512 results about "Flood discharge" patented technology

The invention discloses a dam safety monitoring system and method based on digital twinning, and belongs to the technical field of data processing, and the method comprises the steps: collecting dam surface acoustic emission signals and internal infrared thermal image data in real time through a multi-source sensor, and generating a multi-dimensional damage feature matrix; constructing a disaster node topology network in combination with density peak clustering and dynamic weight; on the basis of gravitational field intensity calculation and improved Monte Carlo simulation, a damage chain reaction path is accurately predicted; generating a dynamic risk thermodynamic diagram through space-time folding mapping and a bidirectional diffraction equation; and extracting hidden danger indexes by adopting multi-axis domain characteristic distillation, dynamically comparing a safety envelope function, and generating a flood discharge scheduling and reinforcing scheme on line. According to the method, cross-modal fusion, a gravitational field dynamic topology network and a time-space folding mapping technology are adopted, deep fusion of accurate simulation of a damage energy conduction path, carbonization-deformation bidirectional coupling prediction and intelligent risk hidden danger disposal decision can be realized, and the accuracy and initiative of dam safety early warning are improved.

The invention discloses a reservoir scheduling decision support system for multi-objective optimization, and relates to the technical field of hydraulic engineering scheduling. According to the system, comprehensive optimization of flood control, power generation and ecological targets is realized through cooperative work of the multi-source dynamic constraint analysis module, the collaborative optimization module, the scheduling module and the correction module. A dynamic constraint boundary table is generated by collecting meteorological, hydrological and ecological data in real time. And matching a multi-target coordination rule through a physical constraint double-depth network algorithm, generating a Pareto feasible solution set, and mapping the Pareto feasible solution set into a coordination strategy of flood discharge flow and power generation output. In combination with a hydraulic model, flood control and power generation weights are adjusted, an executable dispatching instruction is generated, it is ensured that the ecological flow reaches the standard, and the influence of a downstream submerged area is optimized. And correcting the dynamic constraint boundary table according to actual monitoring data, and continuously optimizing a scheduling decision. Accurate management and multi-objective optimization of reservoir dispatching are realized, and the utilization efficiency of water resources is improved.

The invention relates to the technical field of water conservancy project risk early warning, in particular to a multi-modal time-space fusion water conservancy risk real-time early warning system, which comprises a multi-modal time-space data fusion module for performing time-space alignment and feature extraction calculation based on reservoir group sensor data flow, remote sensing images and weather forecast to obtain a fusion time-space situation value. According to the invention, by fusing the reservoir group sensor data flow, the remote sensing image and the weather forecast data, executing the space-time alignment and feature extraction calculation, and constructing the fused space-time situation value, the collaborative analysis precision and situation awareness of the multi-source heterogeneous data are improved, and the data utilization rate and the risk analysis accuracy are improved; when a potential scheduling operation set is established, gate opening degrees and flood discharge flow adjustment options under different time windows are defined, and the flexibility and the strain capacity of a scheduling scheme are enhanced, so that the scheduling operation better fits actual hydrological condition changes.

The invention discloses a reinforcement learning-based intelligent flood discharge scheduling method for a small reservoir. The method comprises the following steps of S1, forming a complete reservoir data set; s2, constructing an environment state vector required by reinforcement learning based on the reservoir data set; s3, generating an initial flood discharge scheduling strategy; s4, establishing an improved reinforcement learning model based on the environment state vector and the initial flood discharge scheduling strategy; s5, updating the strategy network in the improved reinforcement learning model to obtain an optimal flood discharge decision scheme; s6, gate operation is carried out according to the optimal flood discharge decision scheme, and the water level change of the small reservoir, the safety state of the downstream drainage basin and the ecological demand satisfaction degree after execution are monitored; and S7, inputting the feedback information into the improved reinforcement learning model again, and performing iterative updating and strategy correction on the improved reinforcement learning model in combination with the reservoir data set and the environment state vector. According to the invention, the efficiency and reliability of flood discharge scheduling of the small reservoir are obviously improved.

