round of coagulation experiment are obtained; Step 6.76, determine the optimal flocculant dosage based on the post-sedimentation turbidity T(s) after the j-th round of coagulation experiment, the post-sedimentation turbidity T(s+1) after the j+1-th round of coagulation experiment, the post-sedimentation turbidity T(s+2) after the j+2-th round of coagulation experiment, the post-sedimentation turbidity T(s+3) after the j+3-th round of coagulation experiment, and the post-sedimentation turbidity T(s+4) after the j+4-th round of coagulation experiment.

9. The method for automatically optimizing the flocculant dosage according to claim 8, characterized in that: The step 6.76 comprises: Determine whether the turbidity after sedimentation T(s+n) after the j+nth round of coagulation experiment is greater than the turbidity after sedimentation T(s+n+1) after the j+nth round of coagulation experiment, where the value of n is 0, 1, 2 or 3; If T(s+n)>T(s+n+1) is never true, the flocculant dosage of the jth round is taken as the optimal flocculant dosage. Otherwise, it is determined whether the turbidity after sedimentation T(s+n) after the j+nth round of coagulation experiment is greater than the turbidity after sedimentation T(s) after the jth round of coagulation experiment. If the turbidity after sedimentation T(s+n) after the j+nth round of coagulation experiment is less than or equal to the turbidity after sedimentation T(s) after the jth round of coagulation experiment, then when the value of n is 0, if T(s)>T(s+1), then the first end value is updated to 0, the second end value is updated to the flocculant dosage of the jth round, and jump to the step 6.2, and continue to run according to the step 6.2 until the optimal flocculant dosage is obtained; If the post-sedimentation turbidity T(s+n) after the j+nth round of coagulation experiment is greater than the post-sedimentation turbidity T(s) after the jth round of coagulation experiment, when the value of n is 1, 2 or 3, if any one of the first condition, the second condition or the third condition is met, the intermediate parameter is updated to the third intermediate parameter, and jump to the step 5, and the calculation coefficient is updated according to the third intermediate parameter to continue running until the optimal flocculant dosage is obtained, wherein the first condition is T(s+1)>T(s+2)≥T(s), the second condition is T(s+2)>T(s+3) and T(s)≤T(s+1)≤T(s+2), and the third condition is T(s+3)>T(s+4) and T(s)≤T(s+1)≤T(s+2)≤T(s+3).

10. An automatic optimization system for flocculant dosage based on intelligent cup coagulation, characterized in that: The flocculant dosage automatic optimization system comprises: A first dosage generating module, used for obtaining a first flocculant dosage of the (i+1)th round according to the flocculant dosage of the i-th round and the difference of the flocculant dosage of the i-th round; A post-settling turbidity generation module, used for obtaining a first post-settling turbidity after the i+1th round of coagulation experiment based on the coagulation experiment performed with the first flocculant dosage in the i+1th round; A post-settling turbidity difference generation module is used to obtain the first turbidity difference of the i+1th round according to the first post-settling turbidity after the i+1th round of coagulation experiment and the target turbidity, and to obtain the first post-settling turbidity difference according to the difference between the first post-settling turbidity after the i-th round of coagulation experiment and the first post-settling turbidity after the i+1th round of coagulation experiment; A judgment module, judging whether the first turbidity difference of the i+1th round is less than 0, if the first turbidity difference of the i+1th round is greater than or equal to 0, executing the method of the second dosage generation module, if the first turbidity difference of the i+1th round is less than 0, taking the first flocculant dosage of the i+1th round as the preset flocculant dosage, and executing the optimal dosage generation module method; A second dosage generation module is used to obtain the monotonicity of the functional relationship between the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round based on a monotonicity judgment algorithm to obtain a monotonicity judgment result, obtain a monotonicity Boolean value and update an intermediate parameter according to the monotonicity judgment result, and jump to the method of the post-settling turbidity generation module to re-execute the method of the post-settling turbidity generation module according to the monotonicity Boolean value and the updated intermediate parameter until a preset flocculant dosage is obtained; wherein, if the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round show an increasing trend, the monotonic Boolean value t=0, and the intermediate parameter is updated to obtain the first intermediate parameter; if the first post-settling turbidity after the i+1th round of coagulation experiment and the first flocculant dosage of the i+1th round show a decreasing trend, the monotonic Boolean value t=1, and the intermediate parameter is updated to obtain a second intermediate parameter; The relationship between the intermediate parameter of the flocculant dosage and the difference in flocculant dosage between adjacent rounds is: Q = M1(i)*P*r / T dis0 , where Q is the calculation coefficient of the difference in flocculant dosage between adjacent rounds, Q = M1(i)*P*r / T dis0 , r is the proportional coefficient in the process of selecting the detection value, M1(i)=T1(i)-T tar , T1(i) is the first sedimentation turbidity after the i-th round of coagulation experiment, T dis0 =T1(i-1)-T1(i), T1(i-1) is the first sedimentation turbidity after the i-1th round of coagulation experiment, T tar Indicates the target turbidity of raw water quality; The optimal dosage generation module is used to determine the optimal flocculant dosage according to the updated intermediate value obtained from the flocculant dosage of the i-1th round, the flocculant dosage of the i-th round and the preset flocculant dosage.

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