8718 results about "Hydraulic engineering" patented technology

The invention relates to the technical field of hydraulic engineering monitoring control, and discloses an automatic monitoring method and system for ecological hydraulic engineering. The method comprises the steps that water body parameters are collected through a sensor and preprocessed to obtain standard monitoring data; performing noise reduction alignment and correlation analysis on the monitoring data to obtain an optimized data set and a feature library; evaluating the water environment state according to the data set and the feature library to obtain an evaluation index and an early warning signal; analyzing the treatment scheme according to the index and the signal to obtain a regulation and control instruction; adjusting equipment operation parameters according to the instruction to obtain operation state data; and performing cycle analysis and strategy optimization based on the state data to obtain regulation and control parameters. Multi-dimensional correlation analysis of water quality parameters is realized, an accurate water environment regulation and control scheme is formulated on the basis, and the pertinence and efficiency of water quality improvement are improved.

The invention discloses a riverway flood control and disaster reduction risk point AI identification method and device based on a digital twinborn computable engine. The method comprises the following steps: acquiring three-dimensional scene basic data and hydraulic engineering parameters in a drainage basin; acquiring real-time rain condition, water condition, soil moisture content, reservoir condition and dike monitoring data to obtain real-time data; establishing a physical entity and a twin simulation scene according to the three-dimensional scene basic data and hydraulic engineering parameters; performing AI simulation calculation of water regimen according to the real-time data to obtain a simulation result; carrying out twinborn computable simulation according to the physical entity, the twinborn simulation scene and the simulation result to obtain a simulation result; and identifying the risk point of the river channel in the drainage basin according to the simulation result. By implementing the method, the problem that the prediction accuracy is affected due to the fact that the digital twinborn technology mainly lacks intelligent risk identification and multi-factor integration in flood control and disaster reduction of the river channel can be solved.

The invention relates to the technical field of data processing, and discloses an AI knowledge base construction method and system for intelligent water conservancy. The method comprises the following steps: forming a water conservancy intelligent perception data set by integrating hydrological monitoring data, engineering operation records and expert literatures; knowledge sprouts are identified, and a water conservancy native knowledge unit is generated; key features are extracted, knowledge element decomposition is carried out, and a knowledge evolution chain network is constructed through correlation analysis; screening in combination with a historical application effect and expert evaluation to obtain a preferred knowledge body; performing intelligent reconstruction on a scheduling rule, risk prevention experience and an operation and maintenance method to form an innovative knowledge base; and finally, intelligently matching with real-time engineering requirements to generate an intelligent water conservancy AI knowledge base. According to the application, by establishing a self-adaptive knowledge acquisition, organization and application mechanism, the knowledge base can autonomously update the knowledge content according to the environment change, the knowledge structure is optimized, and the intelligent operation management level of the water conservancy project is improved.

The invention relates to the technical field of hydraulic engineering management, and discloses a hydraulic engineering seepage intelligent monitoring system. Comprising a multi-sensor sensing module, a data acquisition module, a data fusion and processing module, a machine learning prediction module, an intelligent decision module, an adaptive monitoring scheduling module, an automatic inspection and response module, a digital twinning and simulation analysis module and a communication module. The multi-sensor sensing module is responsible for collecting multi-dimensional data related to seepage in real time. A machine learning algorithm is adopted to intelligently predict the seepage trend, and risk assessment is performed in combination with real-time data, so that compared with a traditional monitoring method based on a preset threshold value, the method can automatically identify a complex seepage mode penguin through learning historical data and real-time data to predict the future risk in advance, and the risk assessment efficiency is improved. The prospective management of the seepage risk of the water conservancy project is realized, and the prediction precision and the response speed of the system are remarkably improved.

