Hydrometric station monitoring management system and method

Abstract

This invention relates to the field of water conservancy engineering and intelligent automation control technology, specifically to a hydrological station monitoring and management system and method, comprising: a hydrological parameter acquisition module for acquiring hydrological environmental parameters; a physical state acquisition module for acquiring non-hydrological physical state data of actuators; a hydrological processing module for determining the optimal hydrological control command; a fatigue monitoring module for determining the current structural resonance energy reserve; a risk assessment module for determining the physical survival risk index of the actuators; and an adaptive control module for determining the optimal hydrological control command or the survival-priority suboptimal control command as the final control command based on the risk index. This invention avoids the catastrophic consequences of actuators completely losing control due to jamming, ensuring the long-term safe operation of hydrological stations.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering and intelligent automation control technology, specifically to a hydrological station monitoring and management system and method. Background Technology

[0002] With the continuous advancement of hydrological monitoring technology, the scheduling and management of hydrological stations are increasingly reliant on automated systems. Currently, the control of hydrological stations typically relies solely on hydrological environmental parameters such as upstream water levels and predicted rainfall, using hydrological models to calculate optimal scheduling commands to meet flood control or water storage needs. However, traditional hydrological control models often neglect the non-hydrological physical states of actuators such as gates, failing to detect high-frequency vibrations and stress damage caused by the coupling resonance between water flow and structure. This limitation means that in pursuing hydrological scheduling efficiency, the actuators may face the risk of jamming or loss of control due to accumulated fatigue, seriously threatening the operational safety of the stations. Therefore, how to ensure hydrological scheduling efficiency while monitoring and mitigating the physical survival risks of actuators in real time has become an urgent problem to be solved in this field. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides a hydrological station monitoring and management system and method. Specifically, the technical solution of this invention is as follows:

[0004] A hydrological station monitoring and management system includes:

[0005] Hydrological parameter acquisition module, used to acquire hydrological environmental parameters;

[0006] The physical state acquisition module is used to acquire non-hydrological physical state data of the actuator;

[0007] The hydrological processing module is used to determine the optimal hydrological control command based on hydrological environmental parameters and a preset optimal hydrological scheduling model.

[0008] The fatigue monitoring module is used to determine the current structural resonance energy stock based on non-hydrological physical state data and a preset structural fatigue evolution model.

[0009] The risk assessment module is used to determine the physical survival risk index of the actuator based on the structural resonance energy reserves and the preset emergency intervention threshold.

[0010] The adaptive control module is used to determine the hydrological optimal control command as the final control command when the actuator physical survival risk index is less than or equal to a preset risk threshold; and to determine the survival-priority suboptimal control command as the final control command based on the hydrological optimal control command and the preset resonance damage disturbance amount when the actuator physical survival risk index is greater than the preset risk threshold.

[0011] Preferably, the hydrological parameter acquisition module is used to acquire hydrological environmental parameters, including: upstream real-time water level, downstream safe water level, upstream flood control limit water level, predicted rainfall, and current actual gate opening.

[0012] Preferably, the physical state acquisition module is used to acquire non-hydrological physical state data of the actuator, including vibration amplitude and vibration main frequency.

[0013] Preferably, the hydrological processing module is used to determine the optimal hydrological control command based on hydrological environmental parameters and a preset optimal hydrological scheduling model, including:

[0014] Based on hydrological environmental parameters, a pre-set hydrodynamic model is used to predict the water level in the future prediction time domain.

[0015] The optimal gate opening sequence is calculated by minimizing a preset hydrological safety cost function;

[0016] Extract the first element of the optimal gate opening sequence as the optimal hydrological control command.

[0017] Preferably, the fatigue monitoring module is also used for:

[0018] Based on the vibration principal frequency in non-hydrological physical state data, and combined with the preset gate structure's inherent resonant frequency and resonant peak half-width, the resonance amplification factor is calculated.

[0019] The structural resonance energy growth rate is calculated based on the vibration amplitude in non-hydrological physical state data, the resonance amplification factor, and the preset structural energy coupling coefficient and fatigue damage index.

[0020] Preferably, the fatigue monitoring module is also used for:

[0021] Based on the structural resonance energy growth rate and the preset fatigue energy dissipation coefficient, the current structural resonance energy stock is determined by solving the preset dynamic change differential equation.

[0022] Preferably, the risk assessment module is used to determine the physical survival risk index of the actuator based on the structural resonance energy reserve and a preset emergency intervention threshold, including:

[0023] Divide the current structural resonance energy stock by the preset emergency intervention threshold to determine the actuator physical survival risk index.

