173 results about "Arch dam" patented technology

The invention discloses an alpine region-based double-curvature arch dam aeration ice-melting anti-icing device, and relates to the technical field of anti-icing, the alpine region-based double-curvature arch dam aeration ice-melting anti-icing device comprises a double-curvature arch dam body, a lifting structure, an aeration anti-icing structure, a PLC controller, a temperature sensor and a liquid level sensor are arranged on the outer convex curved surface side of the double-curvature arch dam body, and the aeration anti-icing structure comprises a plurality of fourth connecting pipes; the bottoms of the outer sides of the fourth connecting pipes are fixedly connected with a plurality of pressure release valves, and the bottoms of the pressure release valves are fixedly connected with bubble generators, so that along with the rise of the internal air pressure of the fourth connecting pipes, the air flow bursts through the pressure release valves and then is discharged through the bubble generators, and a large number of bubbles are generated; and in the process that the bubbles move towards the water surface, the water surface is stirred, the water surface is prevented from being frozen, the anti-freezing effect on the upstream side of the hyperbolic arch dam body is comprehensively achieved, and damage to the structure of the upstream side of the hyperbolic arch dam body caused by freezing is reduced.

The invention provides an arch dam shape efficient intelligent optimization method and system based on an agent model. The method comprises the steps that an arch dam physical-numerical model is constructed, a double optimization target with structural safety and economical efficiency as the core is determined, design parameters are selected, a constraint function is set, and an evaluation index system is established; samples are generated through Latin hypercube sampling, a data set is constructed in combination with finite element calculation, and a multi-task learning architecture is adopted to train a high-precision agent model. And then, coupling the proxy model with a multi-objective optimization algorithm, quickly searching a Pareto optimal solution set, and screening out a comprehensive optimal figure by using a multi-attribute decision-making method. And finally, through a finite element simulation verification result, prediction precision and performance improvement are ensured. The method has the advantages of lightweight modeling, efficient prediction and accurate search, and provides an effective tool for intelligent optimization and rapid decision making of hydraulic structures such as arch dams and the like.

The invention discloses a concrete arch dam global structural mechanical parameter zoning rapid inversion method, and relates to the technical field of dam operation safety monitoring and management, and the method comprises the steps: building a dam body and foundation three-dimensional finite element model through finite element software according to engineering design and monitoring data, and building a foundation three-dimensional finite element model according to damming material mechanical parameter information; partitioning the three-dimensional finite element model, analyzing the sensitivity of mechanical parameters of each region, determining sensitive mechanical parameters influencing the deformation of the concrete arch dam, and carrying out self-adaptive intelligent sampling on the sensitive mechanical parameters according to a sensitivity analysis result, and constructing a deep learning agent model reflecting a nonlinear relationship between the sensitive mechanical parameters of the dam and the deformation of each monitoring point, and carrying out deep learning inversion on the elastic modulus of the dam body and the deformation modulus of the bedrock. According to the invention, the method can efficiently and accurately invert and determine the structural mechanical parameters of the arch dam in the actual operation period, and provides a good basis for the safety analysis of the dam.

The invention relates to the technical field of arch dam deformation monitoring data processing, in particular to an arch dam deformation monitoring data preprocessing method and system, and the method comprises the steps: collecting arch dam deformation monitoring data; constructing a track matrix for the original deformation monitoring data sequence, and performing singular value decomposition on the track matrix to obtain a feature value and a feature vector; selecting a principal component according to the contribution rate of the characteristic value, and reconstructing a signal; the reconstructed signals are analyzed, and gross errors are identified and eliminated; dividing the deformation monitoring data without the gross error into a training set and a test set; constructing a neural network model, and training the neural network model by adopting the training set; and filling missing data in the test set by using the trained neural network model. According to the invention, monitoring data gross error identification and monitoring data missing processing are realized.

