2419 results about "Water level" patented technology

The invention provides a control node locating protecting method of undercutting channel segment water level lowering amplitude. The method comprises the steps that a lateral erosion zone and a deep erosion zone are divided; a target channel section is subjected to meshing, a plane two-dimension water flow mathematic model is established, parameter calibration and verification are carried out; a protection project is generalized to the plane two-dimension water flow mathematic model, the arranging zone and the width of the protecting project are determined; local gradient amplification and upstream water level amplification corresponding to each working condition are obtained, mesh sequences are analyzed respectively; key nodes or other nodes which have obvious influence are selected, for lateral erosion nodes, a hidden closure dam and a beach protection part are arranged on a river branch or a bottomland, and for deep erosion nodes, a bottom protecting band or a hidden closure dam are placed in a main groove. According to the method, nodes are divided into the lateral erosion nodes and the deep erosion nodes, protection part difference of the nodes in different types is provided, by comparing the efficiency of a local channel segment arranging protecting project, the positions of the nodes are accurately located, and the optimum efficiency of the protecting project is guaranteed powerfully.

The invention discloses a reservoir water regimen analysis method and system based on artificial intelligence, and the method comprises the steps: collecting original signals from multi-source monitoring indexes, such as water level, flow, rainfall and water quality, carrying out the standardized conversion through employing distributed calculation nodes, and forming a unified multi-source data set; based on this, using a feature extraction network to fuse upstream rainfall and reservoir flow, extracting space-time correlation features, and determining a short-term water level change trend; historical water quality abnormal data are integrated through a sequence prediction network, a time sequence is modeled, and potential pollution risks are judged; when the risk exceeds a threshold value, dynamically adjusting the weight of the prediction model, and generating an optimized water regimen simulation scene; finally, resource scheduling logic is fused, multi-scene risks are evaluated, and an optimization management strategy is output. Through deep fusion of spatial-temporal feature extraction and dynamic prediction, accurate water regimen prediction and flood control water supply decision support are realized, and the water resource management efficiency and the pollution prevention and control capability are improved.

The invention discloses a wharf shoreline terrain reconstruction method based on remote sensing data, and belongs to the technical field of three-dimensional terrain reconstruction. The method comprises the following steps: acquiring a multi-temporal multispectral remote sensing image, a synthetic aperture radar image, a laser radar point cloud and synchronous tidal water level data of a target wharf area; processing the multispectral image to generate an initial land and water segmentation map; carrying out tide correction by utilizing the tide water level data, fusing the multi-polarization characteristics of the synthetic aperture radar image, and correcting the ground feature type to obtain an accurate land and water boundary diagram; processing the laser radar point cloud to generate a digital surface model, extracting a shoreline contour with sub-pixel-level precision from the digital surface model, and endowing the shoreline contour with an elevation value; and superposing the shoreline contour with the elevation with the multispectral image to generate a three-dimensional terrain model. According to the method, the problems of low terrain reconstruction precision, large tide influence and insufficient automation degree of a traditional method in a complex wharf environment are solved, and high-precision and high-efficiency wharf shoreline three-dimensional automatic reconstruction is realized.

The invention relates to the technical field of exploration, and discloses a water depth inversion method and system based on a multispectral remote sensing image, which utilizes an independent verification sample set to carry out hierarchical precision evaluation, and analyzes model performance differences according to dimensions such as a water depth range and a substrate type. Error propagation of links such as atmospheric correction and water level correction is quantified through full-chain uncertainty analysis, an uncertainty quantification model of ensemble learning is constructed, and a pixel-level precision distribution diagram is generated. Therefore, according to the technical scheme, a closed-loop dynamic adaptation framework is formed by systematically integrating multi-temporal data dynamic modeling and an uncertainty quantification mechanism, a spatio-temporal variation compensation mechanism is embedded in the whole process from data acquisition to result verification, the interference of spatial-temporal heterogeneity of water optical characteristics on water depth inversion is effectively dealt with, and the accuracy of water depth inversion is improved. The problems of parameter mismatch and precision reduction of the water depth inversion model caused by dynamic change of optical characteristics of a coastal water body in seasonal and tidal scales are solved.