[0024] Preferably, the adaptive control module is also used for:

[0025] When the physical survival risk index of the actuator is less than or equal to the preset risk threshold, the system is determined to be in the hydrological optimal control state.

[0026] When the physical survival risk index of the actuator exceeds a preset risk threshold, the system is determined to switch to physical survival control state.

[0027] Preferably, the adaptive control module is also used for:

[0028] In response to the optimal hydrological control state, the optimal hydrological control command is determined as the final control command;

[0029] In response to the physical survival control state, the second-best control command that prioritizes survival is determined as the final control command.

[0030] A method for monitoring and managing hydrological stations includes the following steps:

[0031] Obtain hydrological and environmental parameters;

[0032] Acquire non-hydrological physical state data of the actuator;

[0033] Based on the hydrological environmental parameters and the preset optimal hydrological scheduling model, the optimal hydrological control command is determined.

[0034] Based on the aforementioned non-hydrological physical state data and the preset structural fatigue evolution model, the current structural resonance energy stock is determined;

[0035] Based on the structural resonance energy reserves and the preset emergency intervention threshold, the physical survival risk index of the actuator is determined;

[0036] In response to the actuator's physical survival risk index being less than or equal to a preset risk threshold, the hydrological optimal control command is determined as the final control command.

[0037] In response to the actuator's physical survival risk index being greater than a preset risk threshold, based on the hydrological optimal control command and the preset resonance damage disturbance amount, the survival-priority suboptimal control command is determined as the final control command.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. This application constructs a dual-sensing closed loop that integrates hydrological and physical conditions, solving the traditional blind spots. In addition to collecting conventional hydrological environmental parameters, it adds real-time monitoring of non-hydrological physical condition data such as actuator vibration amplitude, main frequency, and structural stress. By constructing a closed-loop system that integrates hydrological scheduling and physical survival status monitoring, it overcomes the shortcomings of existing technologies that only focus on hydrological indicators and ignore the physical health of actuators. It realizes effective perception of high-frequency damage caused by the coupling resonance of water flow and structure, and significantly improves the system's early warning capability for potential physical faults.

[0040] 2. This application establishes an energy-based structural fatigue evolution model, realizes dynamic quantification of damage, introduces a structural fatigue monitoring module, uses a resonance amplification factor to quantify the destructive effect when the vibration frequency is close to the natural frequency, and calculates the accumulation and dissipation of structural resonance energy through differential equations. This method transforms the abstract actuator accumulated damage into a calculable structural resonance energy stock, which not only considers the instantaneous damage rate caused by resonance, but also covers the physical process of stress release, providing accurate quantitative indicators that conform to physical reality for control decisions.

[0041] 3. This application designs a standardized risk assessment mechanism and provides clear decision criteria. The calculated structural resonance energy stock is compared with the preset emergency intervention threshold through the risk assessment module to generate a normalized actuator physical survival risk index. This mechanism transforms the complex physical fatigue state into a dimensionless intuitive indicator, enabling the control system to quickly and accurately identify whether the actuator is on the verge of failure. This provides a unique and reliable logical basis for the system to switch between pursuing hydrological efficiency and ensuring physical safety.

[0042] 4. This application implements a survival-first adaptive control strategy, ensuring the overall robustness of the system and possessing adaptive arbitration capabilities. When the physical survival risk index is detected to exceed the standard, it can proactively violate the optimal hydrological command and execute a suboptimal command that includes resonance-induced disturbance. By proactively changing the gate opening to disrupt the resonance condition, although the system temporarily sacrifices short-term hydrological scheduling optimality, it effectively suppresses the malignant growth of fatigue damage, avoids the catastrophic consequence of the actuator completely losing control due to jamming, and ensures the long-term safe operation of the hydrological station. Attached Figure Description

[0043] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0044] Figure 1 This is a structural diagram of the system of the present invention;

[0045] Figure 2 This is a flowchart illustrating the generation of the final control command in this invention.

[0046] Figure 3 This is a flowchart of the method of the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0048] Example 1:

[0049] Please see Figure 1 A hydrological station monitoring and management system, comprising:

[0050] Hydrological parameter acquisition module, used to acquire hydrological environmental parameters;

[0051] The physical state acquisition module is used to acquire non-hydrological physical state data of the actuator;

[0052] The hydrological processing module is used to determine the optimal hydrological control command based on hydrological environmental parameters and a preset optimal hydrological scheduling model.

[0053] The fatigue monitoring module is used to determine the current structural resonance energy stock based on non-hydrological physical state data and a preset structural fatigue evolution model.

[0054] The risk assessment module is used to determine the physical survival risk index of the actuator based on the structural resonance energy reserves and the preset emergency intervention threshold.

