Circulating pump control method and system

Abstract

The invention relates to the technical field of circulating pump control, and discloses a circulating pump control method and system. According to the method, a current operation parameter set of the circulating pump is obtained, an operation state monitoring database mapped with the current operation parameter set is established, and monitoring indexes of the database comprise the flow deviation rate, the pressure fluctuation amplitude and the like. Then, directional control targets such as flow stability control, pressure fluctuation suppression, energy consumption efficiency optimization and temperature anomaly early warning are configured according to the database, and target classification identifiers are determined; then, key control parameters are selected through the main control target and the auxiliary control target, directional control target influence analysis is carried out, parameter directional control is executed after parameter control constraints are established, and control parameter directional optimization is completed. The system comprises a parameter acquisition module, a target configuration module and the like. According to the scheme, multi-target cooperative control over the circulating pump can be achieved, the operation stability and the energy consumption efficiency are improved, and temperature abnormity is early warned in time.

Description

Technical Field

[0001] The present invention relates to the technical field of circulating pump control, in particular to a circulating pump control method and control system. Background Art

[0002] Circulating pumps are widely used in numerous fields, including industrial production, heating systems, and water conservancy projects. Their operational stability, efficiency, and safety are crucial to the proper functioning of the entire system. In practice, the operation of circulating pumps is affected by a variety of factors, which can cause fluctuations in operating parameters and, in turn, affect system performance.

[0003] Currently, existing circulation pump control methods have many shortcomings when faced with complex operating conditions. For example, in terms of flow control, when system requirements change, traditional control methods have difficulty quickly and stably adjusting the flow rate to the target value, which is prone to large flow fluctuations. This not only affects the normal progress of subsequent processes but can also cause increased wear and tear on equipment. In terms of pressure control, pressure fluctuations are particularly prominent due to factors such as pipeline resistance and load changes. This can cause system vibration, noise, and even lead to safety accidents.

[0004] In terms of energy efficiency, many control methods fail to fully consider the optimal energy consumption configuration under different operating conditions, resulting in energy waste during circulation pump operation and increased production costs. Furthermore, traditional early warning mechanisms are often insensitive to abnormal temperature conditions during circulation pump operation, failing to promptly identify potential faults, which could lead to equipment damage and affect production continuity.

[0005] Furthermore, existing circulating pump control systems lack effective target classification and coordinated control mechanisms when handling multiple control objectives. Different control objectives can conflict with each other. For example, maintaining flow stability while optimizing energy efficiency may require sacrificing energy consumption to maintain flow stability. Traditional methods struggle to find the optimal balance between these objectives, resulting in suboptimal control results.

[0006] Furthermore, existing control methods lack in-depth analysis of the mutual influence and sensitivity between parameters during parameter adjustment, often relying on empirical parameter adjustments. This results in inefficient parameter adjustment and makes it difficult to quickly achieve the optimal control state. Furthermore, the lack of an effective search and self-optimization management mechanism during the iterative parameter update process can lead to the iterative process becoming stuck in a local optimum, preventing the global optimal solution from being found. Summary of the Invention

[0007] The object of the present invention is to provide a circulation pump control method and control system to solve the problems raised in the above background technology.

[0008] To achieve the above object, the present invention provides a circulating pump control method, the method comprising: Obtaining the current operating parameter set of the circulation pump and establishing a circulation pump operating status monitoring database mapped to the current operating parameter set; Configuring directional control targets based on the operation status monitoring database, wherein the directional control targets include flow stability control, pressure fluctuation suppression, energy efficiency optimization, and temperature anomaly warning; Determining a target classification identifier among the directional control targets, wherein the target classification identifier includes a primary control target, an auxiliary control target, and a maintained target; After selecting key control parameters using the main control objectives and auxiliary control objectives, performing directional control objective impact analysis of the key control parameters; After establishing parameter control constraints according to the directional control target impact analysis results, parameter directional control is performed, and the parameter directional control results are used to complete the directional optimization of the circulation pump control parameters.

[0009] Preferably, after selecting key control parameters using the primary control objective and the auxiliary control objective, performing directional control objective impact analysis of the key control parameters includes: Get the set of adjustable parameters of the circulation pump; Performing quantitative mapping of the influence of the adjustable parameter set on the main control target and the auxiliary control target; Constructing a target impact matrix of all control targets in the directional control target, wherein the target impact matrix represents the mutual relationships between different control targets, and the mutual relationships include positive promotion relationships and negative conflict relationships; Calculating sensitivity coefficients of the adjustable parameter set based on the impact degree quantification mapping and the target impact matrix; A directional control target impact analysis result is established based on the sensitivity coefficient calculation result.

[0010] Preferably, the execution parameter directional control includes: After establishing the adjustment range of the parameters, an initial solution set is created based on the current operating parameter set; After executing the fitness evaluation of the solutions in the initial solution set, establishing the control direction and the control step size according to the parameter control constraints and the fitness evaluation results; Iteratively updating the initial solution set using the control direction and the control step size; Parameter-oriented control is completed according to the iterative update result.

[0011] Preferably, the iterative update of the initial solution set using the control direction and the control step size includes: Establish an iterative trajectory for each solution, and identify the iterative trajectory through the solution fitness value of each iteration; Configuring an iterative evaluation interval, performing update state identification of the iterative trajectory in the iterative evaluation interval, and generating an evaluation classification, wherein the evaluation classification includes an excellent control evaluation classification, an exploration evaluation classification, and a poor control evaluation classification; Search self-optimization management is performed with iterative updates based on the evaluation classification.

[0012] Preferably, the search self-optimization management that is iteratively updated according to the evaluation classification includes: Configuring a local prediction model in the optimal control evaluation classification, using the local prediction model to perform improvement trend prediction, and generating a first reference control direction; A penalty control identification layer is configured in the poor control evaluation classification, and the penalty control identification layer is used to identify the wrong improvement direction and establish a window improvement taboo; The first reference control direction and window improvement taboo are used to perform iterative fine-tuning updates on the solutions within the superior control evaluation category. The first reference control direction and window improvement taboo are used to perform mixed exploration iterative updates on the exploration evaluation category. Random factors are configured to perform iterative updates on the solutions within the inferior control evaluation category.

[0013] Preferably, the execution parameter directional control further includes: Establishing parameter energy consumption evaluation function; Establishing a balance performance function based on the energy consumption evaluation function and the performance evaluation function; A control scheme screening for parameter-oriented control is performed based on the balance performance function, and the control scheme screening result is output as a parameter-oriented control result.

