Intelligent control method and system for running state of motor of energy-saving water pump

Abstract

The invention discloses an intelligent control method and system for the running state of an energy-saving water pump motor, relates to the technical field of water pump motor control, and aims to solve the problem that preset parameters of a control system are mismatched with actual working conditions due to changes of internal and external physical conditions of the system in modern industrial and municipal water supply systems. The method comprises the steps that pressure response data of a water pump in the operation process are obtained, at least one operation performance index is determined according to the pressure response data, and whether current closed-loop adjustment parameters of a water pump control system are mismatched with the actual hydraulic working condition of the water pump or not is judged according to the at least one operation performance index and a preset ideal operation performance range; when it is judged that mismatch exists, according to a preset parameter adjusting rule, gradual fine adjustment is conducted on the closed-loop adjusting parameters, and the parameter adjusting rule covers the adjusting direction and the adjusting amplitude corresponding to the closed-loop adjusting parameters when different operation performance indexes deviate from the ideal operation performance range.

Description

Technical Field

[0001] This application relates to the field of water pump motor control technology, and in particular to an intelligent control method and system for the operating status of an energy-saving water pump motor. Background Technology

[0002] Modern industrial and municipal water supply systems widely employ intelligent control methods to optimize pump motor operation, achieving energy savings and ensuring stable water supply. These systems typically rely on preset equipment characteristic data and sensor feedback for precise adjustments. However, in complex environments with long-term continuous operation, the internal and external physical conditions of the system undergo slow and continuous changes. These changes may cause the initial settings of the control system to become unsuitable for actual operating conditions, thereby affecting its energy-saving performance and operational reliability. Summary of the Invention

[0003] This application provides an intelligent control method and system for the operating status of an energy-saving water pump motor, aiming to solve the problem that in modern industrial and municipal water supply systems, the intelligent control system for water pump motors suffers from mismatch between preset parameters and actual operating conditions due to changes in internal and external physical conditions during long-term operation, which in turn affects energy-saving performance and operational reliability.

[0004] Firstly, to address the aforementioned technical problems, this invention provides an intelligent control method for the operating status of an energy-saving water pump motor. This method includes: acquiring pressure response data of the water pump during operation, whereby the pressure response data characterizes the dynamic characteristics of the water pump outlet pressure in response to changes in water supply demand; determining at least one operating performance indicator based on the pressure response data, whereby the operating performance indicator quantifies the actual operating quality of the water pump control system; determining whether the current closed-loop adjustment parameters of the water pump control system are mismatched with the actual hydraulic conditions of the water pump based on the at least one operating performance indicator and a preset ideal operating performance range; and when a mismatch is determined, progressively fine-tuning the closed-loop adjustment parameters according to preset parameter adjustment rules, whereby the parameter adjustment rules cover the adjustment direction and magnitude of the corresponding closed-loop adjustment parameters when different operating performance indicators deviate from the ideal operating performance range.

[0005] Secondly, this application provides an intelligent control system for the operating status of an energy-saving water pump motor. The system includes: an acquisition unit for acquiring pressure response data of the water pump during operation, the pressure response data being used to characterize the dynamic characteristics of the water pump outlet pressure in response to changes in water supply demand; a determination unit for determining at least one operating performance indicator based on the pressure response data, the operating performance indicator being used to quantify the actual operating quality of the water pump control system; a judgment unit for determining whether the current closed-loop adjustment parameters of the water pump control system are mismatched with the actual hydraulic conditions of the water pump based on at least one operating performance indicator and a preset ideal operating performance range; and an adjustment unit for progressively fine-tuning the closed-loop adjustment parameters according to preset parameter adjustment rules when a mismatch is determined, the parameter adjustment rules covering the adjustment direction and magnitude of the corresponding closed-loop adjustment parameters when different operating performance indicators deviate from the ideal operating performance range.

[0006] This application has at least the following beneficial effects: The intelligent control method for the operating status of an energy-saving water pump motor disclosed in this application acquires pressure response data during the operation of the water pump and determines operating performance indicators based on this data, enabling real-time and quantitative evaluation of the actual operating quality of the water pump control system. This method further determines whether the current closed-loop adjustment parameters are mismatched with the actual hydraulic conditions of the water pump based on the operating performance indicators and the preset ideal operating performance range. When a mismatch is detected, the closed-loop adjustment parameters are progressively fine-tuned according to preset parameter adjustment rules. This method effectively solves the problem in the prior art where, during long-term operation, the preset parameters of the intelligent control system for the water pump motor gradually deviate from the actual operating conditions due to implicit physical degradation factors such as changes in the properties of the transported liquid, changes in the roughness of the pipe inner wall, and sensor measurement deviations, thus affecting energy-saving effects and operational reliability. By introducing dynamic feature analysis of pressure response data and multi-dimensional operating performance indicator evaluation, this application can accurately identify implicit physical degradation inside and outside the system, overcoming the limitations of traditional systems that rely on fixed parameters and single feedback. The progressive fine-tuning strategy ensures the stability and safety of parameter adjustment, avoiding system instability that may result from aggressive adjustments. Attached Figure Description

[0007] Figure 1 This is a flowchart illustrating an intelligent control method for the operating status of an energy-saving water pump motor provided in this application. Detailed Implementation

[0008] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0009] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0010] Traditional intelligent control systems for water pump motors, during long-term operation, suffer from changes in internal and external physical conditions, such as the properties of the pumped liquid, the roughness of the pipe wall, and hidden physical degradation factors like sensor measurement deviations. This causes the initially set parameters of the control system to become unsuitable for actual operating conditions. Consequently, the system may overshoot, undershoot, or exhibit slow response when maintaining the target flow rate or pressure, leading to unnecessary increases in energy consumption and potentially accelerating hidden wear and tear on related components. Furthermore, existing intelligent control logic cannot effectively identify, diagnose, and adaptively adjust these issues, resulting in energy savings far below expectations.

[0011] In view of the above problems, this application provides an intelligent control method for the operating status of an energy-saving water pump motor. This application obtains pressure response data during the operation of the water pump, determines the operating performance indicators based on these data, and then judges whether the closed-loop regulation parameters are mismatched with the actual hydraulic conditions. When mismatch occurs, it performs progressive fine-tuning, thereby realizing intelligent control of the operating status of the water pump motor. This effectively solves the problems of control parameter mismatch and increased energy consumption caused by changes in operating conditions in the prior art, and improves the energy-saving effect and operational reliability of the system.

[0012] The following specific embodiments will provide a detailed introduction and explanation of the precision fertilization program control method and system for intelligent agricultural equipment provided in this application.

[0013] Reference Figure 1 This application provides an intelligent control method for the operating status of an energy-saving water pump motor, which may include the following steps:

[0014] S1. Obtain pressure response data of the water pump during operation.

[0015] Among them, pressure response data is used to characterize the dynamic characteristics of the water pump outlet pressure in response to changes in water supply demand.

[0016] Specifically, pressure response data can be the dynamic characteristics of the pump outlet pressure in response to changes in water supply demand. This data reflects the responsiveness and stability of the pump control system to external changes. For example, when water supply demand suddenly increases or decreases, the pressure at the pump outlet will change accordingly; the time series data of these changes constitutes pressure response data. This data forms the basis for evaluating the operational quality of the pump control system.

[0017] This application embodiment can employ various methods to acquire pressure response data of the water pump during operation. For example, a high-precision pressure sensor can be installed at the water pump outlet to continuously collect pressure signals at a preset sampling frequency. These pressure signals can be analog signals, which are then converted into digital signals by an analog-to-digital converter to form pressure time-series data. This time-series data can comprehensively record the dynamic changes in the water pump outlet pressure, providing a raw basis for subsequent analysis. As another implementation method, digitized pressure data can also be directly acquired through an existing SCADA (Supervisory Control and Data Acquisition) system, as long as this data can fully characterize the dynamic characteristics of the water pump outlet pressure in response to changes in water supply demand.