The invention belongs to the field of dam safety monitoring, and particularly provides an arch dam structure safety monitoring method and system, and the method comprises the steps: obtaining monitoring data, comparing the monitoring data with corresponding early warning values, and recording the monitoring data as normal if all the monitoring data are smaller than the corresponding early warning values; otherwise, acquiring an early warning score of the abnormal measuring point, and executing a preset judgment process; the preset judgment process comprises the following steps: firstly checking measuring points of similar spaces, the same type and the same dam section, if the measuring points are abnormal at the same time, forming an early warning measuring point group, and calculating the similarity to determine a correlation weight coefficient; otherwise, directly calculating an early warning score. The early warning score is determined according to the abnormal rate weight coefficient, the association weight coefficient and the abnormal measuring point early warning score. And finally, according to a preset monitoring index system and the early warning score of the early warning measuring point group, determining the early warning score of the monitoring item, the sub-item and the object step by step. According to the technical scheme, the accuracy and reliability of safety monitoring of the arch dam structure can be improved, and more effective technical support is provided for safety monitoring stop of the arch dam structure.

The invention belongs to the field of hydraulic engineering, and relates to an arch dam cable crane real-time obstacle avoidance trajectory smooth transition planning method, which comprises the following steps: 1) initializing working initialization parameters of an arch dam cable crane; 2) constructing a two-dimensional grid environment map; 3) performing simplest geometric obstacle avoidance path planning based on the two-dimensional grid environment map to obtain path nodes; 4) optimizing the simplest geometric obstacle avoidance path plan to generate a trajectory cluster; 5) screening the trajectory clusters to form a preferred trajectory; 6) executing the optimal trajectory, and updating the two-dimensional grid environment map in combination with the collision risk in the event; and 7) in combination with the updated two-dimensional grid environment map, repeatedly executing the step 3), and constructing a real-time obstacle avoidance track smooth curve. The invention provides the smooth transition planning method for the real-time obstacle avoidance track of the arch dam cable crane, which can provide theoretical research and engineering application support for dynamic simulation and beforehand rehearsal of a cable crane hoisting operation process, real-time obstacle avoidance track result output and safe and efficient construction guidance of a construction process.

The invention relates to the technical field of hydraulic structure service behavior analysis and computational mechanics, and particularly discloses a high arch dam deformation behavior fractional order numerical analysis physical and mechanical parameter inversion method and module. A viscoplasticity parameter inversion method is provided based on a Levenberg-Marquardt method by using rheological test data. Optimizing to obtain a to-be-inverted parameter sample combination by means of central composite design; constructing an elastic and viscoelastic parameter inversion objective function in combination with deformation in-situ monitoring data; based on a multiple-input-multiple-output support vector machine, establishing an elastic and viscoelastic parameter inversion agent model; a random inertia weight, an asynchronous change learning factor, golden sine disturbance and differential evolution variation disturbance are introduced to improve a particle swarm algorithm, so that a parameter optimal inversion value search strategy is established. The method aims at improving the accuracy and objectivity of numerical analysis of the deformation state of the high arch dam, provides technical support for in-service engineering safety monitoring and dangerous case early warning, and has wide application prospects and markets.

The invention relates to the technical field of dam health monitoring, in particular to a dam operation deformation prediction method, device and equipment and a computer storage medium. According to the invention, aiming at a structure monitoring mode of current point detection, one of core factors influencing arch dam deformation is solved in a targeted manner by combining a temperature field model. Therefore, a CNN-based deformation field reconstruction model is finally constructed based on data such as a temperature field and a water pressure field. For each predicted location, the parameters of the reconstructed model are universal and unified. The globally unified model can export high-precision and high-density deformation reconstruction data, and the overall deformation behavior of the arch dam can be analyzed more accurately.

The invention discloses an arch dam aging deformation mechanism analysis method, and relates to the field of hydraulic structure safety. The method comprises the steps that based on three-dimensional terrain and geological data, a high-precision arch dam-foundation overall finite element mesh model is established, concrete materials and permeation partitions are divided carefully, and an anti-seepage and drainage system structure is embedded; by means of multi-source monitoring data, real boundary conditions such as water temperature and air temperature and thermodynamic parameters are dynamically recognized and optimized through the intelligent inversion technology; respectively analyzing the aging influence of single factors such as a temperature field and valley amplitude deformation on arch dam deformation by adopting finite element simulation; on the basis of the normalized deformation response data, a Bayesian optimized long-short-term memory neural network and a hierarchical correlation propagation algorithm are adopted, contribution weights of all factors to deformation are calculated, and weight rationality is verified through global sensitivity analysis. According to the method, quantitative separation and evaluation of the main deformation influence effect of the arch dam are realized, and a theoretical basis can be provided for structural health monitoring and safety management.