[0014] Preferably, the monitoring indicators of the operation status monitoring database include flow deviation rate, flow distribution uniformity, pressure fluctuation amplitude, pressure standard deviation, energy efficiency value, temperature anomaly frequency, and temperature distribution range.

[0015] Preferably, the present invention further includes a circulation pump control system for implementing the above-mentioned circulation pump control method, the system comprising: A parameter acquisition module is used to obtain the current operating parameter set of the circulation pump and establish a circulation pump operating status monitoring database mapped to the current operating parameter set; A target configuration module, configured to configure directional control targets according to the operation status monitoring database, wherein the directional control targets include flow stability control, pressure fluctuation suppression, energy efficiency optimization, and temperature anomaly warning; A classification identification module, configured to determine a target classification identification in the directional control target, wherein the target classification identification includes a main control target, an auxiliary control target, and a hold target; An impact analysis module, configured to perform a directional control target impact analysis of the key control parameters after selecting the key control parameters using the primary control target and the auxiliary control target; The directional control module is used to establish parameter control constraints according to the directional control target impact analysis results, perform parameter directional control, and use the parameter directional control results to complete the directional optimization of the circulation pump control parameters.

[0016] Preferably, the impact analysis module includes: An adjustable parameter acquisition unit, used to acquire an adjustable parameter set of a circulation pump; a quantitative mapping unit, configured to perform quantitative mapping of the influence of an adjustable parameter set on the main control target and the auxiliary control target; a matrix construction unit, configured to construct a target impact matrix of all control targets in the directional control target, wherein the target impact matrix represents the mutual relationships between different control targets, wherein the mutual relationships include positive promotion relationships and negative conflict relationships; a coefficient calculation unit, configured to calculate the sensitivity coefficients of the adjustable parameter set according to the influence degree quantization mapping and the target influence matrix; A result establishing unit is used to establish a directional control target impact analysis result according to the sensitivity coefficient calculation result.

[0017] Preferably, the directional control module includes: An interval establishing unit, configured to create an initial solution set based on a current operating parameter set after establishing an adjustment interval of the parameter; An evaluation execution unit, configured to perform fitness evaluation of solutions in the initial solution set and establish a control direction and a control step size based on the parameter control constraints and the fitness evaluation results; an iterative updating unit, configured to iteratively update an initial solution set using the control direction and the control step size; The control completion unit is used to complete parameter-oriented control according to the iterative update result.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The circulation pump control method and control system provided by the present invention can obtain the current operating parameter set of the circulation pump and establish an operating status monitoring database, and configure directional control targets including flow stability control, pressure fluctuation suppression, energy efficiency optimization, temperature anomaly warning, etc. on this basis. By determining the target classification identifier, selecting key control parameters and performing directional control target impact analysis, parameter directional control is executed after establishing parameter control constraints, thereby achieving directional optimization of the circulation pump control parameters.

[0019] In practical applications, this method and system can comprehensively and real-time monitor and analyze the operating parameters of the circulation pump. By using indicators such as flow deviation rate, flow distribution uniformity, pressure fluctuation amplitude, pressure standard deviation, energy efficiency value, temperature anomaly frequency, and temperature distribution range in the operating status monitoring database, the operating status of the circulation pump can be accurately understood.

[0020] In terms of flow stability control, directional control target impact analysis is used to quantitatively map the impact of the adjustable parameter set, construct a target impact matrix, and calculate the sensitivity coefficient. This allows us to accurately determine the key parameters affecting flow stability and perform targeted regulation to enable the flow to reach the target value quickly and stably, reducing flow fluctuations.

[0021] For pressure fluctuation suppression, through a similar analysis and control process, relevant parameters can be adjusted in a timely manner according to the pressure fluctuation situation, effectively suppressing pressure fluctuations, reducing system vibration and noise, and improving system safety and stability.

[0022] In terms of energy efficiency optimization, an energy consumption evaluation function and a balanced performance function of the parameters are established. In the process of parameter-oriented regulation, energy consumption and performance are comprehensively considered to screen out the optimal regulation scheme, so that the circulation pump can reduce energy consumption as much as possible while meeting performance requirements, reduce energy waste and reduce production costs.

[0023] In terms of temperature anomaly warning, by monitoring and analyzing indicators such as temperature anomaly frequency and temperature distribution range, temperature anomalies can be discovered in a timely manner and warnings can be issued in advance so that staff can take timely measures to avoid equipment damage due to temperature anomalies and ensure production continuity.

[0024] In terms of multi-objective collaborative control, by determining the main control objective, auxiliary control objective and maintenance objective, the priority of each objective can be clarified, and the objective impact matrix can be used to analyze the positive promotion relationship and negative conflict relationship between different objectives. In the process of parameter regulation, the needs of each objective are comprehensively considered to find the best balance point and realize multi-objective collaborative optimization control.

[0025] During the parameter control process, the control direction and step size are determined by establishing a control interval, creating an initial solution set, and evaluating the solution fitness, then iteratively updating the initial solution set. During the iterative update process, an iterative trajectory is established for each solution, and the update state is identified through the iterative evaluation interval. Evaluation categories such as optimal control, exploration, and inferior control are generated, and search and self-optimization management are performed based on different evaluation categories. A local prediction model is configured in the optimal control evaluation category to predict improvement trends and generate a first reference control direction. A penalty control identification layer is configured in the inferior control evaluation category to establish window improvement taboos. The first reference control direction and window improvement taboos are used to iteratively update solutions within different evaluation categories, improving the efficiency and accuracy of parameter control, preventing the iterative process from falling into local optimality, and quickly finding the global optimal solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a working principle diagram of the circulating pump control method of the present invention; Figure 2 Flowchart for key control parameter impact analysis; Figure 3 Flowchart for parameter-directed control execution; Figure 4 A flowchart for iterative update management; Figure 5 Flowchart for search self-optimization management. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0028] See also Figure 1-Figure 5 The present invention provides a circulating pump control method, and the specific implementation steps are as follows: Obtain the current operating parameter set of the circulation pump and establish a circulation pump operating status monitoring database mapped to the current operating parameter set. The monitoring indicators of the operating status monitoring database include flow deviation rate, flow distribution uniformity, pressure fluctuation amplitude, pressure standard deviation, energy efficiency value, temperature anomaly frequency, and temperature distribution range.

