A multi-stage circulating water purification system and its control method

Abstract

This invention relates to the field of circulating water treatment technology and proposes a multi-stage circulating water purification system and its control method. The method includes: collecting water quality parameters and proportional parameters of a PID control algorithm for each purification step of the multi-stage circulating water purification system, and marking the target water quality parameters; obtaining clusters at the collection times, marking the target water quality parameters and the target collection time, determining the dosing effect and a first reference value for the proportional parameters, and then determining a second reference value for the proportional parameters of each purification step; obtaining water quality parameter clusters, calculating the adjustment influence, and determining a third reference value for the proportional parameters of each purification step; and combining the second and third reference values ​​to determine the optimal value of the proportional parameters for each purification step, thereby achieving multi-stage circulating water purification control. This invention can adaptively determine the proportional parameter values ​​of the PID control algorithm, ensuring precise adjustment of the water quality in the water circulation system.

Description

Technical Field

[0001] This invention relates to the field of circulating water treatment technology, specifically to a multi-stage circulating water purification system and its control method. Background Technology

[0002] Multi-stage purification processes for circulating water employ a multi-stage combination model to treat circulating water, such as combining physicochemical synergistic purification, electrochemical and biological coupling technology, and membrane separation processes. Because the water quality in a circulating water system is affected by a combination of factors during operation, including hardness, alkalinity, pH value, concentration factor, temperature, and ambient humidity, PID control equipment is generally used to control the dosage of relevant chemicals in order to adapt to changes in water quality, dynamically adjust chemical dosing, precisely control the dosage, and improve the stability and reliability of the system.

[0003] PID control equipment uses the PID control algorithm to control the reagents. The proportional parameter is a parameter used in the PID control algorithm to control the system's response to errors. It is generally taken as a fixed constant value. However, the operating conditions of the circulating water system are complex and changeable. A fixed proportional parameter is often difficult to adapt to the dynamic changes in water quality, and cannot guarantee the stable operation of the water circulation system and the precise regulation of water quality. Summary of the Invention

[0004] This invention provides a multi-stage circulating water purification system and its control method to solve the problems of complex and variable operating conditions in circulating water systems, where fixed proportional parameter values ​​cannot adapt to dynamic changes in water quality, thus failing to guarantee stable operation of the water circulation system and precise water quality regulation. The specific technical solution adopted is as follows:

[0005] In a first aspect, one embodiment of the present invention provides a method for multi-stage purification and control of circulating water, the method comprising the following steps:

[0006] Collect all types of water quality parameters and the values ​​of the proportional parameters of the PID control algorithm corresponding to each purification step of the multi-stage circulating water purification system at the current collection time and the corresponding historical collection time, and mark the target water quality parameters of each purification step.

[0007] For the same purification step, cluster all collection times based on the differences of the same type of water quality parameters at all collection times to obtain collection time clusters. Record any type of water quality parameter as the target water quality parameter and any collection time as the target collection time. Based on the differences between the target water quality parameters at the target collection time and all historical collection times of the target collection time for all adjacent purification steps, determine the dosing effect of the target water quality parameter at the target collection time for each purification step. Based on the dosing effect, weighted summation of the proportional parameters of the corresponding PID control algorithm is performed to obtain the first reference value of the proportional parameters of the same type of water quality parameter in the same purification step. Based on all the first reference values ​​of the proportional parameters and the target water quality parameter, determine the second reference value of the proportional parameters for each purification step.

[0008] For all water quality parameters of the same type collected at the same time in the same purification step within the collection time cluster containing the current sampling time, obtain the water quality parameter clusters of the same purification step. Based on the differences in the dosing effect between the purification steps corresponding to the water quality parameter clusters and the number of water quality parameter clusters, calculate the adjustment influence of each purification step, and determine the third reference value of the proportional parameter of each purification step based on the adjustment influence.

[0009] Based on the second and third reference values ​​of the proportional parameters for each purification step, the optimal value of the proportional parameters for each purification step is determined, thereby achieving multi-stage purification control of circulating water.

