Closed-loop control method for hydraulic control butterfly valve of PCCP long-distance high-pressure water conveying pipeline

Abstract

The invention discloses a closed-loop control method for a hydraulic control butterfly valve of a PCCP (prestressed concrete cylinder pipe) long-distance high-pressure water conveying pipeline, and belongs to the technical field of long-distance high-pressure water conveying pipeline control. The problems that in the prior art, due to manual scheduling or single-point PID control, a long-distance PCCP water conveying system has response lag and lacks global cooperation, the water attack risk is difficult to effectively deal with, and the optimal overall energy consumption of the system cannot be considered are solved. According to the invention, by constructing a hierarchical control architecture in which a distributed measurement and control network is coordinated with a central supervision control and data acquisition system platform, a variable-parameter PID control algorithm is built in an equipment PLC, so that millisecond-level identification and active suppression of a sudden water attack working condition are realized; a hydraulic simulation model and a multi-objective optimization algorithm are deployed in a central supervision control and data acquisition system master station, and a whole-line optimal pressure set value is solved through iterative calculation and is issued to each PLC for execution, so that the system energy consumption minimization is realized on the premise of ensuring the pipeline safety.

Description

Technical Field

[0001] This invention relates to the field of control technology for long-distance high-pressure water transmission pipelines, specifically a closed-loop control method for hydraulic butterfly valves in PCCP long-distance high-pressure water transmission pipelines. Background Technology

[0002] With the rapid development of water resource allocation projects in my country, long-distance, high-pressure, and high-flow water transmission systems constructed using PCCP pipelines are increasingly common. These systems typically extend for tens or even hundreds of kilometers, with numerous hydraulically controlled butterfly valves distributed along the route for flow regulation and pressure control. Because PCCP pipelines are highly sensitive to pressure fluctuations, and long-distance water transmission systems exhibit significant time delays, nonlinearity, and strong coupling characteristics, traditional manual scheduling or simple single-point PID control is insufficient to effectively handle complex operating conditions. Especially during pump start-up and shutdown, valve operation, or sudden changes in water consumption, water hammer can easily occur, leading to sudden changes in pipeline pressure and potentially causing major safety accidents such as pipeline rupture and equipment damage. In existing technologies, each valve control point often operates independently, lacking global collaborative optimization, and cannot achieve optimal overall system energy consumption while ensuring pipeline safety; therefore, this approach does not meet current requirements. To address this, we propose a closed-loop control method for hydraulically controlled butterfly valves in long-distance, high-pressure PCCP water transmission pipelines. Summary of the Invention

[0003] The purpose of this invention is to provide a closed-loop control method for hydraulic butterfly valves in long-distance high-pressure water transmission pipelines using PCCP. By utilizing the variable parameter PID control algorithm embedded in the PLC, millisecond-level identification and active suppression of water hammer conditions can be achieved, avoiding the risk of pipeline rupture. At the same time, with the help of the hydraulic simulation model and multi-objective optimization algorithm of the main station of the monitoring control and data acquisition system, the pressure setpoints of all control points along the entire line are globally optimized in a coordinated manner while ensuring pipeline safety. This overcomes the shortcomings of traditional independent control modes in that they cannot take into account the overall energy consumption optimization of the system, and solves the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a closed-loop control method for hydraulically controlled butterfly valves in a PCCP long-distance high-pressure water transmission pipeline, applied to a long-distance high-pressure water transmission system composed of PCCP pipelines, wherein the system includes multiple hydraulically controlled butterfly valves distributed along the pipeline, and the method includes the following steps:

[0005] Step 1: Construct a distributed measurement and control network based on a fieldbus control system. Connect the actuators of each hydraulic butterfly valve, as well as the pressure and flow sensors deployed upstream and downstream of the valve, to the corresponding PLC via the fieldbus protocol. Make the PLC have a built-in variable parameter PID control algorithm that includes water hammer pressure suppression logic.

[0006] The fieldbus protocol uses the PROFINET IRT industrial Ethernet protocol, and the network parameters are configured as follows:

[0007] Set the cyclic data exchange cycle between the PLC and the hydraulic butterfly valve actuator to 20ms, set the cyclic data exchange cycle between the PLC and the pressure sensor and flow sensor to 50ms, set the maximum number of slave stations in each bus segment to no more than 16, and ensure that the end-to-end control delay time from sensor data acquisition to actuator action completion is less than 100ms.

[0008] Step 2: Establish a remote monitoring platform for the Supervisory Control and Data Acquisition (SCADA) system, connect all PLCs to the SCADA system master station through the backbone network, and deploy the full-line hydraulic simulation model in the SCADA system master station;

[0009] Step 3: The PLC executes local autonomous closed-loop control. The PLC collects upstream and downstream pressure and flow values ​​in real time according to a 100ms scan cycle, and performs the following judgments and controls:

[0010] If the pressure change rate is not detected to exceed the preset safety threshold, the valve opening adjustment amount is calculated according to the deviation between the current pressure value and the locally stored set value using the conventional PID algorithm, and then output to the hydraulic butterfly valve actuator through the fieldbus control system.

[0011] If the pressure change rate is detected to exceed the preset safety threshold, it is determined to be a water hammer condition. The PLC immediately clears the integral term of the PID algorithm to zero, adjusts the proportional gain to 1.5-3 times the normal value, and forces the valve to close or open quickly until the pressure change rate returns to within the safety threshold, and then smoothly switches back to the normal PID algorithm.

[0012] Step 4: The Supervisory Control and Data Acquisition (SCADA) system performs global optimization settings. The SCADA system master station collects pressure, flow, and valve opening data uploaded by each PLC along the entire line at a cycle of 1-5 minutes. It runs the hydraulic simulation model and, combined with the current operating status of the pumping station and changes in water demand, uses minimizing the pressure fluctuation and minimizing the total energy consumption of the system as the dual objective functions. The optimal pressure setpoint for each control point is solved through iterative calculation.

[0013] Step 5: The Supervisory Control and Data Acquisition (SCADA) system master station sends the optimal pressure setpoint calculated in Step 4 to the corresponding PLC through the backbone network. After receiving the optimal setpoint, the PLC automatically replaces the original setpoint stored locally and repeats the local autonomous closed-loop control in Step 3.

[0014] Furthermore, it also includes: correcting the valve opening adjustment amount based on the opening deviation between the actual opening degree of the hydraulic butterfly valve and the calculated valve opening adjustment amount, specifically as follows:

[0015] After the PLC executes local autonomous closed-loop control, the actual opening degree of the hydraulic butterfly valve is obtained, and the opening degree deviation between the actual opening degree and the calculated valve opening degree adjustment amount is obtained.

[0016] The pressure value of the PCCP pipeline is obtained when the PLC executes local autonomous closed-loop control. Based on the pressure value, the disturbance deviation of the hydraulic butterfly valve is determined. Based on the difference between the opening deviation and the disturbance deviation, the opening deviation to be corrected is obtained.

[0017] The system acquires the opening deviation to be corrected within a preset number of times the PLC executes local autonomous closed-loop control, forms a deviation sequence, calculates the rate of change of deviation between adjacent deviations in the deviation sequence, and calculates the regularity index of the deviation sequence. When the rate of change of all deviations between adjacent deviations is less than the preset deviation rate of change threshold and the regularity index is greater than the preset regularity index threshold, it is determined that the opening deviation to be corrected has a systematic cumulative deviation, and opening correction is triggered. Otherwise, it is determined that the opening deviation to be corrected is not a systematic cumulative deviation, and opening correction is not triggered.

[0018] Once the opening correction is triggered, the mapping relationship between the actual opening and the opening adjustment is corrected based on the difference between the opening deviation to be corrected and the historical opening deviation to be corrected corresponding to the previous correction, to obtain the latest mapping relationship. The valve opening adjustment amount is then initially corrected based on the latest mapping relationship to obtain the intermediate valve opening adjustment amount.