[0029] Directional control targets are configured according to the operation status monitoring database. The directional control targets include flow stability control, pressure fluctuation suppression, energy efficiency optimization, and temperature anomaly warning.

[0030] Determine the target classification identification in the directional control target, which includes the main control target, auxiliary control target and maintenance target.

[0031] After selecting key control parameters using the primary and secondary control objectives, a directional control objective impact analysis of the key control parameters is performed. Specifically, the adjustable parameter set of the circulating pump is obtained, and the degree of influence of the adjustable parameter set is quantitatively mapped for the primary and secondary control objectives. A target impact matrix for all control objectives in the directional control objective is constructed. This target impact matrix characterizes the relationships between different control objectives, including positive promotion relationships and negative conflict relationships. Based on the quantitative impact mapping and the target impact matrix, the sensitivity coefficients of the adjustable parameter set are calculated, and the directional control objective impact analysis results are established based on the sensitivity coefficient calculation results.

[0032] After establishing parameter control constraints based on the results of the directional control objective impact analysis, parameter-directed control is executed, and the results of parameter-directed control are used to complete the directed optimization of the circulating pump control parameters. During parameter-directed control, an energy consumption evaluation function is established for the parameters. Based on the energy consumption evaluation function and the performance evaluation function, a balance performance function is established. Control schemes for parameter-directed control are screened based on the balance performance function, and the results of the control scheme screening are output as the parameter-directed control results. Simultaneously, after establishing the parameter adjustment range, an initial solution set is created based on the current operating parameter set. After evaluating the solution fitness within the initial solution set, the control direction and control step are determined based on the parameter control constraints and the fitness evaluation results. The initial solution set is iteratively updated using the control direction and control step. Parameter-directed control is then completed based on the iterative update results. During the iterative update of the initial solution set using the control direction and control step, an iteration trajectory is established for each solution, and the trajectory is identified by the solution fitness value of each iteration. An iterative evaluation interval is configured, and the update status of the iterative trajectory is identified within the iterative evaluation interval. Evaluation categories are generated, including optimal control evaluation category, exploration evaluation category, and inferior control evaluation category. Search self-optimization management for iterative updates is performed based on the evaluation categories. During the search self-optimization management that is iteratively updated according to the evaluation classification, a local prediction model is configured in the superior control evaluation classification, and the improvement trend is predicted by using the local prediction model to generate a first reference control direction. A penalty control identification layer is configured in the inferior control evaluation classification, and the erroneous improvement direction is identified by using the penalty control identification layer. A window improvement taboo is established, and the first reference control direction and the window improvement taboo are used to iteratively fine-tune the solution within the superior control evaluation classification. The first reference control direction and the window improvement taboo are used to iteratively update the mixed exploration evaluation classification, and random factors are configured to perform iterative updates of the solution within the inferior control evaluation classification.

[0033] Example 1: After obtaining the current operating parameter set of the circulation pump and establishing the operating status monitoring database, it is necessary to configure and classify the directional control targets. First, extract the various monitoring indicator data from the operating status monitoring database. These data cover flow deviation rate, flow distribution uniformity, pressure fluctuation amplitude, pressure standard deviation, energy efficiency value, temperature anomaly frequency, temperature distribution range, etc. For example, when the flow deviation rate exceeds the pre-set threshold, it is necessary to combine the flow distribution uniformity data in the database to determine whether there is a problem with flow stability. If the flow distribution uniformity also deviates from the normal range, flow stability control needs to be used as the main control target.

[0034] After determining the main control target, it is necessary to further determine the auxiliary control target and the maintenance target. Taking pressure fluctuation suppression as an example, if the fluctuation range of the extracted pressure fluctuation amplitude data is large and the pressure standard deviation also exceeds the normal range, this may affect the flow stability. At this time, pressure fluctuation suppression can be set as an auxiliary control target. Energy efficiency optimization and temperature anomaly warning need to be judged as maintenance targets based on actual monitoring data. For example, when the energy efficiency value is within the normal range, the frequency of temperature anomalies is low, and the temperature distribution range is also within a reasonable range, these two targets can be set as maintenance targets, that is, during the control process, their current status needs to be maintained without significant deterioration.

[0035] When determining target classification and identification, the importance of each target and their interrelationships must be comprehensively considered. The primary control target is the issue that needs to be addressed immediately, and its resolution plays a key role in the normal operation of the circulation pump. Auxiliary control targets support the achievement of the primary control target, and there may be a positive correlation between the two. For example, proper suppression of pressure fluctuations can help improve flow stability. Maintenance targets are targets that need to be maintained within a certain range during the control process. Although they are not the current priority, they cannot deviate significantly to avoid affecting the overall operation of the circulation pump.

[0036] After determining the main control objective and auxiliary control objective, these two types of objectives need to be used to select key control parameters. Obtain the set of adjustable parameters of the circulation pump, which usually includes speed, valve opening, inlet pressure adjustment parameters, etc. Quantify the degree of influence of the adjustable parameter set on the main control objective and auxiliary control objective. This process requires analyzing the impact of each adjustable parameter on the main control objective and auxiliary control objective. For example, for the main control objective of flow stability control, analyze the impact of changes in speed on the flow deviation rate and flow distribution uniformity. Through certain quantitative methods, such as establishing a graded classification of the degree of influence, determine the degree of influence of the speed on this objective. Similarly, analyze the degree of influence of other adjustable parameters such as valve opening.

[0037] After completing the quantitative mapping of the degree of influence, it is necessary to construct a target impact matrix for all control objectives in the directional control objective. This matrix is ​​used to characterize the relationships between different control objectives, which include positive promotion relationships and negative conflict relationships. Taking flow stability control and pressure fluctuation suppression as an example, if improving flow stability can lead to a reduction in pressure fluctuations, then there is a positive promotion relationship between the two objectives; however, there may be a negative conflict relationship between flow stability control and energy efficiency optimization. For example, in order to improve flow stability, it may be necessary to increase the speed, which will lead to an increase in energy consumption.

[0038] After constructing the target impact matrix, the sensitivity coefficients for the set of adjustable parameters are calculated based on the previously obtained impact quantification mapping and the target impact matrix. The sensitivity coefficients reflect the sensitivity of each adjustable parameter to each control objective, that is, the degree to which a small change in the parameter affects the control objective. By calculating the sensitivity coefficients, we can determine which parameters are critical control parameters, i.e., those that have the greatest impact on the primary and secondary control objectives.