[0010] Furthermore, the target water quality parameter of the purification step specifically refers to the type of water quality parameter controlled by the purification step.

[0011] Furthermore, the method for obtaining the clusters at the acquisition time is as follows:

[0012] For the same purification step, the normalized value of the square of the difference of the same type of water quality parameter obtained at different collection times is recorded as the first normalized value of the same type of water quality parameter obtained at different collection times. The arithmetic square root of the sum of all the first normalized values ​​of the same type of water quality parameter obtained at different collection times is recorded as the difference of water quality parameter at different collection times in the same purification step.

[0013] The difference in water quality parameters at different collection times within the same purification step is used as the distance metric for clustering. Clustering is performed on the current collection time and all historical collection times to obtain the collection time cluster corresponding to the same purification step.

[0014] Furthermore, the method for determining the dosing effect in the purification step is as follows:

[0015] For the same purification step, the variance of the target water quality parameter at the target acquisition time and all historical acquisition times is denoted as the first variance of the same purification step at the target acquisition time. The ratio of the first variance of the purification step to the first variance of the next adjacent purification step at the target acquisition time is denoted as the first ratio of the target water quality parameter at the target acquisition time of the purification step.

[0016] For the same purification step, the sum of the absolute values ​​of the differences between the target water quality parameters and the standard values ​​of the target water quality parameters at the target sampling time and all historical sampling times is recorded as the first sum at the target sampling time.

[0017] The normalized value of the ratio of the first ratio of the target water quality parameter to the first sum at the target sampling time in the same purification step is recorded as the dosing effect of the target water quality parameter at the target sampling time in the same purification step.

[0018] Furthermore, the method for obtaining the first reference value of the proportion of the same type of water quality parameters in the same purification step is as follows:

[0019] For two different collection times within the same collection time cluster, the average value of the dosing effect of the same type of water quality parameter at the same collection time in the same purification step is recorded as the first average value of the same type of water quality parameter at the same collection time in the same purification step. The normalized value of the ratio of the first average value to the distance metric of the corresponding cluster at the two collection times is recorded as the reference weight of the same type of water quality parameter at the same collection time in the same purification step.

[0020] The reference weight is used as the weight of the average value of the proportional parameter of the PID control algorithm of the corresponding water quality parameter of the corresponding type at the two collection times. The average value of the proportional parameter of the PID control algorithm of the same type of water quality parameter at all different collection times in all clusters is weighted and summed to obtain the first reference value of the proportional parameter of the same type of water quality parameter in the same collection time cluster in the same purification step.

[0021] Furthermore, the method for determining the second reference value of the proportional parameter for each purification step is as follows:

[0022] The first reference value of the proportion parameter of the target water quality parameter corresponding to the same purification step, which includes the current collection time cluster, is used as the second reference value of the proportion parameter of the same purification step.

[0023] Furthermore, the method for obtaining the water quality parameter clusters is as follows:

[0024] The absolute value of the difference in water quality parameters is used as the distance metric for clustering. All water quality parameters of the same type collected at the same time in the same purification step are clustered within the cluster containing the current sampling time, thus obtaining clusters of water quality parameters in the same purification step.

[0025] Furthermore, the specific steps for calculating the regulatory influence of each purification step based on the differences in dosing effects among the purification steps corresponding to water quality parameter clusters and the number of water quality parameter clusters, and determining the third reference value of the proportional parameter for each purification step based on the regulatory influence, include:

[0026] The variance of the dosing effect of all historical collection times corresponding to all water quality parameters in the water quality parameter cluster at the corresponding purification step is denoted as the second variance of the water quality parameter cluster. The ratio of the number of water quality parameter clusters to the sum of the second variances of all water quality parameter clusters is denoted as the second ratio of the purification step and the corresponding type of water quality parameter corresponding to the water quality parameter cluster.