The invention relates to the technical field of water conservancy management, and discloses a water conservancy dynamic decision-making method and system based on digital twinning and multi-source heterogeneous data, and the method comprises the steps: carrying out the real-time information capturing of a target water conservancy system, and generating a system operation information scheduling matrix based on a grid geographic model and a time dislocation mark; performing hierarchical slicing on the system operation information scheduling matrix according to a multi-scale time window to form a multi-channel flow framework of regional hydrological dynamic behaviors; analyzing the evolution trends of the water level, the flow and the water quality by using a multi-channel flowing framework and a dynamic fusion analysis operator; dividing a river reach, a reservoir and a regulation and control facility corresponding to the potential risk event as candidate scheduling areas; and based on the local risk coupling network, dynamically optimizing a scheduling strategy, a pump gate operation sequence and a data acquisition frequency, and generating a real-time scheduling and emergency response scheme of the candidate region. The method has the advantage of improving flood early warning accuracy and water supply scheduling efficiency.

The invention discloses a hydraulic engineering construction operation parameter optimization and data management method and system. The method comprises the steps of 1, multi-source data access and vectorization; step 2, time sequence feature extraction and multi-modal fusion; step 3, identifying interpretable influence factors; 4, performing multi-task dynamic anomaly prediction; 5, risk weighted fusion and uncertainty quantification are carried out; 6, carrying out digital twinborn simulation verification; step 7, governance strategy optimization and security auditing; and step 8, feedback acquisition and model adaptive updating. The method has the advantages that multi-modal unified representation is constructed by fusing structured data such as water level and flow with unstructured information such as meteorological images and operation and maintenance logs, time sequence feature extraction is carried out in combination with the space-time diagram neural network, the dynamic sensing and prediction capability of the complex hydrological process is remarkably improved, and the method is suitable for being popularized and applied. According to the invention, the conversion from static threshold alarm to multi-task and prospective abnormal early warning is realized, and the adaptability of the system to multiple scenes is enhanced.

The invention discloses an intelligent method and system for multi-source heterogeneous data fusion management, and belongs to the field of data processing, and the intelligent method for multi-source heterogeneous data fusion management comprises the following steps: deploying a sensor network in a historical ponding area based on historical ponding point data and urban hydrological geographic information, acquiring real-time monitoring data, wherein the real-time monitoring data comprises rainfall intensity, road waterlogging depth, community waterlogging condition and drainage pipe network water level / flow; compared with the prior art, the method has the beneficial effects that sensors are arranged in the historical ponding area to obtain real-time monitoring data, and weather forecast, a terrain model and a pipe network model are combined to construct a waterlogging prediction model to predict whether a ponding risk exists in the historical ponding area in future set time (such as 0.5-3 hours in the future); the ponding risk is treated in advance, so that the problems of traffic interruption caused by ponding, citizen travel obstruction and the like are solved.

The invention discloses an inland river basin intelligent ecological scheduling rehearsal method fusing a scheduling process and an ecological process. The inland river basin intelligent ecological scheduling rehearsal method comprises the steps of multi-source data acquisition and digital twinborn construction; carrying out reservoir intelligent scheduling reinforcement learning modeling; ecological process lag response modeling is carried out; spatial diffusion modeling of ecological influence; performing cross attention guided ecological response interpolation; and carrying out rehearsal and visual display on the ecological scheduling scheme. According to the method, a hydrological-ecological response modeling mechanism is introduced, and a time-space response relationship between scheduling behaviors such as water level and water volume and ecological indexes such as vegetation indexes and habitat indexes is combined, so that lagging response characteristics of an ecological process to the scheduling behaviors can be quantitatively described, and the defect that a traditional scheduling model is insufficient in ecological expression capability is overcome. A reinforcement learning algorithm is utilized to fuse multi-source data for state perception and strategy iteration, and the scheduling strategy can be dynamically adjusted according to the current hydrological situation and ecological feedback result of the watershed. Compared with static rule type scheduling, the regulation and control efficiency and ecological adaptability are remarkably improved.