[0039] Based on the calculated sensitivity coefficients, a directional control objective impact analysis is developed. This analysis details the impact of each key control parameter on different control objectives, as well as the interactions between control objectives, providing an important basis for subsequent parameter adjustments. When developing the analysis results, comprehensive and accurate presentation of all data and analysis conclusions is required to ensure that subsequent parameter adjustments can be carried out in a targeted manner, thereby achieving effective control of the circulating pump's operating status.

[0040] Example 2: After completing the targeted control objective impact analysis of key control parameters, the targeted parameter control phase begins. Parameter adjustment ranges are established, based on the mechanical performance limitations, safe operating specifications, and process requirements of the circulating pump. For example, the circulating pump's speed adjustment range must consider physical constraints such as the motor's rated speed and the bearing's tolerance limit. The valve opening adjustment range must be based on the pipeline pressure level and fluid delivery process requirements to ensure that parameter adjustments remain within a safe and controllable range.

[0041] When creating an initial solution set based on the current operating parameter set, the range of the parameter adjustment range and the control objective requirements must be comprehensively considered. This initial solution set can be generated by uniformly sampling within the parameter adjustment range or by filtering out parameter combinations that have performed well in historical operating data to form a set containing multiple parameter combinations. Each parameter combination corresponds to a set of possible control parameter values, such as specific combinations of speed, valve opening, inlet pressure, and other parameters. These combinations form the basis for subsequent optimization.

[0042] After the initial solution set is generated, the fitness evaluation of the solutions within the initial solution set is performed. During the evaluation process, specific evaluation criteria need to be set based on the directional control objectives. For situations where flow stability control is the main control objective, the evaluation criteria may include whether the flow deviation rate is within the allowable range and whether the flow distribution uniformity meets the set requirements; for situations where pressure fluctuation suppression is an auxiliary control objective, it is also necessary to consider whether the pressure fluctuation amplitude and pressure standard deviation meet expectations. By substituting each parameter combination into the operating model or actual operating scenario of the circulating pump for simulation or testing, the corresponding operating parameters are obtained and compared with the evaluation criteria to determine the fitness value of each solution, which reflects the degree to which the parameter combination satisfies the control objective.

[0043] After obtaining the solution fitness evaluation results, the control direction and control step are established in combination with the parameter control constraints. Parameter control constraints come from multiple aspects, including the physical limitations of the equipment, process safety requirements, and the parameter interaction relationships determined in the previously established directional control objective impact analysis results. For example, when the adjustment of a certain parameter will have a significant negative conflict with other control objectives, the adjustment amplitude and direction of the parameter need to be restricted in the control constraints. The determination of the control direction is based on the fitness evaluation results. For solutions with higher fitness, fine-tuning may be performed along the current direction to seek a better solution; for solutions with lower fitness, the parameter adjustment direction needs to be adjusted. The setting of the control step size needs to take into account both optimization efficiency and stability. A step size that is too small may lead to a slow optimization process, and a step size that is too large may skip the optimal solution. Therefore, it needs to be reasonably set according to the sensitivity of the parameters and the requirements of the control objectives.

[0044] The initial solution set is iteratively updated using the determined control direction and control step size. During the iteration process, an iterative trajectory is established for each solution, recording the parameter values ​​and corresponding fitness values ​​of the solution in each iteration, forming a complete trajectory curve. The iterative trajectory is marked by the solution fitness value of each iteration, for example, using different colors or symbols to mark the fitness values ​​of different iteration rounds, so that the optimization trend of the solution can be intuitively observed.

[0045] Configuring the iterative evaluation interval is a crucial step in the iterative update process. The length of this interval is determined based on the parameter adjustment range and optimization accuracy requirements; for example, it can be set to five or ten consecutive iterations. Within the iterative evaluation interval, the update status of the iterative trajectory is identified, and evaluation categories are generated by analyzing features such as the trajectory's direction, the magnitude of fitness value changes, and trends. These categories primarily include optimal control evaluation, exploration evaluation, and inferior control evaluation. Solutions classified as optimal control have consistently improved and stabilized fitness values ​​during the iteration process, indicating that the current control direction and step size are effective. Solutions classified as exploration have fluctuating fitness values ​​that show little change, suggesting that the control strategy may need to be adjusted to explore a more optimal solution space. Solutions classified as inferior control have declining or stagnant fitness values, indicating that the current control direction or step size is problematic and requires correction.

[0046] Example 3: After the evaluation classification is generated, iteratively updated search self-optimization management is required for different evaluation classifications. For the solutions in the optimal control evaluation classification, since their fitness values ​​continue to increase and stabilize during the iteration process, indicating that the current control direction and strategy are relatively effective, a local prediction model is configured at this time. This model is based on the historical iteration trajectory data of the solutions in the optimal control evaluation classification, including the parameter values, fitness values, control direction and step size of each round. By analyzing the changing trends of these data, it predicts future improvement trends. For example, if historical data shows that in a certain parameter dimension, as the parameter value gradually increases, the fitness value shows a regular increase, the local prediction model can predict the possible optimal adjustment direction of the parameter based on this trend and generate the first reference control direction.

[0047] For solutions in the poor control evaluation category, if their fitness values ​​decrease or stagnate, this indicates a problem with the current control direction or step size, and a penalty control identification layer is required. This identification layer analyzes the iterative trajectories of solutions within the poor control evaluation category to identify the specific control direction that caused the fitness value to deteriorate, namely the incorrect improvement direction. For example, if a solution increases the speed parameter in a certain iteration, causing a significant decrease in the fitness value, the penalty control identification layer will mark the control direction of "increasing the speed" as an incorrect improvement direction and establish a window improvement taboo. The window improvement taboo specifies a range of iterations in which control in this incorrect direction is prohibited. For example, the incorrect improvement direction is prohibited from being used again in the next five iterations to prevent the recurrence of poor control.

[0048] After completing the configuration of the local prediction model and the penalty control identification layer, the iterative update operation of the solutions within different evaluation categories begins. For the solutions within the optimal control evaluation category, the solution fine-tuning iterative update is performed based on the first reference control direction and the window improvement taboo. Specifically, according to the reference direction generated by the local prediction model, small parameter adjustments are made near the current solution. The adjustment amplitude needs to be determined in combination with the sensitivity of the parameters and the control step size. At the same time, the control direction prohibited by the window improvement taboo is strictly avoided to ensure that the fine-tuning process is carried out within an effective and safe range. For example, if the first reference control direction indicates that the valve opening needs to be slightly increased, and there is no relevant prohibition in the window improvement taboo, then a smaller step value is added to the current valve opening to form a new parameter combination, and its fitness value is calculated to determine whether it is further optimized.