[0027] The variance of the dosing effect at all historical collection times corresponding to all water quality parameters within all water quality parameter clusters in the corresponding purification steps of the water quality parameter clusters is denoted as the third variance of the water quality parameter of the corresponding type in the corresponding purification steps of the water quality parameter clusters.

[0028] The normalized value of the product of the third difference and the second ratio of the water quality parameters of the corresponding type in the water quality parameter cluster in the corresponding purification step of the water quality parameter cluster is denoted as the moderating influence of the water quality parameters of the corresponding type in the water quality parameter cluster in the corresponding purification step of the water quality parameter cluster.

[0029] The water quality parameter corresponding to the adjustment influence degree that is greater than the influence degree threshold is recorded as the important water quality parameter of the purification step corresponding to the adjustment influence degree. The sum of the adjustment influence degrees of all important water quality parameters in the same purification step is recorded as the important adjustment influence degree. The ratio of the adjustment influence degree of the important water quality parameter in the same purification step to the important adjustment influence degree is used as the weight. The proportional parameters of the PID control algorithm of the important water quality parameter in the same purification step at the corresponding acquisition time are weighted and summed to obtain the third reference value of the proportional parameter of the same purification step.

[0030] Furthermore, the specific steps for determining the optimal value of the proportional parameter for each purification step based on the second and third reference values ​​of the proportional parameter for each purification step include:

[0031] The average of the second and third reference values ​​of the proportional parameters for the same purification step is used as the value of the proportional parameter of the PID algorithm in the same purification step at the current acquisition time.

[0032] Secondly, embodiments of the present invention also provide a multi-stage circulating water purification system, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0033] The beneficial effects of this invention are:

[0034] This application clusters the sampling times corresponding to the same type of water quality parameters in the same purification step, grouping water quality parameters with similar values ​​into clusters based on the sampling time. The purification effect of circulating water is evaluated and the dosing effect is obtained based on the water quality parameters corresponding to all sampling times within the same cluster. A better purification effect for the target water quality parameter in a purification step corresponds to a greater dosing effect for that parameter in that step. The proportional parameters of the corresponding PID control algorithm are weighted and summed based on the dosing effect to obtain a first reference value for the proportional parameters. Then, a second reference value for the proportional parameters of each purification step is determined. This second reference value is an estimated value of the proportional parameters of the PID control algorithm determined based on the values ​​of the water quality parameters at each sampling time. Furthermore, the differences between water quality parameters at historical sampling times and the corresponding differences in dosing effects are analyzed. This study evaluates the impact of different water quality parameter clusters on the treatment effect of circulating water in corresponding purification steps, obtains the degree of adjustment influence, and determines the third reference value of the proportional parameter for each purification step based on the degree of adjustment influence. The third reference value of the proportional parameter is an estimated value of the proportional parameter of the PID control algorithm determined based on the influence of water quality parameters on the dosing effect. Finally, based on the second and third reference values ​​of the proportional parameter for each purification step, the optimal value of the proportional parameter for each purification step is determined, realizing multi-stage purification control of circulating water. This addresses the problem that fixed proportional parameter values ​​cannot adapt to the dynamic changes in water quality due to the complex and variable operating conditions of the circulating water system, and cannot guarantee the stable operation of the water circulation system and the precise regulation of water quality. The optimal value of the proportional parameter of the PID control algorithm is adaptively determined to ensure the precise regulation and stability of water quality in the water circulation system. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a schematic flowchart of a multi-stage purification and control method for circulating water provided in one embodiment of the present invention;

[0037] Figure 2 This is a flowchart of the data acquisition process for clustering at a specific time, provided in one embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Please see Figure 1 The diagram illustrates a flowchart of a multi-stage purification control method for circulating water according to an embodiment of the present invention. The method includes the following steps:

[0040] Step S001: Collect all types of water quality parameters and the values ​​of the proportional parameters of the PID control algorithm corresponding to the water quality parameters at the current collection time and the corresponding historical collection time for each purification step of the circulating water multi-stage purification system, and mark the target water quality parameters for each purification step.