The invention relates to the technical field of water ecological restoration, solves the technical problems that in the prior art, fine design, adaptability and robustness are insufficient, and particularly relates to a lakeside zone ecological restoration method based on microtopography and vegetation community integration. Constructing a lakeside zone water depth and flooding duration pattern, parameterizing a bank slope microtopography by step elevation, width and gradient, and calculating a corrected water depth and a hydrodynamic exposure index by adjusting parameters; introducing a suitability scoring function to establish a functional response model for realizing quantitative matching of the microtopography steps and the vegetation communities; and constructing a comprehensive evaluation function and a robustness index by integrating ecological function indexes under various hydrological scenes, and carrying out joint optimization on microtopography and vegetation configuration. According to the method, the lakeside zone recovery design is converted from experience zoning into a computable and comparable integrated scheme, and the method is suitable for various lakeside zones such as natural gentle slope lakesides and urban hard revetments.

The invention discloses a DEM-based reservoir flood control dispatching temporary submerging area rapid generation method and device, and relates to the field of hydraulic and hydro-power engineering temporary submerging area definition. The method comprises the following steps: dividing a river channel higher than a reservoir inundation area into a plurality of units by obtaining or generating a reservoir reach DEM, a river channel section line, a normal water storage level inundation area range and water return meters under different working conditions; calculating the water level of each unit grid by adopting an inverse distance weighting method in an interpolation manner, and comparing with the DEM elevation to determine the grid meeting the condition; and merging the units after boundary tracking and smoothing, and erasing a normal water storage level submerging area to obtain a temporary submerging area. The method solves the problems that an existing method is long in time consumption and insufficient in precision, gives consideration to efficiency and precision, and provides reliable support for flood control dispatching decision making, submerging loss evaluation and the like.

The invention discloses a channel flow velocity measurement error compensation method based on multi-source fusion, and the method comprises the following steps: S1, synchronously collecting flow velocity, position, attitude and environment data, including ADCP radial flow velocity, GNSS position / speed and IMU attitude angular velocity, through a multi-source sensor, aligning multi-source data based on a time synchronization mechanism, and achieving microsecond time synchronization based on PPS time service; according to the method, RTK high-precision positioning and ADCP bottom tracking data are integrated, the water surface elevation and the water bottom distance are inversed in real time, and the actual water depth and the riverbed erosion and deposition rate are dynamically calculated; edge calculation, motion compensation and external compass correction technologies are fused, the flow velocity and flow direction measurement precision is improved, and platform motion and attitude interference is eliminated; multi-source data local fusion processing and real-time generation of a flow velocity thermodynamic diagram and a water level change curve are realized, remote transmission and visualization are supported, and comprehensive and accurate hydrological data support is provided for maritime affair intelligent supervision, navigation safety early warning and digital channel construction.

The invention discloses a multi-channel high-precision water level dynamic real-time monitoring system for a drilling water pumping test, and the system comprises a sensing layer which is used for deploying a multi-source sensor array, inhibiting interference through distributed layout and electromagnetic shielding, collecting multi-dimensional data in real time, and carrying out the preliminary filtering; according to the transmission layer, an optical fiber and twisted pair redundant network is constructed, an EtherCAT protocol is adopted for low-delay transmission, AES-128 encryption tampering prevention is integrated, and edge nodes compress data and verify integrity; the processing layer is used for carrying out real-time preprocessing on edge calculation and switching a standby sensor in abnormal detection; the cloud end predicts the water level trend through Spark Streaming analysis and an LSTM model, distinguishes interference through a random forest algorithm, and outputs calibration data and an analysis report; the application layer is used for constructing a three-dimensional drilling model based on Unity, dynamically displaying water level changes, synchronizing a multi-parameter curve and supporting historical backtracking; the early warning module notifies abnormity through sound and light and short messages, the decision module generates a report and supports multi-drill-hole comparison, and the test strategy is optimized.

