Automatic regulating system and method for hydraulic butterfly valve

Abstract

The present application relates to the technical field of hydraulic automatic control, in particular to a hydraulic butterfly valve automatic regulating system and method, the system comprises a hydraulic power control module, opening detection and correction module, flow dynamic matching module, pressure balance optimization module, self-matching adjustment module of actuator, in the present application, the pressure and flow characteristics are extracted by the hydraulic pump operating parameters, the adaptability and accuracy of hydraulic transmission are effectively improved, in the butterfly valve regulating execution, the quantitative error accumulation of opening deviation and response time is analyzed in real time, the timeliness and target consistency of regulating action are enhanced, the precise allocation of flow and pressure resources is realized, in the dynamic control stage, the output matching order is continuously adjusted according to the corresponding relationship between the unmet demand and the remaining capacity, the response delay and regulating deviation are significantly reduced, thereby the continuity, coordination and regulating precision of butterfly valve control are improved, and the stable operation of hydraulic system under variable working conditions is effectively guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hydraulic automatic control, in particular to a liquid-operated butterfly valve automatic regulating system and method. BACKGROUND

[0002] The technical field of hydraulic automatic control mainly involves the use of hydraulic drive systems to achieve automatic control of mechanical equipment. The core issues of this technical field include pressure, flow, and temperature control of hydraulic systems, precise control of hydraulic actuators, and stability and reliability assurance of hydraulic systems. Hydraulic automatic control technology is widely used in fields such as engineering machinery, aerospace, ships, metallurgy, and mining, covering the design and optimization of core equipment such as hydraulic pumps, hydraulic valves, and hydraulic cylinders. Hydraulic automatic control technology also includes real-time monitoring, fault diagnosis, automatic adjustment, and optimization of hydraulic transmission and control systems, aiming to improve the automation level and efficiency of hydraulic equipment, reduce human intervention, and ensure precise operation and safety of the equipment.

[0003] Among them, the traditional liquid-operated butterfly valve automatic regulating system refers to controlling the opening of the butterfly valve through hydraulic drive to achieve the regulation of pipeline flow. The traditional liquid-operated butterfly valve automatic regulating system usually adopts manual or automatic control based on hydraulic actuators to adjust the opening of the butterfly valve, relying on the action of hydraulic pumps and valves to control flow and pressure. In this process, the opening adjustment of the liquid-operated butterfly valve depends on the pressure and flow control of the hydraulic system, and there are many mechanical adjustments and manual operations, and the adjustment accuracy and response speed are limited, which is easily affected by environmental changes and system stability problems, and cannot achieve rapid and accurate automatic adjustment.

[0004] The traditional technology relies on fixed hydraulic action and manual intervention to complete flow and pressure regulation during the execution of the regulation process. The core of system regulation is based on the static linkage between hydraulic pressure and flow, and the influence of environmental variables and system feedback states on control accuracy cannot be quantified in real time. Especially in the context of temperature fluctuations or load mutations, response delays and regulation error amplifications are prone to occur, and the system lacks recognition and correction mechanisms for accumulated regulation errors, leading to frequent target deviations and control lags during valve control. It is difficult to continuously ensure control stability and execution reliability in complex environments that require high response speed and consistent regulation. SUMMARY

[0005] To solve the technical problems existing in the prior art, the present application provides a liquid-operated butterfly valve automatic regulating system and method. The technical solution is as follows:

[0006] On the one hand, a liquid-operated butterfly valve automatic regulating system is provided, which includes:

[0007] The hydraulic power output adaptation table includes pressure grading parameters, flow control ranges, temperature-viscosity compensation coefficients, and opening coupling coefficients, the butterfly valve opening correction dataset includes opening error factors, response delay parameters, change rate indicators, and correction weighting values, the flow demand matching table includes hierarchical flow intervals, demand priority levels, fluctuation thresholds, and matching coefficient weights, and the initial pressure balance scheme includes pressure distribution structures, node adjustment sequences, fluctuation correction factors, and flow distribution factors.

[0008] The opening detection and correction module extracts a butterfly valve real-time opening value and a target opening deviation based on the hydraulic power output adaptation table, identifies an opening change rate and a response time, quantifies an opening error accumulation effect, induces an opening correction weight, and obtains a butterfly valve opening correction dataset.

[0009] The flow dynamic matching module extracts flow demand distribution parameters based on the butterfly valve opening correction dataset, performs hierarchical weighted analysis on pressure fluctuation characteristics of a hydraulic system and a butterfly valve opening change law, and obtains a flow demand matching table.

[0010] The pressure balance optimization module sorts flow priorities and pressure demand proportions according to the flow demand matching table, identifies a pressure distribution relationship between a hydraulic system and a butterfly valve, adjusts a distribution sequence through pressure node fluctuation conditions, and constructs an initial pressure balance scheme.

[0011] As a further scheme of the present application, the hydraulic power output adaptation table includes pressure grading parameters, flow control ranges, temperature-viscosity compensation coefficients, and opening coupling coefficients, the butterfly valve opening correction dataset includes opening error factors, response delay parameters, change rate indicators, and correction weighting values, the flow demand matching table includes hierarchical flow intervals, demand priority levels, fluctuation thresholds, and matching coefficient weights, and the initial pressure balance scheme includes pressure distribution structures, node adjustment sequences, fluctuation correction factors, and flow distribution factors.

[0012] As a further scheme of the present application, the hydraulic power output adaptation table includes:

[0013] The hydraulic characteristic extraction submodule extracts hydraulic power output parameters according to a hydraulic pump output pressure and flow characteristic curve, classifies hydraulic oil temperature and viscosity influence factors, and generates a hydraulic power output characteristic table.

[0014] The power transmission analysis submodule analyzes the influence of hydraulic oil temperature and viscosity on power transmission efficiency based on the hydraulic power output characteristic table, calculates hydraulic power output adaptation values under different working conditions, and generates a hydraulic power and butterfly valve opening relationship model.

[0015] The adaptation table generation submodule sorts hydraulic power output parameters based on the hydraulic power and butterfly valve opening relationship model, analyzes the corresponding relationship with a target butterfly valve opening value, and generates a hydraulic power output adaptation table.

[0016] As a further scheme of the present application, the opening detection and correction module includes:

[0017] The opening degree deviation extraction submodule extracts the deviation of the real-time opening degree value of the butterfly valve from the target opening degree based on the hydraulic power output adaptation table, records the opening degree change rate and response time data, and generates an opening degree deviation data table;

[0018] The error accumulation quantification submodule quantifies the opening degree error accumulation effect based on the opening degree deviation data table, analyzes the difference between the hydraulic power distribution and the opening degree demand ratio, and generates an opening degree error accumulation effect table;

[0019] The correction weight induction submodule extracts the opening degree deviation magnitude and correction frequency based on the opening degree error accumulation effect table, filters high-frequency error sections and labels the deviation direction, induces the opening degree correction weight, and generates a butterfly valve opening degree correction dataset.