The invention provides a hydro-junction water level adjusting method and system. Wherein the sediment deposition space-time atlas containing the sedimentary gradient is constructed and periodically corrected through scanning of an underwater robot and synchronous acquisition of satellite remote sensing data. A radar array is deployed at a bend section of a flood discharge channel, and vector distribution of a three-dimensional sediment flow velocity field is analyzed by using multi-frequency pulse signals. Through correlation analysis of the dynamic coupling sedimentary gradient and the flow velocity field, a correlation area of flow velocity sudden change and sediment deposition is accurately identified, and a constraint condition set including coordinate positioning and a flow-sediment matching rule is established. And in combination with real-time water level monitoring data, calculating and generating a dynamic adjustment parameter sequence of the opening degree of the flood discharge gate by using a constraint condition set, thereby realizing accurate regulation and control of the water level. According to the technical scheme, the flood discharge parameters are intelligently optimized, the water level of the hydro-junction can be accurately regulated and controlled, the sediment deposition problem of a high-sediment-content water area is effectively relieved, and safe operation and flood control efficiency of the junction are guaranteed.

The invention relates to the technical field of flood discharge tunnel detection, and discloses a flood discharge tunnel automatic inspection and erosion defect intelligent detection method. The method comprises the following steps: acquiring structural state data in the flood discharge tunnel and performing standardization processing; dividing standard classification data according to preset hydrological working condition intervals, and extracting multi-modal sensing features of each interval to generate a working condition feature set; monitoring the switching frequency of the hydrological working condition interval, and activating a dynamic analysis strategy to identify an abnormal working condition interval when the switching frequency exceeds a preset threshold value; performing feature decoupling on the working condition feature set of the non-abnormal working condition interval according to the matching degree of the historical erosion stage feature and the current multi-mode sensing feature, and separating out an erosion feature subset; on the basis of coupling relevance of mechanical parameters and hydraulic parameters of the tunnel structure, parameter collaborative correction is carried out on the erosion feature subset; and finally, reversely tracing a potential defect source region along a defect evolution path by utilizing the corrected erosion feature subset, determining a repair priority and outputting a maintenance instruction.

The invention discloses a hydraulic engineering data intelligent monitoring method and system based on digital twinning, and the method comprises the steps: comprehensively considering the actual physical structure, operation parameters and surrounding environment information of a hydraulic engineering when a hydraulic engineering digital twinning model is constructed, and breaking through the limitation that a conventional monitoring means only pays attention to a single parameter or a few parameters; model association data is utilized and visualized display is carried out, management personnel can visually check states and parameter changes of all parts, the monitoring efficiency and comprehensiveness are improved, and the limitation that a traditional monitoring means lacks effective analysis and mining is solved. A risk assessment formula is adopted to convert data into risk indexes, so that managers can visually know the safety condition, when a risk assessment value exceeds a threshold value, the risk development trend and consequences are simulated and analyzed in combination with a model, problems and risks are found in advance, early warning is triggered, and related personnel can formulate response measures such as flood discharge flow adjustment and structure reinforcement according to simulation results. Disaster loss is reduced, and the safety and reliability of hydraulic engineering are improved.

An integrated system for detecting dam breaches, as an early warning system and for evacuation assistance, consisting of: A geoinformatics analysis module comprising a modeling processor with a graphics processing unit, configured to: analyze spatial, hydrological, and topographic data of a dam and its downstream area; generate hydrological models using probable maximum rainfall (PMP) data to determine probable maximum flood discharge (PMF); generate hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood arrival time; create flood vulnerability models, vulnerability models, and flood hotspot models using a multi-criteria decision-making (MCDM) framework; and generate evacuation plans for high-risk zones based on the models. A sensor monitoring subsystem includes: a distributed fiber optic sensor (DFOS) configured to monitor the structural load and deformation of a dam, and a radar level gauge configured to measure the water level in the reservoir; a microcontroller unit configured to receive and process sensor data from the sensor monitoring subsystem, to detect dam breaches based on abnormal structural movements detected by the DFOS or sudden drops in water level below predefined thresholds detected by the radar level gauge; a communication module configured to transmit warning messages when dam breaches are detected; a warning system configured to: send SMS notifications to residents in downstream high-risk zones via a GSM communication module, generate real-time alerts via an IoT platform on user devices, and activate siren systems in villages to issue loud alarms and voice announcements; and an evacuation assistance platform configured to provide real-time evacuation assistance in emergencies due to dam breaks, displaying site maps with nearby emergency shelters, evacuation routes, hospitals, government buildings and aid centers, showing hydrological layers including flood extent, water depth, flow velocity and arrival time of the water, and enabling real-time location tracking in relation to safety zones and flood-prone areas.