[0055] The adaptive control module is used to determine the hydrological optimal control command as the final control command when the actuator physical survival risk index is less than or equal to a preset risk threshold; and to determine the survival-priority suboptimal control command as the final control command based on the hydrological optimal control command and the preset resonance damage disturbance amount when the actuator physical survival risk index is greater than the preset risk threshold.

[0056] This embodiment provides a hydrological station monitoring and management system. Based on the physical architecture of the gate actuator, the system constructs a closed-loop control system that integrates optimal hydrological scheduling and actuator physical survival status monitoring. The actuator mentioned here specifically refers to the physical equipment used to control water flow in the hydrological station, such as floodgates, turbine guide vanes, or valves. In this embodiment, a floodgate is used as a preferred example as an actuator. The system includes six core modules.

[0057] The purpose of the hydrological parameter acquisition module is to provide real-time environmental data input for optimal hydrological scheduling. In this embodiment, it is used to acquire hydrological environmental parameters of the gate actuator, such as upstream real-time water level, downstream safe water level, and predicted rainfall.

[0058] The physical state acquisition module aims to acquire data reflecting the health status of actuators, such as floodgates, which is usually overlooked in traditional hydrological models. In this embodiment, it is used to acquire non-hydrological physical state data of the actuators, such as high-frequency data like vibration and stress obtained by sensors deployed on the gate.

[0059] The hydrological processing module aims to calculate a theoretically optimal hydrological control command based on the current hydrological conditions. This module uses environmental parameters acquired by the hydrological parameter acquisition module and a pre-defined optimal hydrological scheduling model, such as Model Predictive Control (MPC), to determine a function that minimizes the hydrological safety cost. Hydrological optimal control command for the target ;

[0060] The fatigue monitoring module is technically motivated by the need to quantify the instantaneous energy accumulation state caused by water flow-structure coupling resonance, which may lead to actuator jamming or loss of control. Based on non-hydrological physical state data acquired by the physical state acquisition module and according to a pre-set structural fatigue evolution model, this module calculates and determines the current structural resonance energy stock in real time. ;

[0061] The risk assessment module aims to abstract the structural resonance energy stock. This is transformed into a standardized risk index that can be used for decision-making; this module is based on the calculations of the fatigue monitoring module. With a preset emergency intervention threshold Comparison to determine the actuator's physical survival risk index ;

[0062] The adaptive control module is the core of the decision-making process in this invention; its purpose is to intelligently arbitrate between the two potentially conflicting objectives of hydrological optimization and physical survival.

[0063] In response to the risk assessment module If the value is less than or equal to a preset risk threshold, such as 1, it indicates that the actuator is physically safe; at this time, the module determines the value calculated by the hydrological processing module. For final control commands ;

[0064] In response to If the value exceeds this threshold, it indicates that the actuator is on the verge of failure; at this point, the module actively violates the hydrological optimality instruction, based on... With a preset resonance-destructive disturbance Determine a survival-first, suboptimal control command. For final control commands ;

[0065] By constructing a dual closed-loop feedback system that balances hydrological optimality and physical survivability, this system overcomes a major technical deficiency in existing hydrological control models that can lead to runaway control due to neglecting the physical health of actuators. It ensures that the system operates under normal conditions, i.e. At times, the pursuit is for high efficiency in hydrological scheduling, but in extreme situations where actuators are on the verge of failure, i.e. At times, it can proactively sacrifice short-term hydrological optimality and instead implement a physical survival strategy in exchange for the continued physical controllability of the entire control system, thereby improving the overall operational robustness and safety of the hydrological station.

[0066] Example 2:

[0067] The hydrological parameter acquisition module is used to acquire hydrological environmental parameters, including: upstream real-time water level, downstream safe water level, upstream flood control limit water level, predicted rainfall, and current actual gate opening.

[0068] In this embodiment, the hydrological parameter acquisition module is described in detail; this module is a prerequisite for the optimal scheduling of the hydrological processing module.

[0069] The purpose of the hydrological parameter acquisition module is to obtain the function for calculating hydrological security costs. All required real-time variables; in this embodiment, this module is used to acquire hydrological environmental parameters, specifically including: upstream real-time water level. Its source is the real-time data collected by water level gauges deployed upstream; downstream safe water level Its source is the benchmark value set according to the flood control regulations of downstream cities; the upstream flood control limit water level. Its source is the benchmark value set according to the watershed design specifications and flood control plan; predicted rainfall The data is obtained from weather radar or third-party weather service interfaces, and the current actual opening degree of the gate. The source of this information is feedback from the gate actuator's opening encoder or sensor.

[0070] By clearly defining and limiting the core input variables of hydrological scheduling This ensures that the hydrological processing module obtains comprehensive and necessary status information, which is essential for subsequent calculation of accurate optimal hydrological control commands based on the MPC model. The foundation and premise of.