The invention discloses a freezing and thawing stratum grouting numerical analysis modeling method and system, particularly relates to the technical field of hydraulic engineering numerical simulation, and is used for solving the problem of grouting parameter prediction inaccuracy caused by neglecting the dynamic coupling relationship between the thermodynamic behavior of a phase-change material and a seepage field and a damage field in an existing grouting model. A dynamic correlation system of phase change energy storage performance parameters and seepage field-damage evolution is established, a slurry diffusion path priority channel weight is corrected based on a freeze-thaw interface migration track, a bidirectional iteration equation of a seepage field and a diffusion migration field is coupled, and multi-physical field spatial-temporal scale cooperative solution is realized through a separated iteration algorithm; through multi-dimensional coupling of thermodynamic characteristics of the phase-change material, heterogeneous evolution of seepage paths and damage mechanical response, the prediction precision of the mechanical characteristics of the grouting stone body and the slurry diffusion range under the action of freeze-thaw cycle is remarkably improved, and the leakage and structural instability risks are effectively reduced.

The invention relates to the technical field of pipeline maintenance, and discloses a pipeline inner wall corrosion detection method and system suitable for hydraulic engineering, and the method comprises the steps: obtaining a plurality of sensor data from a sensor assembly arranged in a to-be-detected pipeline; performing feature extraction to obtain detection data features; performing time-space synchronization fusion to obtain fusion features; acquiring historical corrosion data and fusion features of the inner wall of the pipeline and inputting the historical corrosion data and the fusion features into the long-short-term memory network model to obtain a first corrosion prediction result; generating a second corrosion prediction result through a random forest algorithm; generating a third corrosion prediction result by a gradient boosting tree algorithm; and inputting the three prediction results into a preset detection model to obtain a detection report. According to the method, multiple sensor data are obtained and fused to obtain the fused features, multiple factors influencing corrosion are comprehensively referenced, prediction analysis is carried out through multiple algorithms according to the fused features to obtain three prediction results, the detection report is generated, and the accuracy of the detection result is effectively 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 discloses a hydraulic engineering operation and maintenance monitoring system based on digital twinning, and the system comprises the steps: S1, a data collection module which is used for obtaining multi-modal actual detection data from a plurality of monitoring points of a hydraulic engineering; s2, a data generation module which simulates and generates multi-dimensional virtual monitoring data and an abnormal sample library related to hydraulic engineering operation and maintenance; s3, a data fusion module which fuses the multi-dimensional virtual monitoring data and the multi-modal actual detection data; s4, a digital twinborn model construction module which dynamically constructs a multi-dimensional digital twinborn model of the water conservancy project based on the fused multi-modal data set; s5, an anomaly detection module which detects potential anomaly and sudden faults through an anomaly sample library generated by the generative adversarial network in combination with a multi-dimensional spatial-temporal trajectory clustering analysis method; and S6, an operation and maintenance monitoring module which is used for providing real-time operation and maintenance monitoring service for the multi-dimensional digital twin model. The method has the advantages of being high in dynamic adaptive capacity, high in monitoring accuracy and high in abnormal response speed.

The present invention discloses a digital management method and system for a water conservancy project construction process, and belongs to the technical field of water conservancy projects. The method specifically comprises: real-time collection of relevant data from a water conservancy project construction site, and preprocessing, by comparing the actual construction progress with the planned progress, calculating the construction progress deviation, and analyzing the future construction progress trend, analyzing the construction quality data, training a prediction model through historical data, identifying construction quality hazards, combining the construction progress and quality, resource conditions and external environmental factors, intelligently scheduling construction resources, building a risk prediction model, and evaluating the risks in the construction process; in the context of complex water conservancy projects, it is possible to achieve process progress and quality management, reasonable resource scheduling and risk control, and better ensure the smooth progress of the project.