The invention discloses a seismic oscillation parameter selection and high arch dam response prediction method based on random forest-recursive feature elimination. The method comprises the following steps: (1) constructing a high arch dam finite element model; (2) seismic oscillation input of a finite element is obtained, and nonlinear seismic response of the arch dam under the seismic oscillation input is obtained through nonlinear dynamic time-history analysis; (3) taking the output parameters as a data set to obtain an optimal feature set of the high arch dam; and (4) on the basis of the obtained optimal IM feature set of the high arch dam and the corresponding random forest model, in combination with seismic oscillation input data, predicting a response result of the high arch dam through sampling. According to the seismic oscillation parameter selection and high arch dam response prediction method based on random forest-recursive feature elimination, the complex nonlinear relation between the features can be fully captured, the interaction between the features can be better considered, the complexity of the model can be better controlled, too many or too few features are prevented from being selected, the over-fitting risk is reduced, and the method is suitable for large-scale popularization and application. The performance and the effect of feature selection are improved.

The utility model provides a position measuring device for a gate groove embedded part of a concrete arch dam gate, which belongs to the technical field of engineering construction and comprises two bases, the upper surfaces of the two bases are fixedly connected with support frames and positioning assemblies, each positioning assembly comprises two guide rods fixedly connected between the tops of the support frames, and the two guide rods are fixedly connected with the support frames. And the two guide rods are slidably connected with moving seats in a sleeving mode, the bottom faces of the two moving seats are fixedly connected with limiting guide grooves, the limiting guide grooves are slidably connected with limiting blocks in a sleeving mode, the bottom faces of the limiting blocks are fixedly connected with connecting columns, and the bottom ends of the connecting columns are fixedly connected with a bearing plate. According to the utility model, through the arrangement of the positioning assembly, the pre-embedded position can be conveniently positioned, the operation is convenient, the positioning is accurate, and through the arrangement of the stabilizing assembly, the pre-embedded position after the measurement is completed can be stabilized, so that the subsequent efficient and stable pre-embedded construction is ensured.

The invention belongs to the technical field of arch dam shape design and artificial intelligence, and discloses an arch dam shape multi-target intelligent design and optimization method based on machine learning. Comprising the following steps: step 1, collecting and sorting arch dam body type design data of a domestic arch dam body type; step 2, performing data cleaning on the collected arch dam shape design data, performing correlation analysis based on the arch dam shape design data, and performing feature dimension reduction by using principal component analysis to complete feature engineering of the arch dam shape design data; and 3, calling the machine learning model for design optimization, inputting to-be-designed input parameters, performing intelligent design and optimization of arch dam shape design by using the machine learning model, and outputting an arch dam arch crown beam curve equation and a horizontal arch ring linear equation. According to the method, multi-target intelligent design and optimization of arch dam shape design are realized, and the efficiency of arch dam shape design is effectively improved.

The invention discloses an arch dam abutment block safety evaluation method considering spatial force system decomposition, which comprises the following steps of: calculating an external load borne by an arch dam abutment block by adopting a finite element method, judging the sliding direction of the block, decomposing the external load borne by the block on a block sliding calculation spatial force system, and calculating the sliding force and the anti-sliding force of the block. And calculating a block safety coefficient, and evaluating a block safety state. According to the method, spatial force system decomposition is utilized, the block sliding force and the block anti-sliding force can be accurately decomposed to the block sliding-out direction, the numerical values and the acting directions of the block sliding force and the block anti-sliding force can be more accurately obtained, and the safety of the dam abutment block can be more accurately evaluated. The invention further provides arch dam abutment block safety evaluation equipment.