The invention discloses a hydropower station water level detection method and system. The method comprises the steps that an original water flow characteristic parameter set is obtained through multiple sets of Doppler effect radar flow measuring devices; performing segmentation extraction to obtain a water flow feature sub-data set; inputting a Transform network coding layer to generate a water flow feature coding vector; outputting a preliminary water level predicted value sequence through a decoding layer; a radar flow measurement model is called for correction to obtain a correction sequence; time sequence integration is carried out to obtain a water level change curve. The system comprises a multi-source Doppler radar signal acquisition unit, a spatial-temporal feature segmentation extraction unit, a Transform coding processing unit, a water level preliminary prediction unit, a radar model correction unit and a time sequence integration output unit. According to the method and system, multi-source parameters are deeply fused, the environmental adaptability is improved, the continuity and reliability of a detection result are enhanced, the water level of the hydropower station can be accurately monitored, and support is provided for scheduling decision and safety prevention and control.

The invention relates to the technical field of data processing, in particular to an engineering geological survey data processing method and system, and the method comprises the following steps: obtaining hole site space positioning and lithologic boundary information, collecting a structure segment sequence, extracting resistance change direction classification disturbance behaviors, recognizing node sequence conflicts, and judging hydrological turning positions. Identifying the corresponding relation between the structural section and the water level track, and generating a structural section water level merging mapping table. According to the method, the spatial information, the lithology identification, the sampling level and the penetration resistance of the drilling structure sections are collected and serialized, disturbance identification and non-sampling section classification are performed based on the resistance change trend between the sections, and node conflicts are identified in combination with the numbering relation and the lithology combination; continuous modeling and classified merging of geological information on the spatial level are achieved, the linkage adaptability of data in a multi-dimensional analysis scene is enhanced, misjudgment interference caused by information isolation is avoided, and dynamic recognition and hydrological response analysis of a geological structure are supported.

The invention discloses an integrated intelligent management and control method and system for underground water pumping and injection based on the Internet of Things, and the method comprises the steps: carrying out the geological investigation of a target region, constructing a three-dimensional geological model, and planning the layout of a pumping and injection well group and a sensor network according to the three-dimensional geological model; deploying a monitoring network and collecting data based on the layout scheme, and fusing a three-dimensional geologic model to construct a polluted site digital twinborn body; groundwater situation data are extracted through the digital twinborn body, a pollutant migration path and a water level dynamic state are predicted by using an LSTM model, and pollution scene simulation information corrected by geologic features is output; by taking the simulation information as input and coupling geological parameters as constraints, generating a pumping and injection well group cooperative control strategy set by adopting a BLMFO double-layer multi-objective optimization algorithm; and finally, a control instruction is executed, the real-time situation is monitored in the repairing process, strategy change suggestions including the flow adjustment amplitude, the agent optimization scheme and equipment operation parameter correction are judged and pushed, the repairing efficiency is improved, and the method adapts to the complex geological environment.

The invention provides a saline-alkali soil underground water regulation and control method and device, electronic equipment and a storage medium, and relates to the technical field of land governance. Inputting the first historical monitoring information into a pre-constructed prediction model to obtain a predicted value of soil salinity in a future time period; the predicted value of the soil salinity is input into the analysis model, and the target water level of underground water in the future time period is obtained; wherein the target water level of the underground water is used for restraining the target value of the soil salinity to be smaller than a preset salinity threshold value and the target value of the soil humidity to be larger than a preset humidity threshold value; generating a water level adjusting strategy based on the target water level of the underground water, and controlling the opening or closing of the water pump based on the water level adjusting strategy. According to the method, the soil salinity in the future time period is predicted by acquiring the saline-alkali soil monitoring information, so that the target water level of the underground water is obtained, the water level regulation strategy is generated, and the perspectiveness, dynamic nature and stability of underground water level regulation are ensured.