[0020] As a further scheme of the present application, the flow dynamic matching module comprises:

[0021] The flow demand extraction submodule extracts flow demand distribution parameters based on the butterfly valve opening degree correction dataset, classifies flow demand priority data, and generates a flow demand distribution table;

[0022] The pressure fluctuation analysis submodule calculates pressure node fluctuation state values based on the flow demand distribution table, in combination with the pressure fluctuation characteristics of the hydraulic system and the butterfly valve opening degree change law, and generates a pressure fluctuation state table;

[0023] The hierarchical weighted analysis submodule performs multi-dimensional comparison of flow demand and pressure fluctuation based on the pressure fluctuation state table, filters flow demand distribution adaptation relationships, and generates a flow demand matching table.

[0024] As a further scheme of the present application, the pressure node fluctuation state value uses the formula:

[0025] ;

[0026] Wherein, represents the pressure node fluctuation state value, represents the pressure change amount in the i-th time period, represents the valve opening degree change amount for each pressure fluctuation, represents the time interval, represents the flow change amount, represents the initial flow, and n represents the number of fluctuation periods.

[0027] As a further scheme of the present application, the pressure balance optimization module comprises:

[0028] The priority sorting submodule extracts the flow peak position and pressure difference threshold based on the flow demand matching table, analyzes the flow contribution degree under unit pressure difference, and generates a flow priority sorting table.

[0029] The pressure distribution identification submodule extracts the main channel node pressure change trajectory, identifies the pressure difference balance point and the offset direction, and generates a pressure distribution relationship table based on the flow priority ranking table.

[0030] The fluctuation adjustment submodule adjusts the distribution order based on the pressure distribution relationship table, extracts the node pressure difference change frequency and amplitude sequence, counts the offset amplitude and duration of the pressure difference out-of-limit node, divides the stable interval and the fluctuation transition section, selects the main channel access order and the bypass auxiliary channel connection node, and generates an initial pressure balance scheme.

[0031] As a further scheme of the present application, the system further comprises an actuator self-matching adjustment module:

[0032] The actuator self-matching adjustment module monitors the hydraulic system pressure state and the butterfly valve opening execution based on the initial pressure balance scheme, compares the unsatisfied flow demand and the remaining hydraulic capacity in real time, fills in the pressure fluctuation gap by adjusting the hydraulic power output and the butterfly valve opening matching order, and generates a butterfly valve dynamic adjustment adjustment scheme.

[0033] The butterfly valve dynamic adjustment adjustment scheme includes residual error adjustment parameters, execution order configuration, residual pressure utilization rate, and adjustment completion criterion.

[0034] As a further scheme of the present application, the actuator self-matching adjustment module comprises:

[0035] The state monitoring submodule collects pressure node values and butterfly valve opening feedback based on the initial pressure balance scheme, records the jump time and deviation amplitude, labels the pressure mutation and opening deviation position, and generates a state monitoring data table.

[0036] The demand comparison submodule extracts the corresponding time point of the unsatisfied flow based on the state monitoring data table, identifies the hydraulic power surplus and the instantaneous gap, matches the target gap and the power section, and generates a demand comparison result table.

[0037] The dynamic adjustment submodule fills in the pressure fluctuation gap by adjusting the hydraulic power output and the butterfly valve opening matching order based on the demand comparison result table, identifies the power gap node and the response lag section, extracts the unexecuted section and the standby path, updates the hydraulic output timing and the butterfly valve control curve, and generates a butterfly valve dynamic adjustment adjustment scheme.

[0038] On the other hand, the hydraulic butterfly valve automatic adjustment method is executed based on the above-mentioned hydraulic butterfly valve automatic adjustment system, comprising the following steps:

[0039] S1: According to the hydraulic pump output pressure and flow characteristic curve, the hydraulic power output parameter and the butterfly valve target opening value are extracted, the normalized hydraulic oil temperature and viscosity influence factor are matched, the hydraulic power and the target opening relationship are matched, and the hydraulic power output adaptation table is generated;

[0040] S2: Based on the hydraulic power output adaptation table, the target and real-time opening deviation value is extracted, the offset amplitude and response duration are calculated, the opening change rate and response time data are screened, and the butterfly valve opening correction data set is generated;

[0041] S3: Based on the butterfly valve opening correction data set, the flow change frequency and peak node in unit time are extracted, the differential pressure response value is associated to identify abnormal transition points and stable recovery points, the echo time and jump boundary in the pressure fluctuation interval are extracted, and the flow demand matching table is generated;

[0042] S4: Based on the flow demand matching table, the high-frequency flow priority section and the fluctuation peak position are analyzed, the step change node is identified and the main channel and compensation path are reconstructed, and the initial flow path and pressure balance scheme are constructed;

[0043] S5: Based on the initial flow path and pressure balance scheme, the flow demand parameter and key node fluctuation state value that are not met are screened, the offset frequency peak value is extracted and the opening adjustment control logic is corrected, and the butterfly valve dynamic adjustment adjustment scheme is generated.

[0044] The technical scheme provided by the embodiment of the application has at least the following beneficial effects:

[0045] By extracting the pressure and flow characteristics of the hydraulic pump operating parameters, the influence factors of the hydraulic oil temperature and viscosity are fused to establish an associated model, the adaptability and accuracy of the hydraulic transmission are effectively improved, in the butterfly valve adjustment execution, the opening deviation and response time error accumulation are quantified by real-time analysis, the timeliness and target consistency of the adjustment action are enhanced, the flow demand change and pressure fluctuation distribution in the system are compared layer by layer, the accurate allocation of flow and pressure resources is realized, in the dynamic control stage, the output matching order is continuously adjusted according to the corresponding relationship between the unmet demand and the remaining capacity, the response delay and adjustment deviation are significantly reduced, thereby the continuity, coordination and adjustment precision of the butterfly valve control are improved, and the stable operation of the hydraulic system under variable working conditions is effectively guaranteed. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creating laborious work.

[0047] Figure 1 is a schematic diagram of the automatic adjusting system of the liquid-operated butterfly valve provided by the embodiment of the present application;

[0048] Figure 2 is a schematic diagram of the system framework of the present application;

[0049] Figure 3 is a flow chart of the hydraulic power regulation module in the present application;

[0050] Figure 4 is a flow chart of the opening detection and correction module in the present application;

[0051] Figure 5 is a flow chart of the flow dynamic matching module in the present application;

[0052] Figure 6 is a flow chart of the pressure balance optimization module in the present application;

[0053] Figure 7 is a flow chart of the actuator self-matching adjustment module in the present application;

[0054] Figure 8 is a flow chart of the automatic adjusting method of the liquid-operated butterfly valve provided by the embodiment of the present application. DETAILED DESCRIPTION

[0055] The technical solutions in the present application will be described below with reference to the drawings.