[0019] The parameters of the actuator and the hydraulic butterfly valve are obtained. Combined with the parameters of historical calibration, the hydraulic butterfly valve fluid torque is compensated in real time for the opening adjustment of the intermediate valve to obtain the compensation amount. Based on the compensation amount, the opening adjustment of the intermediate valve is compensated to obtain the final valve opening adjustment amount.

[0020] Furthermore, the local storage settings include three sources, selected in the following priority order:

[0021] Highest priority: Optimal pressure setpoints issued in real time by the Supervisory Control and Data Acquisition (SCADA) system master station;

[0022] Secondary priority: When communication is interrupted, the PLC automatically recalls the last Supervisory Control and Data Acquisition (SCADA) system settings received before the communication interruption;

[0023] Basic priority: When the PLC is put into operation for the first time or when there are no SCADA system commands for a long time, the corresponding pressure safety value is automatically matched from the pre-stored flow-pressure data table in the PLC according to the current measured flow.

[0024] Furthermore, the integral term of the PID algorithm is cleared to zero, the proportional gain is adjusted to 1.5-3 times the normal value, and the valve is forced to close or open quickly. This includes the following steps:

[0025] The PLC determines the nature of the water hammer wave based on the positive and negative directions of the pressure change rate.

[0026] If the pressure suddenly increases, execute the quick-close command; if the pressure suddenly decreases, execute the quick-open command.

[0027] The valve's operating speed is executed according to the pre-calibrated water hammer intensity-operating speed correspondence curve, enabling the valve to complete the specified stroke to counteract the water hammer peak.

[0028] Furthermore, by taking the minimum pressure fluctuation across the entire line and the minimum total system energy consumption as dual objective functions, the optimal pressure setpoints for each control point are solved through iterative calculation. The specific method is as follows:

[0029] Using a multi-objective genetic algorithm, under constraints such as the maximum allowable pressure of the pipeline, the minimum negative pressure, and the valve adjustment range, the algorithm optimizes and calculates a set of set values ​​that minimizes the pressure variance at all monitoring points along the entire line and the total energy consumption of each pumping station.

[0030] Furthermore, a multi-objective genetic algorithm is employed to optimize and calculate a set of setpoints that minimizes the pressure variance at all monitoring points along the entire line and minimizes the total energy consumption of all pumping stations. This process includes the following steps:

[0031] Minimize the pressure variance of N pressure monitoring points along the entire line and minimize the total energy consumption of M pumping stations along the entire line as dual objective functions, and use the maximum allowable pressure of the pipeline, the minimum pressure that does not generate negative pressure, the valve opening adjustment range, and the pressure change rate limit as constraints.

[0032] With a population size of 100 and an iteration count of 200 generations, a set of non-dominated solutions that meet the constraints is calculated through selection, crossover, and mutation operations. Each solution in this set represents a balance between pressure fluctuations and system energy consumption.

[0033] From this solution set, select the set of solutions that minimizes the weighted sum of the two objective functions, pressure variance and total energy consumption, as the optimal pressure setpoint for each control point;

[0034] The weighting coefficient for pressure variance can be selected as 0.6, and the weighting coefficient for total energy consumption can be selected as 0.4.

[0035] Furthermore, when the PLC collects data in real time and performs judgment and control according to a 100ms scanning cycle, if a communication failure is detected, the following fault autonomous response procedure will be executed:

[0036] When the PLC detects that the backbone network communication with the Supervisory Control and Data Acquisition (SCADA) system master station has been interrupted for more than 30 seconds, it automatically switches the control mode from remote setpoint tracking mode to local experience mode, and continues to execute local closed-loop control based on the last setpoint received before the communication interruption as the control target.

[0037] If the set value is not received before the communication is interrupted, the PLC will automatically match the corresponding pressure safety value as the control target from the internally stored flow-pressure correspondence data table based on the current real-time monitored pipeline flow.

[0038] After communication is restored, if the PLC receives a stable setpoint from the Supervisory Control and Data Acquisition (SCADA) system for three consecutive scan cycles and the local pressure fluctuation is less than the preset range, the control target value will be gradually transitioned to the newly received remote setpoint within 30 seconds.

[0039] Furthermore, in step three, the specific method by which the PLC forcibly executes the valve's quick-closing or quick-opening action after determining that a water hammer condition has occurred is as follows:

[0040] The PLC determines the nature of the water hammer wave based on the positive and negative directions of the pressure change rate.

[0041] If the pressure rises within 1 second and exceeds 0.2 MPa, it is determined to be a positive water hammer, and a valve quick-closing command is executed;

[0042] If the pressure drops by more than 0.15 MPa within 1 second, it is determined to be negative water hammer, and a valve quick-opening command is executed;

[0043] The valve actuation speed is executed according to a pre-calibrated water hammer intensity-actuation speed curve. The water hammer intensity is divided into three levels based on the absolute value of the pressure change rate, and the corresponding valve actuation speeds are as follows:

[0044] During a first-stage water hammer, the valve actuation speed is 10 degrees per second.

[0045] During a secondary water hammer, the valve actuation speed is 20 degrees / second;

[0046] The valve actuation speed is 30 degrees / second during a third-stage water hammer.

[0047] Furthermore, when the PLC executes local autonomous closed-loop control, it also simultaneously performs an online correction step for valve action deviation, specifically:

[0048] In each control cycle, the PLC reads the actual opening value fed back by the hydraulic butterfly valve actuator through the fieldbus control system and calculates the deviation from the commanded opening value.

[0049] When the deviation exceeds the set threshold for three consecutive control cycles, the PLC automatically triggers the valve zero-point calibration process, sends a full-close command to the hydraulic butterfly valve actuator and records the full-close position feedback value, then sends a full-open command and records the full-open position feedback value, and recalibrates the valve opening degree-feedback correspondence curve based on the newly recorded full-close and full-open position values.

[0050] After calibration, the PLC stores the updated correspondence curve in its memory and uses it as the basis for calculating the opening feedback in subsequent control cycles.

[0051] Furthermore, in step four, when the Supervisory Control and Data Acquisition (SCADA) system master station runs the hydraulic simulation model, it also performs a multi-timescale prediction and correction step, which specifically includes the following steps:

[0052] The Supervisory Control and Data Acquisition (SCADA) system master station simultaneously runs two hydraulic simulation models with different time scales: a short-time prediction model and a long-time planning model.

[0053] Among them, the short-term forecasting model uses 1 minute as the cycle and predicts the pressure change trend in the next 30 minutes based on historical data from the past 15 minutes, which is used to quickly respond to sudden changes in water demand.

[0054] The long-term planning model uses one hour as a cycle and predicts the pressure change trend in the next 6 hours based on historical data from the past 24 hours, in order to smooth out the peak and valley fluctuations in water consumption during the day.

[0055] The Supervisory Control and Data Acquisition (SCADA) system master station weighted and fused the output results of the short-term prediction model and the long-term planning model to generate the final optimal pressure setpoint.

[0056] After each global optimization setting is completed, the Supervisory Control and Data Acquisition (SCADA) system master station feeds back the actual pressure and flow data of the current cycle to the two hydraulic simulation models to correct the prediction deviations of the models and update the model parameters.

[0057] Furthermore, the Supervisory Control and Data Acquisition (SCADA) system master station periodically performs online valve performance evaluations, specifically including the following steps:

[0058] The Supervisory Control and Data Acquisition (SCADA) system master station compiles the historical valve action data uploaded by each PLC every 24 hours, and calculates the root mean square value of the set opening degree - actual opening degree following error, the average value of the full stroke opening time, the average value of the full stroke closing time, and the number of actions for each hydraulic butterfly valve in the past 24 hours.

[0059] The four indicators mentioned above are compared with the historical benchmark values ​​of the valve. When the deviation rate of any indicator exceeds 20%, the valve icon is highlighted in yellow and a warning message pops up on the human-machine interface of the Supervisory Control and Data Acquisition (SCADA) system to prompt maintenance personnel to conduct preventive inspections of the valve.