[0049] For the solutions in the exploration and evaluation classification, hybrid exploration and iterative updates are also performed based on the first reference control direction and the window improvement taboo. The fitness values ​​of the solutions in the exploration and evaluation classification fluctuate less and are in the exploration stage. Potential optimal solutions need to be found in a larger solution space. At this time, a variety of exploration strategies are adopted, combining the possible optimization directions indicated by the first reference control direction while avoiding the wrong directions in the window improvement taboo. For example, on the basis of the reference direction, a certain amount of random perturbation is added to expand the parameter search range; or, in combination with other possible control directions, multi-directional exploration attempts are made to discover new potential optimal solution areas.

[0050] For solutions in the poor control evaluation category, a random factor is configured to perform iterative updates. Because the current control strategy for these solutions is ineffective, the introduction of a random factor is necessary to break the current poor state. The range of the random factor's value must take into account the parameter adjustment range and control step size, generating random control directions and step sizes within the permitted range. For example, a new set of parameter values ​​within the parameter adjustment range is randomly generated as the solution for the next iteration, thereby exploring new solution spaces and hoping to find parameter combinations that improve fitness.

[0051] Throughout the entire search self-optimization management process, it is necessary to continuously monitor the iterative updates of solutions within each evaluation category. Based on the changes in the solution's fitness value and the characteristics of the iterative trajectory, timely adjustments should be made to the parameters of the local prediction model, the range of window improvement taboos, and the value strategy of the random factor. For example, when the fitness value of the solution in the optimal control evaluation category slows down, the prediction parameters of the local prediction model can be adjusted to more accurately capture the improvement trend. When the solution in the inferior control evaluation category shows signs of improving fitness value after random updates, the value range of the random factor can be narrowed to gradually guide it towards optimal control.

[0052] Furthermore, different evaluation categories are not completely independent; as iterations proceed, solutions may shift between them. For example, a solution in the exploration evaluation category, after effective hybrid exploration, may see its fitness continuously improve and be transferred to the optimal control evaluation category. However, if a solution in the optimal control evaluation category experiences a decrease in fitness in subsequent iterations, it may be reclassified as an inferior control evaluation category. Therefore, dynamic adjustments to the management strategy for each solution are necessary to ensure the effectiveness and relevance of search self-optimization management.

[0053] Through this differentiated search self-optimization management method for different evaluation categories, we can fully utilize the optimization trend of the optimal control solution, effectively correct the error direction of the inferior control solution, and actively explore new solution spaces, thereby improving the efficiency and accuracy of the entire iterative update process, accelerating the optimization process of the circulation pump control parameters, and making it approach the optimal solution that meets the directional control objectives more quickly and accurately.

[0054] Example 4: When performing parameter-oriented control, it is necessary to establish an energy consumption evaluation function and a performance evaluation function, and to construct a balanced performance function based on the two to achieve comprehensive optimization of energy consumption and performance. First, establish a parameter energy consumption evaluation function. This function is used to quantify the energy consumption level of the circulating pump under different parameter combinations, and its construction needs to consider key parameters related to energy consumption. The energy consumption evaluation function The specific definition is ,in is the real-time input power of the circulation pump, t is the running time, and this function directly quantifies the total energy consumption of the circulation pump under a specific parameter combination by multiplying the input power by the running time. There is a mapping relationship with the adjustable parameters of the circulation pump, which can be expressed as ,in is the circulating pump speed, is the valve opening, It is a power calculation function determined based on the operating characteristics of the circulating pump. Its logic is: when the speed n increases or the valve opening When the adjustment causes the fluid resistance to change, the input power Corresponding changes, for example, within the rated operating range, the speed n and the input power P are approximately in a cubic relationship, that is, , valve opening The increase of will reduce the pipe resistance within a certain range, thus making the input power The real-time input power The specific calculation is based on the characteristic curve of the circulating pump and the fitting of experimental data, for example, by collecting the circulating pump at different speeds n (unit: r / min) and valve openings The measured power value under (unit: %) is fitted by the least square method to obtain the mapping relationship between P and n, k, as shown in , where α, β, and γ are fitting coefficients, which are determined by the model of the circulating pump and the characteristics of the pipeline. Taking a certain model of circulating pump as an example, after fitting 100 sets of experimental data, α=0.0001, β=-0.2, and γ=50. At this time, when n=1500r / min and k=50%, P=0.0001×1500³+(-0.2)×50+50=3375-10+50=3415W. The deviation between the calculated value and the measured value is controlled within 5%, ensuring the accuracy of P calculation. Finally, through The calculation of energy consumption can achieve quantitative comparison of energy consumption levels under different parameter combinations.

[0055] Next, a performance evaluation function is established. This function is used to measure whether the operating performance of the circulating pump under a specific parameter combination meets the directional control target. It contains evaluation indicators related to each control target. Taking flow stability control and pressure fluctuation suppression as an example, the performance evaluation function The specific form is ,in They are the preset maximum allowable flow deviation rate, ideal flow distribution uniformity (usually taken as 100%), maximum allowable pressure fluctuation amplitude, and maximum allowable pressure standard deviation; is the weight coefficient of each indicator and the sum is 1. This function maps each performance indicator to the [0,1] interval through normalization processing, where the flow deviation rate, pressure fluctuation amplitude, and pressure standard deviation adopt the "1-actual value / maximum value" format (the larger the value, the better), and the flow distribution uniformity adopts the "actual value / ideal value" format (the larger the value, the better). Through weighted summation, a comprehensive quantitative evaluation of the operating performance is achieved. The specific calculation is =|actual flow - target flow| / target flow×100%; flow distribution uniformity The specific calculation is = Standard deviation of flow at each monitoring point / average flow × 100% (the smaller the value, the more uniform it is. When normalizing, take 1- / ); Pressure fluctuation amplitude The difference between the maximum and minimum values ​​in the pressure monitoring data; the pressure standard deviation is the statistical standard deviation of the pressure monitoring data. Weight coefficient Determined by the AHP, for example, in a scenario where traffic stability is the main goal, 、 =0.3, =0.2, =0.1, ensuring that the weight of each indicator matches the priority of the control objective.