[0056] In the embodiments of the present application, the words such as "example", "for example" and the like are used to represent an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two optionally.

[0057] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times, and it should be pointed out that the meanings expressed thereby are consistent when the distinction is not emphasized. "Of", "corresponding" and "relevant" can be used interchangeably at times, and it should be pointed out that the meanings expressed thereby are consistent when the distinction is not emphasized.

[0058] In the embodiments of the present application, the subscript such as W1 can be written in the form of non-subscript such as W1 at times, and the meanings expressed thereby are consistent when the distinction is not emphasized.

[0059] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail in combination with the drawings and specific embodiments.

[0060] The embodiment of the present application provides a liquid-operated butterfly valve automatic adjusting system, as shown in the schematic diagram of the liquid-operated butterfly valve automatic adjusting system. Figures 1-2 The schematic diagram of the liquid-operated butterfly valve automatic adjusting system is shown in the figure, and the system comprises:

[0061] The hydraulic power regulation module extracts the hydraulic power output parameters according to the hydraulic pump output pressure and flow characteristic curve, analyzes the influence of the hydraulic oil temperature and viscosity on the power transmission, sorts the hydraulic power and the butterfly valve opening degree relationship model, and obtains the hydraulic power output adaptation table;

[0062] The opening degree detection and correction module extracts the butterfly valve real-time opening degree value and target opening degree deviation based on the hydraulic power output adaptation table, identifies the opening degree change rate and response time, quantifies the opening degree error accumulation effect, induces the opening degree correction weight, and obtains the butterfly valve opening degree correction data set;

[0063] The flow dynamic matching module extracts the flow demand distribution parameters based on the butterfly valve opening degree correction data set, and performs hierarchical weighted analysis combined with the hydraulic system pressure fluctuation characteristics and the butterfly valve opening degree change law to obtain the flow demand matching table;

[0064] The pressure balance optimization module sorts the flow priority and pressure demand proportion according to the flow demand matching table, identifies the pressure distribution relationship between the hydraulic system and the butterfly valve, adjusts the distribution order through the pressure node fluctuation, and constructs the initial pressure balance scheme;

[0065] The actuator self-matching adjustment module monitors the hydraulic system pressure state and the butterfly valve opening degree execution based on the initial pressure balance scheme, compares the unsatisfied flow demand and the residual hydraulic capacity in real time, fills the pressure fluctuation gap by adjusting the hydraulic power output and the butterfly valve opening degree matching order, and generates the butterfly valve dynamic adjustment adjustment scheme.

[0066] The hydraulic power output adaptation table comprises pressure grading parameters, flow control range, temperature and viscosity compensation coefficients, and opening degree coupling coefficients. The butterfly valve opening degree correction data set comprises opening degree error factors, response delay parameters, change rate indicators, and correction weighting values. The flow demand matching table comprises hierarchical flow intervals, demand priority levels, fluctuation thresholds, and matching coefficient weights. The initial pressure balance scheme comprises pressure distribution structures, node adjustment orders, fluctuation correction factors, and flow distribution factors. The butterfly valve dynamic adjustment adjustment scheme comprises residual adjustment parameters, execution order configurations, residual pressure utilization rates, and adjustment completion criteria.

[0067] In the automatic adjustment system of hydraulic butterfly valve, the hydraulic power output adaptation table, the butterfly valve opening correction data set, the flow demand matching table, the initial pressure balance scheme and the butterfly valve dynamic adjustment adjustment scheme represent different characteristics of the hydraulic and butterfly valve adjustment in the system. The determination of these factors and levels is obtained through detailed analysis of the real-time data of hydraulic pump output parameters, butterfly valve opening, flow demand and pressure fluctuation, and accurate calculation and model derivation. Specifically, the pressure classification parameters, flow control range, temperature viscosity compensation coefficient and opening coupling coefficient in the hydraulic power output adaptation table reflect the pressure and flow regulation ability of the hydraulic system under different working conditions. By monitoring the output pressure and flow of the hydraulic pump in real time, and combining the influence of hydraulic oil temperature and viscosity on power transmission, the experimental data and theoretical model are used to derive the adaptation table of the hydraulic system to ensure accurate control of the system. The opening error factor, response delay parameter, change rate index and correction weight in the butterfly valve opening correction data set represent the error caused by opening deviation and its influence on response time during the adjustment process of the butterfly valve. These characteristics are quantitatively analyzed and corrected through the comparison of real-time collected butterfly valve opening data and target opening value, combined with the error accumulation effect in historical data, and finally the correction weight is generated to optimize the adjustment process. The flow demand matching table includes the classification flow interval, demand priority level, fluctuation threshold and matching coefficient weight, which reflects how to optimally allocate resources according to the flow priority and pressure change under different flow demand and pressure fluctuation conditions. Through the analysis of the characteristics of flow demand and pressure fluctuation, combined with the change law of butterfly valve opening, weighted analysis is carried out to determine the optimal matching relationship, so as to ensure the stable operation of the system in the dynamic adjustment stage. The pressure distribution structure, node adjustment sequence, fluctuation correction factor and flow distribution factor in the initial pressure balance scheme represent how the system adjusts the pressure distribution and flow scheduling of the hydraulic system to realize stable control. These factors ensure the balance and effectiveness of system pressure regulation by analyzing different flow demand and pressure fluctuation states, using priority sorting and fluctuation correction strategy. The butterfly valve dynamic adjustment adjustment scheme contains residual adjustment parameters, execution sequence configuration, residual pressure utilization rate and adjustment completion criterion, which aims to adjust the matching sequence of hydraulic power output and butterfly valve opening in real time according to the system monitoring data to fill the pressure fluctuation gap and optimize the response time and accuracy. Through comparison of real-time monitoring data, the gap between flow demand and residual capacity is identified, and then dynamic adjustment is carried out. The generation of these characteristics and factors depends on the parameters of hydraulic system and butterfly valve opening obtained through real-time monitoring and data feedback, as well as accurate mathematical models and calculation methods, to ensure that each step of adjustment can maximize the response speed, accuracy and regulation consistency of the hydraulic system. Finally, through step-by-step optimization and model derivation of system parameters, the required characteristic data is formed to ensure that the entire system can stably and accurately perform the adjustment task.