[0060] Furthermore, the parameters of the actuator and the hydraulic butterfly valve are obtained, and combined with the parameters corrected historically, to perform real-time compensation of the hydraulic butterfly valve fluid torque on the intermediate valve opening adjustment, resulting in a compensation amount, including:

[0061] Obtain the factory calibration parameters of the hydraulic butterfly valve, and collect and calculate the real-time pressure difference between the upstream and downstream sides of the hydraulic butterfly valve based on the pressure sensor.

[0062] Based on the factory calibration parameters and real-time pressure difference of the hydraulic butterfly valve, the fluid torque of the hydraulic butterfly valve is calculated.

[0063] Based on the fluid torque of the hydraulic butterfly valve and the factory calibration parameters of the actuator, the real-time compensated angular displacement based on the fluid torque of the hydraulic butterfly valve is calculated.

[0064] Based on the relationship between angular displacement and compensation amount, the compensation amount corresponding to the real-time compensation angular displacement of the fluid torque of the hydraulic butterfly valve is determined.

[0065] Compared with the prior art, the beneficial effects of the present invention are:

[0066] This invention constructs a hierarchical control architecture that coordinates a distributed measurement and control network based on a fieldbus control system with a remote monitoring platform for supervisory control and data acquisition systems. This architecture enables closed-loop control of hydraulic butterfly valves in long-distance water transmission systems. At the equipment level, the PLC's built-in variable-parameter PID control algorithm immediately suppresses sudden water hammer conditions at the millisecond level by clearing the integral term, amplifying the proportional gain, and forcibly executing fast-closing / fast-opening valve actions when the pressure change rate exceeds the limit. This solves the problem of delayed response and ineffective water hammer suppression in traditional single-point PID control, thereby reducing the risk of PCCP pipeline rupture caused by sudden pressure changes. At the central control and data acquisition system, the master station iteratively solves the optimal pressure setpoint across the entire line using a hydraulic simulation model with a dual-objective function. This avoids the limitations of lack of global coordination among valve points in traditional manual scheduling or independent control modes. Thus, while ensuring the pipeline's maximum allowable pressure and minimizing negative pressure, the system minimizes total energy consumption. In complex water transmission systems with long distances, large time delays, and strong coupling, this achieves a comprehensive improvement in operational safety, pressure stability, and energy efficiency. Attached Figure Description

[0067] Figure 1The flowchart is a closed-loop control method for the hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to the present invention.

[0068] Figure 2 This is an execution diagram of the closed-loop control method for the hydraulic butterfly valve in a long-distance high-pressure water transmission pipeline according to the present invention. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] To address the challenges in existing technologies for long-distance water transmission systems, such as significant time delays, strong coupling characteristics, and independent operation of valve control points, which make it difficult to effectively suppress water hammer during pump start-up / shutdown or sudden changes in water consumption, and thus fail to balance pipeline pressure safety with optimal overall system energy consumption, please refer to [the relevant documentation / reference]. Figures 1-2 This embodiment provides the following technical solution:

[0071] A closed-loop control method for hydraulically controlled butterfly valves in a PCCP long-distance high-pressure water transmission pipeline is disclosed, applicable to a long-distance high-pressure water transmission system composed of PCCP pipelines. The system includes multiple hydraulically controlled butterfly valves distributed along the pipeline. The method includes the following steps:

[0072] Step 1: Construct a distributed measurement and control network based on a fieldbus control system. Connect the actuators of each hydraulic butterfly valve, as well as the pressure and flow sensors deployed upstream and downstream of the valve, to the corresponding PLC via the fieldbus protocol. Make the PLC have a built-in variable parameter PID control algorithm that includes water hammer pressure suppression logic.

[0073] The fieldbus protocol uses the PROFINET IRT industrial Ethernet protocol, and the network parameters are configured as follows:

[0074] Set the cyclic data exchange cycle between the PLC and the hydraulic butterfly valve actuator to 20ms, set the cyclic data exchange cycle between the PLC and the pressure sensor and flow sensor to 50ms, set the maximum number of slave stations in each bus segment to no more than 16, and ensure that the end-to-end control delay time from sensor data acquisition to actuator action completion is less than 100ms.

[0075] Step 2: Establish a remote monitoring platform for the Supervisory Control and Data Acquisition (SCADA) system, connect all PLCs to the SCADA system master station through the backbone network, and deploy the full-line hydraulic simulation model in the SCADA system master station;

[0076] Step 3: The PLC executes local autonomous closed-loop control. The PLC collects upstream and downstream pressure and flow values ​​in real time according to a 100ms scan cycle, and performs the following judgments and controls:

[0077] If the pressure change rate is not detected to exceed the preset safety threshold, the valve opening adjustment amount is calculated according to the deviation between the current pressure value and the locally stored set value using the conventional PID algorithm, and then output to the hydraulic butterfly valve actuator through the fieldbus control system.

[0078] If the pressure change rate is detected to exceed the preset safety threshold, it is determined to be a water hammer condition. The PLC immediately clears the integral term of the PID algorithm to zero, adjusts the proportional gain to 1.5-3 times the normal value, and forces the valve to close or open quickly until the pressure change rate returns to within the safety threshold, and then smoothly switches back to the normal PID algorithm.

[0079] Step 4: The Supervisory Control and Data Acquisition (SCADA) system performs global optimization settings. The SCADA system master station collects pressure, flow, and valve opening data uploaded by each PLC along the entire line at a cycle of 1-5 minutes. It runs the hydraulic simulation model and, combined with the current operating status of the pumping station and changes in water demand, uses minimizing the pressure fluctuation and minimizing the total energy consumption of the system as the dual objective functions. The optimal pressure setpoint for each control point is solved through iterative calculation.

[0080] Step 5: The Supervisory Control and Data Acquisition (SCADA) system master station sends the optimal pressure setpoint calculated in Step 4 to the corresponding PLC through the backbone network. After receiving the optimal setpoint, the PLC automatically replaces the original setpoint stored locally and repeats the local autonomous closed-loop control in Step 3.

[0081] In this embodiment, when the PLC executes local autonomous closed-loop control in step three, it also automatically switches the parameter group in the variable parameter PID control algorithm according to the pipeline operating conditions, specifically including the following steps:

[0082] The PLC has three sets of different PID control parameters pre-stored, each corresponding to one of the three different pipeline operating conditions:

[0083] The first set of parameters is the normal operating parameters: proportional coefficient Kp = 1.2, integral time Ti = 60s, and derivative time Td = 5s;

[0084] The second set of parameters is for water hammer suppression: proportional coefficient Kp=2.5, integral time Ti=∞, and differential time Td=2s, which means the integral term is cleared and the proportional gain is enhanced.

[0085] The third set consists of start-stop transient parameters: proportional coefficient Kp = 0.8, integral time Ti = 120s, and derivative time Td = 8s;

[0086] The PLC monitors the pressure change rate and valve operating status in real time during each scan cycle, and automatically identifies the current operating condition and switches to the corresponding parameter group according to the following rules:

[0087] When the absolute value of the pressure change rate is less than 0.05 MPa / s and the valve opening change rate is less than 5% / s, it is determined to be a normal operating condition, and the first set of normal operating parameters is selected.

[0088] When the absolute value of the pressure change rate is detected to be greater than or equal to 0.05 MPa / s and less than 0.15 MPa / s, and the valve is in the start-up process after being fully closed or fully open, it is determined to be a start-stop transition condition, and the third set of start-stop transition parameters is selected.

[0089] When the absolute value of the pressure change rate is detected to be greater than or equal to 0.15 MPa / s, it is determined to be a water hammer suppression condition. The second set of water hammer suppression parameters is immediately selected, and after the pressure change rate recovers to below 0.05 MPa / s and continues for 10 scan cycles, it is smoothly switched back to the first set of normal operating parameters.