[0041] Each stage of the circulating water purification process in the multi-stage circulating water purification system is recorded as a purification step, and water quality parameters of all types are collected using water quality sensors at the inlet of each purification step of the multi-stage circulating water purification system.

[0042] The water quality parameters selected in this embodiment include pH value, turbidity, total phosphorus, color, suspended solids, conductivity, dissolved oxygen, ammonia nitrogen, total nitrogen, and hardness. In practical applications, as other implementation methods, implementers can decide on the types of water quality parameters according to the specific needs of the circulating water, and this application does not impose any special restrictions.

[0043] Specifically, water quality parameters are collected at the current sampling time and at *a* sampling times prior to the current sampling time. In this embodiment, the sampling time interval for water quality parameters is set to 1 minute, where *a* represents a first preset parameter, which is a preset parameter value. In this embodiment, the value of the first preset parameter is 30. The *a* sampling times prior to the current sampling time are all recorded as historical sampling times for the current sampling time. In practical applications, as other implementation methods, the implementer can determine the sampling time interval and the number of historical sampling times for water quality parameters according to the specific needs of the circulating water; this application does not impose any special restrictions.

[0044] Furthermore, the values ​​of the proportional parameters of the PID control algorithm corresponding to all types of water quality parameters at the current acquisition time and all historical acquisition times are extracted.

[0045] It is important to understand that for a multi-stage circulating water purification system, each purification step has only one purpose and involves the addition of only one type of reagent. Therefore, it is only necessary to obtain the proportional parameter values ​​corresponding to the water quality parameters that need to be controlled for each purification step. The type of water quality parameter controlled by the purification step is recorded as the purpose water quality parameter of the purification step.

[0046] Thus, the system obtains the values ​​of the proportional parameters of the PID control algorithm corresponding to all types of water quality parameters at the current acquisition time and a preset number of historical acquisition times for each purification step of the circulating water multi-stage purification system, and obtains the target water quality parameters for each purification step.

[0047] Step S002: For the same purification step, cluster all collection times according to the differences of the same type of water quality parameters at all collection times to obtain a collection time cluster. Record any type of water quality parameter as the target water quality parameter and any collection time as the target collection time. Based on the differences between the target water quality parameters of all adjacent purification steps at the target collection time and all historical collection times of the target collection time, determine the dosing effect of the target water quality parameter at the target collection time for each purification step. Based on the dosing effect, weighted summation of the proportional parameters of the corresponding PID control algorithm is performed to obtain the first reference value of the proportional parameters of the same type of water quality parameter in the same purification step. Based on all the first reference values ​​of the proportional parameters and the target water quality parameter, determine the second reference value of the proportional parameters of each purification step.

[0048] For the same purification step, the normalized value of the square of the difference between the same type of water quality parameters obtained at different sampling times is denoted as the first normalized value of the same type of water quality parameter obtained at different sampling times. The arithmetic square root of the sum of all the first normalized values ​​of the same type of water quality parameters obtained at different sampling times is denoted as the difference in water quality parameters at different sampling times in the same purification step. Using the difference in water quality parameters at different sampling times in the same purification step as a distance metric for clustering, clustering is performed on the current sampling time and all historical sampling times to obtain the sampling time cluster corresponding to the same purification step.

[0049] The flowchart for obtaining clusters at the time of data collection is as follows: Figure 2 As shown.

[0050] In this embodiment, the DBSCAN clustering algorithm is used to cluster all historical acquisition times. In practical applications, while achieving the goal of clustering, implementers can use other existing methods such as Mean Shift clustering, OPTICS clustering, Gaussian Mixture Models clustering, and Spectral Clustering, etc., for clustering. This application does not impose any special restrictions. This embodiment uses the Z-Score standard normalization method to calculate the normalized value. In practical applications, implementers can use other existing methods such as the maximum-minimum normalization method and the sigmoid function to calculate the normalized value, and these are not limited here.