The invention relates to the technical field of hydraulic engineering safety monitoring, in particular to a safety monitoring method and system for a flood discharge and sand flushing service gate. The method comprises the steps that a super-strong permanent magnet sensor is installed on an underwater flood discharge and sand flushing service gate, and the magnetic attraction strength of the super-strong permanent magnet sensor is controlled according to real-time water flow; when the real-time water flow is larger than the preset water flow high threshold value, the magnetic attraction strength is enhanced; if the water flow is lower than the preset water flow high threshold value, the magnetic attraction strength is recovered to the standard magnetic attraction value; the ultra-strong permanent magnet sensor monitors vibration state data and dynamic stress data of each structure in the operation process of the underwater flood discharge and sand flushing service gate; obtaining a rigidity evaluation value and a dynamic stress safety evaluation value of the underwater flood discharge and sand flushing service gate; and performing evaluation in combination with the characteristic data in the operation process of the underwater flood discharge and sand flushing service gate to obtain the safety coefficient of the current underwater flood discharge and sand flushing service gate. The stability of the gate is dynamically enhanced, the magnetic attraction strength is matched with water flow impact in real time, and high-flow-speed loads are effectively resisted.

The invention relates to the technical field of reservoir flood control dispatching, and discloses a dam hydraulic opening and closing control method, device and equipment and a storage medium. The method comprises the steps that multi-source hydrological data, weather forecast information and unit operation states of a current reservoir are collected; inputting the multi-source hydrological data and the weather forecast information into a preset hydrological prediction model, and outputting a hydrological prediction result; based on the hydrological prediction result and the real-time reservoir area water level and the unit operation state in the multi-source hydrological data, a gate opening control instruction is generated through a reservoir optimization scheduling model; and a hydraulic opening and closing system is adjusted according to the gate opening control instruction, and the current reservoir flood discharge gate opening is controlled. According to the method, data such as upstream incoming water, reservoir area water level and water consumption are utilized, weather forecast information is combined, a hydrological prediction model is constructed, a reservoir dispatching scheme is optimized according to a hydrological model prediction result, the reservoir area water level and unit operation conditions, and on the premise that flood prevention safety is guaranteed, reservoir dispatching is optimized, the reservoir area water level is automatically adjusted, and power generation benefits are improved.

The invention discloses a distributed flood forecasting scheduling model construction method based on sub-basins, particularly relates to the technical field of flood forecasting model optimization, and is used for solving the problem of local prediction failure due to spatio-temporal differences caused by neglecting parameter sensitivity of an existing flood forecasting model. A target drainage basin is divided into sub-drainage basins, hydrological and geographic feature parameters are extracted, and a cross-drainage-basin water conservancy facility topology network is constructed to dynamically correct river channel evolution boundary conditions; quantifying parameter sensitivity spatial diversity based on a Sobo index method, identifying a sensitive abnormal response region in combination with historical flood event distribution, and applying spatial lag correction through a river topology network to generate parameter sensitivity grade classification; constructing a dynamic weight matrix, and performing partition parameter calibration by adopting global optimization and local adjustment strategies respectively; and the hydraulic equilibrium constraint of the calibration result is verified based on the river topological relation, and a partition and grading flood discharge scheduling scheme is generated after iterative correction, so that the forecasting capability in a sudden flood scene is remarkably improved.

The invention provides a flood control risk identification and early warning system and method for a reservoir group, and belongs to the technical field of flood prevention and fighting. According to the method, a standard data set is generated by collecting rainfall, reservoir water level, flood discharge flow and landform data and performing data processing. And based on the standardized data set, constructing a hydrological model of the reservoir group in combination with GIS data, simulating flood discharge capacities under different rainfall scenes, calculating a flood discharge capacity index, a flood control risk index, a downstream vulnerability index, an upstream flood formation index and a midstream flood propagation index, and carrying out weighted fusion to generate a comprehensive risk index. And according to comparison between the comprehensive risk index and preset low, medium and high early warning threshold values, determining a current risk level and issuing early warning information. Meanwhile, user feedback is received, and model parameters and an early warning strategy are dynamically adjusted. According to the invention, through a multi-source data fusion technology, a deep learning algorithm and a dynamic feedback mechanism, accurate identification and timely early warning of the flood control risk of the reservoir group are realized.