[0090] The technical effects of the above solution are as follows: By constructing a high real-time distributed measurement and control network based on the fieldbus protocol and configuring the cycle time and number of slave stations for each node, the end-to-end control delay from pressure and flow sensing to valve action can be ensured to be less than 100ms, thus laying a hardware foundation for the rapid suppression of water hammer pressure; the variable parameter PID control algorithm built into the PLC can switch to the optimal control parameter set in real time and automatically according to the pressure change rate. In particular, it can instantly clear the integral term and enhance the proportional gain when water hammer is detected, which can force fast closing or fast opening actions, thereby rapidly suppressing destructive water hammer pressure within seconds. The system also avoids secondary impacts on control actions through a smooth switching mechanism after pressure change rate recovery, thereby improving the operational safety and stability of PCCP pipelines during high-pressure water transmission. In addition, combined with the full-line hydraulic simulation model deployed by the SCADA system, global optimization calculations with the dual objectives of minimizing pressure fluctuations and minimizing total system energy consumption can be performed at minute-level cycles, and the local pressure setpoints of each PLC can be dynamically updated. This achieves the organic unity of local rapid closed-loop control and global collaborative optimization, giving the entire long-distance water transmission system comprehensive performance of high response speed, high reliability, and economical and efficient operation.

[0091] In one embodiment, the method further includes: correcting the valve opening adjustment amount based on the opening deviation between the actual opening degree of the hydraulic butterfly valve and the calculated valve opening adjustment amount, specifically as follows:

[0092] After the PLC executes local autonomous closed-loop control, the actual opening degree of the hydraulic butterfly valve is obtained, and the opening degree deviation between the actual opening degree and the calculated valve opening degree adjustment amount is obtained.

[0093] The pressure value of the PCCP pipeline is obtained when the PLC executes local autonomous closed-loop control. Based on the pressure value, the disturbance deviation of the hydraulic butterfly valve is determined. Based on the difference between the opening deviation and the disturbance deviation, the opening deviation to be corrected is obtained.

[0094] The system acquires the opening deviation to be corrected within a preset number of times the PLC executes local autonomous closed-loop control, forms a deviation sequence, calculates the rate of change of deviation between adjacent deviations in the deviation sequence, and calculates the regularity index of the deviation sequence. When the rate of change of all deviations between adjacent deviations is less than the preset deviation rate of change threshold and the regularity index is greater than the preset regularity index threshold, it is determined that the opening deviation to be corrected has a systematic cumulative deviation, and opening correction is triggered. Otherwise, it is determined that the opening deviation to be corrected is not a systematic cumulative deviation, and opening correction is not triggered.

[0095] Once the opening correction is triggered, the mapping relationship between the actual opening and the opening adjustment is corrected based on the difference between the opening deviation to be corrected and the historical opening deviation to be corrected corresponding to the previous correction, to obtain the latest mapping relationship. The valve opening adjustment amount is then initially corrected based on the latest mapping relationship to obtain the intermediate valve opening adjustment amount.

[0096] The parameters of the actuator and the hydraulic butterfly valve are obtained. Combined with the parameters of historical calibration, the hydraulic butterfly valve fluid torque is compensated in real time for the opening adjustment of the intermediate valve to obtain the compensation amount. Based on the compensation amount, the opening adjustment of the intermediate valve is compensated to obtain the final valve opening adjustment amount.

[0097] In this embodiment, the mapping relationship between actual opening degree and opening degree adjustment is, for example, that the original actual opening degree was 2, and the corresponding opening degree adjustment value was 0.5. Now the deviation difference has increased by 0.1, and the corresponding opening degree adjustment value is modified to 0.6.

[0098] In this embodiment, the preset deviation change rate threshold and the preset regularity index threshold are preset based on historical experience and actual conditions.

[0099] In this embodiment, the regularity index of the deviation sequence can be determined, for example, by the Lyapunov index. A value less than zero indicates that the deviation sequence tends to a steady state and the regularity index is large; a value greater than or equal to 0 indicates that the deviation sequence is irregular and the regularity index is small.

[0100] In this embodiment, the preset number of times is, for example, 5, that is, after the PLC performs local autonomous closed-loop control 5 times, the deviation is analyzed and the valve opening adjustment is corrected.

[0101] In this embodiment, the pressure value of the PCCP pipeline will cause a slight displacement of the hydraulic butterfly valve. This is a disturbance deviation that does not need to be corrected. The opening deviation to be corrected includes hydraulic deviation, mechanical deviation, and sensing deviation, etc.

[0102] The beneficial effects of the above design scheme are as follows: By quantifying disturbance deviations based on real-time pipeline pressure values, external disturbances such as fluid torque changes and pressure transients are directly correlated and eliminated from the total opening deviation. This ensures that the deviation to be corrected only reflects the valve's actual performance degradation or mapping relationship deviation, avoiding misjudging temporary disturbances as systemic problems. It requires that the rate of change of adjacent deviations be less than a preset value, and that the deviation sequence exhibit strong regularity, ensuring that the deviation triggering correction is steadily accumulated. This distinguishes between systemic and random deviations, significantly reducing the misjudgment rate of correction triggering. It avoids both over-correction and under-correction, ensuring that correction actions are triggered only when necessary. To improve the stability of system control, the mapping relationship is adjusted based on the difference between the current deviation to be corrected and the historical correction deviation, realizing iterative optimization of the mapping relationship. Each correction is based on historical correction data, allowing the mapping relationship to be dynamically adjusted as valve performance deteriorates, always maintaining a precise match between the actual opening degree and the adjustment amount. Combined with the actuator parameters and hydraulic butterfly valve parameters, the adjustment deviation caused by the differences in the characteristics of the equipment itself is compensated: different valves have different manufacturing errors and different degrees of aging of actuators. Personalized compensation can be achieved through parameter adaptation, avoiding insufficient local adjustment accuracy caused by uniform correction standards, and ultimately achieving continuous stability of valve opening adjustment accuracy.

[0103] In one embodiment, the process of acquiring the parameters of the actuator and the hydraulic butterfly valve, and combining them with historically corrected parameters, to perform real-time compensation of the hydraulic butterfly valve fluid torque on the intermediate valve opening adjustment amount, thereby obtaining the compensation amount, includes:

[0104] Obtain the factory calibration parameters of the hydraulic butterfly valve, and collect and calculate the real-time pressure difference between the upstream and downstream sides of the hydraulic butterfly valve based on the pressure sensor.

[0105] Based on the factory calibration parameters and real-time pressure difference of the hydraulic butterfly valve, the fluid torque T of the hydraulic butterfly valve is calculated as follows:

[0106] ;

[0107] in, This indicates the real-time pressure difference between the upstream and downstream sides of the hydraulic butterfly valve. represents the natural constant, with a value of 3.14. This indicates the valve opening degree of the hydraulic butterfly valve. The effective area of ​​the valve plate under pressure. This indicates the real-time valve opening degree of the hydraulic butterfly valve. This indicates the single eccentricity of the hydraulic butterfly valve. Indicates the effective radius of the valve plate of the hydraulic butterfly valve;

[0108] Based on the fluid torque of the hydraulic butterfly valve and obtaining the factory calibration parameters of the actuator, the real-time compensated angular displacement based on the fluid torque of the hydraulic butterfly valve is calculated. ;

[0109] ;

[0110] in, This represents the total moment of inertia of the actuator of a hydraulic butterfly valve. This indicates the control scan cycle of the PLC. This indicates the torque gain coefficient of the actuator of the hydraulic butterfly valve. This indicates the control voltage output from the PLC to the actuator of the hydraulic butterfly valve. This is the historical compensation angular displacement from the previous control scan cycle of the PLC. This is the historical compensation angular displacement for the second and third control scan cycles of the PLC;

[0111] Based on the relationship between angular displacement and compensation amount, the compensation amount corresponding to the real-time compensation angular displacement of the fluid torque of the hydraulic butterfly valve is determined.