[0051] The water quality parameters corresponding to all sampling times within the same sampling time cluster for the same purification step have similar values. Based on the water quality parameters corresponding to all sampling times within the same sampling time cluster, the purification effect of circulating water can be evaluated. Furthermore, based on the proportional parameter values ​​corresponding to sampling times with better purification effects, the optimal value of the proportional parameter for the current sampling time can be determined.

[0052] Record any type of water quality parameter as the target water quality parameter, and record any one of the current collection time and all historical collection times as the target collection time.

[0053] It is understandable that the a acquisition times prior to the target acquisition time are the historical acquisition times of the target acquisition time.

[0054] Based on the differences between the target water quality parameters at the target sampling time and all historical sampling times at the target sampling time for all adjacent purification steps, the dosing effect of each purification step at the target sampling time is determined.

[0055] For the same purification step, the variance of the target water quality parameter at the target sampling time and at all historical sampling times is denoted as the first variance of the same purification step at the target sampling time. The ratio of the first variance of the purification step to that of the next adjacent purification step at the target sampling time is denoted as the first ratio of the target water quality parameter at the target sampling time of the purification step. For the same purification step, the sum of the absolute values ​​of the differences between the target water quality parameter and its standard value at the target sampling time and at all historical sampling times is denoted as the first cumulative sum at the target sampling time. The normalized value of the ratio of the first ratio of the target water quality parameter to the first cumulative sum at the target sampling time of the same purification step is denoted as the dosing effect of the target water quality parameter at the target sampling time in the same purification step.

[0056] It is understandable that the last purification step does not have an adjacent next purification step, and the effect of the chemical dosing in the last purification step is not analyzed. For the last purification step, the purification effect can be judged by comparing the water quality parameters of the purified circulating water with the target water quality parameters. It should be noted that the standard values ​​of the target water quality parameters are determined by experts in this field based on the purification requirements of the circulating water.

[0057] If the difference between the target water quality parameters at the target sampling time and all historical sampling times is smaller relative to the difference corresponding to the target sampling time, and the difference between the target water quality parameters of the purification step and the next adjacent purification step is larger, then the purification effect of the target water quality parameters in the purification step is better, that is, the dosing effect of the target water quality parameters in the purification step is greater.

[0058] It should be noted that for any one of the current and all historical sampling times, the target water quality parameter has a corresponding dosing effect in each purification step; at the same time, for each water quality parameter, for any one of the current and all historical sampling times, each purification step has a corresponding dosing effect.

[0059] The same method can be used to obtain the dosing effect of any type of water quality parameter at any time during the current sampling time and at any time during any of the historical sampling times, and at any purification step.

[0060] Based on the dosing effect of the same type of water quality parameters from different collection times within the same cluster at the same collection time in the same purification step, the proportional parameters of the corresponding PID control algorithm are weighted and summed to obtain the first reference value of the proportional parameters of the same type of water quality parameters from the same cluster at the same collection time in the same purification step.

[0061] For two different sampling times within the same cluster, the average value of the dosing effect of the same type of water quality parameter at the same sampling time in the same purification step is recorded as the first average value of the same type of water quality parameter at the same sampling time in the same purification step. The normalized value of the ratio of the first average value to the distance metric of the corresponding cluster at the two sampling times is recorded as the reference weight of the same type of water quality parameter at the same sampling time in the same purification step. The reference weight is used as the weight of the average value of the proportional parameter of the corresponding type of water quality parameter at the corresponding sampling time in the corresponding purification step. The average values ​​of the proportional parameters of the PID control algorithm of the same type of water quality parameter at all different sampling times within all clusters are weighted and summed to obtain the first reference value of the proportional parameter of the same type of water quality parameter in the same sampling time cluster in the same purification step.

[0062] The first reference value of the proportion parameter of the target water quality parameter corresponding to the same purification step, which includes the current collection time cluster, is used as the second reference value of the proportion parameter of the same purification step.

[0063] At this point, the second reference value of the proportional parameter for each purification step is obtained.