[0068] Specifically, as shown in Figure 2 , 3 the hydraulic power regulation module includes:

[0069] The hydraulic characteristic extraction submodule extracts hydraulic power output parameters according to the hydraulic pump output pressure and flow characteristic curve, classifies hydraulic oil temperature and viscosity influence factors, and generates a hydraulic power output characteristic table;

[0070] According to the hydraulic pump output pressure and flow characteristic curve, in the hydraulic hoist system of a large-scale water conservancy project, the output pressure and flow data of the hydraulic pump under different working conditions are monitored in real time through pressure sensors and flow sensors, for example, when the hydraulic pump speed is 1000 rpm, the output pressure is 15 MPa, and the flow is 200 L / min, when the speed rises to 1200 rpm, the output pressure is 18 MPa, and the flow is 240 L / min, for the collected original pressure-flow data, the pressure data is taken as the abscissa, and the flow data is taken as the ordinate, the P-Q curve of the hydraulic pump is drawn, the hydraulic power output parameters are extracted through the curve fitting method, such as the least square method, the nonlinear relationship expression between pressure and flow is determined, for example, the flow Q=f(P) is fitted, wherein f(P) is a cubic polynomial, at the same time, the temperature sensor and viscosity sensor installed in the hydraulic oil tank are used to obtain the temperature (such as 45 degrees Celsius) and viscosity (such as 32 cSt) data of the hydraulic oil in real time, and the data is compared with the preset temperature-viscosity table, the influence degree under different temperature and viscosity conditions is quantified, for example, when the hydraulic oil temperature is between 40-50 degrees Celsius, the viscosity influence factor is set to 0.98, when the viscosity is between 30-40 cSt, the temperature influence factor is set to 1.02, the influence factor is applied in the subsequent power transmission efficiency calculation, and finally a data set containing the hydraulic power output capacity under different speed, pressure, flow, and hydraulic oil temperature, viscosity conditions is formed, and a hydraulic power output characteristic table is generated.

[0071] The power transmission analysis submodule analyzes the influence of hydraulic oil temperature and viscosity on power transmission efficiency based on the hydraulic power output characteristic table, calculates the hydraulic power output adaptation value under different working conditions, and generates a hydraulic power and butterfly valve opening degree relationship model;

[0072] Based on the hydraulic power output characteristic table, in the hydraulic hoist system of large-scale water conservancy project, by consulting the hydraulic power output characteristic table, the output parameters of the current hydraulic pump and the influence factors of the hydraulic oil temperature and viscosity are obtained, for example, the current hydraulic pump output pressure is 16 MPa, the flow is 220 L / min, the hydraulic oil temperature is 50 degrees Celsius, and the viscosity is 30 cSt, according to the historical experimental data and theoretical model, the influence of hydraulic oil temperature on power transmission efficiency can be quantified as: when the temperature is higher than 60 degrees Celsius, the efficiency decreases by 2%, when the temperature is lower than 30 degrees Celsius, the efficiency decreases by 1.5%, the influence of viscosity on power transmission efficiency is quantified as: when the viscosity is higher than 40 cSt, the efficiency decreases by 1.8%, when the viscosity is lower than 25 cSt, the efficiency decreases by 1.2%, the influence degree is taken as a correction coefficient, and the initial power transmission efficiency (for example, 90%) is multiplied to calculate the hydraulic power transmission efficiency under different working conditions, for example, when the temperature is 50 degrees Celsius (without additional efficiency reduction) and the viscosity is 30 cSt (without additional efficiency reduction), the power transmission efficiency remains 90%, when the temperature is 65 degrees Celsius and the viscosity is 45 cSt, the efficiency is 90%(1-2%)(1-1.8%) = 86.65%, then, according to the calculated power transmission efficiency, the theoretical output power of the hydraulic pump is multiplied by the efficiency to calculate the actual hydraulic power output adaptive value, for example, the theoretical output power is 58.67, and the actual adaptive value is 52.80, at the same time, by testing the torque and flow required by the butterfly valve of the hoist under different opening degrees, the corresponding data of the butterfly valve opening degree and the required hydraulic power are collected, for example, when the butterfly valve opening degree is 30%, the required hydraulic power is 15kW, when the butterfly valve opening degree is 60%, the required hydraulic power is 40kW, combining the calculated hydraulic power output adaptive value and the butterfly valve opening degree demand, a function relationship between the two is established, for example, by polynomial regression analysis, the hydraulic power is obtained, wherein is the butterfly valve opening degree, and a hydraulic power and butterfly valve opening degree relationship model is generated.

[0073] The adaptive table generation submodule generates a hydraulic power output adaptive table based on the hydraulic power and butterfly valve opening degree relationship model, organizes the hydraulic power output parameters, and analyzes the corresponding relationship with the target butterfly valve opening degree value.

[0074] Based on the relationship model of hydraulic power and butterfly valve opening degree, in the application of water conservancy hoist butterfly valve control, by calling the established relationship model of hydraulic power and butterfly valve opening degree, the required hydraulic power output parameters under different butterfly valve opening degrees are obtained, for example, according to the model calculation, when the target butterfly valve opening degree is 25%, the required hydraulic power output is 12kW, when the target butterfly valve opening degree is 75%, the required hydraulic power output is 55kW, the calculated hydraulic power output parameters are arranged into a data sequence, at the same time, each hydraulic power output parameter is associated with its corresponding target butterfly valve opening degree value to form a series of parameter pairs, for example, (12kW, 25%), (55kW, 75%), set a target opening step, for example, every 5% opening as a step, from 0% to 100% traversal, for each step corresponding to the target opening degree value, query or calculate its corresponding hydraulic power output value, generate a detailed hydraulic power output adaptation table.

[0075] Specifically, as shown in Figure 2 、 4 The opening degree detection and correction module includes:

[0076] The opening degree deviation extraction submodule extracts the opening degree deviation of the butterfly valve from the hydraulic power output adaptation table, records the opening degree change rate and response time data, and generates an opening degree deviation data table;

[0077] Based on the hydraulic power output adaptation table, in the operation process of the water conservancy hoist butterfly valve, by real-time collecting the actual opening degree value of the butterfly valve, for example, the target opening degree is 50%, the real-time opening degree value fed back by the sensor is 48%, then, the real-time opening degree value is compared with the value corresponding to the target opening degree in the hydraulic power output adaptation table, the opening degree deviation of the butterfly valve is calculated, for example, 48%-50%=-2% opening degree deviation, at the same time, the system records the time spent by the butterfly valve opening degree from 48% to the target 50% with a sampling period of 100 milliseconds, for example, in a correction process, the opening degree changes from 48% to 50% in 150 milliseconds, the opening degree change rate is calculated as (50%-48%) / 150=0.02%, and the data is recorded to generate an opening degree deviation data table.