[0112] In this embodiment, the total moment of inertia of the actuator of the hydraulic butterfly valve is measured in kg / These are parameters for Guo Yong, and they do not change with operating conditions; they are factory calibration values.

[0113] In this embodiment, the torque gain coefficient is expressed in Nm / V, which is the factory calibration value.

[0114] In this embodiment, the single eccentricity of the hydraulic butterfly valve is obtained based on the factory calibration parameters of the hydraulic butterfly valve, and is the distance between the center of the valve stem and the center of the valve plate, which affects the size of the fluid lever arm.

[0115] In this embodiment, the unit of real-time pressure difference is Pascal.

[0116] In this embodiment, ,in, This indicates the effective port diameter of the valve plate in a hydraulic butterfly valve. These two values, representing the valve plate thickness of the hydraulic butterfly valve, are obtained from the valve's factory specifications. =2 / d.

[0117] In this embodiment, the relationship between angular displacement and compensation amount is predetermined based on historical experience and actual conditions.

[0118] The beneficial effects of the above design scheme are as follows: By using the factory calibration parameters of the hydraulic butterfly valve as the calculation parameters for fluid torque, the calculation deviation caused by adapting a unified model to all valves is avoided, achieving one-to-one personalized torque calculation. The pressure sensor collects and calculates the pressure difference between the upstream and downstream of the valve in real time, directly reflecting the real-time operating conditions of the pipeline water transport. This allows for rapid response to changes in operating conditions, avoiding torque calculation lag caused by pressure fluctuations and ensuring that the fluid torque always matches the actual operating conditions. By incorporating the actuator's factory calibration parameters when calculating the compensation angular displacement, the compensation action strictly matches the physical limits and dynamic characteristics of the actuator, avoiding compensation action errors caused by parameter mismatch. Furthermore, by incorporating the PLC control scan cycle, the timing of the compensation angular displacement calculation is completely synchronized with the PLC's local autonomous closed-loop control. This step avoids the misalignment of compensation actions with valve control rhythm caused by differences in calculation cycles, ensuring that the compensation amount can be superimposed on the intermediate valve opening adjustment amount in real time without interfering with the continuity of the original control logic. By incorporating the historical compensation angular displacement of the previous one or two control cycles, the calculation of the current compensation angular displacement is based on the historical adjustment effect, so that the compensation accuracy continues to improve with the operating cycle. The angular displacement and valve opening are on the same physical dimension. Through the mapping relationship between the two, the compensation angular displacement corresponding to the fluid torque is directly converted into a valve opening compensation amount that can be directly superimposed. This allows the opening control of the hydraulic butterfly valve to resist both internal performance degradation and external flow field disturbances. Under the complex working conditions of PCCP long-distance high-pressure water transmission, the control accuracy, stability and working condition adaptability of the system are further improved.

[0119] Local storage settings include three sources, selected in the following priority order:

[0120] Highest priority: Optimal pressure setpoints issued in real time by the Supervisory Control and Data Acquisition (SCADA) system master station;

[0121] Secondary priority: When communication is interrupted, the PLC automatically recalls the last Supervisory Control and Data Acquisition (SCADA) system settings received before the communication interruption;

[0122] Basic priority: When the PLC is put into operation for the first time or when there are no SCADA system commands for a long time, the corresponding pressure safety value is automatically matched from the pre-stored flow-pressure data table in the PLC according to the current measured flow.

[0123] The technical effects of the above solution are as follows: By constructing a three-level priority-based setpoint source mechanism, the control robustness and autonomous intelligence of long-distance high-pressure water transmission systems can be enhanced. The highest priority ensures that the optimal pressure setpoint calculated by the SCADA master station based on the hydraulic model of the entire system can be issued and executed in real time, achieving the coordinated control goal of optimal global energy efficiency and minimal pressure fluctuation. The secondary priority design is highly practical in engineering; in abnormal situations such as communication interruption, the PLC can seamlessly switch to the last received valid setpoint, thus avoiding control blind spots caused by communication failures and ensuring stable system operation during fault transitions, saving valuable time for maintenance and repair. The basic priority provides a reliable safety net for initial system commissioning or long-term offline states. Relying on pre-stored flow-pressure data tables, the PLC can automatically match safe pressure values ​​based on real-time flow, ensuring that even in isolated operation mode without external commands, the pipeline pressure will not exceed the safe range, thus avoiding overpressure risks caused by human error or data loss. Based on the above three-level priority settings, the long-term safe operation of the PCCP pipeline is effectively guaranteed.

[0124] The integral term of the PID algorithm is cleared to zero, the proportional gain is adjusted to 1.5-3 times the normal value, and the valve is forced to close or open quickly. The specific steps include:

[0125] The PLC determines the nature of the water hammer wave based on the positive and negative directions of the pressure change rate.

[0126] If the pressure suddenly increases, execute the quick-close command; if the pressure suddenly decreases, execute the quick-open command.

[0127] The valve's operating speed is executed according to the pre-calibrated water hammer intensity-operating speed correspondence curve, enabling the valve to complete the specified stroke to counteract the water hammer peak.

[0128] In this embodiment, the valve action speed is executed according to the pre-calibrated water hammer intensity-action speed correspondence curve. The water hammer intensity is divided into multiple levels according to the absolute value of the pressure change rate. Each level corresponds to a preset valve action speed to ensure that the valve action is performed at the fastest speed to offset the peak during strong water hammer and at a moderate speed during medium-intensity water hammer to avoid triggering secondary water hammer.

[0129] During valve operation, the PLC continuously collects pressure change data in real time at 10ms intervals, dynamically calculates the deviation between the current pressure change rate and the target suppression curve, and finely adjusts the valve's operating speed in real time based on the deviation to achieve variable rate closed-loop regulation.

[0130] When the pressure change rate recovers to 80% of the safe threshold, the PLC automatically starts to smoothly reduce the valve action speed and gradually restores the integral term of the PID control algorithm and gradually restores the proportional gain to the normal value. After the pressure change rate fully recovers to the safe threshold and remains stable for 3 scan cycles, it fully switches back to the normal PID algorithm, thereby achieving a seamless switch from water hammer suppression mode to normal regulation mode.

[0131] The technical effects of the above solution are as follows: By introducing an intelligent judgment mechanism for the nature of water hammer waves and an adaptive valve action mechanism, it is possible to accurately suppress water hammer conditions. The PLC can quickly identify the nature of water hammer waves based on the positive or negative direction of the pressure change rate and execute fast closing or fast opening actions accordingly, thereby avoiding control direction errors caused by misjudgment and preventing the aggravation of water hammer hazards. At the same time, the valve action is executed according to the pre-calibrated water hammer intensity-action speed correspondence curve, so that the valve adjustment amount and the real-time water hammer energy are dynamically matched. This can not only offset the pressure peak at a sufficient speed during strong water hammer, but also avoid over-adjustment that could cause secondary water hammer.

[0132] The optimal pressure setpoints for each control point are determined by using the minimum overall pressure fluctuation and the minimum total system energy consumption as dual objective functions. The specific method is as follows:

[0133] Using a multi-objective genetic algorithm, under constraints such as the maximum allowable pressure of the pipeline, the minimum negative pressure, and the valve adjustment range, the algorithm optimizes and calculates a set of setpoints that minimizes the pressure variance at all monitoring points along the entire line and the total energy consumption of all pumping stations. The specific steps include:

[0134] Minimize the pressure variance of N pressure monitoring points along the entire line and minimize the total energy consumption of M pumping stations along the entire line as dual objective functions, and use the maximum allowable pressure of the pipeline, the minimum pressure that does not generate negative pressure, the valve opening adjustment range, and the pressure change rate limit as constraints.

[0135] With a population size of 100 and an iteration count of 200 generations, a set of non-dominated solutions that meet the constraints is calculated through selection, crossover, and mutation operations. Each solution in this set represents a balance between pressure fluctuations and system energy consumption.