[0018] S2. Based on the pressure response data, determine at least one operational performance indicator.

[0019] Among them, the performance indicators are used to quantify the actual operating quality of the water pump control system;

[0020] Specifically, performance indicators can be parameters used to quantify the actual operating quality of a pump control system. These indicators can be extracted from pressure response data, such as pressure overshoot, pressure settling time, and pressure variability. They can intuitively reflect the system's performance during the adjustment process. For example, excessive pressure overshoot may mean that the system response is too aggressive, while excessively long pressure settling time may indicate that the system response is sluggish.

[0021] In determining at least one operational performance indicator based on pressure response data, this application embodiment can extract multiple key indicators from the acquired pressure time series data. For example, the maximum deviation of the actual pressure value from the target pressure setpoint within a preset time period can be calculated and used as a pressure overshoot indicator. This indicator reflects situations where the instantaneous pressure may be too high or too low during the system's adjustment process. The time it takes for the actual pressure value to first stabilize within the first allowable error range of the target pressure setpoint can also be determined and used as a pressure stabilization time indicator. This indicator reflects the speed at which the system stabilizes from response. Furthermore, the dispersion of the pressure time series data can be calculated within a preset time window after the actual pressure value has stabilized within a preset time period and used as a pressure volatility indicator. This indicator reflects the system's stability in a steady state. At least one of these indicators can serve as an operational performance indicator. For example, only the pressure overshoot indicator can be used to evaluate system performance, or both the pressure overshoot indicator and the pressure stabilization time indicator can be used simultaneously.

[0022] S3. Based on at least one performance indicator and the preset ideal performance range, determine whether the current closed-loop regulation parameters of the pump control system are mismatched with the actual hydraulic conditions of the pump.

[0023] In a proportional-integral-derivative (PID) controller, the closed-loop control parameters typically refer to the proportional, integral, and derivative coefficients. These parameters determine how the control system adjusts its output based on error signals to bring the actual output close to the target value. The setting of these parameters is crucial to the performance of the pump control system. The ideal operating performance range refers to the preset allowable intervals between various operating performance indicators that ensure the efficient and stable operation of the pump system. When the actual operating performance indicators exceed this range, it indicates a potential problem with the system.

[0024] In determining whether the current closed-loop control parameters of the pump control system are mismatched with the actual hydraulic conditions of the pump based on at least one performance indicator and a preset ideal performance range, this application requires pre-setting ideal thresholds corresponding to each performance indicator. For example, a maximum allowable pressure overshoot, a maximum allowable pressure stabilization time, and a maximum allowable pressure fluctuation can be set. Over multiple consecutive monitoring cycles, the system continuously checks whether these performance indicators consistently exceed their corresponding ideal thresholds. For instance, if the pressure overshoot indicator exceeds the preset first ideal threshold for three consecutive monitoring cycles, it can be determined that the current closed-loop control parameters are mismatched with the actual hydraulic conditions. This mismatch may be caused by one or more latent physical degradation factors, such as changes in the properties of the transported liquid, changes in the roughness of the pipe wall, and sensor measurement deviations.

[0025] S4. When a mismatch is detected, the closed-loop control parameters are gradually fine-tuned according to the preset parameter adjustment rules.

[0026] Among them, the parameter adjustment rules cover the adjustment direction and adjustment range of the corresponding closed-loop control parameters when different operating performance indicators deviate from the ideal operating performance range.

[0027] Specifically, parameter adjustment rules are pre-defined strategies used to guide the adjustment of closed-loop control parameters. These rules define how to adjust the proportional, integral, and derivative coefficients, including the direction and magnitude of adjustment, when performance indicators deviate from the ideal range.

[0028] In this embodiment, when a mismatch is detected, the closed-loop control parameters are progressively fine-tuned according to preset parameter adjustment rules. These rules are pre-defined and cover the adjustment direction and magnitude of the closed-loop control parameters when different performance indicators deviate from the ideal performance range. For example, when the pressure overshoot indicator continuously exceeds the first ideal threshold, the parameter adjustment rules can specify reducing the current proportional coefficient by a first preset percentage. When the pressure stabilization time indicator continuously exceeds the second ideal threshold, the rules can specify increasing the current integral coefficient by a second preset percentage. When the pressure fluctuation indicator continuously exceeds the third ideal threshold, the rules can specify adjusting the current derivative coefficient, with the adjustment direction and magnitude determined based on the frequency and amplitude of pressure oscillations. This progressive fine-tuning ensures the stability and safety of parameter adjustments, avoiding system instability that may result from large adjustments.

[0029] Understandably, the intelligent control method for the operating status of the energy-saving water pump motor in this application acquires pressure response data of the water pump during operation and determines operating performance indicators based on this data. This allows for the assessment of whether the closed-loop control parameters of the water pump control system are mismatched with the actual hydraulic conditions of the water pump. When a mismatch is identified, the closed-loop control parameters are progressively fine-tuned according to preset parameter adjustment rules. This method effectively solves the problem in existing technologies where the implicit physical degradation caused by long-term water pump operation renders the initial settings of the control system unsuitable for actual operating conditions.

[0030] Compared to existing technologies, the advantages of this application lie in its adaptability and robustness. Existing technologies often employ fixed PID parameters or require periodic manual parameter calibration, which proves inadequate when facing complex and ever-changing real-world operating conditions. This application, however, through progressive fine-tuning of closed-loop control parameters, enables the control system to continuously adapt to changes in the actual hydraulic conditions of the pump, thereby ensuring that the pump motor always operates near its optimal efficiency point and significantly reducing energy consumption. For example, when increased pipe wall roughness leads to increased system resistance, this method can automatically adjust the integral or derivative coefficients by monitoring changes in pressure stabilization time or pressure fluctuation indicators to compensate for this change and maintain stable system operation. This adaptive adjustment mechanism not only improves the system's energy-saving effect but also extends the equipment's service life and reduces maintenance costs.

[0031] In some embodiments, the acquisition of pressure response data of the water pump during operation can be achieved in the following manner: Acquiring pressure response data of the water pump during operation includes: acquiring analog pressure signals at a preset frequency using a pressure sensor installed at the water pump outlet; converting the analog pressure signals into digital pressure signals to obtain pressure time series data; and using the pressure time series data as the pressure response data of the water pump during operation.

[0032] A pressure sensor can be understood as a device that converts pressure changes at the water pump outlet into an electrical signal. This pressure sensor is typically installed on the pipe at the water pump outlet to monitor the pump's operating status in real time. For example, piezoresistive, capacitive, or piezoelectric pressure sensors can be used. The preset frequency refers to the data acquisition time interval, such as 10 or 100 times per second. Its selection should ensure sufficient capture of the dynamic changes in the water pump outlet pressure while avoiding excessive data volume. The pressure analog signal is a continuously changing electrical signal directly output by the pressure sensor, and its amplitude is proportional to the actual pressure value at the water pump outlet. For subsequent digital processing and analysis, this pressure analog signal needs to be converted into a pressure digital signal. This conversion process is usually completed by an analog-to-digital converter (ADC), discretizing the continuous analog signal into a series of digital values. This yields pressure time-series data, a set of discrete pressure values ​​arranged in chronological order, which can completely record the trajectory of the water pump outlet pressure changes over time.

[0033] The solution proposed in this application, by installing a pressure sensor at the water pump outlet, can directly and in real-time sense changes in outlet pressure during pump operation. The pressure sensor converts physical pressure into an electrical signal and acquires it at a preset frequency, ensuring the ability to capture dynamic pressure changes. Subsequently, the acquired analog pressure signal is converted into a digital signal, forming pressure time-series data. This process allows the pressure data to be accurately stored, transmitted, and processed. It is precisely because of this direct, high-frequency digital acquisition method that the acquired pressure response data can accurately and comprehensively characterize the dynamic characteristics of the pump outlet pressure in response to changes in water supply demand, providing a reliable basis for determining subsequent operational performance indicators.