[0071] Example 3:

[0072] The physical state acquisition module is used to acquire non-hydrological physical state data of the actuator, including vibration amplitude and vibration main frequency.

[0073] In this embodiment, the physical state acquisition module is described in detail; this module is the sensing basis for the fatigue monitoring module to quantify structural damage.

[0074] The physical state acquisition module aims to capture high-frequency physical signals caused by water flow excitation that may lead to structural resonance. In this embodiment, the module is used to acquire non-hydrological physical state data of the actuator, i.e., the floodgate. Specifically, it is implemented by deploying sensor arrays at key stress points of the gate body, for example, by acquiring vibration amplitude through high-frequency vibration sensors, such as accelerometers. The dominant frequency of vibration can be obtained by using acoustic sensors or by performing a Fourier transform (FFT) on the vibration signal. ;

[0075] By collecting The presence of high-frequency physical quantities enables this system to monitor, in real time and directly, the flow-structure coupling resonance phenomenon, which is typically imperceptible in traditional hydrological models at the second or minute level. This provides a basis for subsequent precise quantification of the structural resonance energy growth rate. and existing stock It provides critical, real-time raw data input.

[0076] Example 4:

[0077] The hydrological processing module is used to determine the optimal hydrological control commands based on hydrological environmental parameters and a preset optimal hydrological scheduling model, including:

[0078] Based on hydrological environmental parameters, a pre-set hydrodynamic model is used to predict the water level in the future prediction time domain.

[0079] The optimal gate opening sequence is calculated by minimizing a preset hydrological safety cost function;

[0080] Extract the first element of the optimal gate opening sequence as the optimal hydrological control command.

[0081] In this embodiment, the internal calculation logic of the hydrological processing module is described in detail. The core of this module is based on Model Predictive Control (MPC) theory to achieve the optimal balance between flood control safety and water storage supply. The calculation logic of this module is as follows:

[0082] The module is based on the hydrological parameter acquisition module. Parameters such as those used in a pre-defined hydrodynamic model, for example ,in The hydrodynamic transfer function is used to predict the future time domain. Upstream predicted water level and downstream predicted water level ;

[0083] By minimizing the preset hydrological safety cost function Calculate an optimal gate opening sequence. The cost function In this embodiment, the following definitions apply:

[0084]

[0085] In this formula, Let be the hydrological safety cost function, and minimizing it is the optimization objective of this step; For the prediction time domain, it refers to the length of time the model predicts forward, such as the next 24 hours; The upstream predicted water level at time t is obtained from the aforementioned hydrodynamic model; This is the upstream flood control limit level, which is a preset value determined according to flood control regulations; The downstream predicted water level at time t is obtained from the aforementioned hydrodynamic model; The safe water level for downstream cities is determined by a preset value based on the watershed design specifications. and The scheduling weighting factor is derived from historical flood control plans and pre-set watershed management objectives. For example, during peak flood periods, the weighting factor is increased. The weighting is prioritized to ensure downstream flood control safety, and during the dry season, the weighting is increased. Weighting is used to ensure upstream water storage;

[0086] The module extracts the optimal gate opening sequence. The first element This is used as the optimal hydrological control command and transmitted to the adaptive control module as the decision-making benchmark.

[0087] By adopting the MPC model and minimizing the cost function This module can calculate a value in the prediction time domain. The theoretically optimal control command that comprehensively balances the two major objectives of flood control and water storage. This provides a scientific and quantifiable basis for decision-making regarding the system's operation under optimal hydrological conditions.

[0088] Example 5:

[0089] The fatigue monitoring module is also used for:

[0090] Based on the vibration principal frequency in non-hydrological physical state data, and combined with the preset gate structure's inherent resonant frequency and resonant peak half-width, the resonance amplification factor is calculated.

[0091] The vibration amplitude is calculated based on non-hydrological physical state data; the resonance amplification factor is used; and the pre-set structural energy coupling coefficient and fatigue damage index are combined to calculate the structural resonance energy growth rate.

[0092] Based on the structural resonance energy growth rate and the preset fatigue energy dissipation coefficient, the current structural resonance energy stock is determined by solving the preset dynamic change differential equation.

[0093] In this embodiment, the internal calculation logic of the fatigue monitoring module is described in detail. The core task of this module is to construct and solve the structural fatigue evolution model to determine the current structural resonance energy reserves. ;

[0094] The calculation process includes the following steps:

[0095] Calculate the structural resonance energy growth rate The technical motivation for this step is to quantify the instantaneous structural damage rate caused to the actuator by the current flow-structure coupling resonance.