[0078] The error accumulation quantification submodule quantifies the opening degree error accumulation effect based on the opening degree deviation data table, analyzes the difference between the hydraulic power distribution and the opening degree demand ratio, and generates an opening degree error accumulation effect table;

[0079] Based on the opening deviation data table, in the precise control of the hydraulic opening and closing machine butterfly valve, the historical data in the opening deviation data table is statistically analyzed, the sum of the opening deviation at each time point and the deviation at the previous time point is calculated, for example, if the deviation at the previous time point is -2%, the deviation at the current time point is -0.5%, the cumulative deviation is -2%+(-0.5%)=-2.5%, the cumulative effect of the opening error is quantified, a cumulative threshold of the opening error is set, for example, when the cumulative amount of error reaches 5%, it is considered that there is a significant cumulative effect of error, by analyzing the proportional relationship between the actual output value of the hydraulic power under different working conditions and the demand of the butterfly valve opening, for example, in the process of the butterfly valve opening from 20% to 30%, the hydraulic power demand increases from 10kW to 18kW, and the actual hydraulic power output is 11kW and 17kW, which indicates that there is a power shortage, the difference between the actual hydraulic power output and the opening demand ratio is calculated, for example, when the opening demand is 30%, if the actual hydraulic power is 17kW, and the adaptive table requires 18kW, the difference is 1kW, and the opening error cumulative effect table is generated.

[0080] The correction weight induction submodule extracts the opening deviation magnitude and correction frequency based on the opening error cumulative effect table, filters the high-frequency error section and labels the deviation direction, induces the opening correction weight, and generates the butterfly valve opening correction dataset;

[0081] Based on the opening error cumulative effect table, in the adaptive control of the water conservancy opening and closing machine butterfly valve, by traversing the data in the opening error cumulative effect table, the magnitude of each opening deviation is extracted, for example, one deviation magnitude is 2% and the other is 0.5%, and the correction frequency of the deviation is extracted, for example, in the past one hour, the 2% deviation occurred 15 times, and the 0.5% deviation occurred 30 times, according to the preset frequency threshold, for example, the threshold is set to 10 times / hour, the high-frequency error section with a frequency higher than the threshold is selected, for example, the positive deviation frequently occurs in the 0%-5% opening interval, and the negative deviation frequently occurs in the 90%-100% opening interval, and the direction of the deviation is labeled, for example, the positive deviation indicates that the actual opening is greater than the target opening, and the negative deviation indicates that the actual opening is less than the target opening, for the high-frequency error section, the opening correction weight is induced according to the deviation magnitude and the correction frequency, for example, for a 2% positive deviation, if the correction frequency is high, a larger correction weight 0.8 is given, and for a 0.5% negative deviation, if the correction frequency is low, a smaller correction weight 0.2 is given, and finally the butterfly valve opening correction dataset is generated.

[0082] Specifically, as shown in Figure 2 , 5 , the flow dynamic matching module includes:

[0083] The flow demand extraction submodule extracts flow demand distribution parameters based on the butterfly valve opening correction dataset, classifies flow demand priority data, and generates a flow demand distribution table;

[0084] Based on the butterfly valve opening correction dataset, in the accurate control of the flow of the water conservancy hub butterfly valve, by reading the butterfly valve opening value at each time point recorded in the butterfly valve opening correction dataset, for example, at a certain time point, the butterfly valve opening correction dataset shows that the target opening of the butterfly valve is 60%, and the corrected actual opening is 59.5%, according to the corrected butterfly valve opening value, combined with the known butterfly valve flow characteristic curve, for example, the butterfly valve opening and flow show a nonlinear relationship, when the opening is 60%, the flow is 1200 cubic meters / hour, when the opening is 59.5%, the flow is 1180 cubic meters / hour, the flow demand distribution parameters under the current working condition are extracted, for example, the flow demand is 1180 cubic meters / hour, at the same time, according to the operation strategy of the system, different flow demands are given priority, for example, the priority of maintaining the main pipeline flow is higher than that of the auxiliary pipeline flow, the flow demand in the system is classified according to its importance, for example, the priority of flood discharge flow is set to the highest (1st), the priority of ecological flow is set to the middle (2nd), and the priority of irrigation flow is set to the lowest (3rd), the flow demand priority data is classified, and a flow demand distribution table is generated, which clearly lists the flow demand at each time point and its corresponding priority.

[0085] The pressure fluctuation analysis submodule calculates the pressure node fluctuation state value based on the flow demand distribution table, combined with the pressure fluctuation characteristics of the hydraulic system and the change law of the butterfly valve opening, and generates a pressure fluctuation state table;

[0086] The pressure node fluctuation state value uses the formula:

[0087] ;

[0088] Among them, represents the pressure node fluctuation state value, represents the pressure change amount in the ith time period, represents the valve opening change amount of each pressure fluctuation, represents the time interval, represents the flow change amount, represents the initial flow, and n represents the number of fluctuation periods;

[0089] The pressure node fluctuation state value is a comprehensive index for measuring the pressure fluctuation and the adjustment response ability of the key pressure node in the hydraulic system at different time periods. By calculating the pressure change amount, the valve opening change amount, the time interval, the flow change amount, and the initial flow in each time period, the pressure stability and the flow response characteristics of the system in the dynamic adjustment process are comprehensively reflected. When the value is high, it indicates that there is severe pressure fluctuation and large adjustment instability at the node; when the value is low, it indicates that the system runs smoothly and accurately, and the index is widely used in flow demand analysis and pressure balance optimization, and is an important basis for realizing accurate control of the hydraulic butterfly valve and ensuring efficient and stable operation of the hydraulic system.

[0090] Based on the flow demand distribution table, combined with the pressure fluctuation characteristics of the hydraulic system and the butterfly valve opening change law, the flow data in the flow demand distribution table is analyzed in the hydraulic system of the water conservancy hub. For example, according to the flow demand distribution table, the system needs to change from 1200 cubic meters / hour to 1500 cubic meters / hour in a certain time period, and at the same time, the pressure change of each key node in the hydraulic system is monitored in real time by a high-precision pressure sensor, for example, in the process of rapid opening of the butterfly valve, the upstream pressure decreases from 5MPa to 4.5MPa, and the downstream pressure rises from 2MPa to 2.5MPa, and the opening change law of the butterfly valve, for example, the time for the butterfly valve to change from 50% opening to 70% opening is 2 seconds, and the data is used to calculate the pressure node fluctuation state value, wherein the pressure node fluctuation state value represents the pressure node fluctuation state value, represents the pressure change amount in the time period, represents the valve opening change amount of each pressure fluctuation, represents the time interval, represents the flow change amount, represents the initial flow, represents the number of fluctuation periods, the formula aims to quantify the severity of pressure fluctuation and the response of flow change, the core of which is to evaluate the influence of pressure fluctuation amplitude and valve opening change on fluctuation through the numerator part, and the denominator part normalizes the fluctuation through the pressure change amplitude and the relative flow change amount, so as to more accurately reflect the pressure stability of the system when the flow changes. For example, in a flood discharge process, the system monitors 5 fluctuation periods, i.e. , the pressure change amount (unit: MPa) in each period is: , , , , , the valve opening change amount of each pressure fluctuation is (i.e. 2%), time interval is seconds, initial flow rate is , corresponding flow rate change is then:

[0091] ;

[0092] The result shows that the pressure fluctuation state value under the current working condition is 5.214, which indicates that the pressure fluctuation of the hydraulic system is relatively significant when the flow rate change and valve opening change are given, and further attention and optimization are needed. If the preset pressure fluctuation state value threshold is 4.0, then 5.214 indicates that the pressure fluctuation exceeds the acceptable range. This pressure fluctuation state value will be used to evaluate the stability of the system and guide the subsequent pressure balance optimization, generating a pressure fluctuation state table.