The invention provides a mine slope risk assessment method and system based on multi-source data space-time fusion, and relates to the technical field of mine monitoring, and the method comprises the steps: obtaining geological and engineering data, and constructing a basic model representing a slope three-dimensional space structure; collecting multi-source heterogeneous monitoring data on a mine slope field, and aligning and fusing the multi-source heterogeneous monitoring data with the basic model in a space-time dimension to generate a continuous dynamic parameter field; and setting a data fusion model, and taking the basic model and the dynamic parameter field as input to obtain a four-dimensional space-time fusion risk field. According to the method, the basic model representing the three-dimensional space structure of the slope is constructed, and a unified space-time bearing base is provided for all heterogeneous monitoring data, so that originally isolated data such as GNSS displacement, deep displacement, blasting vibration and underground water level can be fused in a unified coordinate system; the problem of data splitting in the prior art is fundamentally solved, and integral and integrated expression of slope engineering and geological conditions is formed.

The invention discloses an intelligent early warning method and system for snow-melting flood. The method comprises the following steps: constructing digital twin integrating snow-melting confluence and hydrological hydrodynamic force; collecting multi-source monitoring information, and forming driving data through quality control and spatio-temporal interpolation; driving data are input into digital twinning, and model parameters and states are updated through data assimilation; simulating snow-melting runoff, water level and flow to obtain snow-melting flood probability prediction; the method comprises the following steps of: solving a river reservoir gate pump scheduling scheme by using a multi-objective evolutionary algorithm by taking reservoir outlet flow, gate opening and pump station starting and stopping as decision variables, calculating a water level, flow and a submerging range in digital twinning, and selecting a target scheme according to an evaluation rule to generate a scheduling instruction and graded early warning information; monitoring data is collected during scheduling execution and compared with probability prediction, and when the deviation exceeds a threshold value, data assimilation and scheduling scheme updating are triggered. According to the invention, the snow-melting flood forecasting precision and flood control scheduling collaboration are improved.

The invention relates to the technical field of hydraulic engineering safety monitoring, and discloses a dam safety studying and judging method based on monitoring data multi-physics field simulation, which comprises the following steps: S1, multi-source data acquisition and time-space alignment; s2, dynamically updating the numerical model; s3, safety evaluation and early warning decision making; s4, performing multi-source risk coupling analysis; and S5, issuing the early warning information in a multi-mode manner. According to the method, time-space reference unification of multi-source monitoring data is achieved through feature point matching and sliding window cross-correlation analysis, a self-adaptive Kalman filtering algorithm is adopted to dynamically invert permeability coefficients and elastic modulus parameters, and boundary conditions of a finite element model are adjusted in combination with real-time water level changes; the dynamic simulation precision of a seepage field-displacement field-stress field coupling model is improved, the static evaluation limitation of a fixed threshold value method is broken through through a three-dimensional time-varying safety envelope surface and a Bayesian network grading early warning decision tree, and the risk prediction capability in the flood routing process is enhanced through multi-parameter joint probabilistic reasoning.

The invention provides a water body water level monitoring method of an image segmentation model, and the method comprises the steps: obtaining multi-modal water flow data of a target water area, carrying out the feature extraction of the multi-modal water flow data, and obtaining a turbulence feature map, the multi-modal water flow data comprising water flow motion data and water body image data; performing physical constraint segmentation processing on the turbulence feature map and the water body image data to obtain a water body region segmentation mask and a corresponding pixel-level confidence map; carrying out water gauge geometric correction processing on the water body region segmentation mask to obtain a corrected water line; and performing water level value conversion processing on the corrected water level line and the pixel-level confidence map to obtain a water level measurement value and uncertainty data. By adopting the method, the real water line and the dynamic water flow artifact can be effectively distinguished, and the monitoring precision under the complex hydrological condition is ensured.