[0136] From this solution set, select the set of solutions that minimizes the weighted sum of the two objective functions, pressure variance and total energy consumption, as the optimal pressure setpoint for each control point;

[0137] The weighting coefficient for pressure variance can be selected as 0.6, and the weighting coefficient for total energy consumption can be selected as 0.4.

[0138] The technical effects of the above solution are as follows: A multi-objective genetic algorithm is used to globally optimize the long-distance high-pressure water transmission system, achieving an intelligent balance between pressure fluctuation control and energy economy; by minimizing the overall pressure variance and the total energy consumption of the pumping stations as dual objective functions, and performing iterative calculations under multiple constraints such as pipeline pressure-bearing capacity, negative pressure protection, and valve adjustment range, the engineering safety and feasibility of the optimization results are guaranteed; setting a population size of 100 and an iteration cycle of 200 generations ensures that a high-quality non-dominated solution set can be efficiently searched in complex nonlinear hydraulic systems, thus providing operators with multiple balanced solutions that consider both stability and economy; the above design enables the SCADA system to dynamically generate globally coordinated optimal control objectives, thereby minimizing water transmission energy consumption while ensuring hydraulic stability throughout the entire line.

[0139] When the PLC collects data in real time and performs judgment and control according to a 100ms scan cycle, if a communication failure is detected, the following fault autonomous response procedure will be executed:

[0140] When the PLC detects that the backbone network communication with the Supervisory Control and Data Acquisition (SCADA) system master station has been interrupted for more than 30 seconds, it automatically switches the control mode from remote setpoint tracking mode to local experience mode, and continues to execute local closed-loop control based on the last setpoint received before the communication interruption as the control target.

[0141] If the set value is not received before the communication is interrupted, the PLC will automatically match the corresponding pressure safety value as the control target from the internally stored flow-pressure correspondence data table based on the current real-time monitored pipeline flow.

[0142] After communication is restored, when the PLC receives a stable setpoint from the Supervisory Control and Data Acquisition (SCADA) system for three consecutive scan cycles and the local pressure fluctuation is less than the preset range, the control target value will be gradually transitioned to the newly received remote setpoint within 30 seconds to achieve a seamless switching.

[0143] The technical effects of the above solution are as follows: When the backbone network is interrupted for more than 30 seconds, the PLC automatically switches to local experience mode, prioritizing the use of the last valid setpoint as the control target to ensure the continuity of the control strategy. If no data is available, the safe pressure value is dynamically matched according to the pre-stored flow-pressure correspondence table, which can achieve autonomous safety assurance in the isolated operation state, thereby avoiding control blind spots caused by communication failure. After communication is restored, the stability of the remote setpoint is verified through multiple consecutive scanning cycles, and the switching timing is determined in combination with local pressure fluctuation conditions. Then, a 30-second gradual transition is used to smoothly transition to the remote setpoint, effectively avoiding pressure oscillations and secondary water hammer risks caused by sudden changes in the control target. This mechanism realizes seamless connection and bumpless switching between remote centralized control and local autonomous operation, thus providing a reliable guarantee for the all-weather safe operation of long-distance high-pressure water transmission systems.

[0144] In step three, the specific method by which the PLC forcibly executes the valve quick-closing or quick-opening action after determining that a water hammer condition has occurred is as follows:

[0145] The PLC determines the nature of the water hammer wave based on the positive and negative directions of the pressure change rate.

[0146] If the pressure rises within 1 second and exceeds 0.2 MPa, it is determined to be a positive water hammer, and a valve quick-closing command is executed;

[0147] If the pressure drops by more than 0.15 MPa within 1 second, it is determined to be negative water hammer, and a valve quick-opening command is executed;

[0148] The valve actuation speed is executed according to a pre-calibrated water hammer intensity-actuation speed curve. The water hammer intensity is divided into three levels based on the absolute value of the pressure change rate, and the corresponding valve actuation speeds are as follows:

[0149] During a first-stage water hammer, the valve actuation speed is 10 degrees per second.

[0150] During a secondary water hammer, the valve actuation speed is 20 degrees / second;

[0151] The valve actuation speed is 30 degrees / second during a third-stage water hammer.

[0152] The technical effects of the above solution are as follows: The PLC accurately identifies the positive and negative water hammer nature based on the pressure change amplitude within 1 second, and executes fast closing or fast opening commands accordingly. The water hammer intensity is divided into three levels, and the corresponding valve action speed is pre-calibrated, so that the valve adjustment rate and water hammer energy are dynamically matched. Through the hierarchical and progressive control logic, the traditional single fast action can be optimized into adaptive damping control based on water hammer intensity. This ensures both the rapid suppression capability during strong water hammer and the prevention of over-adjustment during weak water hammer, thereby minimizing the structural impact of water hammer on the PCCP pipeline.

[0153] When the PLC performs local autonomous closed-loop control, it also simultaneously performs an online correction step for valve action deviation, specifically:

[0154] In each control cycle, the PLC reads the actual opening value fed back by the hydraulic butterfly valve actuator through the fieldbus control system and calculates the deviation from the commanded opening value.

[0155] When the deviation exceeds the set threshold (e.g., ±2%) for three consecutive control cycles, the PLC automatically triggers the valve zero-point calibration process, sends a full-close command to the hydraulic butterfly valve actuator and records the full-close position feedback value, then sends a full-open command and records the full-open position feedback value, and recalibrates the valve opening degree-feedback correspondence curve based on the newly recorded full-close and full-open position values.

[0156] After calibration, the PLC stores the updated correspondence curve in its memory and uses it as the basis for calculating the opening feedback in subsequent control cycles.

[0157] The technical effects of the above solution are as follows: By introducing an online valve action deviation correction mechanism, the control accuracy and reliability of the hydraulic butterfly valve in the PCCP water transmission system can be improved over a long period of time. The PLC compares the commanded opening degree with the actual feedback value in real time during each control cycle. When the deviation continues to exceed the limit, it can automatically identify changes in actuator characteristics caused by mechanical wear, sensor drift, or foreign object obstruction, and promptly trigger the automatic zero-point and full-scale calibration process. By re-recording the feedback values ​​of the fully closed and fully open positions and updating the opening degree-feedback correspondence curve, accumulated errors can be effectively eliminated, ensuring that the valve always executes actions according to the precise opening command, avoiding over-adjustment or under-adjustment caused by control deviation. Introducing the online valve action deviation correction mechanism not only ensures the accuracy of valve actions under critical operating conditions such as water hammer suppression, but also reduces the frequency and cost of manual on-site calibration.

[0158] In step four, when the Supervisory Control and Data Acquisition (SCADA) system master station runs the hydraulic simulation model, it also performs a multi-timescale prediction and correction step, which specifically includes the following steps:

[0159] The Supervisory Control and Data Acquisition (SCADA) system master station simultaneously runs two hydraulic simulation models with different time scales: a short-time prediction model and a long-time planning model.

[0160] Among them, the short-term forecasting model uses 1 minute as the cycle and predicts the pressure change trend in the next 30 minutes based on historical data from the past 15 minutes, which is used to quickly respond to sudden changes in water demand.

[0161] The long-term planning model uses one hour as a cycle and predicts the pressure change trend in the next 6 hours based on historical data from the past 24 hours, in order to smooth out the peak and valley fluctuations in water consumption during the day.

[0162] The Supervisory Control and Data Acquisition (SCADA) system master station weighted and fused the outputs of the short-term prediction model and the long-term planning model to generate the final optimal pressure setpoint.

[0163] Under normal circumstances, the weighting coefficient of the short-term prediction model is set to 0.3, and the weighting coefficient of the long-term planning model is set to 0.7.

[0164] If a sudden change in flow rate is detected to exceed 10% / min, the weight coefficient of the short-term prediction model will be temporarily adjusted to 0.8, and the weight coefficient of the long-term planning model will be adjusted to 0.2, in order to enhance the response speed to sudden operating conditions.