The invention relates to the technical field of risk management, in particular to a water conservancy project risk early warning analysis method and system based on multi-source information, and the method comprises the following steps: dividing a dam body, a flood discharge gate and a spillway region according to spatial dimensions, extracting leakage monitoring records of a flood season, a dry season and an emergency weather event period, and storing the leakage monitoring records; and calculating a trigger factor frequency to generate a trigger factor feature sequence. According to the method, through hierarchical division of space and time dimensions, extraction of trigger factor frequency and analysis of support degree and confidence degree are combined, so that extraction of risk factor features is more comprehensive and accurate. In the construction of the dynamic propagation path, the spatial trajectory and the time evolution rule of the risk factor are deeply analyzed, so that the propagation path of the risk factor is clearly displayed, the accurate prediction of the risk diffusion region is realized, and a basis is provided for the division of the risk level in the subsequent region.

The invention discloses a reservoir flood discharge flow simulation calculation method based on an LSTM model. The reservoir flood discharge flow simulation calculation method comprises the steps of collecting reservoir historical operation characteristic data; establishing a reservoir flood discharge scheduling model: taking flow matching, operation simplification and operation continuity as optimization targets, introducing constraint conditions, and solving flood discharge parameters of various flood discharge buildings; creating a flood discharge operation label: associating the water level of the reservoir and the inflow with the flood discharge operation; the LSTM model learns a flood discharge operation rule; simulation verification period flood discharge scheduling: simulating reservoir flood discharge operations under different reservoir water levels and inflow conditions in the verification period; and in combination with a weir / hole flood discharge flow formula, simulating by using an LSTM model to obtain an optimal flood discharge parameter and calculating the flood discharge flow. According to the method, an optimization algorithm and a deep learning technology are combined, so that reservoir scheduling is converted into data-driven intelligent scheduling from a traditional rule decision mode, and intelligent, precise and real-time scheduling optimization is realized.

The invention relates to the technical field of water level monitoring and early warning, in particular to an intelligent reservoir spillway water level monitoring and spillway early warning system, which comprises an anti-interference water level sensing module, an anti-siltation sensing array is arranged on a key section of a spillway, and the key section comprises a curve section and a gate section; the dynamic hydraulic twinning module is used for processing through a lightweight fluid network algorithm on the basis of the water surface transverse slope, the absolute water level and the gate vibration displacement in combination with a hydraulic BIM model; the edge cloud cooperative flow calculation module comprises an edge node and a cloud server; the risk self-adaptive early warning module is used for executing early warning when the calibrated real-time spilling volume breaks through a spilling threshold value; according to the method, the flow calculation error under the high turbulence working condition is remarkably reduced, the accuracy of flood discharge amount calculation is effectively improved, and it is ensured that flood discharge control is more accurate especially under the scene that the curve flow state is complex and the gate opening degree changes remarkably.

The invention discloses a water level monitoring system based on flood discharge gate control, and relates to the technical field of flood discharge gate control, and the water level monitoring system comprises an upstream water level monitoring module, a downstream water level monitoring module, a gate discharge monitoring module, an early warning terminal and a database. Analyzing a water level future coefficient corresponding to the upstream end of the reservoir, judging whether the reservoir needs to open a gate for flood discharge or not, and analyzing to obtain a gate opening width corresponding to flood discharge of the reservoir, and analyzing to obtain a gate opening width corresponding to development of the downstream end of the reservoir when no flood occurs at the upstream end of the reservoir; meanwhile, the state of the reservoir gate during flood discharge is known, and whether adjustment is conducted or not is analyzed, so that safe reservoir flood discharge is achieved, ecological safety is guaranteed, efficient and accurate flood discharge is achieved, it is further guaranteed that surrounding development obtains effective water source support, and reasonable allocation of water resources and efficient utilization of the resources are achieved.