The utility model relates to the technical field of hydraulic engineering monitoring, in particular to a water level monitoring device for water resource management, which comprises a stand column, a signal box and a solar cell panel are fixedly connected to the surface and the top end of the stand column, and an adjusting mechanism comprises a first supporting rod hinged to the surface of the stand column. An electric push rod is fixedly connected to the inner wall of the bottom end of the stand column, a sliding groove is formed in the surface of the stand column, and a connecting block is slidably connected into the sliding groove; when the ultrasonic sensor needs to be maintained, the first supporting rod can be directly pulled to rotate through the electric push rod, so that the ultrasonic sensor moves towards the shore while descending, and a worker can conveniently maintain the ultrasonic sensor; the height and the distance between the ultrasonic sensor and the water area to be monitored can be randomly adjusted according to the environment, so that the monitoring data is more practical and more stable.

The invention belongs to the technical field of water conservancy and hydropower engineering, and particularly relates to a computer vision-based dam seepage field rapid calculation method, which comprises the following steps of: acquiring geological attribute parameters and upstream and downstream water level working condition parameters, and constructing a sample space; constructing a data set by using a dam seepage numerical model considering the spatial variability of the permeability coefficient based on the sample space; and establishing an improved conditional deep convolutional generative adversarial network model based on the data set to realize rapid calculation of the dam seepage field. The problems that in an existing dam seepage behavior analysis and research method, a numerical simulation method occupies too many computing resources and consumes long time, most agent models only pay attention to local scattered measuring points for modeling, and overall seepage field modeling at a key section cannot be achieved are solved. However, most of the current image generation researches based on computer vision neglect the generation precision problem of high-frequency details of the image, and the high-frequency edge information of the image cannot be accurately generated.

The invention relates to the technical field of water conservancy flood prevention monitoring, and discloses a water conservancy flood prevention monitoring and early warning method and system. The method comprises the following steps: acquiring multi-source hydrological monitoring data including real-time rainfall, riverway water level, soil humidity and weather forecast data, and constructing a comprehensive hydrological information basis; flood risk analysis is carried out based on the data, a flood risk prediction signal and a flood situation evolution signal are synchronously generated, and the flood occurrence probability and the development trend are clarified. And combining the flood risk prediction signal with the multi-source data to determine flood prevention regulation and control parameters and generate an optimized flood prevention signal. Flood prevention facility operation is adjusted according to the optimized flood prevention signal and the flood situation evolution signal, an early warning control signal is output, the two signals are processed at the same time to generate a comprehensive early warning index, and the severity of the flood situation is visually reflected. According to the method, hydrological data multi-dimensional fusion is realized, flood prevention monitoring and early warning are promoted to change from single data dependence to multi-source collaboration, and the flood situation response efficiency is improved.

The invention relates to the field of water conservancy and hydropower engineering construction land acquisition and physical index investigation, in particular to a method and a system for quickly generating a mountainous area riverway type reservoir inundation area based on a high-precision DEM (Digital Elevation Model), and aims to solve the problems of poor reservoir inundation area generation precision, long time consumption and large personal error in the prior art. The method comprises the following steps: acquiring or generating a reservoir reach DEM, a river section line and a water return meter, and preprocessing; expanding section lines to divide river channel units; calculating a grid water level based on inverse distance weighting interpolation, and comparing the grid water level with DEM elevation to determine a submerged area grid; and generating a closed surface domain through boundary tracking and smoothing processing, and combining to obtain a whole submerged region. The method gives consideration to efficiency and precision, supports second-level dynamic generation of multiple schemes, improves analysis precision and efficiency, is suitable for mountainous river type reservoirs, and provides data support for scheme comparison and selection and object investigation.

The invention discloses an underground water pollution diffusion model construction method based on multi-modal data fusion, and the method comprises the steps: fusing the dynamic time sequence characteristics of a monitoring well and the static space attributes of a geological field, and generating an initial state vector with rich information for a graph node; based on the instantaneous water level difference between the nodes and the equivalent permeability coefficient, a dynamic graph topological structure which evolves along with time and represents the hydraulic connection relation is constructed; deducing a future state through numerical integration by using a graph neural network model with a node state derivative as output; and constructing a composite loss function containing a data fitting item and a physical law residual item, and training the model through back propagation. According to the method, the dynamic graph of physical driving is constructed and the physical equation constraint is introduced, so that the model prediction has the data driving precision and the reliability of the physical mechanism, and the generalization ability and the prediction precision of the model under the complex hydrogeological condition are improved.