[0096] To perform this calculation, the resonance amplification factor is calculated. Its purpose is to quantify the current dominant vibration frequency. Approaching the structure's natural resonant frequency The destructive amplification effect produced at that time;

[0097] To ensure dimensional uniformity and conformity to the physical resonance model, in this embodiment, the formula is modified and defined as a standardized Lorentz function form, specifically: ;

[0098] In this formula, The dimensionless resonance amplification factor has a value in It reaches its maximum value of 1, i.e., the peak value, at [time]. Deviation Its value drops rapidly at that time; The main vibration frequency being monitored is obtained in real time by the physical state acquisition module; The inherent resonant frequency of the gate structure is determined in advance through finite element modal analysis or on-site frequency sweep testing of the gate actuator system. The full width at half maximum (FWHM) of the resonance peak, i.e., the frequency width at which the power spectral density drops to half, originates from the same source as... Certify together;

[0099] Based on dimensionless resonance amplification factor and real-time vibration amplitude Calculate the structural resonance energy growth rate Its formula is: ;

[0100] In this formula, The structural resonance energy growth rate; The structural energy coupling coefficient is derived from the energy absorption rate measured under unit amplitude by conducting a sweep frequency vibration experiment on the gate structure. The real-time vibration amplitude is obtained in real time by the physical state acquisition module. The fatigue damage index is usually... Its source is the same Certify together; This is the resonance amplification factor, calculated in the previous step;

[0101] Obtaining the instantaneous structural resonance energy growth rate Subsequently, the fatigue monitoring module needs to further calculate its cumulative effect, that is, the current structural resonance energy stock. ;

[0102] It is defined as a structural stress state that can be accumulated and dissipated; its dynamic change process is described by a pre-defined dynamic change differential equation:

[0103]

[0104] In this formula, The instantaneous rate of change of the resonance energy; The resonant energy growth rate is calculated in the previous step; This is the fatigue energy dissipation coefficient, and its unit is the reciprocal of the second. The calibration method is derived from calculating the logarithmic decay rate by conducting free decay vibration experiments on the gate structure. The current structural resonance energy stock represents the level of resonance energy currently accumulated in the structure.

[0105] The system determines the current structural resonance energy stock by solving the differential equation in real time, for example, using the Euler method of integration. And transmit it to the risk assessment module;

[0106] This embodiment introduces... and The calculations, for the first time, quantified the resonance effect and fatigue accumulation rate that cause actuator jamming or malfunction, solving the problem that traditional models cannot detect this type of high-frequency damage; and, by introducing The dissipation coefficient in this invention not only considers the accumulation of damage. It also innovatively considers the dissipation of damage. A complete fatigue evolution model that better reflects physical reality was constructed, providing accurate and dynamic quantitative indicators for subsequent risk assessment. .

[0107] Example 6:

[0108] The risk assessment module is used to determine the physical survival risk index of the actuator based on the structural resonance energy reserve and the preset emergency intervention threshold, including:

[0109] Divide the current structural resonance energy stock by the preset emergency intervention threshold to determine the actuator physical survival risk index.

[0110] In this embodiment, the calculation logic of the risk assessment module is explained in detail;

[0111] The technical motivation behind this module is to quantify the current structural resonance energy reserves. relative to emergency intervention threshold Based on the degree of proximity, a dimensionless risk index is constructed to provide a clear and unique criterion for the adaptive control module;

[0112] This module is used to calculate the physical survival risk index of the actuator. Its formula is:

[0113]

[0114] In this formula, The physical survival risk index of the actuator is dimensionless. The energy reserve for structural resonance is calculated by the fatigue monitoring module. The emergency intervention threshold is derived from a preset threshold; it is based on the material's maximum permissible fatigue energy. This represents material fracture, taking into account safety margins, for example... And set; The source is derived from calculations based on the ultimate strain energy of the structure, and the specific calculation method is as follows: ,in The equivalent stiffness of the gate structure. Both parameters, which are the critical displacement values ​​that cause the gate to jam or undergo plastic deformation, are obtained in advance through finite element structural simulation analysis.

[0115] The calculation logic for this step is: directly use the output from the fatigue monitoring module. As a molecule, divided by a preset threshold , obtained This will serve as the core decision signal, which will be transmitted to the adaptive control module.

[0116] By storing the energy of complex, physically dimensional structures resonating. Normalized to a dimensionless risk index This invention provides an extremely clear, unique, and easily judged decision criterion for switching control strategies, specifically between hydrological optimality and physical survival; when Intervention is triggered immediately upon arrival, with simple and clear logic and high reliability.