The invention relates to the technical field of flood discharge gate equipment, in particular to a flood discharge gate equipment operation fault diagnosis method, which comprises the steps of extracting and fusing first target data; analyzing and calculating the extracted and fused first target data, and generating second target data; and inputting the second target data into a historical database for calculation, and verifying the operation state of the gate equipment. The method has the beneficial effects that a multi-source heterogeneous data fusion technology is utilized, various internal parameters such as structural stress, deformation and vibration characteristics as well as hydraulic hoist system pressure, radial gate online vibration monitoring signals and water temperature signals are comprehensively considered, so that the actual operation state of equipment is more comprehensively reflected, the fault diagnosis accuracy is remarkably improved, and the fault diagnosis efficiency is improved. Key parameters during flood discharge of the arc-shaped service gate are monitored in real time, the state change of equipment is quickly responded, and the real-time performance of fault detection is enhanced.

The invention provides a multi-dimensional flood disaster analysis method. The method comprises disaster space-time analysis, disaster semantic analysis, response adequacy analysis and population exposure degree analysis. According to the disaster situation space-time analysis, disaster situation related information extracted from a text is associated with a time attribute and a space coordinate attribute; analyzing the disaster information from the angles of time sequence and space distribution; the time sequence analysis adopts a quantitative statistics mode, and key nodes of the flood event are analyzed from the precipitation trend, the flood discharge trend, the microblog number trend, the ponding point number trend, the help seeking information number trend and the taken measure number trend; according to disaster semantic analysis, subject analysis is carried out on the text of each help-seeking point, and semantic information of disaster manifestation in space is mined; according to the response measure sufficiency analysis, the disaster response sufficiency is obtained by analyzing the correlation between the number of response measures and the number of help seeking information.

The invention relates to the technical field of tunnel construction, in particular to a jamming risk early warning method and system for a flood discharge tunnel TBM tunneling process, and the method comprises the steps: building a lithology-tunneling model based on lithology parameter data and tunneling parameter data; dividing the end of the flood discharge tunnel to be tunneled based on the matching degree of the lithology comprehensive parameters of the flood discharge tunnel to be tunneled and the lithology-tunneling model; reducing the rotating speed of the cutterhead or increasing the inclination angle of the cutterhead based on the difference between the expansion rate and the expansion rate threshold; establishing a jamming risk early warning adjustment model based on the plurality of tunneling parameters before and after adjustment and the surrounding rock deformation values, and determining an early warning threshold correction coefficient; determining whether to monitor the fluctuation of the pore distribution of the surrounding rock based on the porosity of the surrounding rock so as to optimize the early warning threshold correction coefficient according to the correction coefficient optimization value; and reducing the surrounding rock deformation threshold value based on the correction coefficient optimization value. According to the invention, the accuracy of machine jamming risk early warning is improved.

The invention discloses an intelligent water conservancy-oriented drainage basin flood forecasting system based on capacity expansion of a flood storage and detention area, relates to the technical field of intelligent water conservancy flood prevention forecasting and early warning, and aims to solve the problem of flood simulation forecasting errors caused by distortion of a water level-volume curve under a low storage capacity condition when internal subsections of a flood storage and detention area are started or partially outburst. The system comprises a main riverway hydrodynamic simulation forecasting module, a flood storage and detention area starting judgment module, a flood storage and detention area topology analysis module and a flood storage and detention area subsection expansion simulation module. The main river channel hydrodynamic simulation forecasting module adopts a hydrodynamic model to carry out flood simulation forecasting, the flood storage and detention area starting judgment module judges whether a flood storage and detention area is started or not according to user input data and a main river channel simulation result, and the flood storage and detention area topology analysis module determines the connection and capacity expansion sequence of each independent branch. The flood storage and detention area subsection capacity expansion simulation module realizes subsection capacity expansion simulation by dynamically calculating the outer boundary and the internal flood diversion flow, and calculation is scientific and efficient.

The invention provides a hydraulic engineering water level monitoring method and system based on artificial intelligence. Meteorological parameters and soil humidity parameters of a cross-basin reservoir group and water level measurement parameters generated by magnetic levitation displacement induction are obtained, dynamic change rules of the parameters are analyzed, and a correlation strength coefficient reflecting the hydraulic interaction between reservoirs is calculated. And the coefficient and a water level measurement parameter are jointly coded, and a cross-reservoir dynamic association map is constructed. And synchronously acquiring real-time water level signals of each reservoir, matching the real-time water level signals with a preset fluctuation feature library, and identifying a water level abnormal interval related to the water flow path node. And in combination with a mapping relationship between the dynamic association map and the abnormal fluctuation interval, determining a water level imbalance risk level, and generating regulation and control instructions including flood discharge path optimization and water storage capacity adjustment according to the water level imbalance risk level. According to the technical scheme, the water level monitoring efficiency and accuracy of the water conservancy project can be improved.