[0056] After establishing the energy consumption evaluation function and the performance evaluation function, a balanced performance function is established based on the two. The construction of the balanced performance function needs to consider the trade-off between energy consumption and performance, and a comprehensive evaluation of the two is achieved by introducing a weight coefficient. Let the balanced performance function be:

[0057] in, To balance the performance values, it is used to comprehensively evaluate the advantages and disadvantages of parameter combinations; is the energy consumption weight coefficient, and its value range is , its size reflects the importance of energy consumption in the comprehensive evaluation; is the minimum value of the energy consumption evaluation function, that is, the lowest energy consumption that the circulation pump can achieve in theory; is the maximum value of the performance evaluation function, that is, the ideal state of the circulating pump's operating performance.

[0058] The meaning of each character in the formula is as follows: : Balanced performance value is an evaluation index that comprehensively considers energy consumption and performance. The larger the value, the better the comprehensive performance of the parameter combination in terms of energy consumption and performance.

[0059] : Energy consumption weight coefficient, determined by the importance of energy consumption in actual application scenarios. When it approaches 1, it means that more attention is paid to energy consumption optimization; when When it approaches 0, it focuses more on performance improvement.

[0060] : The minimum value of the energy consumption evaluation function represents the lowest energy consumption level that the circulation pump can reach under specific operating conditions. This value is determined by the equipment characteristics and operating parameter range of the circulation pump.

[0061] : Energy consumption evaluation value under the current parameter combination, through the energy consumption evaluation function The calculation shows the energy consumption of the circulation pump under this parameter combination.

[0062] : The performance evaluation value under the current parameter combination is determined by the performance evaluation function Determined, it reflects the operating performance of the circulating pump under this parameter combination.

[0063] : The maximum value of the performance evaluation function is the ideal target of the circulating pump operation performance, which depends on the requirements of the directional control target for various performance indicators.

[0064] When screening the control scheme for parameter-oriented control based on the balance performance function, first obtain the corresponding energy consumption evaluation value for each possible control scheme. and performance evaluation values Then, these values ​​are substituted into the balance performance function to calculate the corresponding balance performance value By comparing the balance performance values ​​of different control schemes , sort the control schemes. Prioritize the balanced performance value Larger control schemes are preferred because these schemes achieve a better balance between energy consumption and performance and are more in line with the requirements of directional control objectives.

[0065] For example, for a certain control scheme A, the energy consumption evaluation value is calculated Higher, but performance evaluation value The energy consumption evaluation value of control scheme B is also higher. Low, but performance evaluation value After calculation through the balance performance function, if the balance performance value of scheme A is Greater than the balance performance value of option B , then it means that the current energy consumption weight coefficient Under these conditions, Scheme A has better overall performance and should be preferred as the result of parameter-oriented regulation.

[0066] In practical applications, the energy consumption weight coefficient It can be adjusted according to different operating scenarios and needs. For example, in scenarios with high energy consumption requirements, Set it to a larger value to highlight the importance of energy consumption optimization; in scenarios with more stringent requirements on operating performance, it can be appropriately reduced. value to focus more on performance improvement.

[0067] During the entire application process of the balanced performance function, the accuracy of the energy consumption evaluation function and the performance evaluation function must be ensured. This requires that when establishing the function, the actual operating characteristics of the circulation pump and the relationship between various parameters must be fully considered. Specifically, the function parameters are calibrated through multiple sets of experimental data. For example, for the energy consumption evaluation function, the input power and operating time of the circulation pump under different operating conditions such as rated operating conditions, 50% load, and 80% load are collected, the function calculation value is compared with the measured energy consumption, and the fitting coefficients α, β, and γ are corrected to control the error within 5%; the second is to introduce a real-time feedback mechanism, by installing high-precision power sensors, electromagnetic flow meters and other equipment, continuously collecting operating data, and updating the function parameters once a month to ensure that it matches the actual situation such as equipment aging and pipeline resistance changes; the third is the threshold value of each indicator in the performance evaluation function (such as ) needs to be set according to industry standards and actual system requirements, such as in the heating system Set to 5%, and in industrial cooling systems The threshold is set to 3%, and the rationality of the threshold is verified through on-site debugging. Taking a heating circulation pump system as an example, through three consecutive months of operation data monitoring, it is found that the weight of the pressure fluctuation amplitude in the performance evaluation function The function's accuracy in evaluating system performance increased from 82% to 95% after adjusting from 0.2 to 0.25 to reflect the importance of pressure stability in actual operation. Through appropriate modeling and data collection methods, the function was ensured to accurately reflect the energy consumption and performance of the circulation pump. Furthermore, when selecting control options, all possible parameter combinations must be considered to avoid missing a potential optimal solution.

[0068] By screening control options through a balanced performance function and outputting the screening results as parameter-oriented control results, targeted optimization of the circulation pump's control parameters can be achieved. This optimization method not only considers the circulation pump's operating performance, ensuring that it meets targeted control objectives such as flow stability control and pressure fluctuation suppression, but also takes into account energy efficiency, minimizing energy consumption while ensuring performance, thereby improving the operating economy and reliability of the circulation pump.

[0069] Example 5: During the implementation of the circulating pump control method, the various modules of the circulating pump control system work together to achieve precise control of the circulating pump. Taking the circulating pump in an industrial cooling system as an example, the parameter acquisition module collects the circulating pump's current operating parameters in real time, including speed, flow rate, pressure, energy consumption, and temperature. This module continuously acquires real-time operating data from various sensors installed on the circulating pump and pipeline, such as flow sensors, pressure sensors, and temperature sensors. For example, the flow sensor monitors the fluid flow in the pipeline in real time and transmits this flow data to the parameter acquisition module; the pressure sensor measures the pressure at the pump inlet and outlet in real time, generating pressure data. After acquiring this data, the parameter acquisition module establishes a circulating pump operating status monitoring database mapped to the current operating parameter set. The module stores collected monitoring indicators such as flow deviation rate, flow distribution uniformity, pressure fluctuation amplitude, pressure standard deviation, energy efficiency value, temperature anomaly frequency, and temperature distribution range in the database, providing data support for subsequent control target configuration.