The present invention belongs to the technical field of engineering monitoring, and relates to a method for monitoring construction of water conservancy projects, including: collecting monitoring data from a water conservancy project construction site; inputting the monitoring data into a structural stability prediction model for analysis to generate a safety factor assessment value; inputting the monitoring data into a seepage risk prediction model for analysis to generate a seepage risk probability; combining the safety factor assessment value and the seepage risk probability, presetting a threshold, and triggering a graded warning signal; in response to the graded warning signal, calling a multi-objective optimization algorithm to dynamically adjust the current construction parameters and generate an optimized construction plan; loading the optimized construction plan into a digital twin system for virtual construction simulation to obtain predicted performance parameters; comparing the deviation value of the predicted performance parameters with the measured monitoring data, and iteratively updating the parameters of the prediction model when the deviation exceeds the tolerance range. The present invention solves the problem that traditional methods are difficult to discover potential problems and make optimization adjustments before construction.

The invention discloses a digital intelligent management method and system for hydraulic engineering construction, particularly relates to the technical field of hydraulic engineering construction management, and is used for solving the problems of regulation lag and insufficient environmental disturbance adaptability of an existing method under the action of multi-physics field coupling. According to the method, a concrete three-dimensional temperature field model is established, initial regulation and control parameters are generated, and a heat conductivity coefficient under the seepage influence is corrected based on space-time relevance of pore water pressure and temperature data; the constraint boundary is dynamically adjusted in combination with the construction progress and the material strength curve, a cooling water pipe coordinated regulation and control matrix is constructed, and target flow instructions of space differentiation are generated through the included angle between the distance and the water flow direction; setting a lag time threshold and optimizing an execution time sequence according to the thermal inertia parameter, splitting the threshold and allocating a weight coefficient when the environmental wind speed suddenly changes, and finally updating the model parameter and the regulation and control instruction; accurate temperature control response and abnormal heat conduction suppression under multi-field coupling are achieved, and the structural safety and construction efficiency under complex working conditions are improved.

The invention provides a hydraulic engineering three-dimensional design method, system and equipment and a storage medium, and relates to the field of three-dimensional design. The method comprises the steps of obtaining topographic data, hydrological data and engineering design requirements of an area where a project is located; performing feature extraction on the topographic data and the hydrological data to obtain key feature parameters; determining design constraint conditions according to engineering design requirements, and establishing a three-dimensional design optimization model based on the key feature parameters as design variables and the design constraint conditions; solving the three-dimensional design optimization model through a genetic algorithm to obtain a group of non-inferior solutions as a first candidate design scheme; optimizing the first candidate design scheme through a preset reinforcement learning model to obtain a second candidate design scheme; and performing simulation analysis based on the second candidate design scheme to obtain feedback information, and optimizing the second candidate design scheme based on the feedback information to obtain a target design scheme. Through the scheme, the hydraulic engineering design efficiency and the optimization degree of the design scheme are improved.

The invention relates to the technical field of computers, and discloses a digital twin hydraulic engineering operation and maintenance monitoring system which comprises a data acquisition module, a twin modeling module, a principal stress extraction module, a stress evolution prediction module, a safety domain judgment module, a regulation and control decision module, a control execution module and a state feedback module. The invention also discloses a digital twin hydraulic engineering operation and maintenance monitoring method, which comprises the following steps: data acquisition: real-time sensing data of a hydraulic engineering structure area is acquired through the data acquisition module, and the sensing data comprises strain, water pressure, temperature and displacement information and is used for representing the current state of the structure; and carrying out twin modeling, and receiving the real-time sensing data transmitted by the data acquisition module. According to the method, intelligent sensing and dynamic regulation and control of the structure state are realized by constructing a closed-loop system of principal stress prediction, regulation and control decision, control execution and state feedback.