[0034] Through the above technical solution, this application can achieve accurate and real-time acquisition of pressure response data during water pump operation. By using a pressure sensor for high-frequency acquisition and performing analog-to-digital conversion, the accuracy and completeness of the data are ensured, effectively avoiding missed reports or misjudgments that may be caused by traditional manual inspections or low-frequency sampling. This provides high-quality raw data for the subsequent quantification of operational performance indicators, significantly improving the reliability and precision of the water pump control system's operational quality assessment, thus laying a solid data foundation for the effective implementation of intelligent control methods.

[0035] In some embodiments described above in this application, a scheme for determining at least one operational performance indicator based on pressure response data is proposed. Specifically, the step of determining at least one operational performance indicator based on pressure response data may include the following operations: extracting the maximum deviation of the actual pressure value from the target pressure setpoint within a preset time period from the pressure time series data, and using the maximum deviation value as a pressure overshoot indicator; determining the time taken for the actual pressure value to first stabilize within a first error range allowed by the target pressure setpoint, and using the time as a pressure stabilization time indicator; calculating the dispersion of the pressure time series data within a preset time window after the actual pressure value has reached a stable state within the preset time period, and using the dispersion as a pressure volatility indicator; the stable state refers to the actual pressure value remaining within a preset first error range for subsequent consecutive second time thresholds; and using at least one of the pressure overshoot indicator, the pressure stabilization time indicator, and the pressure volatility indicator as the operational performance indicator.

[0036] Specifically, the pressure overshoot index refers to the maximum instantaneous deviation of the actual pressure value from the target pressure setpoint when the pump control system responds to changes in water supply demand. This index quantifies the transient performance of the system during dynamic response, reflecting the degree of over-response to changes in the setpoint. For example, when water supply demand suddenly increases or decreases, the pump's output pressure may temporarily exceed or fall below the target pressure setpoint before gradually stabilizing. By monitoring and extracting the maximum deviation of the actual pressure value from the target pressure setpoint within a preset time period, the overshoot or undershoot of the system can be accurately assessed.

[0037] The pressure stabilization time metric refers to the time required for the actual pressure value to first enter and remain within the first allowable error range of the target pressure setpoint. This metric measures the speed at which the system transitions from a dynamic response state to a steady state. The first error range can be understood as an acceptable fluctuation interval around the target pressure setpoint, for example, ±2% or ±5% of the target pressure setpoint. Once the actual pressure value enters this first error range, if it remains within this range for subsequent consecutive second time thresholds, the system is considered to have reached a steady state. The second time threshold is set to avoid situations where the system briefly enters the error range but fails to truly stabilize.

[0038] In practical applications, the pressure volatility index refers to the degree of dispersion of pressure time series data within a preset time window after the actual pressure value has reached a stable state. This index is used to quantify the stability of the system during stable operation. The degree of dispersion can be calculated using various statistical methods, such as standard deviation, variance, or mean absolute deviation. The criterion for determining a stable state is that the actual pressure value remains within a preset first error range for a subsequent consecutive second time threshold. The preset time window can be a fixed duration, such as several minutes or hours, used to collect sufficient data to accurately assess the pressure fluctuation under stable conditions. By calculating the degree of dispersion within this time window, the fine control capability and anti-interference capability of the pump control system during stable operation can be reflected.

[0039] As a preferred implementation, at least one of the pressure overshoot index, pressure settling time index, and pressure fluctuation index can be used as the operational performance index. This means that one or more indexes can be selected to comprehensively evaluate the operational quality of the pump control system, depending on the actual application scenario and different emphases on system performance. For example, in scenarios with high requirements for transient response, the pressure overshoot index may be more critical; while in scenarios with high requirements for long-term stability and energy efficiency, the pressure settling time index and pressure fluctuation index are more important.

[0040] This application's solution introduces pressure overshoot, pressure settling time, and pressure volatility indices to provide a multi-dimensional and refined quantitative evaluation of the pump control system's operational quality. Traditionally, the focus might be solely on whether the pressure reaches the setpoint; however, this solution delves deeper into the dynamic process of pressure response and the volatility characteristics after stabilization. The pressure overshoot index reveals the impact and overshoot during rapid response, helping to identify overly aggressive control parameters. The pressure settling time index reflects the convergence speed required for the system to stabilize from dynamic changes, aiding in assessing the control system's response efficiency. The pressure volatility index quantifies the system's stability in a steady state, helping to identify insufficient control precision or persistent disturbances. Through the comprehensive application of these indices, a more complete understanding of the pump control system's actual performance under different operating conditions can be achieved, providing a more accurate and guiding basis for subsequent closed-loop adjustment of control parameters.

[0041] Through the above technical solution, this application provides a more comprehensive and refined method for evaluating the operational quality of a water pump control system. Compared with traditional methods that rely on only a single or coarse indicator, this solution, by introducing pressure overshoot, pressure settling time, and pressure fluctuation indicators, can accurately quantify the actual operational quality of the water pump control system from multiple dimensions, including transient response, dynamic convergence, and steady-state stability. This allows for more effective identification of performance bottlenecks and potential problems of the water pump control system under different hydraulic conditions, providing a solid data foundation for subsequent optimization and adjustment of closed-loop control parameters, thereby significantly improving the energy efficiency, stability, and reliability of water pump operation.

[0042] In some embodiments described above in this application, although it is proposed to determine whether the closed-loop control parameters of the pump control system are mismatched with the actual hydraulic conditions of the pump based on the operational performance indicators and the preset ideal operational performance range, in practical applications, the pump operating environment is complex and variable. Short-term fluctuations in operating conditions or instantaneous disturbances may cause the operational performance indicators to temporarily deviate from the ideal range. If judgment is made based solely on a single or short-term deviation, it may lead to misjudgment or frequent and unnecessary parameter adjustments, thereby affecting the stability and energy efficiency of the system. Furthermore, the basic solution does not clearly identify and attribute the underlying causes of the mismatch.

[0043] In response, this application further proposes a method for determining whether the current closed-loop control parameters of the water pump control system are mismatched with the actual hydraulic conditions of the water pump based on at least one operational performance indicator and a preset ideal operational performance range. This method includes: pre-setting a first ideal threshold corresponding to the pressure overshoot indicator, a second ideal threshold corresponding to the pressure stabilization time indicator, and a third ideal threshold corresponding to the pressure fluctuation indicator; determining whether the pressure overshoot indicator is continuously greater than the first ideal threshold, or the pressure stabilization time indicator is continuously greater than the second ideal threshold, or the pressure fluctuation indicator is continuously greater than the third ideal threshold within multiple consecutive monitoring cycles; if any operational performance indicator exceeds its corresponding ideal threshold within multiple consecutive monitoring cycles, then it is determined that the current closed-loop control parameters are mismatched with the actual hydraulic conditions, and the mismatch is caused by one or more latent physical degradation factors, including changes in the properties of the transported liquid, changes in the roughness of the pipe inner wall, and sensor measurement deviations.

[0044] Specifically, the pre-set first, second, and third ideal thresholds are used to define the acceptable ranges of pressure overshoot, pressure stabilization time, and pressure fluctuation under ideal operating conditions, respectively. These thresholds can be calibrated based on pump design parameters, system performance requirements, and historical operating data to ensure that the system maintains optimal energy efficiency and stability while meeting water supply demands. For example, the first ideal threshold can be set as the maximum allowable pressure overshoot percentage, the second ideal threshold as the longest allowable stabilization time, and the third ideal threshold as the maximum allowable pressure fluctuation amplitude.