[0064] Step S003: For all water quality parameters of the same type collected at the same time in the same purification step within the collection time cluster containing the current sampling time, obtain the water quality parameter clusters of the same purification step. Based on the differences in the dosing effects between the purification steps corresponding to the water quality parameter clusters and the number of water quality parameter clusters, calculate the adjustment influence degree of each purification step, and determine the third reference value of the proportional parameter of each purification step based on the adjustment influence degree.

[0065] In a multi-stage circulating water purification system, each stage of the purification process has different treatment objectives, and interference may occur between different processes. For example, in the process of using activated carbon to adsorb and treat organic matter, color, and odor in water, residual chlorine in the water may oxidize the activated carbon, reducing its adsorption capacity and resulting in poor adsorption performance. Therefore, it is necessary to analyze the differences in water quality parameters at historical data collection points and the corresponding differences in dosing effects to determine the appropriate value for the proportional parameter of the PID control algorithm.

[0066] The absolute value of the difference in water quality parameters is used as the distance metric for clustering. All water quality parameters of the same type collected at the same time in the same purification step are clustered within the cluster containing the current sampling time, thus obtaining clusters of water quality parameters in the same purification step.

[0067] In this embodiment, the DBSCAN clustering algorithm is used to cluster all water quality parameters. In practical applications, in addition to achieving the purpose of clustering, implementers may use other existing methods such as Mean Shift clustering algorithm, OPTICS clustering algorithm, Gaussian Mixture Models clustering algorithm, and Spectral Clustering for clustering. This application does not impose any special restrictions.

[0068] It is understandable that if the values ​​of water quality parameters within the same water quality parameter cluster are similar, the corresponding dosing effects should also be similar. In other words, the purification effects of the purification steps corresponding to the water quality parameters within the same water quality parameter cluster should be similar. When the differences in the values ​​of water quality parameters within the same water quality parameter cluster are greater, the impact of the water quality parameters corresponding to the water quality parameter cluster on the purification effect of circulating water is greater.

[0069] Based on the differences in the dosing effects of the purification steps corresponding to the water quality parameter clusters, and the number of water quality parameter clusters, the adjustment impact of each purification step is calculated.

[0070] The variance of the dosing effect of all historical sampling times for all water quality parameters within a water quality parameter cluster at the corresponding purification step is denoted as the second variance of the water quality parameter cluster. The ratio of the number of water quality parameter clusters to the sum of the second variances of all water quality parameter clusters is denoted as the second ratio of the corresponding purification step and the corresponding type of water quality parameter within the water quality parameter cluster. The variance of the dosing effect of all historical sampling times for all water quality parameters within a water quality parameter cluster at the corresponding purification step is denoted as the third variance of the corresponding type of water quality parameter within the water quality parameter cluster at the corresponding purification step. The normalized value of the product of the third variance and the second ratio of the corresponding type of water quality parameter within the water quality parameter cluster at the corresponding purification step is denoted as the moderating influence of the corresponding type of water quality parameter within the water quality parameter cluster at the corresponding purification step.

[0071] The smaller the difference between all water quality parameters within a water quality parameter cluster, and the greater the difference between the dosing effects of all historical data collection times corresponding to all water quality parameters within a water quality parameter cluster at the corresponding purification step, the greater the impact of the type of water quality parameter corresponding to the water quality parameter cluster on the treatment effect of the circulating water in the corresponding purification step.

[0072] The water quality parameter corresponding to the adjustment influence degree that is greater than the influence degree threshold is recorded as the important water quality parameter of the purification step corresponding to the adjustment influence degree. The sum of the adjustment influence degrees of all important water quality parameters in the same purification step is recorded as the important adjustment influence degree. The ratio of the adjustment influence degree of the important water quality parameter in the same purification step to the important adjustment influence degree is used as the weight. The proportional parameters of the PID control algorithm of the important water quality parameter in the same purification step at the corresponding acquisition time are weighted and summed to obtain the third reference value of the proportional parameter of the same purification step.

[0073] At this point, the third reference value for the proportional parameters of each purification step is obtained.