The invention relates to the technical field of seepage monitoring, and discloses a seepage monitoring system based on a hydraulic engineering project. The system collects water level, flow velocity, seepage flow, soil humidity, soil temperature and soil pressure data through a data collection module, a data analysis module calculates standard soil humidity, standard water flow velocity, standard soil pressure, standard soil temperature and standard seepage flow according to the data, establishes a mathematical model, calculates seepage abnormal indexes, and calculates the seepage abnormal indexes according to the standard soil humidity, the standard water flow velocity, the standard soil pressure, the standard soil temperature and the standard seepage flow. The risk assessment and early warning module performs threshold judgment on the seepage abnormal indexes, sends out an overrun signal when an overrun condition occurs, predicts a future seepage trend by using a moving average method at the moment, generates a future seepage trend broken line graph and a seepage risk assessment report, and uniformly transmits the future seepage trend broken line graph and the seepage risk assessment report to the emergency response module; and when the emergency response module receives the overrun signal, an emergency plan is started, and related managers are informed of the emergency plan, the future seepage trend broken line graph and the seepage risk assessment report in a short message mode.

The invention discloses a river model multi-data processing analysis method and system, and relates to the technical field of hydraulic engineering, and the method comprises the steps: extracting a motion feature vector from a digital twin model, and carrying out the preprocessing to generate a standard river motion data set; according to the method, the sediment space distribution concentration Nsc (x, y, z, t) in a three-dimensional coordinate grid is calculated through a standardized data set, and the change trend of the sediment space distribution concentration Nsc (x, y, z, t) along with time is evaluated. When the sediment space distribution concentration Nsc (x, y, z, t) is larger than 0, highlighting marking is conducted on the abnormal area through a visual interface; when the sediment space distribution concentration Nsc (x, y, z, t) is less than or equal to 0, the sediment concentration is normal. For an abnormal area, the method further calculates the sediment conveying capacity Qs and the sediment deposition rate S, accurately predicts the moving path, the sediment deposition area and the sediment deposition speed of the sediment, dynamically analyzes the sediment movement condition of the river, and can track the sediment change trend in real time in a complex dynamic environment.

The invention discloses a dam seepage stability analysis method based on flood forecasting, and relates to the technical field of hydraulic engineering safety monitoring, comprising the following steps: S1, integrating a flood forecasting system and a seepage monitoring system into a data acquisition layer, and acquiring flood forecasting data and seepage monitoring data by a sensor of the data acquisition layer; s2, performing space-time alignment on the flood forecast data and the seepage monitoring data through a space-time coupling interface of the dynamic fusion layer, and generating a dynamic driving variable of a seepage field boundary condition based on a flood routing model and a geographic information system spatial interpolation technology; through the space-time coupling interface, space-time alignment and dynamic driving variable generation of flood forecast data and seepage monitoring data are achieved, the problem that the real-time flood routing process cannot be reflected due to the fact that the boundary condition is static or lagged in traditional analysis is solved, the seepage field calculation boundary condition can be dynamically updated along with flood forecast, and the real-time flood routing process cannot be reflected. And the timeliness and accuracy of model calculation are improved.

The invention relates to the technical field of pressure steel pipe stiffening ring welding, in particular to a hydraulic engineering pressure steel pipe stiffening ring welding machine which comprises two fixed bottom plates arranged in parallel and a sliding bottom plate installed between the two fixed bottom plates in a sliding mode. The upper portion of the right side of the sliding bottom plate is connected with a first adjusting seat through a hydraulic cylinder, and two clamping assemblies used for clamping the inner walls of the two ends of the pressure steel pipe are installed on the outer side of the supporting column at equal intervals. A first clamping mechanism used for clamping the outer side of one end of the pressure steel pipe is fixed to the outer side of the right end of the supporting column, and the supporting column is arranged over the sliding bottom plate. Supporting roller assemblies used for lifting and limiting the lower portion of the pressure steel pipe are symmetrically installed above the sliding bottom plate. According to the hydraulic engineering pressure steel pipe stiffening ring welding machine, a pressure steel pipe can be horizontally moved to adjust the welding position only by pushing the sliding bottom plate, the pressure steel pipe does not need to be separated from the supporting roller assemblies, operation is convenient, and time and labor are saved.