[0045] The judgment made over multiple consecutive monitoring cycles means that the system does not make an immediate judgment based on a single monitoring result, but rather continuously tracks and evaluates operational performance indicators over a period of time. Each monitoring cycle can be a fixed time period, such as several minutes, hours, or days, depending on the dynamic response characteristics and frequency of changes in operating conditions of the pump system. Only when an operational performance indicator consistently exceeds its corresponding ideal threshold throughout these consecutive monitoring cycles is it considered to have a genuine, non-instantaneous performance degradation or mismatch. This continuous judgment mechanism effectively avoids misjudgments caused by occasional interference or measurement errors.

[0046] In practical applications, if any performance indicator exceeds its corresponding ideal threshold for multiple consecutive monitoring cycles, it is considered a mismatch between the current closed-loop control parameters and the actual hydraulic conditions. This mismatch is not always an obvious external fault, but is often caused by some hidden physical degradation factors. For example, changes in the properties of the transported liquid may include changes in viscosity, density, or temperature, which directly affect the pump's head and flow characteristics; changes in the roughness of the pipe wall may be due to scaling, corrosion, or wear, thereby increasing pipe resistance and altering the system's hydraulic characteristics; sensor measurement deviations may be caused by sensor aging, calibration drift, or external interference, leading to distorted feedback signals. Identifying these hidden factors helps to understand the root causes of system performance degradation more deeply, providing a more accurate basis for subsequent parameter adjustments.

[0047] This application's solution effectively addresses potential misjudgment issues in basic solutions by introducing an ideal threshold and a continuous multi-cycle monitoring mechanism. Specifically, the preset ideal threshold clarifies the performance boundaries of the pump system under normal and efficient operating conditions, providing a quantitative standard for judgment. The judgment logic of "continuously exceeding the limit over multiple consecutive monitoring cycles" enables the system to distinguish between transient disturbances and persistent performance degradation. Mismatch judgment is triggered only when the operating performance indicators deviate from the ideal range stably for an extended period. This indicates that the actual hydraulic conditions of the pump have changed significantly and continuously, causing the current closed-loop control parameters to become unsuitable. Therefore, the system avoids overreacting to short-term fluctuations, thereby improving the accuracy and stability of judgment. Furthermore, explicitly pointing out that mismatch may be caused by implicit physical degradation factors such as changes in the properties of the transported liquid, changes in the roughness of the pipe inner wall, and sensor measurement deviations helps to fundamentally understand the causes of system performance degradation, providing more targeted guidance for subsequent parameter adjustments and enabling adjustment strategies to better adapt to changes in actual operating conditions.

[0048] Through the above technical solution, this application can significantly improve the accuracy and robustness of the pump control system in judging the mismatch between closed-loop regulation parameters and actual hydraulic conditions. By setting a precise ideal threshold and combining it with continuous multi-cycle monitoring, the system can effectively filter out instantaneous interference and occasional fluctuations, avoiding frequent or unnecessary parameter adjustments due to misjudgment, thereby ensuring the stability and energy efficiency of pump operation. In addition, the in-depth identification of the causes of mismatch, especially the revelation of hidden physical degradation factors, enables the system to more accurately understand the root cause of performance degradation, providing a more reliable basis for subsequent intelligent parameter fine-tuning, further optimizing the energy-saving operation of the pump, and extending the service life of the equipment.

[0049] In some preferred embodiments, a specific example is given below. Assume a water pump in a water supply system has a target pressure setpoint of 0.5 MPa. Based on historical operating data and system requirements, the preset ideal operating performance ranges are: a first ideal threshold of 5% for pressure overshoot, a second ideal threshold of 10 seconds for pressure stabilization time, and a third ideal threshold of 0.01 MPa for pressure fluctuation. The system is set to a monitoring cycle of 10 minutes, and a mismatch is only determined if the thresholds are exceeded for three consecutive monitoring cycles.

[0050] During a certain period, due to the gradual increase in the viscosity of the transported liquid—a change in the properties of the transported liquid—the dynamic response characteristics of the water pump altered in response to changes in water supply demand. Specifically: In the first monitoring cycle, the pressure overshoot was 6%, the pressure stabilization time was 12 seconds, and the pressure fluctuation was 0.008 MPa. At this point, both the pressure overshoot and stabilization time exceeded the thresholds, but had not yet reached three consecutive cycles. In the second monitoring cycle, the pressure overshoot was 6.5%, the pressure stabilization time was 13 seconds, and the pressure fluctuation was 0.009 MPa. At this point, the pressure overshoot and stabilization time continued to exceed the thresholds. In the third monitoring cycle, the pressure overshoot was 7%, the pressure stabilization time was 14 seconds, and the pressure fluctuation was 0.011 MPa. At this point, the pressure overshoot, stabilization time, and pressure fluctuation all continuously exceeded their respective ideal thresholds, and this had been the case for three consecutive monitoring cycles.

[0051] According to the judgment logic of this application, if at least one (in this example, all three) of the pressure overshoot index, pressure stabilization time index, and pressure fluctuation index continuously exceeds the corresponding ideal threshold for three consecutive monitoring cycles, the system will determine that the current closed-loop control parameters are mismatched with the actual hydraulic operating conditions of the pump. Furthermore, the system can attribute this mismatch to implicit physical degradation factors such as changes in the properties of the transported liquid, based on preset rules, thus providing a clear direction for subsequent parameter fine-tuning. For example, the system may adjust the proportional and integral coefficients according to parameter adjustment rules to accommodate the system response hysteresis caused by increased liquid viscosity.

[0052] In some embodiments described above, an intelligent control method for the operating status of an energy-saving water pump motor is proposed. This method can acquire pressure response data of the water pump during operation, determine operating performance indicators based on this data, and then determine whether the closed-loop regulation parameters of the water pump control system are mismatched with the actual hydraulic conditions of the water pump. When a mismatch occurs, it performs gradual fine-tuning according to preset parameter adjustment rules. However, the description of the "preset parameter adjustment rules" in the above scheme is relatively macroscopic and lacks specific adjustment strategies for different operating performance indicators. This may lead to low efficiency of parameter adjustment in practical applications, and even inaccurate adjustment direction or inappropriate adjustment range, thereby affecting the system's ability to quickly recover to the optimal operating state.

[0053] In response, this application further proposes that the aforementioned closed-loop control parameters include a proportional coefficient, an integral coefficient, and a derivative coefficient; when a mismatch is determined, the aforementioned closed-loop control parameters are progressively fine-tuned according to preset parameter adjustment rules, including: when the aforementioned pressure overshoot index exceeds the aforementioned first ideal threshold in multiple consecutive monitoring cycles, the current proportional coefficient is reduced by a first preset percentage of the current proportional coefficient; when the aforementioned pressure stabilization time index exceeds the aforementioned second ideal threshold in multiple consecutive monitoring cycles, the current integral coefficient is increased by a second preset percentage of the current integral coefficient; when the aforementioned pressure volatility index exceeds the aforementioned third ideal threshold in multiple consecutive monitoring cycles, the current derivative coefficient is adjusted, with the adjustment direction and adjustment magnitude determined according to the frequency and amplitude of pressure oscillations.

[0054] Specifically, the aforementioned closed-loop control parameters typically refer to the proportional coefficient, integral coefficient, and derivative coefficient. These are core parameters in a PID (Proportional-Integral-Derivative) controller, used to control the system's immediate response to errors, eliminate cumulative errors, and predict the rate of change of errors, respectively. When the pressure overshoot exceeds the first ideal threshold for multiple consecutive monitoring cycles, it indicates that the system's response to changes in water demand is too drastic, causing the pressure to significantly exceed the target setpoint. In this case, by reducing the current proportional coefficient, the immediate response intensity to the current error can be reduced, thereby effectively suppressing pressure overshoot. The reduction amount is set to a first preset percentage of the current proportional coefficient to ensure the gradualness and stability of the adjustment.