[0093] The hierarchical weighted analysis submodule performs multi-dimensional comparison of flow demand and pressure fluctuation based on the pressure fluctuation state table, screens the flow demand distribution adaptation relationship, and generates a flow demand matching table;

[0094] Based on the pressure fluctuation state table, in the dynamic matching of the hydraulic system flow of the water conservancy hub, the pressure fluctuation state value at each time point in the pressure fluctuation state table is compared in multiple dimensions. For example, if the current pressure fluctuation state value is 5.214 and the flow demand is 1500 cubic meters / hour, at the same time, according to the preset weight distribution rule, different weights are given to different flow demands and pressure fluctuation states. For example, the weight corresponding to the high-priority flow demand is 0.7, the medium-priority is 0.2, and the low-priority is 0.1. When the pressure fluctuation state value is higher than the threshold, for example, higher than 4.0, an additional weight of 0.1 is added. The flow demand distribution parameters and the pressure fluctuation state value are comprehensively evaluated, for example, the flow demand and the pressure fluctuation state value are multiplied, and the respective weights are considered to obtain a comprehensive evaluation index. For example, the flow demand under the high-priority flow (weight 0.7) is 1500 cubic meters / hour, the pressure fluctuation state value is 5.214, and the comprehensive index is 5474.7. For the medium-priority flow (weight 0.2), the flow demand is 800 cubic meters / hour, the pressure fluctuation state value is 3.5, and the comprehensive index is 560. Then, according to the size of the comprehensive evaluation index, the adaptation relationship that can minimize the system pressure fluctuation and meet the flow demand distribution is selected, for example, the scheme with the lowest comprehensive index is selected from all flow distribution schemes, and a flow demand matching table is generated. This table records in detail the best matching scheme of different flow demands under various pressure fluctuation conditions.

[0095] Specifically, as Figure 2 ,6 The pressure balance optimization module includes:

[0096] The priority ranking submodule extracts the flow peak position and the pressure difference threshold based on the flow demand matching table, analyzes the flow contribution degree under unit pressure difference, and generates a flow priority ranking table.

[0097] Based on the flow demand matching table, in the water conservancy hoist system, by analyzing the data in the flow demand matching table, the flow peak position under different working conditions is extracted, for example, when the hoist starts, the flow demand rises rapidly from 0 to 2000 cubic meters / hour within 3 seconds, and 2000 cubic meters / hour is the peak value. At the same time, a pressure difference threshold is set, for example, the threshold of the pressure difference between the two ends of the main pipeline is set to 0.5 MPa. When the pressure difference exceeds this value, it is considered that there is pressure imbalance. By calculating the flow contribution degree of each flow channel under unit pressure difference, for example, under the condition of maintaining 0.1 MPa pressure difference, the main channel can provide 100 cubic meters / second of flow, and the bypass channel can provide 20 cubic meters / second of flow, thereby determining the actual contribution of each flow channel to the overall flow, and generating a flow priority ranking table.

[0098] The pressure distribution identification submodule extracts the main channel node pressure change trajectory based on the flow priority ranking table, identifies the pressure difference balance point and the deviation direction, and generates a pressure distribution relationship table.

[0099] Based on the flow priority ranking table, in the hydraulic system of the water conservancy hub, by referring to the flow priority ranking table, the pressure distribution under different flow priorities is obtained, for example, when the high-priority flow channel is opened, the pressure change trajectory of the main channel node shows a downward trend first and then an upward trend. By installing pressure sensors at key nodes of the main channel (such as before and after the valve, pump outlet), real-time pressure data is collected, for example, the pressure of main channel node A is monitored to decrease from 10 MPa to 8 MPa, and then rise to 9.5 MPa, and the pressure change trajectory is recorded. At the same time, by analyzing the trajectory, the pressure difference balance point is identified, for example, when the pressure difference between main channel node A and node B stabilizes at 0.2 MPa, it is the balance point, and the pressure deviation direction is marked, for example, if the actual pressure difference is higher than 0.2 MPa, it is identified as positive deviation, and if it is lower than 0.2 MPa, it is identified as negative deviation, and a pressure distribution relationship table is generated.

[0100] The fluctuation adjustment submodule adjusts the distribution order based on the pressure distribution relationship table by the pressure node fluctuation, extracts the node pressure difference change frequency and amplitude sequence, counts the deviation amplitude and duration of the pressure difference out-of-limit node, divides the stable interval and the fluctuation transition section, selects the main channel access sequence and the bypass auxiliary channel connection node, and generates an initial pressure balance scheme.

[0101] Based on the pressure distribution relationship table, in the pressure balance optimization of the hydraulic system of the water conservancy hub, by identifying the pressure node fluctuation recorded in the pressure distribution relationship table, for example, the pressure fluctuation amplitude of node A is large, the duration is long, combined with the preset adjustment strategy of the system, the distribution order of each channel of the hydraulic system is adjusted, for example, the main channel with large fluctuation is adjusted first, and the bypass channel with small fluctuation is adjusted second, through high-frequency sampling, for example, sampling once every 10 milliseconds, the frequency of the pressure difference change of each node is extracted, for example, the pressure difference of node A changes 15 times in 1 second, and the amplitude sequence, for example, the pressure difference change amplitude is 0.1 MPa, 0.05 MPa, 0.12 MPa, etc., the offset amplitude of the pressure difference out-of-limit node is counted, for example, the amplitude of the pressure difference of node B exceeding the threshold of 0.5 MPa is 0.1 MPa, and the duration is counted, for example, it lasts for 3 seconds, according to the statistical data, the working state of the hydraulic system is divided into a stable interval, for example, an interval with a pressure difference fluctuation less than 0.1 MPa, and a fluctuation transition paragraph, for example, an interval with a pressure difference fluctuation greater than 0.1 MPa and less than 0.5 MPa, by analyzing the historical data, the main channel access order that can maintain the pressure balance of the system under different working modes is screened out, for example, the main channel 1 is opened first in the flood discharge mode, the main channel 2 is opened first in the power generation mode, and the bypass auxiliary channel connects the nodes, for example, when the main channel pressure fluctuates violently, the bypass channel 3 is connected, and the initial pressure balance scheme is generated.