[0117] Example 7:

[0118] Please see Figure 2 The adaptive control module is also used for:

[0119] When the physical survival risk index of the actuator is less than or equal to the preset risk threshold, the system is determined to be in the hydrological optimal control state.

[0120] When the physical survival risk index of the actuator exceeds a preset risk threshold, the system is determined to switch to physical survival control state.

[0121] In response to the optimal hydrological control state, the optimal hydrological control command is determined as the final control command;

[0122] In response to the physical survival control state, the second-best control command that prioritizes survival is determined as the final control command.

[0123] In this embodiment, the decision-making logic and control command generation of the adaptive control module are described in detail;

[0124] Risk Status Determination: This module compares the risk status data input from the risk assessment module in real time. The preset risk threshold is 1 in this embodiment;

[0125] In response to The system determines that the actuator is physically safe and that the system is in the optimal hydrological control state.

[0126] In response to The system determines that the fatigue energy exceeds the intervention threshold and the actuator is on the verge of failure, and then switches the system to physical survival control state.

[0127] Control commands are generated, and the module executes different control strategies based on the determined state:

[0128] Response to the optimal hydrological control state:

[0129] when At that time, the system prioritizes hydrological safety; the module determines the optimal hydrological control command. Its source is calculated by the hydrological processing module, and it serves as the final control command. Their relationship is:

[0130]

[0131] In response to physical survival control status:

[0132] when At this time, the system control logic switches, actively violating the hydrological optimal command. Switch to a control strategy prioritizing physical survival; the module determines the next best control command with survival as the primary objective. For final control commands This survival-first suboptimal control command The technical motivation is to sacrifice the optimality of the hydrological model in order to prioritize physical control, and the formula is as follows:

[0133]

[0134] In this formula, Suboptimal control commands prioritizing survival; This is the original optimal hydrological instruction, which is derived from calculations by the hydrological processing module. The disturbance caused by resonance disruption originates from a preset disturbance value, such as a fixed step size, random disturbance, or low-frequency jitter, and its source is the control strategy design; its objective is to maximize the resonance amplification factor. The rate of decline, i.e., the disruption of resonance, rather than minimizing the hydrological cost function. ;

[0135] In a preferred embodiment, It is set to a preset fixed step size, such as 1%-5% of the total gate opening. This step size is determined through offline simulation testing and is large enough to allow the dominant vibration frequency to reach its maximum within a reasonable time. Significant deviation from the resonant frequency In another embodiment, It could also be based on the current risk index. or energy growth rate The dynamic disturbance quantity is intended to make The value should be converted to a negative value as quickly as possible and reach its minimum, thereby rapidly suppressing resonance and restoring the system to a safe state.

[0136] By clearly defining state divisions and instruction switching, this invention constructs a closed-loop adaptive survival logic; when a detection is made... At that time, the system introduces disturbances. To execute Actively changing the gate opening alters the water flow pattern; this action leads to a change in the dominant vibration frequency. Deviation from resonant frequency , making Rapidly decreasing, structural resonance energy growth rate It is suppressed; this makes To become negative, that is , The exponential rate begins to decline, achieving resonant energy dissipation; this is done by disrupting the resonant condition, namely reducing the growth rate. , making This leads to the accumulation of resonant energy. The rapid reduction avoids the catastrophic consequence of the actuator jamming due to high-energy resonance and losing all physical control capabilities, thus ensuring the physical controllability of the system.

[0137] Example 8:

[0138] Please see Figure 3 A method for monitoring and managing hydrological stations, comprising the following steps:

[0139] Obtain hydrological and environmental parameters;

[0140] Acquire non-hydrological physical state data of the actuator;

[0141] Based on the hydrological environmental parameters and the preset optimal hydrological scheduling model, the optimal hydrological control command is determined.

[0142] Based on the aforementioned non-hydrological physical state data and the preset structural fatigue evolution model, the current structural resonance energy stock is determined;

[0143] Based on the structural resonance energy reserves and the preset emergency intervention threshold, the physical survival risk index of the actuator is determined;

[0144] In response to the actuator's physical survival risk index being less than or equal to a preset risk threshold, the hydrological optimal control command is determined as the final control command.

[0145] In response to the actuator's physical survival risk index being greater than a preset risk threshold, based on the hydrological optimal control command and the preset resonance damage disturbance amount, the survival-priority suboptimal control command is determined as the final control command.

[0146] This embodiment provides a specific implementation method for a hydrological station monitoring and management method.

[0147] This method is implemented in the automated control system of water conservancy projects, aiming to integrate optimal hydrological scheduling with actuator physical survival status monitoring to achieve closed-loop control.