[0055] Furthermore, when the aforementioned pressure stabilization time exceeds the second ideal threshold in multiple consecutive monitoring cycles, it indicates that the system requires a relatively long time to stabilize within the allowable error range after reaching the target pressure setpoint. This is usually due to insufficient integral action, resulting in a slow rate at which the system eliminates steady-state errors. To address this, increasing the current integral coefficient can enhance the system's ability to eliminate accumulated errors, thereby accelerating the pressure stabilization process. The increase is set to a second preset percentage of the current integral coefficient to achieve a smooth performance improvement.

[0056] Furthermore, when the aforementioned pressure volatility index exceeds the third ideal threshold for multiple consecutive monitoring periods, it indicates that undesirable pressure oscillations still exist in the system under steady-state conditions. Such oscillations may originate from various factors and require precise damping control. In this case, the current differential coefficient is adjusted, with the direction and magnitude of the adjustment determined based on the specific frequency and amplitude of the pressure oscillations. For example, for high-frequency, small-amplitude oscillations, it may be necessary to increase the differential coefficient to provide stronger damping; for low-frequency, large-amplitude oscillations, fine-tuning may be necessary to avoid over-suppression or the introduction of new instability factors.

[0057] This application's solution specifies the closed-loop control parameters as proportional coefficients, integral coefficients, and derivative coefficients, and formulates specific, directional parameter adjustment strategies for three key performance indicators: pressure overshoot, pressure settling time, and pressure variability. When the pressure overshoot is persistently high, reducing the proportional coefficient effectively reduces the system's transient response intensity, preventing pressure overshoot and resulting in a smoother system response. When the pressure settling time is persistently long, increasing the integral coefficient enhances the system's ability to eliminate steady-state errors, accelerating the process of reaching and maintaining the target pressure. When the pressure variability is persistently large, adjusting the derivative coefficient based on the frequency and amplitude of pressure oscillations provides appropriate damping, effectively suppressing unnecessary pressure fluctuations and improving system stability. This refined adjustment mechanism allows the system to precisely intervene based on specific performance defects, avoiding the negative impacts of blind adjustments.

[0058] Through the above technical solution, this application provides a more refined and intelligent parameter adjustment mechanism. This mechanism can target specific deficiencies in different performance indicators of the water pump control system by adjusting PID parameters accordingly, effectively solving the problems of low efficiency and poor accuracy in parameter adjustment in traditional methods. This precise adjustment can not only quickly restore the optimal operating state of the water pump control system and significantly improve the stability, response speed, and accuracy of water supply pressure control, but also avoid unnecessary energy loss, further improving the energy-saving effect of water pump operation. In addition, through progressive fine-tuning of PID parameters, the system can better adapt to implicit changes in hydraulic conditions, extend the service life of the equipment, reduce maintenance costs, and thus achieve long-term, efficient, and intelligent control of the water pump motor's operating status.

[0059] In some preferred embodiments, assuming that during the operation of a water pump control system, its pressure overshoot index exceeds a preset first ideal threshold for five consecutive monitoring cycles (e.g., the target pressure is 0.5 MPa, the actual peak pressure reaches 0.6 MPa, the overshoot is 20%, and the first ideal threshold is 10%), the system will automatically reduce the current proportional coefficient, for example, reducing it from 0.8 to a first preset percentage (e.g., 5%), i.e., to 0.76. In another scenario, if the system detects that the pressure stabilization time index exceeds a preset second ideal threshold for three consecutive monitoring cycles (e.g., after a change in target pressure, the stabilization time exceeds 15 seconds, while the second ideal threshold is 10 seconds), the system will increase the current integral coefficient, for example, increasing it from 0.2 to a second preset percentage (e.g., 10%), i.e., to 0.22. For example, when the system is operating stably, if the pressure fluctuation index exceeds the preset third ideal threshold for four consecutive monitoring cycles (e.g., the pressure oscillates continuously within ±5% of the target value, while the third ideal threshold is ±2%), and analysis reveals an oscillation frequency of 0.8Hz and an amplitude of 0.03MPa, the system will adjust the derivative coefficient according to a preset adjustment strategy. For instance, if the strategy specifies that the derivative coefficient should be appropriately increased to enhance damping for such high-frequency, medium-amplitude oscillations, the derivative coefficient will be adjusted from 0.1 to 0.12. These specific adjustments enable the system to intelligently optimize PID parameters based on actual operating performance, thereby improving overall control performance.

[0060] After making incremental fine adjustments to the above closed-loop control parameters, if there is no effective evaluation mechanism for the adjustment effect, it may lead to improper adjustment direction or magnitude, which may result in the pump control system not only failing to improve but also deteriorating, or even causing system instability, thereby affecting energy saving effect and water supply stability.

[0061] To address this, this application further proposes a method that, after progressively fine-tuning the aforementioned closed-loop adjustment parameters, includes: re-acquiring pressure response data and determining the corresponding operational performance indicators in a new monitoring cycle after parameter fine-tuning; comparing the operational performance indicators obtained after parameter fine-tuning with those obtained before parameter fine-tuning; if the operational performance indicators after parameter fine-tuning show a trend of improvement towards the ideal operational performance range relative to the operational performance indicators before parameter fine-tuning, then maintaining the fine-tuned closed-loop adjustment parameters; if the operational performance indicators after parameter fine-tuning deteriorate relative to the operational performance indicators before parameter fine-tuning, then reverting the closed-loop adjustment parameters to the state before fine-tuning and implementing an adjustment strategy different from the direction of this fine-tuning.

[0062] Specifically, after fine-tuning the closed-loop control parameters, the system enters a new monitoring cycle. During this cycle, pressure response data of the pump during operation is reacquired, and based on this data, new performance indicators are determined using the method described above, such as pressure overshoot, pressure stabilization time, and pressure fluctuation. These newly determined performance indicators reflect the actual operating quality of the system after parameter fine-tuning. Subsequently, these performance indicators obtained after fine-tuning are compared in detail with the performance indicators recorded before fine-tuning. This comparison aims to evaluate the actual effect of the parameter adjustment.

[0063] If the comparison results show that the performance indicators after parameter fine-tuning show a trend of improvement towards the ideal performance range compared to the indicators before fine-tuning, such as a decrease in pressure overshoot, a shortening of pressure stabilization time, or a reduction in pressure volatility, it indicates that the parameter adjustment is effective. In this case, the fine-tuned closed-loop control parameters will be maintained to preserve and consolidate the improvement in system performance.

[0064] However, if the comparison results show that the performance indicators after parameter fine-tuning have deteriorated compared to those before fine-tuning—for example, an increase in pressure overshoot, a prolonged pressure settling time, or an increase in pressure volatility—it indicates that the parameter adjustment may have been inappropriate. In this case, to prevent further degradation of system performance, the closed-loop control parameters will be immediately reverted to their state before fine-tuning, restoring the system to the known stable point before adjustment. Simultaneously, the system will execute an adjustment strategy different from the direction of this fine-tuning. This means that in the next adjustment attempt, based on the specific deterioration and preset adjustment rules, a parameter adjustment scheme opposite to or different from the direction that caused the deterioration will be selected in order to find the correct optimization path.

[0065] This application's solution effectively addresses the performance degradation issue that parameter adjustments in the aforementioned basic solution may cause. Specifically, after incrementally fine-tuning the closed-loop control parameters, the system does not blindly accept the adjustment results. Instead, it re-acquires pressure response data and determines operational performance indicators within a new monitoring cycle, thereby quantitatively evaluating the adjustment effect. By comparing the operational performance indicators before and after the adjustment, the system can objectively determine whether the fine-tuning has brought improvement or caused deterioration. This real-time effect evaluation mechanism enables the system to promptly identify and correct inappropriate parameter adjustments, avoiding system performance degradation or instability caused by erroneous adjustments. When deterioration is detected, the parameter rollback mechanism ensures that the system can quickly recover to a known stable state. Executing an adjustment strategy different from the direction of the current fine-tuning provides the system with the ability to learn and explore better parameter configurations, thus ensuring the robustness and effectiveness of the parameter adjustment process.