[0102] Specifically, as shown in Figure 2 、 7 , the actuator self-matching adjustment module comprises:

[0103] The state monitoring submodule generates a state monitoring data table based on the initial pressure balance scheme, collects pressure node values and butterfly valve opening degree feedback, records jump time and deviation amplitude, labels pressure mutation and opening degree offset position, and generates a state monitoring data table.

[0104] Based on the initial pressure balance scheme, in the hydraulic control system of the water conservancy hoist, by collecting the pressure node values preset in the initial pressure balance scheme, for example, the scheme requires that the main pipeline pressure is maintained at 10 MPa, and the opening degree feedback data of the butterfly valve, for example, the actual opening degree of the butterfly valve is 50%, at the same time, the accurate time when the pressure or opening degree jumps in the running process of the hoist is recorded, for example, the pressure drops from 10 MPa to 8 MPa at T1 time, and the corresponding deviation amplitude, for example, the pressure deviation amplitude is 2 MPa, and the position where the pressure mutation occurs is labeled, for example, it occurs at the pump outlet, and the position where the opening degree deviates is labeled, for example, it occurs at the valve core of the butterfly valve, and a state monitoring data table is generated.

[0105] The demand comparison submodule extracts the time point corresponding to the unmet flow based on the state monitoring data table, identifies the hydraulic power surplus and the instantaneous gap, matches the target gap with the power paragraph, and generates a demand comparison result table;

[0106] Based on the state monitoring data table, in the hydraulic control system of the water conservancy hoist, by analyzing the pressure mutation and opening deviation data recorded in the state monitoring data table, the corresponding time point that cannot meet the flow demand is identified, for example, the pressure drops suddenly at T1, causing the flow to be temporarily insufficient, at which time T1 is recorded, at the same time, by calculating the operating parameters of the hydraulic pump and the current load, the current power surplus of the hydraulic system is identified, for example, the maximum output power of the hydraulic pump is 100kW, the current actual output power is 60kW, then the power surplus is 40kW, and the power required for the instantaneous flow gap is calculated, for example, the flow gap at T1 requires an additional 15kW power, the target gap is matched with the power paragraph of the hydraulic system, for example, it is identified that the 15kW power gap belongs to the adjustable power paragraph of the system, and a demand comparison result table is generated.

[0107] The dynamic adjustment submodule fills in the pressure fluctuation gap by adjusting the matching order of hydraulic power output and butterfly valve opening, identifies the power gap node and response lag section, extracts the unexecuted section and standby path, updates the hydraulic output timing and butterfly valve control curve, and generates a butterfly valve dynamic adjustment adjustment scheme based on the demand comparison result table.

[0108] Based on the demand comparison result table, in the dynamic adjustment of the hydraulic system of the water conservancy hoist, by analyzing the data in the demand comparison result table, the hydraulic power gap node is identified, for example, a 15kW power gap occurs in the main pipeline flow at T1, and the response lag section, for example, there is a 0.2 second delay from detecting the gap to starting to make up the power, by accurately controlling the speed or displacement of the hydraulic pump, adjusting the hydraulic power output, and adjusting the opening of the butterfly valve, for example, increasing the opening of the butterfly valve from 50% to 52%, to fill in the pressure fluctuation gap, for example, to make up for the pressure drop at T1, at the same time, the unexecuted section is extracted, for example, the duration of time during which a certain flow demand is not fully met, and the standby path, for example, the auxiliary hydraulic circuit is opened, according to the analysis result, the timing of the hydraulic output is updated, for example, the output power of the hydraulic pump at T1 is increased to 75kW, and the control curve of the butterfly valve is adjusted, for example, the opening of the butterfly valve at T1 is quickly increased to 52%, and a butterfly valve dynamic adjustment adjustment scheme is generated.

[0109] Please refer to Figure 8 , the automatic adjustment method of the hydraulic butterfly valve is executed based on the above-mentioned automatic adjustment system of the hydraulic butterfly valve, comprising the following steps:

[0110] S1: According to the hydraulic pump output pressure and flow characteristic curve, the hydraulic power output parameter and the butterfly valve target opening value are extracted, the normalized hydraulic oil temperature and viscosity influence factor are matched, the hydraulic power and the target opening relationship are matched, and the hydraulic power output adaptation table is generated;

[0111] S2: Based on the hydraulic power output adaptation table, the target and real-time opening deviation value is extracted, the offset amplitude and response duration are calculated, the opening change rate and response time data are screened, and the butterfly valve opening correction data set is generated;

[0112] S3: Based on the butterfly valve opening correction data set, the flow change frequency and peak node in unit time are extracted, the differential pressure response value is associated to identify abnormal transition points and stable recovery points, the echo time and jump boundary in the pressure fluctuation interval are extracted, and the flow demand matching table is generated;

[0113] S4: Based on the flow demand matching table, the high-frequency flow priority section and the fluctuation peak position are analyzed, the step change node is identified and the main channel and compensation path are reconstructed, and the initial flow path and pressure balance scheme are constructed;

[0114] S5: Based on the initial flow path and pressure balance scheme, the unsatisfied flow demand parameter and key node fluctuation state value are screened, the offset frequency peak value is extracted and the opening adjustment control logic is corrected, and the butterfly valve dynamic adjustment adjustment scheme is generated.

[0115] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any skilled person in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An automatic regulating system for a hydraulic butterfly valve, characterized in that, The system includes: The hydraulic power control module extracts hydraulic power output parameters based on the hydraulic pump output pressure and flow characteristic curves, analyzes the influence of hydraulic oil temperature and viscosity on power transmission, organizes the hydraulic power and butterfly valve opening relationship model, and obtains the hydraulic power output adaptation table. Based on the hydraulic power output adapter table, the opening detection and correction module extracts the deviation between the real-time opening value and the target opening value of the butterfly valve, identifies the opening change rate and response time, quantifies the cumulative effect of opening error, summarizes the opening correction weight, and obtains the butterfly valve opening correction dataset. Based on the butterfly valve opening correction dataset, the flow dynamic matching module extracts the flow demand distribution parameters and performs hierarchical weighted analysis by combining the hydraulic system pressure fluctuation characteristics and the butterfly valve opening change law to obtain the flow demand matching table. Based on the flow demand matching table, the pressure balance optimization module sorts the flow priority and pressure demand ratio, identifies the pressure distribution relationship between the hydraulic system and the butterfly valve, adjusts the distribution order according to the pressure node fluctuation, and constructs an initial pressure balance scheme.

2. The hydraulic butterfly valve automatic adjustment system according to claim 1, characterized in that: The hydraulic power output adapter table includes pressure classification parameters, flow control range, temperature and viscosity compensation coefficient, and opening coupling coefficient. The butterfly valve opening correction dataset includes opening error factor, response delay parameter, change rate index, and correction weighting value. The flow demand matching table includes graded flow range, demand priority level, fluctuation threshold, and matching coefficient weight. The initial pressure balance scheme includes pressure distribution structure, node adjustment sequence, fluctuation correction factor, and flow distribution factor.