[0148] The method includes the following core steps in logical order:

[0149] Step 1: Obtain hydrological environmental parameters;

[0150] This step is used to obtain real-time environmental data required for calculating optimal hydrological scheduling; specifically, it includes: collecting real-time upstream water levels using water level gauges deployed upstream. The downstream safe water level is obtained by referring to the benchmark values ​​set by the flood control regulations of downstream cities. The upstream flood control limit water level is obtained by referring to the benchmark values ​​set in the watershed design specifications and flood control plans. Predicted rainfall is obtained through weather radar or third-party weather service interfaces. ; and obtain the actual opening degree of the floodgate through feedback from the opening encoder or sensor of the floodgate, which acts as the actuator. ;

[0151] Step 2: Obtain non-hydrological physical state data of the actuator;

[0152] This step is used to capture high-frequency physical signals caused by water flow excitation that may lead to structural resonance, signals that are typically ignored in traditional hydrological models. Specifically, this involves deploying sensor arrays at key stress points on the spillway gate body, which acts as the actuator; for example, acquiring vibration amplitudes using high-frequency vibration sensors. The dominant vibration frequency is obtained through acoustic sensors or by performing a fast Fourier transform on the vibration signal. ;

[0153] Step 3: Determine the optimal hydrological control command;

[0154] This step, based on Model Predictive Control (MPC) theory, is used to calculate a theoretically optimal command. Based on the hydrological environmental parameters obtained in step one, a pre-defined hydrodynamic model is used to predict the water level within the future prediction time domain T. This is achieved by minimizing a pre-defined hydrological safety cost function. To calculate the optimal gate opening sequence Extract the optimal gate opening sequence. The first element , as the optimal control command for hydrology;

[0155] Step 4: Determine the current structural resonance energy level;

[0156] This step aims to quantify the cumulative damage caused by flow-structure coupled resonance; the calculation process includes:

[0157] Calculate the resonance amplification factor Based on the vibration principal frequency obtained in step two and the pre-calibrated structural natural resonant frequency With resonance peak half width value Through the Lorentz function Calculate the resonance amplification factor; this factor is used to quantify the destructive amplification effect when the vibration frequency is close to the natural frequency.

[0158] Calculate the structural resonance energy growth rate Based on vibration amplitude And the resonance amplification factor calculated in the previous step And combined with the preset structural energy coupling coefficient and fatigue damage index Calculate the structural resonance energy growth rate ;

[0159] Solve the dynamic differential equation: based on this growth rate With the preset fatigue energy dissipation coefficient (Characterizing structural damping or stress release) by solving dynamically changing differential equations in real time. Determine the current structural resonance energy stock. ;

[0160] Step 5: Determine the physical survival risk index of the actuator;

[0161] This step will abstract the structural resonance energy storage. This is transformed into a standardized, dimensionless risk index that can be used for decision-making. Its calculation logic is to use the current structural resonance energy stock determined in step four. Divide by a preset emergency intervention threshold ,Right now The It is based on the maximum allowable fatigue energy of the material. And it is preset with consideration of safety margin;

[0162] Step Six: Execute adaptive control decisions;

[0163] This step is the core of the decision-making process in this method, used to intelligently arbitrate between two potentially conflicting objectives: hydrological optimality and physical survival.

[0164] Risk status assessment: Real-time comparison with the risk index determined in step five. And the preset risk threshold;

[0165] Control command generation:

[0166] Optimal hydrological control state: response to The system determines that the physical state of the gate, acting as the actuator, is safe. At this point, with hydrological safety as the primary objective, the system determines the optimal hydrological control command calculated in step three. For final control commands ,Right now ;

[0167] Physical Survival Control State: Responding to The system determines that the fatigue energy exceeds the intervention threshold, and the actuator is on the verge of failure. At this point, the system control logic switches, actively violating the hydrological optimal command. Switch to a control strategy prioritizing physical survival; determine a second-best control command that prioritizes survival. For final control commands ,Right now This suboptimal instruction Through On top of this, a preset resonance-damping disturbance is superimposed. ( To generate;

[0168] Introduction The purpose is to actively change the gate opening to alter the water flow pattern, thereby increasing the dominant vibration frequency. Deviation from resonant frequency This leads to a resonant amplification factor. A rapid decline, leading to a malignant increase in fatigue energy, i.e., achieving... This ultimately avoids the catastrophic consequence of the floodgate, which acts as an actuator, becoming stuck due to high-energy resonance and losing all physical control capabilities, thus ensuring the physical controllability of the system.