[0066] Through the above technical solution, this application significantly improves the adaptability and reliability of the intelligent control method for the operating status of energy-saving water pump motors. This solution not only identifies and corrects improper closed-loop control parameter adjustments, effectively avoiding problems such as system performance degradation, increased energy consumption, or unstable water supply that may result from incorrect adjustments, but also endows the control system with stronger self-learning and optimization capabilities through parameter rollback and strategy adjustment. Therefore, it ensures that the water pump control system can continuously maintain optimal operating conditions when facing complex and changing hydraulic conditions, further improving energy-saving effects and operational stability, and extending equipment lifespan.

[0067] In some preferred embodiments, a specific example is given below. Suppose that during a certain monitoring period, the pump control system is determined to have a mismatch between its closed-loop regulation parameters and the actual hydraulic conditions, specifically manifested as a pressure overshoot consistently exceeding a first ideal threshold. According to preset parameter adjustment rules, the system performs an operation to reduce the current proportional coefficient by a first preset percentage.

[0068] Following this fine-tuning, the system enters a new monitoring cycle to reacquire pressure response data and determine operational performance indicators. Assuming that in the new monitoring cycle, the system finds that although the pressure overshoot indicator has improved, the pressure settling time indicator has significantly increased, exceeding the second ideal threshold, indicating a slower system response speed and a deterioration in overall operational quality.

[0069] At this point, according to the above scheme, the system will revert the closed-loop control parameters to their state before the fine-tuning, that is, restore the proportional coefficient before the reduction. Subsequently, the system will execute an adjustment strategy different from the direction of this fine-tuning. For example, since the current deterioration is mainly reflected in the pressure stabilization time index, the system may try to increase the current integral coefficient by a second preset percentage of the current integral coefficient, or in the next attempt to reduce the proportional coefficient, use a smaller reduction to avoid further deterioration of the pressure stabilization time index. Through this iterative and feedback mechanism, the system can gradually converge to the optimal closed-loop control parameters, ensuring that the water pump can operate efficiently and stably under various operating conditions.

[0070] In some embodiments described above, this application proposes a scheme whereby, after progressively fine-tuning the closed-loop control parameters, pressure response data is reacquired and corresponding performance indicators are determined. These performance indicators are then compared with those obtained before the fine-tuning to assess the effectiveness of the adjustment. However, in practice, if the performance indicators after fine-tuning deteriorate compared to those before, the scheme only instructs the closed-loop control parameters to revert to their pre-adjustment state and implement an adjustment strategy different from the current adjustment direction. It does not explicitly specify how this "different adjustment strategy" should be implemented. This uncertainty may cause the system to fall into a trial-and-error loop during parameter adjustment, reducing adjustment efficiency and potentially exacerbating system instability due to inappropriate adjustment directions, especially when facing complex and nonlinear hydraulic conditions.

[0071] In response, this application further proposes an adjustment strategy that differs from the direction of this fine-tuning, including: if the pressure stabilization time index deteriorates due to the operation of increasing the current integral coefficient, then after reverting to the integral coefficient before adjustment, the current integral coefficient is decreased by a third preset percentage of the current integral coefficient; if the pressure overshoot index deteriorates due to the operation of decreasing the current proportional coefficient, then after reverting to the proportional coefficient before adjustment, the current proportional coefficient is increased by a fourth preset percentage of the current proportional coefficient.

[0072] Specifically, when a pump control system attempts to increase the integral coefficient to improve certain operational performance (e.g., reduce steady-state error), if a deterioration in the pressure settling time is observed instead, this usually indicates that the integral action is too strong, causing the system response to be too slow or oscillations. In this case, reverting to the original integral coefficient and then reducing the current integral coefficient is a targeted correction of the previous erroneous adjustment. The third preset percentage can be a pre-set fixed value, such as 1% or 2%, or it can be a percentage dynamically determined based on the system's historical performance or current operating conditions, aiming to achieve refined and gradual adjustments.

[0073] Similarly, if a pump control system attempts to reduce the proportional gain to decrease pressure overshoot, but this actually worsens the pressure overshoot, it may indicate that the proportional effect has been excessively weakened, making the system response sluggish and unable to quickly and effectively suppress disturbances, potentially leading to larger overshoot or longer response times. In this case, reverting to the original proportional gain and then increasing the current proportional gain can effectively restore the system's rapid response to deviations. The setting method for the fourth preset percentage is similar to that of the third preset percentage and can be configured according to actual needs.

[0074] The proposed solution effectively avoids the control system from falling into an ineffective trial-and-error cycle during parameter optimization by adopting an adjustment strategy opposite to the direction of the current fine-tuning when the operating performance deteriorates due to parameter fine-tuning. Specifically, when increasing the integral coefficient leads to a deterioration in the pressure settling time, this usually indicates that the integral action is too strong, making the system's cumulative error response too aggressive, thus prolonging the time required to reach stability and potentially even triggering low-frequency oscillations. In this case, by backing down and decreasing the integral coefficient, the excessive integral action can be weakened, making the system response smoother and thus helping to shorten the pressure settling time. Conversely, when decreasing the proportional coefficient leads to a deterioration in the pressure overshoot, this may mean that the proportional action is insufficient, the system's immediate response capability to deviations decreases, leading to increased pressure fluctuations and greater overshoot when responding to changes in water supply demand. By backing down and increasing the proportional coefficient, the system's ability to quickly correct deviations can be enhanced, thereby effectively suppressing pressure overshoot. This targeted reverse adjustment strategy is based on a deep understanding of the relationship between PID control parameters and system dynamic response, ensuring the logic and effectiveness of parameter adjustments.

[0075] Through the above technical solution, this application can significantly improve the robustness and efficiency of the intelligent control method for the operating status of energy-saving water pump motors in the process of parameter adaptive adjustment. When the initial parameter fine-tuning direction is incorrect and causes system performance deterioration, this solution no longer simply backtracks and tries arbitrarily different strategies, but intelligently selects the opposite adjustment direction based on the specific deterioration indicators (such as pressure stabilization time or pressure overshoot) and the parameter adjustment direction that caused the deterioration. This avoids blind trial and error, reduces the time the system operates in unstable or suboptimal states, and accelerates the convergence process of parameters to the optimal value. As a result, the control system can adapt to the implicit changes in hydraulic conditions more quickly and accurately, ensuring the long-term stable, efficient, and energy-saving operation of the water pump system, and reducing the frequency and difficulty of manual intervention.

[0076] In some preferred embodiments, a specific example is given below. Suppose that during a parameter adjustment, in order to further eliminate steady-state error, the system increases the current integral coefficient by a second preset percentage (e.g., 2%). However, in a subsequent monitoring period, it is found that the pressure stabilization time index has worsened from 5 seconds to 8 seconds, exceeding the preset second ideal threshold. According to the above scheme, the system first reverts the integral coefficient to its pre-adjustment state. Subsequently, since the increase in the integral coefficient caused the deterioration of the pressure stabilization time index, the system will decrease the current integral coefficient by a third preset percentage (e.g., 1.5%).

[0077] For example, in another adjustment, to reduce pressure overshoot during pump startup, the system reduced the current proportional gain by a first preset percentage (e.g., 3%). However, in subsequent monitoring, the pressure overshoot worsened from 5% to 10%, consistently exceeding the first ideal threshold. At this point, the system reverted the proportional gain to its pre-adjustment state and increased it by a fourth preset percentage (e.g., 2.5%). Through this targeted reverse adjustment, the system can quickly correct erroneous adjustments, avoiding prolonged operation under suboptimal parameters, thus achieving more effective energy savings and stable operation.

[0078] Specifically, in the above-described implementation of determining operational performance indicators, the process for determining the pressure stabilization time indicator can be further refined. Determining the time during which the actual pressure value remains stable within the first allowable error range of the target pressure setpoint includes: continuously monitoring the actual pressure value after a change in the target pressure setpoint; starting a timer when the actual pressure value first enters the first error range; determining that a stable state has been reached if the actual pressure value remains within the first error range for subsequent consecutive second time thresholds, stopping the timer, and using the accumulated time as the pressure stabilization time indicator; and resetting and restarting the timer if the actual pressure value exceeds the first error range during the timer process.