[0165] After each global optimization setting is completed, the Supervisory Control and Data Acquisition (SCADA) system master station feeds back the actual pressure and flow data of the current cycle to the two hydraulic simulation models to correct the prediction deviations of the models and update the model parameters.

[0166] The technical effects of the above-mentioned solution are as follows: By constructing a multi-timescale prediction and correction mechanism, the dynamic optimization capability of the SCADA system for long-distance water conveyance processes is significantly improved. Specifically, the main station simultaneously runs two types of hydraulic models, short-term and long-term, capturing sudden changes in water use and daytime peak-valley patterns at minute and hourly cycles, respectively, thereby achieving comprehensive perception of complex water use patterns. By weighted fusion of the prediction results of the two types of models and dynamically adjusting the weight coefficients according to the flow mutation rate, the system prioritizes long-term planning to ensure overall stability under normal conditions, and then quickly switches to the short-term prediction-dominated mode under sudden conditions, thereby enhancing the response speed and adaptability to emergency events. In addition, after each optimization cycle, the measured data is used to correct model deviations and update parameters, forming a closed-loop iterative optimization self-learning mechanism, which continuously improves prediction accuracy over time.

[0167] The Supervisory Control and Data Acquisition (SCADA) system master station periodically performs online valve performance evaluations, specifically including the following steps:

[0168] The Supervisory Control and Data Acquisition (SCADA) system master station compiles the historical valve action data uploaded by each PLC every 24 hours, and calculates the root mean square value of the set opening degree - actual opening degree following error, the average value of the full stroke opening time, the average value of the full stroke closing time, and the number of actions for each hydraulic butterfly valve in the past 24 hours.

[0169] The four indicators mentioned above are compared with the historical benchmark values ​​of the valve. When the deviation rate of any indicator exceeds 20%, the valve icon is highlighted in yellow and a warning message pops up on the human-machine interface of the Supervisory Control and Data Acquisition (SCADA) system to prompt maintenance personnel to conduct preventive inspections of the valve.

[0170] The technical benefits of the above solution are as follows: The SCADA system master station automatically calculates key performance indicators for each valve daily, such as opening follow-up error, full-stroke opening and closing time, and number of actions. It then compares these indicators with historical benchmark values ​​for the same period, enabling timely identification of potential fault risks in the early stages of equipment performance degradation. When the deviation rate of any indicator exceeds 20%, a visual alarm is immediately displayed on the human-machine interface with a highlighted yellow icon and a warning prompt. This provides maintenance personnel with intuitive and accurate equipment status awareness and preventative maintenance guidance. By introducing an online valve performance evaluation and early warning mechanism, the traditional periodic maintenance model can be transformed into predictive maintenance based on condition monitoring, thereby avoiding problems such as decreased control accuracy and response lag caused by valve mechanical wear, sensor drift, or actuator aging.

[0171] Working Principle: This invention achieves safe and economical operation of long-distance water transmission systems through hierarchical collaborative control. At the equipment level, a distributed measurement and control network is constructed based on a fieldbus control system. Each PLC collects pressure and flow data upstream and downstream of valves in real time with a 100-millisecond scan cycle and executes local autonomous closed-loop control. Under normal operating conditions, a conventional PID algorithm is used to maintain pressure stability. When the pressure change rate exceeds the limit, the PLC immediately determines it to be a water hammer condition. By clearing the integral term, amplifying the proportional gain, and forcibly executing fast valve closing or opening actions, the water hammer peak is actively offset, which can suppress sudden pressure changes within hundreds of milliseconds and avoid the risk of pipeline rupture. At the central level, the monitoring, control, and data acquisition system master station collects data from the entire line through the backbone network, runs a hydraulic simulation model, and uses a multi-objective genetic algorithm to iteratively solve for the optimal pressure setpoint at each control point with the dual objectives of minimizing pressure fluctuations and minimizing total system energy consumption. The optimal setpoint is periodically sent to the corresponding PLC to update the local setpoint, achieving global collaborative optimization. This invention combines the real-time nature of local rapid response with the forward-looking nature of global optimization, effectively solving the problems of large time delay and strong coupling in long-distance water transmission systems, and achieving a significant reduction in overall system energy consumption while ensuring pipeline safety.

[0172] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0173] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A closed-loop control method for hydraulically controlled butterfly valves in a PCCP long-distance high-pressure water transmission pipeline, applied to a long-distance high-pressure water transmission system composed of PCCP pipelines, wherein the long-distance high-pressure water transmission system includes multiple hydraulically controlled butterfly valves distributed along the pipeline, characterized in that, The method includes the following steps: Step 1: Construct a distributed measurement and control network based on a fieldbus control system. Connect the actuators of each hydraulic butterfly valve, as well as the pressure and flow sensors deployed upstream and downstream of the valve, to the corresponding PLC via the fieldbus protocol. Make the PLC have a built-in variable parameter PID control algorithm that includes water hammer pressure suppression logic. Step 2: Establish a remote monitoring platform for the supervision, control and data acquisition system, connect all PLCs to the main station of the supervision, control and data acquisition system through the backbone network, and deploy the full-line hydraulic simulation model in the main station of the supervision, control and data acquisition system; Step 3: The PLC executes local autonomous closed-loop control. The PLC collects upstream and downstream pressure and flow values ​​in real time according to a 100ms scan cycle, and performs the following judgments and controls: If the pressure change rate is not detected to exceed the preset safety threshold, the valve opening adjustment amount is calculated according to the deviation between the current pressure value and the locally stored set value using the conventional PID algorithm, and then output to the hydraulic butterfly valve actuator through the fieldbus control system. If the pressure change rate is detected to exceed the preset safety threshold, it is determined to be a water hammer condition. The PLC immediately clears the integral term of the PID algorithm to zero, adjusts the proportional gain to 1.5-3 times the normal value, and forces the valve to close or open quickly until the pressure change rate returns to within the safety threshold, and then smoothly switches back to the normal PID algorithm. Step 4: The monitoring, control and data acquisition system performs global optimization settings. The main station of the monitoring, control and data acquisition system collects pressure, flow and valve opening data uploaded by each PLC along the entire line at a cycle of 1-5 minutes. The hydraulic simulation model is run, and combined with the current operating status of the pump station and changes in water demand, the minimum pressure fluctuation and the minimum total energy consumption of the system are taken as the dual objective functions. The optimal pressure setpoint value of each control point is solved through iterative calculation. When the monitoring, control, and data acquisition system's main station runs the hydraulic simulation model, it also performs a multi-timescale prediction and correction step, specifically including: The main station of the monitoring, control and data acquisition system simultaneously runs two hydraulic simulation models with different time scales: a short-time prediction model and a long-time planning model. The main station of the monitoring, control and data acquisition system weights and fuses the output results of the short-term prediction model with the output results of the long-term planning model to generate the final optimal pressure setpoint. After each global optimization setting is completed, the main station of the monitoring, control and data acquisition system feeds back the actual pressure and flow data of the current cycle to the two hydraulic simulation models to correct the prediction deviations of the models and update the model parameters. Step 5: The main station of the monitoring, control and data acquisition system sends the optimal pressure setpoint calculated in Step 4 to the corresponding PLC through the backbone network. After receiving the optimal setpoint, the PLC automatically replaces the original setpoint stored locally and repeats the local autonomous closed-loop control in Step 3.