The utility model discloses an underground water level monitor for geotechnical engineering, which relates to the technical field of water level monitoring and comprises a probe rod body and a protective sleeve sleeved outside the probe rod body, and the top end of the probe rod body is provided with a traction rope penetrating out of an annular seat at the top of the protective sleeve; an overturning frame is rotationally installed on the side face of the bottom of the protective sleeve, a floating plate and a plugging frame are arranged at the two ends of the overturning frame respectively, and the plugging frame is arranged at the end, close to the protective sleeve, of the overturning frame; a floating plate is arranged at the upper part of the floating plate; by means of the torque change design of the floating plate, the overturning frame and the plugging frame, when the floating plate does not enter water, the plugging plate covers the open groove in the lower end of the protective sleeve, and rock soil and other sundries can be prevented from entering the protective sleeve to affect the probe rod; when the floating plate enters water, the blocking plate is moved away, so that the probe rod can be in contact with the water body in time to monitor the water level.

The invention relates to the technical field of geological engineering and underground water simulation, and discloses a regional underground water simulation method and system based on a physical mechanism and deep learning, and the method comprises the steps: converting the static attributes of an observation well into the embedding of nodes and edges through a graph neural network, and obtaining spatial features; according to the dynamic input of the observation well, modeling time sequence response of the underground water system under external dynamic driving through a long short-term memory neural network; deep fusion of spatial features and time dynamics is realized through a feature interaction mechanism, and a groundwater level simulation value is generated; combining a water balance constraint with a relative water level consistency constraint between observation wells to jointly construct a composite loss function for quantifying a difference between an analog value and a real observation value, and guiding parameter updating; the time-space dynamic and physical mechanism can be sensed synchronously, and the method is more reliable and efficient.

The invention is suitable for the technical field of pump station intelligent control, and provides a pump station water level self-adaptive regulation and control method and system, and the method comprises the following steps: obtaining water level time sequence data, equipment state data and environment information data in real time; predicting a water level value of a future preset time window based on a physical mechanism prediction model according to the water level time sequence data, the equipment state data and the environment information data to obtain a first prediction value; based on a data-driven prediction model, according to the water level time sequence data, the equipment state data and the environment information data, predicting a water level value of a future preset time window to obtain a second prediction value; performing adaptive weighted fusion on the first predicted value and the second predicted value to obtain a comprehensive predicted value; and according to the comprehensive predicted value, carrying out self-adaptive regulation and control on the pump station water level. According to the invention, by constructing a hybrid prediction model based on a physical mechanism and data driving and introducing an adaptive weighted fusion mechanism, accurate short-term prediction and adaptive regulation and control of the future water level are realized.

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 the technical field of structure health monitoring, in particular to a wharf structure state judgment method based on time sequence image and vibration data collaboration, which comprises the following steps: synchronously acquiring a time sequence image set and a vibration signal set of a wharf structure, and generating an original double-source data set with time-space alignment; respectively extracting a structure displacement sequence and a vibration mode parameter set through sub-pixel displacement tracking and variational mode decomposition; fusing the two to construct a spatial-temporal characteristic matrix, introducing a temperature field and a water level height to construct an environmental interference compensation factor, performing characteristic enhancement and standardization processing, and outputting a damage sensitive matrix; constructing a hybrid discrimination model by using a physical mechanism constraint layer fusing a structural mechanical control equation and a deep learning classification layer formed by one-dimensional convolution-LSTM, and outputting a structural damage probability value; the method has the advantages of space-time cooperative sensing, environmental interference robustness, high damage discrimination precision, high result interpretability and the like, and is suitable for real-time monitoring and damage identification of a wharf structure in a complex marine environment.