[0074] Step S004: Based on the second and third reference values ​​of the proportional parameters for each purification step, determine the optimal value of the proportional parameters for each purification step to achieve multi-stage purification control of circulating water.

[0075] The average of the second and third reference values ​​of the proportional parameters for the same purification step is used as the value of the proportional parameter of the PID algorithm in the same purification step at the current acquisition time, so as to realize the control of multi-stage purification of circulating water in the same purification step.

[0076] This achieves multi-stage purification and control of circulating water.

[0077] Based on the same inventive concept as the above method, this embodiment of the invention also provides a multi-stage circulating water purification system, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described multi-stage circulating water purification control methods.

[0078] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for controlling multi-stage purification of circulating water, characterized in that, The method includes the following steps: Collect all types of water quality parameters and the values ​​of the proportional parameters of the PID control algorithm corresponding to each purification step of the multi-stage circulating water purification system at the current collection time and the corresponding historical collection time, and mark the target water quality parameters of each purification step. For the same purification step, cluster all collection times based on the differences of the same type of water quality parameters at all collection times to obtain collection time clusters. Record any type of water quality parameter as the target water quality parameter and any collection time as the target collection time. Based on the differences between the target water quality parameters at the target collection time and all historical collection times of the target collection time for all adjacent purification steps, determine the dosing effect of the target water quality parameter at the target collection time for each purification step. Based on the dosing effect, weighted summation of the proportional parameters of the corresponding PID control algorithm is performed to obtain the first reference value of the proportional parameters of the same type of water quality parameter in the same purification step. Based on all the first reference values ​​of the proportional parameters and the target water quality parameter, determine the second reference value of the proportional parameters for each purification step. For all water quality parameters of the same type collected at the same time in the same purification step within the collection time cluster containing the current sampling time, obtain the water quality parameter clusters of the same purification step. Based on the differences in the dosing effect between the purification steps corresponding to the water quality parameter clusters and the number of water quality parameter clusters, calculate the adjustment influence of each purification step, and determine the third reference value of the proportional parameter of each purification step based on the adjustment influence. Based on the second and third reference values ​​of the proportional parameters for each purification step, the optimal value of the proportional parameters for each purification step is determined, thereby achieving multi-stage purification control of circulating water.

2. The method for multi-stage purification and control of circulating water according to claim 1, characterized in that, The specific water quality parameters to be controlled in the purification step are: the types of water quality parameters controlled in the purification step.

3. The method for multi-stage purification and control of circulating water according to claim 1, characterized in that, The method for obtaining the clusters at the acquisition time is as follows: For the same purification step, the normalized value of the square of the difference of the same type of water quality parameter obtained at different collection times is recorded as the first normalized value of the same type of water quality parameter obtained at different collection times. The arithmetic square root of the sum of all the first normalized values ​​of the same type of water quality parameter obtained at different collection times is recorded as the difference of water quality parameter at different collection times in the same purification step. The difference in water quality parameters at different collection times within the same purification step is used as the distance metric for clustering. Clustering is performed on the current collection time and all historical collection times to obtain the collection time cluster corresponding to the same purification step.

4. The method for multi-stage purification and control of circulating water according to claim 1, characterized in that, The method for determining the dosing effect in the purification step is as follows: For the same purification step, the variance of the target water quality parameter at the target acquisition time and all historical acquisition times is denoted as the first variance of the same purification step at the target acquisition time. The ratio of the first variance of the purification step to the first variance of the next adjacent purification step at the target acquisition time is denoted as the first ratio of the target water quality parameter at the target acquisition time of the purification step. For the same purification step, the sum of the absolute values ​​of the differences between the target water quality parameters and the standard values ​​of the target water quality parameters at the target sampling time and all historical sampling times is recorded as the first sum at the target sampling time. The normalized value of the ratio of the first ratio of the target water quality parameter to the first sum at the target sampling time in the same purification step is recorded as the dosing effect of the target water quality parameter at the target sampling time in the same purification step.