The invention provides a water conservancy construction progress intelligent management method and system. Wherein hydraulic engineering project plans are collected, dynamic changes in a life cycle are obtained through an integrated building information model technology, and a hydraulic engineering construction progress management framework is generated; extracting multi-source heterogeneous data, performing cross-modal information integration by applying a multi-modal fusion network algorithm, evaluating specific influence of external environment factors by adopting a causal forest technology, and generating a water conservancy construction progress and risk early warning report; establishing a kinetic equation by applying a graph neural differential equation algorithm, performing dynamic system simulation, and constructing a virtual water conservancy construction environment by adopting an enhanced digital twinborn simulation technology to capture construction efficiency and resource utilization conditions and generate a water conservancy construction resource allocation optimization report; and a lean six-sigma methodology is introduced to set a lean improvement plan, project feedback is collected, and a water conservancy construction progress intelligent management scheme is generated. According to the technical scheme provided by the invention, the intelligent level of water conservancy construction progress management is remarkably improved.

The invention provides a water conservancy grid parameter inversion method and system based on artificial intelligence, and the method comprises the steps: obtaining multi-source monitoring data of a target water conservancy project region, combining the multi-source monitoring data with a preset water conservancy grid physical mechanism model, and building an artificial intelligence probability inference frame for heterogeneous medium parameter inversion; and iteratively optimizing an implicit association relationship between permeability coefficient spatial distribution and hydraulic conductivity dynamic change in the water conservancy grid physical mechanism model, generating a parameter probability distribution set, and according to the parameter probability distribution set, combining with a historical seepage field evolution mode of the target water conservancy project area to obtain a historical seepage field evolution model of the target water conservancy project area. And the equivalent parameter value of each grid unit in the water conservancy grid physical mechanism model is dynamically corrected, a water conservancy grid parameter inversion result is generated, the precision and stability of water conservancy grid parameter inversion under complex working conditions are improved, and reliable support is provided for engineering safety and risk early warning of reservoirs and dams.

The invention provides a small and medium-sized reservoir operation safety evaluation system based on sky-ground work, and belongs to the technical field of hydrological monitoring. The device comprises a space-time alignment layer, a feature weighting layer and a dynamic coupling layer which are connected in sequence, the space-time alignment layer is used for performing time alignment and space alignment on the input data of the sky-land water conservancy project; the feature weighting layer is used for quantifying contribution degrees of different monitoring features to safety assessment according to the data after time-space alignment; and the dynamic coupling layer adopts a dynamic weight distribution strategy for different modules through a multi-module coordination engine, fuses feature weighting to obtain a fusion result, and outputs a small and medium-sized reservoir operation safety index according to the fusion result. The evaluation result is more accurate, and the timeliness is better.

The invention relates to the technical field of hydraulic engineering, geotechnical mechanics and geological disaster prevention and control engineering, and discloses a landslide surge physical and numerical hybrid model construction method and system and application. Analyzing the landslide instability evolution motion process, the landslide warehousing first wave height and the surge propagation process of the landslide surge; performing a numerical simulation test according to a second result of the landslide surge numerical model test; adjusting the particle size and the kernel function in the landslide surge numerical simulation test, so that the first wave height, the opposite-bank arrival height and the surge pressure distribution in the landslide surge numerical simulation test and the landslide surge physical model test are consistent; and taking the adjusted landslide surge numerical model as the obtained landslide surge hybrid model. The system comprises a first result acquisition module, a second result acquisition module, a test parameter adjustment module and a hybrid model acquisition module. According to the method, different calculation working conditions can be conveniently analyzed.