[0070] The target configuration module configures the directional control target based on the data in the operation status monitoring database. Assume that it is found from the analysis of the database that the flow deviation rate exceeds the preset normal range in a certain period of time, and the flow distribution uniformity has also decreased significantly, resulting in poor cooling effect of the cooling system. At this time, the target configuration module determines the flow stability control as the current main control target. Further analysis of the pressure fluctuation amplitude and pressure standard deviation data shows that the pressure fluctuation is large, which may affect the flow stability, so the pressure fluctuation suppression is set as the auxiliary control target. When the energy efficiency value is within the normal range, the temperature anomaly frequency is low and the temperature distribution range is within a reasonable range, the target configuration module sets the energy efficiency optimization and temperature anomaly warning as maintenance targets, that is, to maintain these targets without significant deterioration during the control process.

[0071] The classification and identification module classifies and identifies directional control objectives. In the above example, flow stability control, as the primary control objective, is a key issue that needs to be addressed first. Its resolution directly affects the normal operation of the cooling system. Pressure fluctuation suppression, as a secondary control objective, supports the achievement of the primary control objective. There is a positive correlation between the two, and effective suppression of pressure fluctuations helps improve flow stability. Energy efficiency optimization and temperature anomaly warning are maintenance objectives, which must be maintained within a certain range during the control process to avoid significant deviations.

[0072] The impact analysis module begins operation by first obtaining the circulating pump's adjustable parameter set, which includes parameters such as speed and valve opening, through the adjustable parameter acquisition unit. Taking speed as an example, the adjustable parameter acquisition unit specifies that the adjustable speed range is determined based on the motor's rated speed and the equipment's safety limits. The quantitative mapping unit quantitatively maps the impact of the adjustable parameter set on the primary control objective (flow stability control) and the auxiliary control objective (pressure fluctuation suppression). The module analyzes the impact of speed changes on the flow deviation rate and flow distribution uniformity. For example, when the speed increases, the flow rate may increase accordingly. Based on historical data and operating experience, the speed's impact on the flow deviation rate is determined to be high, while its impact on flow distribution uniformity is determined to be medium. Furthermore, the module analyzes the speed's impact on the pressure fluctuation amplitude and pressure standard deviation to determine its impact on pressure fluctuation suppression.

[0073] The matrix construction unit constructs a target impact matrix for all control objectives within the directional control objective and analyzes the interrelationships between flow stability control, pressure fluctuation suppression, energy efficiency optimization, and temperature anomaly warning. For example, flow stability control and pressure fluctuation suppression have a positive promoting relationship, with flow stability contributing to reduced pressure fluctuations. On the other hand, flow stability control and energy efficiency optimization may have a negative conflicting relationship, meaning that improving flow stability may require increasing the speed, leading to increased energy consumption. The coefficient calculation unit calculates the sensitivity coefficients of the adjustable parameter set based on the impact quantification mapping and the target impact matrix, determining the sensitivity of parameters such as speed and valve opening to each control objective. For example, the high sensitivity coefficient of speed to flow stability control means that even a small change in speed can have a significant impact on flow stability. The result generation unit then generates the directional control objective impact analysis results based on the sensitivity coefficient calculations, clarifying the impact of each key control parameter on different control objectives and the interactions between these control objectives, providing a basis for subsequent parameter adjustment.

[0074] The directional control module performs directional parameter control. The interval establishment unit establishes parameter adjustment ranges based on the mechanical performance limitations and process requirements of the circulating pump. For example, the speed adjustment range is 60%-100% of the rated speed, and the valve opening adjustment range is 0-100%. Based on the current operating parameter set, such as the current speed is 75% of the rated speed and the valve opening is 80%, an initial solution set is created. This solution set contains multiple parameter combinations within the parameter adjustment range, such as (speed 70%, valve opening 85%), (speed 80%, valve opening 75%), and so on.

[0075] The evaluation execution unit evaluates the fitness of the solutions within the initial solution set, evaluating each parameter combination based on the evaluation criteria set by the directional control objective, such as a flow deviation rate of less than 5%, flow distribution uniformity greater than 90%, and pressure fluctuation amplitude less than 0.2 MPa. For example, for a parameter combination (speed 70%, valve opening 85%), data such as flow deviation rate, flow distribution uniformity, and pressure fluctuation amplitude are obtained through simulation or actual testing and compared with the evaluation criteria to determine its fitness value. The control direction and control step size are established based on the parameter control constraints and fitness evaluation results. For example, if the flow deviation rate of a parameter combination is 6%, exceeding the standard, the speed needs to be increased to reduce the flow deviation rate. The control direction is to increase the speed, and the control step size is determined to be 2% of the rated speed based on the speed sensitivity.

[0076] The iterative update unit uses the control direction and control step size to iteratively update the initial solution set. An iterative trajectory is established for each solution, and the parameter values ​​and fitness values ​​of each iteration are recorded. For example, the speed of the first iteration is 70%, and the fitness value is 0.8; the speed of the second iteration is 72%, and the fitness value is 0.85, etc. The iterative trajectory is identified by the solution fitness value of each iteration to observe the optimization trend of the solution. An iterative evaluation interval is configured, such as 5 consecutive iterations. The update state of the iterative trajectory is identified within this interval to generate an evaluation classification. If the fitness value of a solution continues to improve during the iteration process, it is classified as an excellent control evaluation category; if the fitness value fluctuates slightly, it is classified as an exploration evaluation category; if the fitness value decreases, it is classified as an inferior control evaluation category.

[0077] The control completion unit completes the parameter directional control according to the iterative update results. During the iteration process, search self-optimization management is performed for different evaluation categories. For example, in the excellent control evaluation category, a local prediction model is configured to predict the improvement trend, generate a reference control direction, and perform solution fine-tuning iterative updates; in the inferior control evaluation category, a penalty control identification layer is configured to identify the wrong improvement direction, establish window improvement taboos, and avoid poor control. After multiple iterations, when the fitness value of the solution meets the set requirements, such as the flow deviation rate is less than 5%, the flow distribution uniformity is greater than 90%, and the pressure fluctuation amplitude is less than 0.2MPa, the final parameter control result is determined, such as the speed is 78% and the valve opening is 82%. The result is applied to the actual operation of the circulation pump to achieve directional optimization of the circulation pump control parameters, so that the circulation pump can operate stably under this parameter combination to meet the needs of the industrial cooling system.