[0079] Specifically, during the operation of the water pump control system, when the target pressure setpoint changes, for example due to adjustments in water supply demand, the system needs to reach a new stable pressure point. At this time, it is necessary to continuously monitor the actual pressure value at the pump outlet. Once the actual pressure value first enters within the first allowable error range of the target pressure setpoint, it indicates that the system is approaching stability, and a timer is started. Subsequently, the system continues to monitor the actual pressure value. If the actual pressure value remains within the first error range for subsequent consecutive second time thresholds, it can be confirmed that the system has reached a stable state. At this point, the timer stops, and the accumulated time is used as the pressure stabilization time indicator. This indicator directly reflects the time required for the system to stabilize from the target pressure setpoint. However, if the actual pressure value exceeds the first error range again during the timing process, it indicates that the system has not yet truly stabilized and there may be fluctuations or disturbances. In this case, the timer needs to be reset and restarted to ensure that the measured pressure stabilization time indicator is accurate and reliable.

[0080] The proposed solution ensures the accuracy of the pressure stabilization time indicator by introducing a mechanism that includes continuous monitoring, timing activation upon first entering the error range, stability determination upon continuous maintenance within the error range, and timing reset upon exceeding the error range. This phased timing and judgment logic effectively avoids misjudgments caused by instantaneous fluctuations or brief entry into the error range, thereby more accurately quantifying the stability performance of the pump control system in response to changes in the target pressure setpoint.

[0081] The above technical solution provides a more accurate and robust method for determining the pressure stabilization time index. Compared to simply stopping the timing once the pressure enters the error range, this solution introduces a continuous second time threshold judgment, effectively eliminating the interference of brief fluctuations or overshoot phenomena that may occur before the system reaches stability on the stabilization time measurement. This allows the obtained pressure stabilization time index to more realistically reflect the dynamic response characteristics and stability of the pump control system under actual hydraulic conditions, providing a more reliable data foundation for subsequent performance evaluation and closed-loop control parameter adjustment.

[0082] In some embodiments described above, the closed-loop control parameters are progressively fine-tuned to address the mismatch between the pump control system and actual hydraulic conditions. However, in practical applications, if continuous parameter fine-tuning is not effectively managed, the system may undergo excessively frequent adjustments within a short period. Such frequent adjustments may cause the system to undergo another adjustment before it has fully responded to the effect of the previous adjustment, leading to system oscillations, unstable regulation, and even causing the parameters to fluctuate around the ideal value, making it difficult to converge to the optimal state, thereby affecting the stability and energy-saving effect of the pump operation.

[0083] In response, this application further proposes the following steps for progressively fine-tuning the closed-loop adjustment parameters: setting a cooling time interval for the closed-loop adjustment parameters, wherein the cooling time interval is used to specify the minimum waiting time between two consecutive progressive fine-tuning operations; and performing the next parameter fine-tuning operation when the cooling time interval ends and the performance index continues to deviate from the ideal performance range.

[0084] Specifically, the cooling time interval refers to the minimum time period that the system must wait before performing the next fine-tuning operation after completing a gradual fine-tuning operation of the closed-loop adjustment parameters. This time interval is designed to provide the pump control system with sufficient time to respond to the effects of the previous parameter adjustment and to allow the system state to stabilize. The length of the cooling time interval can be preset based on the dynamic response characteristics of the pump system, the convergence speed of the control algorithm, and the system stability requirements in practical applications. For example, the cooling time interval can be set to several seconds, tens of seconds, or even several minutes, depending on factors such as pump inertia, pipe length, and liquid properties. After the cooling time interval ends, the system will re-evaluate the current operating performance indicators. Only when these operating performance indicators (such as pressure overshoot, pressure stabilization time, and pressure fluctuation) continue to deviate from the preset ideal operating performance range will the next parameter fine-tuning operation be allowed. This means that if the system performance has improved and returned to the ideal operating performance range after one fine-tuning and cooling time interval, the next adjustment will not be performed immediately, thus avoiding unnecessary frequent intervention.

[0085] This application's solution effectively addresses the instability issue caused by frequent parameter adjustments in the basic scheme by introducing a cooling time interval. Specifically, after a gradual fine-tuning of the closed-loop control parameters, the system does not immediately perform the next adjustment but instead waits for a preset cooling time interval. This waiting mechanism ensures that the system has sufficient time to absorb the impact of the previous parameter adjustment, allowing the actual operating state of the pump to fully reflect its performance under the new parameters. Only when the system's performance indicators continue to deviate from the ideal range after this cooling period will subsequent parameter fine-tuning be triggered. This mechanism avoids continuous adjustments before the system has fully responded, thus preventing parameters from oscillating around their optimal values ​​and improving the stability and convergence of parameter adjustments.

[0086] Through the above technical solution, this application can significantly improve the robustness and stability of the intelligent control method for the operating status of energy-saving water pump motors. By setting a cooling time interval, system oscillation and instability caused by excessively frequent parameter fine-tuning are effectively avoided, ensuring that each parameter adjustment has sufficient time for the system to process and provide feedback. This not only improves the efficiency and accuracy of parameter adjustment, enabling the closed-loop control parameters to converge more smoothly and effectively to the optimal value matching the actual hydraulic conditions, but also reduces unnecessary calculations and control operations, extends the service life of the control system and water pump equipment, and further enhances energy-saving effects and operational reliability.

[0087] As a specific implementation method, suppose a water pump control system experiences a pressure stabilization time index that consistently exceeds the second ideal threshold during operation, indicating a potential mismatch between the current integral coefficient and actual operating conditions. The system, based on preset parameter adjustment rules, increases the current integral coefficient. After this adjustment, the system immediately initiates a preset cooling time interval, for example, 30 seconds. During these 30 seconds, even if the pressure stabilization time index still deviates from the ideal range, the system will not immediately perform a second adjustment of the integral coefficient. After the 30-second cooling time interval ends, the system monitors the pressure stabilization time index again. If the index is still consistently greater than the second ideal threshold, the system will again increase the current integral coefficient. Conversely, if the pressure stabilization time index has fallen back below the second ideal threshold within these 30 seconds, indicating that the previous adjustment was effective, the system will not perform another adjustment, thus avoiding over-adjustment and potential system oscillations. This mechanism ensures that each parameter adjustment is made based on a thorough evaluation of the previous adjustment's effect, thereby improving the effectiveness of the adjustment and the system's stability.

[0088] In some embodiments, this application proposes an intelligent control system for the operating status of an energy-saving water pump motor, comprising: an acquisition unit for acquiring pressure response data of the water pump during operation, the pressure response data being used to characterize the dynamic characteristics of the water pump outlet pressure in response to changes in water supply demand; a determination unit for determining at least one operating performance index based on the pressure response data, the operating performance index being used to quantify the actual operating quality of the water pump control system; a judgment unit for determining whether the current closed-loop adjustment parameters of the water pump control system are mismatched with the actual hydraulic conditions of the water pump based on the at least one operating performance index and a preset ideal operating performance range; and an adjustment unit for progressively fine-tuning the closed-loop adjustment parameters according to preset parameter adjustment rules when a mismatch is determined, the parameter adjustment rules covering the adjustment direction and adjustment magnitude of the closed-loop adjustment parameters corresponding to different operating performance indices deviating from the ideal operating performance range.