The invention provides an optimization opening method for a flood discharge gate of a hydraulic power plant, which comprises the following steps of: 1, calculating flood discharge flow, and calculating and obtaining the flood discharge flow according to a water level condition, a weather condition, a power generation condition and an equipment condition; 2, gate opening modes are calculated, different gate opening positions and gate opening numbers are distributed according to flood discharge flow, and multiple different forms of gate opening combinations capable of meeting requirements are listed; 3, gate opening heights are calculated, specifically, the opening height of each gate is calculated for each gate opening combination, and multiple different forms of gate opening height combinations capable of meeting requirements are listed; and 4, calculating an optimal gate opening mode, obtaining evaluation factors influencing the operation condition of the hydraulic power plant, setting weight parameters of the evaluation factors, evaluating each gate opening height combination under each gate opening combination, and obtaining the optimal gate opening mode. According to the method, the damage influence of flood discharge on environmental equipment can be reduced, and the optimal power generation plan is ensured.

The present invention provides a device for regulating the water temperature discharged from a reservoir. The device for regulating the water temperature discharged from the reservoir includes a power station intake tower, a cable-stayed tower, a support platform and a water retaining system. The cable-stayed towers are respectively arranged on both sides of the water inlet of the power station intake tower. The support platform is a horizontal circular arch, and both ends of the support platform are connected to the cable-stayed towers. The water retaining system is connected to the circular-arch-shaped support platform and extends downward to the lower part of the reservoir. The water retaining system includes columns, collar rings, a water retaining curtain and a hoist. A plurality of collar rings are sleeved on the columns. The water retaining curtain is connected to the support platform and the plurality of collar rings. The hoist is connected to the upper collar ring. By arranging the cable-stayed towers on both sides of the water inlet of the power station intake tower, the present invention realizes the technical solution of implementing the water retaining system on a single-side bank slope, without blocking the main river channel, and the flood discharge condition does not need to bear the flood load.

The invention discloses a cascade reservoir flood control water level combined application scheduling method and scheduling system, and relates to the technical field of cascade reservoir scheduling, and the method comprises the following steps: dividing into a plurality of sub-regions according to an administrative region, determining a sub-reservoir corresponding to each sub-region, and collecting the rainfall and historical flood discharge data; analyzing the water storage capacity of each sub-region at the moment corresponding to the historical data to form a training data set; constructing a flood season flood discharge prediction model, and obtaining the target flood discharge flowing into the sub-reservoir by using the prediction model; analyzing the water level change in the flood season according to the target flood discharge amount, and judging whether scheduling is needed; and if scheduling is needed, determining a drainage flow combination of each sub-reservoir, setting a constraint condition, and performing optimization through a multi-target genetic algorithm to obtain an optimal drainage flow scheme meeting constraints. According to the scheme, the scientificity, the accuracy and the intelligent level of combined dispatching of the cascade reservoirs are remarkably improved.

The invention relates to a water conservancy facility internet of things real-time monitoring method and device, equipment and a medium. The method comprises the following steps: acquiring water quality and quantity data, comparing the data with a preset safety threshold to generate a preliminary abnormal point location set, and processing through a sliding window algorithm and a historical time sequence model to generate a standardized abnormal report; generating an initial control command through the edge-deployed pruning LSTM model in combination with rainfall prediction data, and generating an equipment operation instruction after verification; executing the instruction to drive the equipment and collecting the response state of the equipment, and resolving conflicts through a Raft algorithm to generate a unified scheduling command; and after the unified scheduling command is executed, the model parameters and the preset safety threshold are updated through a Q-learning optimizer according to the flood discharge quantity feedback data. According to the method, real-time monitoring and intelligent regulation and control of the water conservancy facilities are achieved through data processing, intelligent decision making, collaborative scheduling, dynamic optimization and the like, and the safety, stability and intelligent level of operation of the water conservancy facilities are effectively improved.