[0169] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A hydrological station monitoring and management system, characterized in that, include: Hydrological parameter acquisition module, used to acquire hydrological environmental parameters; The physical state acquisition module is used to acquire non-hydrological physical state data of the actuator; The hydrological processing module is used to determine the optimal hydrological control command based on hydrological environmental parameters and a preset optimal hydrological scheduling model. The fatigue monitoring module is used to determine the current structural resonance energy stock based on non-hydrological physical state data and a preset structural fatigue evolution model. The risk assessment module is used to determine the physical survival risk index of the actuator based on the structural resonance energy reserves and the preset emergency intervention threshold. The adaptive control module is used to determine the hydrological optimal control command as the final control command when the physical survival risk index of the actuator is less than or equal to a preset risk threshold. And in response to the actuator's physical survival risk index being greater than a preset risk threshold, based on the hydrological optimal control command and the preset resonance damage disturbance amount, the survival-priority suboptimal control command is determined as the final control command. The physical state acquisition module is used to acquire non-hydrological physical state data of the actuator, including vibration amplitude and vibration main frequency. The fatigue monitoring module is also used for: Based on the vibration principal frequency from non-hydrological physical state data, and combined with the preset natural resonant frequency and resonance peak half-width of the gate structure, the resonance amplification factor is calculated. ; ； In this formula, It is a dimensionless resonance amplification factor; The main vibration frequency being monitored is obtained in real time by the physical state acquisition module; This is the inherent resonant frequency of the gate structure; This represents the full width at half maximum (FWHM) of the resonance peak. The structural resonance energy growth rate is calculated based on vibration amplitude data from non-hydrological physical state data, resonance amplification factor, and pre-defined structural energy coupling coefficient and fatigue damage index. Its formula is: ; In this formula, The structural resonance energy growth rate; The structural energy coupling coefficient; The real-time vibration amplitude is obtained in real time by the physical state acquisition module. The fatigue damage index is usually... ; This is the resonance amplification factor; The fatigue monitoring module is also used for: Based on the structural resonance energy growth rate and the preset fatigue energy dissipation coefficient, the current structural resonance energy stock is determined by solving the preset dynamic variation differential equation. ; ； In this formula, The instantaneous rate of change of the resonance energy; The resonant energy growth rate; The fatigue energy dissipation coefficient; This represents the current structural resonance energy reserves.

2. The hydrological station monitoring and management system according to claim 1, characterized in that, The hydrological parameter acquisition module is used to acquire hydrological environmental parameters, including: upstream real-time water level, downstream safe water level, upstream flood control limit water level, predicted rainfall, and current actual gate opening.

3. The hydrological station monitoring and management system according to claim 1, characterized in that, The hydrological processing module is used to determine the optimal hydrological control commands based on hydrological environmental parameters and a preset optimal hydrological scheduling model, including: Based on hydrological environmental parameters, a pre-set hydrodynamic model is used to predict the water level in the future prediction time domain. The optimal gate opening sequence is calculated by minimizing a preset hydrological safety cost function; Extract the first element of the optimal gate opening sequence as the optimal hydrological control command.

4. The hydrological station monitoring and management system according to claim 1, characterized in that, The risk assessment module is used to determine the physical survival risk index of the actuator based on the structural resonance energy reserve and the preset emergency intervention threshold, including: Divide the current structural resonance energy stock by the preset emergency intervention threshold to determine the actuator physical survival risk index.

5. A hydrological station monitoring and management system according to claim 1, characterized in that, The adaptive control module is also used for: When the physical survival risk index of the actuator is less than or equal to the preset risk threshold, the system is determined to be in the hydrological optimal control state. When the physical survival risk index of the actuator exceeds a preset risk threshold, the system is determined to switch to physical survival control state.

6. A hydrological station monitoring and management system according to claim 5, characterized in that, The adaptive control module is also used for: In response to the optimal hydrological control state, the optimal hydrological control command is determined as the final control command; In response to the physical survival control state, the second-best control command that prioritizes survival is determined as the final control command.

7. A method for monitoring and managing hydrological stations, applied to a hydrological station monitoring and management system as described in any one of claims 1 to 6, characterized in that, Includes the following steps: Obtain hydrological and environmental parameters; Acquire non-hydrological physical state data of the actuator; Based on the hydrological environmental parameters and the preset optimal hydrological scheduling model, the optimal hydrological control command is determined. Based on the aforementioned non-hydrological physical state data and the preset structural fatigue evolution model, the current structural resonance energy stock is determined; Based on the structural resonance energy reserves and the preset emergency intervention threshold, the physical survival risk index of the actuator is determined; In response to the actuator's physical survival risk index being less than or equal to a preset risk threshold, the hydrological optimal control command is determined as the final control command. In response to the actuator's physical survival risk index being greater than a preset risk threshold, based on the hydrological optimal control command and the preset resonance damage disturbance amount, the survival-priority suboptimal control command is determined as the final control command.

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