The invention discloses a large-model-driven intelligent calculation method and system for a water conservancy mechanism model. According to the method, natural language input, structured conversion and intelligent optimization calculation of a scheduling target are realized by integrating a field-enhanced large language model and a water conservancy professional mechanism model. The method comprises the steps of receiving a calculation target expressed by a user in a natural language, and analyzing and converting the calculation target into a constraint condition and a target function which can be recognized by a water conservancy mechanism model; a hydrological model, a hydraulic model, a hydrodynamic model and other models are called based on a workflow engine, and reverse calculation is carried out by adopting a hybrid optimization strategy of'coarse adjustment-fine adjustment-verification '; synchronously and visually displaying the parameter change and the result convergence state in the calculation process; and outputting a calculation result including parameter adjustment logic, standard conformity analysis and multi-scheme comparison. The system comprises a natural language interaction module, a target conversion module, an intelligent calculation engine module, a visualization module and a result generation module, and supports multiple application scenes such as multi-target scheduling, emergency decision making and ecological guarantee. Compared with a traditional scheme, the method has the advantages that the model use threshold is lowered, the dispatching efficiency and calculation transparency are improved, and the method is suitable for complex hydraulic engineering calculation tasks such as reservoir dispatching, cross-basin water transfer and flood control emergency.

The invention discloses a gravity dam safety risk management and control method and system based on a knowledge graph and a large model. The method comprises the following steps: collecting accident case data of a water conservancy project; performing entity and relationship extraction on all case data in the case library by using the fine-tuned model with domain knowledge to obtain a case data knowledge graph; the obtained case data knowledge graph is converted into natural language description, a text is used for fine tuning of a large language model, and finally a large language model with domain knowledge is obtained; performing information extraction on the engineering general situation information by using an engineering model, forming a natural language description problem by using an extraction result, and inputting the natural language description problem into a large language model with domain knowledge; the big language model answers the questions, and the expert judgment module provides expert opinions according to replies of the big language model. The intelligent system integrating artificial intelligence, reasoning and decision making is formed by utilizing the powerful language and reasoning ability of a large model.

The invention relates to a GNSS-based water conservancy facility deformation monitoring and early warning method, system and device and a medium, and the method comprises the steps: obtaining GNSS monitoring network data of a target part of a water conservancy facility, and carrying out the real-time dynamic differential processing, and obtaining corresponding three-dimensional coordinate data; acquiring environmental factor data, and performing multi-source feature fusion on the environmental factor data and the three-dimensional coordinate data to obtain a corresponding deformation feature vector; performing prediction analysis on the deformation feature vector according to a preset whale optimization algorithm to obtain a corresponding deformation trend prediction result; setting a multi-level early warning threshold according to the deformation feature vector, and performing early warning analysis on a deformation trend prediction result to obtain a corresponding initial early warning level; and obtaining standard deformation characteristic information of the deformation rate and the acceleration of the water conservancy facility, and performing comprehensive evaluation on the standard deformation characteristic information based on a deformation trend prediction result to obtain a corresponding early warning index. Potential risks can be found and processed in time, and the possibility of hydraulic engineering accidents is reduced.

The invention discloses a reservoir dam safety monitoring method and system based on edge calculation, and relates to the technical field of hydraulic engineering safety monitoring, and the method comprises the steps: obtaining monitoring data by each edge calculation node, carrying out the preprocessing, and generating a standardized data matrix; establishing a reference database, executing anomaly detection, and generating a labeling time sequence data matrix; performing multi-scale decomposition on the labeled time sequence data matrix, and constructing a node response feature matrix; the central processing unit receives data of each edge computing node, analyzes a multi-parameter spatial propagation mode by constructing a parameter-spatial correlation matrix, and obtains a spatial correlation feature matrix; establishing a Bayesian risk assessment model, predicting a dam risk level and outputting a risk evolution trend; and issuing a differentiated early warning instruction according to the risk assessment result. Through a distributed architecture combining edge calculation and central processing, real-time monitoring, intelligent analysis and accurate early warning of the dam safety state are realized, and the monitoring efficiency and the risk identification accuracy are improved.