The invention discloses a flood discharge gate structure dynamic load time domain rapid identification and dynamic response field inversion method comprising the following steps: 1) carrying out a vibration test of a flood discharge gate structure, and obtaining a multi-source vibration response signal of the flood discharge gate structure; 2) constructing a unit impulse response matrix H and a load shape function matrix N; 3) establishing an inverse analysis model X = HNA for dynamic load time domain identification of the flood discharge gate structure; 4) inversely solving the load shape function coefficient matrix A to obtain a dynamic identification load of the flood discharge gate structure; and 5) inputting the identification load as an external load of the sluice structure to obtain an overall dynamic response field of the sluice structure.The method is based on the multi-source actual measurement vibration response of the sluice structure, the improved dynamic load time domain identification method based on the shape function is adopted, the time domain load of the sluice structure can be rapidly and effectively identified, and the identification accuracy is high.

The invention provides a method for analyzing deformation characteristics of an exit slope of a flood discharge building, which comprises the following steps of: firstly, collecting geotechnical parameters, hydraulic load parameters, GNSS displacement, pore water pressure and clinometer data of the slope; then, constitutive parameters of the slope stability model are dynamically corrected, GNSS displacement is decomposed into creep and elastic displacement components, and the time delay error of pore water pressure data is compensated; thirdly, seepage-stress coupling stability calculation is conducted in combination with the compensated pore water pressure and inclinometer data, and the slope stability safety coefficient is obtained. And finally, outputting the creep displacement, the elastic displacement and the stability safety coefficient to an early warning terminal. According to the invention, the accuracy and reliability of slope stability evaluation can be improved.

The invention relates to the technical field of slope seismic resistance, and discloses an engineering slope seismic stability optimization method and system, and the method comprises the steps: collecting flood discharge tunnel outlet slope data and seismic oscillation parameter values, and carrying out the partitioning according to the flood discharge tunnel outlet slope general situation data; analyzing rock mass weathering and unloading and physical geology phenomena in each area to obtain physical mechanical parameter suggestions; establishing a three-dimensional model of the flood discharge tunnel outlet slope based on the physical and mechanical parameter suggestions and the seismic oscillation parameter values; inputting the non-uniform seismic dynamic load into the three-dimensional model of the flood discharge tunnel outlet slope for analog calculation; establishing a side slope geomechanical model, and performing simulation verification; and comparing the simulation verification result of the side slope geomechanical model with a preset rule threshold value, if the simulation verification result of the side slope geomechanical model is greater than the preset rule threshold value, performing early warning, uploading the simulation verification result of the side slope geomechanical model to a cloud platform, and performing visual output. According to the invention, comprehensive analysis and management of the flood discharge tunnel outlet slope under the earthquake effect are realized.

The invention provides a slope seepage analysis method under a flood discharge atomization condition. The slope seepage analysis method comprises the following steps: S1, acquiring slope pore water pressure data and matrix suction data through a distributed sensor array; s2, the data fusion unit compares the pore water pressure data with a dynamic critical pressure threshold value, compares the matric suction data with a dynamic critical suction threshold value, and generates a seepage analysis trigger instruction when any data exceeds the limit; s3, starting a transient seepage field calculation model by the seepage calculation engine based on the fracture network topology data; s4, generating a slope stability control parameter set according to a seepage pressure distribution diagram output by the transient seepage field calculation model; and S5, the execution system regulates and controls the operation state of the drainage facility according to the slope stability control parameter set. The slope seepage pressure can be reduced, the slope stability is improved, and safe operation of a water conservancy project is guaranteed.

The invention discloses a durability evaluation method for a slope protection layer of a flood discharge atomization area, and the method breaks through the limitation of a conventional static load hypothesis, and accurately reflects the load joint variability through dynamic monitoring and probability modeling. The core problems of inaccurate load feature description, insufficient multi-field coupling simulation precision, lack of time-varying reliability evaluation and the like of a traditional method are effectively solved. The combination of dynamic monitoring and probability modeling improves the load characteristic representation precision, the multi-physics field coupling calculation accurately simulates the water particle impact mechanism, the fusion of the intelligent prediction model and the random process theory realizes the dynamic evaluation of the performance degradation of the protective layer, and finally provides quantitative decision support for engineering maintenance.