[0078] During the operation of the entire control system, data exchange and collaboration are constantly taking place between the various modules. The parameter acquisition module continuously provides real-time operating data to the target configuration module, impact analysis module, and directional control module. The target configuration module and classification identification module determine the control target and classification based on the data, providing an analysis basis for the impact analysis module. The analysis results of the impact analysis module guide the directional control module to perform parameter adjustment. The adjustment results of the directional control module are then fed back to the system through the parameter acquisition module, forming a closed-loop control process, ensuring that the circulation pump always operates under the optimal parameter combination, achieving goals such as flow stability control, pressure fluctuation suppression, energy efficiency optimization, and temperature anomaly warning, thereby ensuring the stable and efficient operation of the system where the circulation pump is located.

[0079] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0080] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A circulating pump control method, characterized in that: The method comprises: Obtaining the current operating parameter set of the circulation pump and establishing a circulation pump operating status monitoring database mapped to the current operating parameter set; Configuring directional control targets based on the operation status monitoring database, wherein the directional control targets include flow stability control, pressure fluctuation suppression, energy efficiency optimization, and temperature anomaly warning; Determining a target classification identifier among the directional control targets, wherein the target classification identifier includes a primary control target, an auxiliary control target, and a maintained target; After selecting key control parameters using the main control objectives and auxiliary control objectives, performing directional control objective impact analysis of the key control parameters; After establishing parameter control constraints according to the directional control target impact analysis results, parameter directional control is performed, and the parameter directional control results are used to complete the directional optimization of the circulation pump control parameters.

2. A circulating pump control method according to claim 1, characterized in that: After the key control parameters are selected using the main control target and the auxiliary control target, a directional control target impact analysis of the key control parameters is performed, including: Get the set of adjustable parameters of the circulation pump; Performing quantitative mapping of the influence of the adjustable parameter set on the main control target and the auxiliary control target; Constructing a target impact matrix of all control targets in the directional control target, wherein the target impact matrix represents the mutual relationships between different control targets, and the mutual relationships include positive promotion relationships and negative conflict relationships; Calculating sensitivity coefficients of the adjustable parameter set based on the impact degree quantification mapping and the target impact matrix; A directional control target impact analysis result is established based on the sensitivity coefficient calculation result.

3. A circulating pump control method according to claim 2, characterized in that: The execution parameter directional control includes: After establishing the adjustment range of the parameters, an initial solution set is created based on the current operating parameter set; After executing the fitness evaluation of the solutions in the initial solution set, establishing the control direction and the control step size according to the parameter control constraints and the fitness evaluation results; Iteratively updating the initial solution set using the control direction and the control step size; Parameter-oriented control is completed according to the iterative update result.

4. A circulating pump control method according to claim 3, characterized in that: The iterative updating of the initial solution set using the control direction and the control step size includes: Establish an iterative trajectory for each solution, and identify the iterative trajectory through the solution fitness value of each iteration; Configuring an iterative evaluation interval, performing update state identification of the iterative trajectory in the iterative evaluation interval, and generating an evaluation classification, wherein the evaluation classification includes an excellent control evaluation classification, an exploration evaluation classification, and a poor control evaluation classification; Search self-optimization management is performed with iterative updates based on the evaluation classification.

5. A circulating pump control method according to claim 4, characterized in that: The search self-optimization management that is iteratively updated according to the evaluation classification includes: Configuring a local prediction model in the optimal control evaluation classification, using the local prediction model to perform improvement trend prediction, and generating a first reference control direction; A penalty control identification layer is configured in the poor control evaluation classification, and the penalty control identification layer is used to identify the wrong improvement direction and establish a window improvement taboo; The first reference control direction and window improvement taboo are used to perform iterative fine-tuning updates on the solutions within the superior control evaluation category. The first reference control direction and window improvement taboo are used to perform mixed exploration iterative updates on the exploration evaluation category. Random factors are configured to perform iterative updates on the solutions within the inferior control evaluation category.

6. A circulating pump control method according to claim 1, characterized in that: The execution parameter directional control also includes: Establishing parameter energy consumption evaluation function; Establishing a balance performance function based on the energy consumption evaluation function and the performance evaluation function; A control scheme screening for parameter-oriented control is performed based on the balance performance function, and the control scheme screening result is output as a parameter-oriented control result.

7. A circulating pump control method according to claim 1, characterized in that: The monitoring indicators of the operation status monitoring database include flow deviation rate, flow distribution uniformity, pressure fluctuation amplitude, pressure standard deviation, energy efficiency value, temperature anomaly frequency, and temperature distribution range.

8. A circulating pump control system, characterized in that: A system for implementing a circulating pump control method according to any one of claims 1 to 7, comprising: A parameter acquisition module is used to obtain the current operating parameter set of the circulation pump and establish a circulation pump operating status monitoring database mapped to the current operating parameter set; A target configuration module, configured to configure directional control targets according to the operation status monitoring database, wherein the directional control targets include flow stability control, pressure fluctuation suppression, energy efficiency optimization, and temperature anomaly warning; A classification identification module, configured to determine a target classification identification in the directional control target, wherein the target classification identification includes a main control target, an auxiliary control target, and a hold target; An impact analysis module, configured to perform a directional control target impact analysis of the key control parameters after selecting the key control parameters using the primary control target and the auxiliary control target; The directional control module is used to establish parameter control constraints according to the directional control target impact analysis results, perform parameter directional control, and use the parameter directional control results to complete the directional optimization of the circulation pump control parameters.

9. A circulation pump control system according to claim 8, characterized in that: The impact analysis module includes: An adjustable parameter acquisition unit, used to acquire an adjustable parameter set of a circulation pump; a quantitative mapping unit, configured to perform quantitative mapping of the influence of an adjustable parameter set on the main control target and the auxiliary control target; a matrix construction unit, configured to construct a target impact matrix of all control targets in the directional control target, wherein the target impact matrix represents the mutual relationships between different control targets, wherein the mutual relationships include positive promotion relationships and negative conflict relationships; a coefficient calculation unit, configured to calculate the sensitivity coefficients of the adjustable parameter set according to the influence degree quantization mapping and the target influence matrix; A result establishing unit is used to establish a directional control target impact analysis result according to the sensitivity coefficient calculation result.

10. A circulation pump control system according to claim 8, characterized in that: The directional control module includes: An interval establishing unit, configured to create an initial solution set based on a current operating parameter set after establishing an adjustment interval of the parameter; An evaluation execution unit, configured to perform fitness evaluation of solutions in the initial solution set and establish a control direction and a control step size based on the parameter control constraints and the fitness evaluation results; an iterative updating unit, configured to iteratively update an initial solution set using the control direction and the control step size; The control completion unit is used to complete parameter-oriented control according to the iterative update result.

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