2. The closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 1, characterized in that, Also includes: Based on the deviation between the actual opening degree of the hydraulic butterfly valve and the calculated valve opening adjustment amount, the valve opening adjustment amount is corrected, specifically as follows: After the PLC executes local autonomous closed-loop control, the actual opening degree of the hydraulic butterfly valve is obtained, and the opening degree deviation between the actual opening degree and the calculated valve opening degree adjustment amount is obtained. The pressure value of the PCCP pipeline is obtained when the PLC executes local autonomous closed-loop control. Based on the pressure value, the disturbance deviation of the hydraulic butterfly valve is determined. Based on the difference between the opening deviation and the disturbance deviation, the opening deviation to be corrected is obtained. The system acquires the opening deviation to be corrected within a preset number of times the PLC executes local autonomous closed-loop control, forms a deviation sequence, calculates the rate of change of deviation between adjacent deviations in the deviation sequence, and calculates the regularity index of the deviation sequence. When the rate of change of all deviations between adjacent deviations is less than the preset deviation rate of change threshold and the regularity index is greater than the preset regularity index threshold, it is determined that the opening deviation to be corrected has a systematic cumulative deviation, and opening correction is triggered. Otherwise, it is determined that the opening deviation to be corrected is not a systematic cumulative deviation, and opening correction is not triggered. Once the opening correction is triggered, the mapping relationship between the actual opening and the opening adjustment is corrected based on the difference between the opening deviation to be corrected and the historical opening deviation to be corrected corresponding to the previous correction, to obtain the latest mapping relationship. The valve opening adjustment amount is then initially corrected based on the latest mapping relationship to obtain the intermediate valve opening adjustment amount. The parameters of the actuator and the hydraulic butterfly valve are obtained. Combined with the parameters of historical calibration, the hydraulic butterfly valve fluid torque is compensated in real time for the opening adjustment of the intermediate valve to obtain the compensation amount. Based on the compensation amount, the opening adjustment of the intermediate valve is compensated to obtain the final valve opening adjustment amount.

3. The closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 1, characterized in that, Local storage settings include three sources, selected in the following priority order: Highest priority: The optimal pressure setpoint issued in real time by the main station of the monitoring, control, and data acquisition system; Secondary priority: When communication is interrupted, the PLC automatically recalls the last set value of the supervisory control and data acquisition system received before the communication interruption; Basic priority: When the PLC is put into operation for the first time or when there are no supervision, control and data acquisition system instructions for a long time, the corresponding pressure safety value is automatically matched from the pre-stored flow-pressure data table in the PLC according to the current measured flow.

4. The closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 1, characterized in that, The integral term of the PID algorithm is cleared to zero, the proportional gain is adjusted to 1.5-3 times the normal value, and the valve is forced to close or open quickly. The specific steps include: The PLC determines the nature of the water hammer wave based on the positive and negative directions of the pressure change rate. If the pressure suddenly increases, execute the quick-close command; if the pressure suddenly decreases, execute the quick-open command. The valve's operating speed is executed according to the pre-calibrated water hammer intensity-operating speed correspondence curve, enabling the valve to complete the specified stroke to counteract the water hammer peak.

5. The closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 1, characterized in that, The optimal pressure setpoints for each control point are determined by using the minimum overall pressure fluctuation and the minimum total system energy consumption as dual objective functions. The specific method is as follows: Using a multi-objective genetic algorithm, under the constraints of the maximum allowable pressure of the pipeline, the minimum negative pressure, and the valve adjustment range, a set of set values ​​that minimizes the pressure variance of each monitoring point along the entire line and the total energy consumption of each pumping station is calculated. The process involves employing a multi-objective genetic algorithm to optimize and calculate a set of setpoints that minimizes the pressure variance at all monitoring points along the entire line and reduces the total energy consumption of all pumping stations. This includes the following steps: Minimize the pressure variance of N pressure monitoring points along the entire line and minimize the total energy consumption of M pumping stations along the entire line as dual objective functions, and use the maximum allowable pressure of the pipeline, the minimum pressure that does not generate negative pressure, the valve opening adjustment range, and the pressure change rate limit as constraints. With a population size of 100 and 200 iterations, a set of non-dominated solutions that meet the constraints is calculated by using selection, crossover, and mutation operations. The solution set that minimizes the weighted sum of the two objective functions, pressure variance and total energy consumption, is selected from the solution set as the optimal pressure setpoint for each control point.

6. The closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 1, characterized in that, When the PLC collects data in real time and performs judgment and control according to a 100ms scan cycle, if a communication failure is detected, the following fault autonomous response procedure will be executed: When the PLC detects that the backbone network communication with the master station of the supervisory control and data acquisition system has been interrupted for more than 30 seconds, it automatically switches the control mode from remote setpoint tracking mode to local experience mode, and continues to execute local closed-loop control based on the last setpoint received before the communication interruption as the control target. If the set value is not received before the communication is interrupted, the PLC will automatically match the corresponding pressure safety value as the control target from the internally stored flow-pressure correspondence data table based on the current real-time monitored pipeline flow. After communication is restored, when the PLC receives stable setpoints from the monitoring, control and data acquisition system for three consecutive scan cycles and the local pressure fluctuation is less than the preset range, the control target value will be gradually transitioned to the newly received remote setpoints within 30 seconds.

7. The closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 1, characterized in that, In step three, the specific method by which the PLC forcibly executes the valve quick-closing or quick-opening action after determining that a water hammer condition has occurred is as follows: The PLC determines the nature of the water hammer wave based on the positive and negative directions of the pressure change rate. If the pressure rises within 1 second and exceeds 0.2 MPa, it is determined to be a positive water hammer, and a valve quick-closing command is executed; If the pressure drops by more than 0.15 MPa within 1 second, it is determined to be negative water hammer, and a valve quick-opening command is executed.

8. The closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 1, characterized in that, When the PLC performs local autonomous closed-loop control, it also simultaneously performs an online correction step for valve action deviation, specifically: In each control cycle, the PLC reads the actual opening value fed back by the hydraulic butterfly valve actuator through the fieldbus control system and calculates the deviation from the commanded opening value. When the deviation exceeds the set threshold for three consecutive control cycles, the PLC automatically triggers the valve zero-point calibration process, sends a full-close command to the hydraulic butterfly valve actuator and records the full-close position feedback value, then sends a full-open command and records the full-open position feedback value, and recalibrates the valve opening degree-feedback correspondence curve based on the newly recorded full-close and full-open position values. After calibration, the PLC stores the updated correspondence curve in its memory and uses it as the basis for calculating the opening feedback in subsequent control cycles.

9. The closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 1, characterized in that, The main station of the monitoring, control, and data acquisition system periodically performs online valve performance evaluations, specifically including the following steps: The monitoring, control and data acquisition system master station compiles the historical valve action data uploaded by each PLC every 24 hours, and calculates the root mean square value of the set opening degree - actual opening degree following error, the average value of the full stroke opening time, the average value of the full stroke closing time, and the number of actions of each hydraulic butterfly valve in the past 24 hours. The four indicators mentioned above are compared with the historical benchmark values ​​of the valve. When the deviation rate of any indicator exceeds 20%, the valve icon is highlighted in yellow on the human-machine interface of the monitoring, control and data acquisition system and a warning message pops up.

10. A closed-loop control method for a hydraulically controlled butterfly valve in a PCCP long-distance high-pressure water transmission pipeline according to claim 2, characterized in that, The process involves acquiring the parameters of the actuator and the hydraulic butterfly valve, combining them with historically corrected parameters, and then performing real-time compensation of the hydraulic butterfly valve's fluid torque on the intermediate valve opening adjustment to obtain the compensation amount, including: Obtain the factory calibration parameters of the hydraulic butterfly valve, and collect and calculate the real-time pressure difference between the upstream and downstream sides of the hydraulic butterfly valve based on the pressure sensor. Based on the factory calibration parameters and real-time pressure difference of the hydraulic butterfly valve, the fluid torque of the hydraulic butterfly valve is calculated. Based on the fluid torque of the hydraulic butterfly valve and the factory calibration parameters of the actuator, the real-time compensated angular displacement based on the fluid torque of the hydraulic butterfly valve is calculated. Based on the relationship between angular displacement and compensation amount, the compensation amount corresponding to the real-time compensation angular displacement of the fluid torque of the hydraulic butterfly valve is determined.

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