[0089] This system aims to address the problem of mismatch between control parameters and actual operating conditions in traditional intelligent control systems for water pump motors during long-term operation. This mismatch is caused by implicit physical degradation factors such as changes in the properties of the pumped liquid, variations in the roughness of the pipe inner wall, and sensor measurement deviations, leading to increased energy consumption and equipment wear. By acquiring real-time pressure response data from the pump's operation, the system analyzes this data to quantify performance indicators. The judgment unit identifies mismatches in closed-loop control parameters by comparing these indicators with ideal ranges. The adjustment unit then progressively fine-tunes the parameters according to preset rules, achieving intelligent and adaptive control of the pump motor's operating state. This ensures efficient and stable operation under constantly changing conditions, significantly improving energy efficiency and operational reliability.

[0090] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for intelligent control of the operating status of an energy-saving water pump motor, characterized in that, include: Acquire pressure response data of the water pump during operation, and the pressure response data is used to characterize the dynamic characteristics of the water pump outlet pressure in response to changes in water supply demand. Based on the pressure response data, at least one operational performance indicator is determined, which is used to quantify the actual operational quality of the water pump control system. Based on the at least one performance indicator and the preset ideal performance range, determine whether the current closed-loop regulation parameters of the pump control system are mismatched with the actual hydraulic conditions of the pump. When a mismatch is detected, the closed-loop adjustment parameters are progressively fine-tuned according to preset parameter adjustment rules. The parameter adjustment rules cover the adjustment direction and magnitude of the closed-loop adjustment parameters when different operating performance indicators deviate from the ideal operating performance range.

2. The intelligent control method for the operating status of an energy-saving water pump motor according to claim 1, characterized in that, The acquisition of pressure response data of the water pump during operation includes: A pressure sensor installed at the water pump outlet collects simulated pressure signals at a preset frequency. The pressure analog signal is converted into a pressure digital signal to obtain pressure time series data, and the pressure time series data is used as the pressure response data of the water pump during operation.

3. The intelligent control method for the operating status of an energy-saving water pump motor according to claim 2, characterized in that, The step of determining at least one operational performance indicator based on the pressure response data includes: From the pressure time series data, extract the maximum deviation of the actual pressure value from the target pressure set value within a preset time period, and use the maximum deviation as the pressure overshoot index; Determine the time taken for the actual pressure value to first stabilize within the first allowable error range of the target pressure setpoint, and use the time as a pressure stabilization time index; Within a preset time window after the actual pressure value has stabilized within a preset duration, the dispersion of the pressure time series data is calculated, and the dispersion is used as a pressure volatility index; the stable state means that the actual pressure value remains within a preset first error range within a subsequent continuous second time threshold. At least one of the pressure overshoot index, the pressure stabilization time index, and the pressure volatility index shall be used as the operational performance index.

4. The intelligent control method for the operating status of an energy-saving water pump motor according to claim 3, characterized in that, The step of determining whether the current closed-loop regulation parameters of the water pump control system are mismatched with the actual hydraulic conditions of the water pump based on the at least one operational performance indicator and a preset ideal operational performance range includes: A first ideal threshold corresponding to the pressure overshoot index, a second ideal threshold corresponding to the pressure stabilization time index, and a third ideal threshold corresponding to the pressure volatility index are preset. Within multiple consecutive monitoring periods, it is determined whether the pressure overshoot index is continuously greater than the first ideal threshold, or whether the pressure stabilization time index is continuously greater than the second ideal threshold, or whether the pressure fluctuation index is continuously greater than the third ideal threshold. If any operational performance indicator exceeds the corresponding ideal threshold in multiple consecutive monitoring cycles, it is determined that the current closed-loop regulation parameter is mismatched with the actual hydraulic conditions. The mismatch is caused by one or more latent physical degradation factors, such as changes in the properties of the transported liquid, changes in the roughness of the pipeline inner wall, and sensor measurement deviations.

5. The intelligent control method for the operating status of an energy-saving water pump motor according to claim 4, characterized in that, The closed-loop adjustment parameters include proportional coefficient, integral coefficient, and derivative coefficient; when a mismatch is detected, the closed-loop adjustment parameters are progressively fine-tuned according to preset parameter adjustment rules, including: When the pressure overshoot index exceeds the first ideal threshold in multiple consecutive monitoring cycles, the current proportional coefficient is reduced by a first preset percentage of the current proportional coefficient. When the pressure stabilization time index exceeds the second ideal threshold in multiple consecutive monitoring cycles, the operation of increasing the current integral coefficient is performed, and the increase is the second preset percentage of the current integral coefficient. When the pressure fluctuation index exceeds the third ideal threshold in multiple consecutive monitoring periods, the current differential coefficient is adjusted. The adjustment direction and magnitude are determined based on the frequency and amplitude of the pressure oscillation.

6. The intelligent control method for the operating status of an energy-saving water pump motor according to claim 5, characterized in that, After progressively fine-tuning the closed-loop adjustment parameters, the method further includes: In the new monitoring cycle after parameter fine-tuning, pressure response data is reacquired, and the corresponding operational performance indicators are determined. Compare the performance indicators obtained after parameter fine-tuning with the performance indicators obtained before parameter fine-tuning. If the performance indicators after parameter fine-tuning show a trend of improvement towards the ideal performance range compared to the performance indicators before parameter fine-tuning, then the fine-tuned closed-loop adjustment parameters are maintained. If the performance indicators after parameter fine-tuning deteriorate compared to the performance indicators before parameter fine-tuning, the closed-loop adjustment parameters will be reverted to the state before fine-tuning, and an adjustment strategy different from the current fine-tuning direction will be executed.

7. The intelligent control method for the operating status of an energy-saving water pump motor according to claim 6, characterized in that, The implementation of adjustment strategies that differ from the direction of this fine-tuning includes: If the pressure stabilization time index deteriorates due to the operation of increasing the current integral coefficient, then after reverting to the integral coefficient before adjustment, the operation of decreasing the current integral coefficient is performed, and the decrease is the third preset percentage of the current integral coefficient. If the pressure overshoot index deteriorates due to the operation of reducing the current proportional coefficient, then after reverting to the proportional coefficient before adjustment, the operation of increasing the current proportional coefficient is performed, and the increase is the fourth preset percentage of the current proportional coefficient.

8. The intelligent control method for the operating status of an energy-saving water pump motor according to claim 3, characterized in that, The time elapsed during which the actual pressure value first stabilizes within the first allowable error range of the target pressure setpoint includes: After the target pressure setpoint changes, the actual pressure value is continuously monitored; When the actual pressure value is detected to enter the first error range for the first time, the timing is started; If the actual pressure value remains within the first error range for consecutive second time thresholds, it is determined that a stable state has been reached, the timing is stopped, and the cumulative time is used as the pressure stabilization time index. If the actual pressure value exceeds the first error range during the timing process, the timer is reset and the timing restarts.

9. The intelligent control method for the operating status of an energy-saving water pump motor according to claim 1, characterized in that, The progressive fine-tuning of the closed-loop adjustment parameters includes: The cooling time interval is set for the closed-loop adjustment parameter, which specifies the minimum waiting time between two consecutive progressive fine-tuning operations. After the cooling time interval ends, and if the performance indicators continue to deviate from the ideal performance range, the next parameter fine-tuning operation is performed.

10. An intelligent control system for the operating status of an energy-saving water pump motor, characterized in that, include: The acquisition unit is used to acquire pressure response data of the water pump during operation. The pressure response data is used to characterize the dynamic characteristics of the water pump outlet pressure in response to changes in water supply demand. The determining unit is used to determine at least one operating performance indicator based on the pressure response data, the operating performance indicator being used to quantify the actual operating quality of the water pump control system. The judgment unit is used to determine whether the current closed-loop adjustment parameters of the water pump control system are mismatched with the actual hydraulic conditions of the water pump based on the at least one operating performance index and the preset ideal operating performance range. The adjustment unit is used to make progressive fine adjustments to the closed-loop adjustment parameters according to preset parameter adjustment rules when a mismatch is determined. The parameter adjustment rules cover the adjustment direction and adjustment range of the closed-loop adjustment parameters when different operating performance indicators deviate from the ideal operating performance range.

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