The invention relates to a reservoir dam operation safety sky-land project intelligent sensing system and an operation method, and relates to the technical field of hydraulic engineering safety monitoring. The system is composed of a sky-land water conservancy project integrated monitoring and sensing system, a self-adaptive sampling module, a layered distributed architecture and a software and hardware integrated module, and multi-source data such as deformation, seepage, stress strain, vibration and environmental quantity are cooperatively collected through five dimensions of sky domain, airspace, territory, water domain and work domain. The monitoring frequency is dynamically adjusted by using an adaptive sampling strategy, and data cleaning, standardization, space-time registration and fusion processing are completed through a distributed architecture to generate a high-quality comprehensive data set. The system can realize total-factor and whole-process refined monitoring, effectively eliminates data islands, improves data quality and monitoring efficiency, has high reliability, real-time performance and expandability, and provides powerful data support and decision basis for dam safety assessment and intelligent early warning.

The invention relates to the technical field of water conservancy projects, in particular to a water conservancy project knowledge question and answer construction method and system based on a large model, and the method comprises the following steps: knowledge preparation, continuous evaluation optimization, user query processing, answer retrieval recall, and content generation. The hydraulic engineering knowledge question and answer construction method and system based on the large model have the beneficial effects that the large model and traditional knowledge of the hydraulic engineering industry are fused, so that the generated content is higher in quality and safer, and the problems of illusion and safety of LLM generation content of the large model are relieved; and a continuous evaluation index of the water conservancy field knowledge document system is provided, so that the system can answer questions with high quality.

The invention discloses a reservoir safety intelligent inspection method and system based on YOLO and VLM fusion, and the method comprises the following steps: S1, multi-source data collection and preprocessing: employing an unmanned plane and ground equipment to collect image / video data, and carrying out the noise reduction, enhancement and space-time alignment processing of the data; s2, improving YOLO target detection: optimizing a network structure and a training strategy; s3, link analysis after VLM: target / scene association judgment is realized by adopting the VLM; and S4, report generation. The invention provides a reservoir safety intelligent inspection method and system fusing YOLO and VLM. Cross-modal semantic understanding, zero sample reasoning and video global analysis capabilities of a visual language large model are utilized, the visual language large model is used as a post-processing tool of YOLO and is fused with the post-processing tool to work in parallel, full-process intelligentization of target detection-semantic analysis-report generation can be realized, the existing technical problems are effectively solved, and the visual language large model has a wide application prospect. And the comprehensiveness of the hydraulic engineering safety monitoring system is enhanced.

The invention discloses a hydraulic engineering digital design method based on digital twinning, and relates to the technical field of hydraulic engineering design. According to the digital twin-based hydraulic engineering digital design method, design demand information of a to-be-designed diversion tunnel is obtained and input into a pre-trained building recognition model for comprehensive analysis, a spatial layout map of the to-be-designed diversion tunnel is obtained, and a tunnel design digital twin model is constructed; simulation data of the tunnel design digital twinborn model are obtained, simulation analysis is carried out respectively, a tunnel construction risk index and a hydraulic action risk comprehensive index of the tunnel design digital twinborn model are obtained, comprehensive analysis is carried out, and a tunnel feasibility index of the tunnel design digital twinborn model is obtained; according to the method, the tunnel design digital twin model is subjected to design optimization based on the feasibility index, so that a lagging mode of re-evaluation after building is effectively avoided, later frequent reinforcement and reworking are prevented, and the engineering safety coefficient is improved.

The invention belongs to the technical field of water conservancy projects, and particularly discloses a water conservancy irrigation gate device and a using method thereof.The water conservancy irrigation gate device comprises a frame installed in a water channel, a gate is slidably connected into the frame, and a filter plate is fixed to the inner wall of the bottom of the frame and used for filtering impurities and garbage in water; the top of the filter plate extends into the gate in a sliding manner; according to the invention, in the up-and-down movement process of the gate, excessive silt can be prevented from entering the collecting groove, silt and sludge in the triangular grooves and the collecting groove can be pumped out and discharged, the sealing performance between the gate and the frame body is ensured, and in addition, the sealing performance between the gate and the frame body is ensured. And the triangular strip, the filter plate and the inclined surface scraper blade are matched to filter sundries and garbage in the water flow.