5. The method for multi-stage purification and control of circulating water according to claim 1, characterized in that, The method for obtaining the first reference value of the proportion of the same type of water quality parameter in the same purification step is as follows: For two different collection times within the same collection time cluster, the average value of the dosing effect of the same type of water quality parameter at the same collection time in the same purification step is recorded as the first average value of the same type of water quality parameter at the same collection time in the same purification step. The normalized value of the ratio of the first average value to the distance metric of the corresponding cluster at the two collection times is recorded as the reference weight of the same type of water quality parameter at the same collection time in the same purification step. The reference weight is used as the weight of the average value of the proportional parameter of the PID control algorithm of the corresponding water quality parameter of the corresponding type at the two collection times. The average value of the proportional parameter of the PID control algorithm of the same type of water quality parameter at all different collection times in all clusters is weighted and summed to obtain the first reference value of the proportional parameter of the same type of water quality parameter in the same collection time cluster in the same purification step.

6. The method for multi-stage purification and control of circulating water according to claim 1, characterized in that, The method for determining the second reference value of the proportional parameter for each purification step is as follows: The first reference value of the proportion parameter of the target water quality parameter corresponding to the same purification step, which includes the current collection time cluster, is used as the second reference value of the proportion parameter of the same purification step.

7. The method for multi-stage purification and control of circulating water according to claim 1, characterized in that, The method for obtaining the water quality parameter clusters is as follows: The absolute value of the difference in water quality parameters is used as the distance metric for clustering. All water quality parameters of the same type collected at the same time in the same purification step are clustered within the cluster containing the current sampling time, thus obtaining clusters of water quality parameters in the same purification step.

8. The method for multi-stage purification and control of circulating water according to claim 1, characterized in that, The specific steps include: calculating the moderating influence of each purification step based on the differences in dosing effects among purification steps corresponding to water quality parameter clusters and the number of water quality parameter clusters; and determining the third reference value of the proportional parameter for each purification step based on the moderating influence. The variance of the dosing effect of all historical collection times corresponding to all water quality parameters in the water quality parameter cluster at the corresponding purification step is denoted as the second variance of the water quality parameter cluster. The ratio of the number of water quality parameter clusters to the sum of the second variances of all water quality parameter clusters is denoted as the second ratio of the purification step and the corresponding type of water quality parameter corresponding to the water quality parameter cluster. The variance of the dosing effect at all historical collection times corresponding to all water quality parameters within all water quality parameter clusters in the corresponding purification steps of the water quality parameter clusters is denoted as the third variance of the water quality parameter of the corresponding type in the corresponding purification steps of the water quality parameter clusters. The normalized value of the product of the third difference and the second ratio of the water quality parameters of the corresponding type in the water quality parameter cluster in the corresponding purification step of the water quality parameter cluster is denoted as the moderating influence of the water quality parameters of the corresponding type in the water quality parameter cluster in the corresponding purification step of the water quality parameter cluster. The water quality parameter corresponding to the adjustment influence degree that is greater than the influence degree threshold is recorded as the important water quality parameter of the purification step corresponding to the adjustment influence degree. The sum of the adjustment influence degrees of all important water quality parameters in the same purification step is recorded as the important adjustment influence degree. The ratio of the adjustment influence degree of the important water quality parameter in the same purification step to the important adjustment influence degree is used as the weight. The proportional parameters of the PID control algorithm of the important water quality parameter in the same purification step at the corresponding acquisition time are weighted and summed to obtain the third reference value of the proportional parameter of the same purification step.

9. The method for multi-stage purification and control of circulating water according to claim 1, characterized in that, The specific steps for determining the optimal value of the proportional parameter for each purification step based on the second and third reference values ​​are as follows: The average of the second and third reference values ​​of the proportional parameters for the same purification step is used as the value of the proportional parameter of the PID algorithm in the same purification step at the current acquisition time.

10. A multi-stage circulating water purification system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as claimed in any one of claims 1-9.

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