3. The automatic adjustment system for the hydraulic butterfly valve according to claim 1, characterized in that: The hydraulic power control module includes: The hydraulic characteristic extraction submodule extracts hydraulic power output parameters based on the hydraulic pump output pressure and flow characteristic curves, classifies the hydraulic oil temperature and viscosity influencing factors, and generates a hydraulic power output characteristic table. Based on the hydraulic power output characteristic table, the power transmission analysis submodule analyzes the influence of hydraulic oil temperature and viscosity on power transmission efficiency, calculates the hydraulic power output adaptation value under different working conditions, and generates a model of the relationship between hydraulic power and butterfly valve opening. The adapter table generation submodule, based on the hydraulic power and butterfly valve opening relationship model, organizes the hydraulic power output parameters, analyzes the correspondence with the target butterfly valve opening value, and generates a hydraulic power output adapter table.

4. The automatic adjustment system for the hydraulic butterfly valve according to claim 3, characterized in that: The opening detection and correction module includes: The opening deviation extraction submodule extracts the deviation between the real-time opening value and the target opening value of the butterfly valve based on the hydraulic power output adapter table, records the opening change rate and response time data, and generates an opening deviation data table. The error accumulation quantification submodule quantifies the cumulative effect of opening error based on the opening deviation data table, analyzes the difference between the hydraulic power distribution and the opening demand ratio, and generates an opening error accumulation effect table. The correction weight summarization submodule extracts the magnitude and correction frequency of the opening error cumulative effect table, filters high-frequency error segments and marks the direction of the deviation, summarizes the opening correction weights, and generates a butterfly valve opening correction dataset.

5. The hydraulic butterfly valve automatic adjustment system according to claim 4, characterized in that: The dynamic traffic matching module includes: The flow demand extraction submodule extracts flow demand distribution parameters, categorizes flow demand priority data, and generates a flow demand distribution table based on the butterfly valve opening correction dataset. The pressure fluctuation analysis submodule calculates the pressure node fluctuation state value based on the flow demand distribution table, combined with the pressure fluctuation characteristics of the hydraulic system and the butterfly valve opening change law, and generates a pressure fluctuation state table. The hierarchical weighted analysis submodule performs a multi-dimensional comparison between flow demand and pressure fluctuation based on the pressure fluctuation status table, filters the flow demand distribution adaptation relationship, and generates a flow demand matching table.

6. The hydraulic butterfly valve automatic adjustment system according to claim 5, characterized in that: The pressure node fluctuation state value is calculated using the following formula: ； in, This represents the fluctuation state value of the pressure node. This represents the pressure change during the i-th time period. This represents the change in valve opening for each pressure fluctuation. Represents a time interval. Represents the change in flow rate. represents the initial flow rate, and n represents the number of fluctuating periods.

7. The hydraulic butterfly valve automatic adjustment system according to claim 5, characterized in that: The pressure balance optimization module includes: The priority ranking submodule extracts the peak flow position and pressure difference threshold based on the flow demand matching table, analyzes the flow contribution under unit pressure difference, and generates a flow priority ranking table. The pressure distribution identification submodule extracts the pressure change trajectory of the main channel node based on the flow priority sorting table, identifies the pressure difference balance point and the offset direction, and generates a pressure distribution relationship table. The fluctuation adjustment submodule, based on the pressure distribution relationship table, adjusts the allocation order according to the pressure node fluctuation, extracts the frequency and amplitude sequence of node pressure difference changes, counts the offset amplitude and duration of nodes with excessive pressure difference, divides the stable interval and fluctuation transition segment, filters the main channel access order and bypass auxiliary channel connection nodes, and generates an initial pressure balance scheme.

8. The automatic adjustment system for the hydraulic butterfly valve according to claim 1, characterized in that: The system also includes an actuator self-matching adjustment module: Based on the initial pressure balance scheme, the actuator self-matching adjustment module monitors the hydraulic system pressure status and butterfly valve opening execution, compares the unmet flow requirements with the remaining hydraulic capacity in real time, fills the pressure fluctuation gap by adjusting the matching sequence of hydraulic power output and butterfly valve opening, and generates a butterfly valve dynamic adjustment scheme. The butterfly valve dynamic adjustment scheme includes residual adjustment parameters, execution sequence configuration, residual pressure utilization rate, and adjustment completion criteria.

9. The automatic adjustment system for the hydraulic butterfly valve according to claim 8, characterized in that: The actuator self-matching adjustment module includes: Based on the initial pressure balance scheme, the status monitoring submodule collects pressure node values ​​and butterfly valve opening feedback, records the jump time and deviation magnitude, marks the pressure change and opening offset position, and generates a status monitoring data table. Based on the status monitoring data table, the demand comparison submodule extracts the time points corresponding to unmet flow rates, identifies the remaining hydraulic power and instantaneous gaps, matches the target gaps with power segments, and generates a demand comparison result table. Based on the demand comparison result table, the dynamic adjustment submodule fills the pressure fluctuation gap by adjusting the matching sequence of hydraulic power output and butterfly valve opening, identifies power gap nodes and response lag segments, extracts unexecuted segments and backup paths, updates the hydraulic output timing and butterfly valve control curve, and generates a butterfly valve dynamic adjustment scheme.

10. An automatic adjustment method for a hydraulic butterfly valve, characterized in that, The method is used to implement the automatic adjustment system of the hydraulic butterfly valve according to any one of claims 1-9, and includes the following steps: S1: Based on the hydraulic pump output pressure and flow characteristic curve, extract the hydraulic power output parameters and the target opening value of the butterfly valve, normalize the hydraulic oil temperature and viscosity influence factors, match the relationship between hydraulic power and target opening, and generate a hydraulic power output adaptation table. S2: Based on the hydraulic power output adapter table, extract the target and real-time opening deviation value, calculate the offset amplitude and response duration, filter the opening change rate and response time data, and generate a butterfly valve opening correction dataset. S3: Based on the butterfly valve opening correction dataset, extract the frequency of flow change and peak nodes per unit time, associate the differential pressure response value to identify abnormal transition points and stable recovery points, extract the echo time and jump boundary within the pressure fluctuation range, and generate a flow demand matching table. S4: Based on the traffic demand matching table, analyze the high-frequency traffic priority segments and fluctuation peak positions, identify step change nodes and reconstruct the main channel and compensation path, and construct the initial traffic path and pressure balance scheme. S5: Based on the initial flow path and pressure balance scheme, filter out parameters that do not meet the flow requirements and key node fluctuation values, extract the peak value of the offset frequency and correct the opening adjustment control logic to generate a butterfly valve dynamic adjustment scheme.

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