The invention discloses a high-pressure air flow uniform disturbance device for an anti-freezing arch dam in an alpine region, and relates to the technical field of anti-freezing of arch dams, the high-pressure air flow uniform disturbance device comprises a fixing frame, sleeves are rotatably connected to the interiors of a plurality of supports, supporting plates are fixedly connected to the two sides of the bottoms of the supports, and connecting plates are fixedly connected to the bottom ends of the two supporting plates; a threaded rod is slidably connected to the interior of the sleeve, a rotating plate is rotatably connected to the bottom end of the threaded rod, a supporting plate is fixedly connected to the bottom of the rotating plate, a rotating pipe is rotatably connected to the interior of the supporting plate, a spray head is fixedly connected to the top end of the rotating pipe, and a plurality of blades are fixedly connected to the outer side of the spray head in an annular array mode; according to the high-pressure air flow uniform disturbance device of the anti-freezing arch dam in the alpine region, turbulent flow is formed in water, the disturbance effect of high-pressure air flow is further improved, the anti-freezing effect of the water surface is improved, the water surface is stirred through the rubber elastic strips, water flow near the water surface is turned over, and the anti-freezing effect is improved.

The invention belongs to the technical field of hydraulic engineering digital twinning, and provides an arch dam static response rapid calculation method which comprises the following steps: sampling and simulating based on a finite element model in an offline stage to obtain a displacement field snapshot matrix, extracting a dominant mode through intrinsic orthogonal decomposition to construct a reduced-order subspace, and calculating a mode coefficient; and training a radial basis function neural network to establish a nonlinear mapping relation by taking the working condition parameters as input and the modal coefficient as output, and finally, inputting the target working condition parameters into the trained network to predict the modal coefficient in an online stage, and quickly reconstructing a complete displacement field response through linear combination with the POD modal. The method achieves the quick and accurate prediction of the static physical field of the arch dam, and remarkably improves the calculation efficiency of the displacement field of the arch dam.

The invention discloses a spatial-temporal feature fusion concrete arch dam deformation prediction method based on multi-scale hierarchical clustering, and the method comprises the following steps: decomposing a dam deformation sequence into trend, period and fluctuation items, and constructing a new multi-scale similarity distance index; adopting a hierarchical clustering method based on a Ward criterion, and utilizing the constructed multi-scale similarity distance index to perform clustering partition on the deformation measuring points with the similar deformation rule; a deep learning model TCT-CANet fused with the spatial and temporal characteristics is constructed; the deformation of the concrete arch dam is predicted by utilizing the constructed TCT-CANet model, the prediction performance of the model is evaluated through various evaluation indexes, and meanwhile, the effect of each module in the aspects of spatial-temporal feature capture and prediction precision improvement is analyzed through an ablation experiment; the TCT-CANet model is compared with various time sequence prediction methods on all measurement points, and the superiority and generalization ability of the model are verified. According to the method, the prediction model TCT-CANet based on spatial-temporal feature fusion is constructed, and accurate prediction of deformation of the concrete arch dam is realized.

The invention discloses a concrete dam gallery arch part concrete cracking analysis method, which comprises the following steps: constructing a gallery arch three-dimensional finite element model, carrying out simulation analysis on a temperature field and a stress field in a dam gallery arch construction period, further evaluating the gallery safety state, analyzing the reason of foundation drainage gallery arch cracking, and determining the concrete cracking degree of the foundation drainage gallery arch. And finally, crack propagation simulation is performed on the gallery part based on a stress result, so that a scientific basis and feasible suggestions can be provided for formulating anti-cracking measures of the gallery in the construction period, the stress-strain process of the concrete at the top arch part of the concrete dam gallery is effectively monitored in real time, the cracking condition is analyzed, and the crack propagation path and trend are simulated. According to the method, a scientific basis is provided for revealing a concrete crack forming mechanism, key technical support is provided for anti-cracking reinforcement of the arch dam gallery top arch part through prospective risk pre-judgment, and controllability and reliability of structural safety in the concrete dam construction period are improved.

An arch dam overall deformation coordination monitoring method based on a full convolutional neural network comprises the following steps: S1, selecting a plurality of measuring points to construct an overall deformation measuring point monitoring network according to the arrangement condition of arch dam monitoring deformation measuring points; s2, collecting historical deformation monitoring data of the arch dam, and preparing overall deformation data samples of the arch dam at different moments in combination with the overall deformation monitoring network; s3, constructing a full convolutional neural network model for monitoring the overall deformation coordination of the arch dam; s4, performing unsupervised training on the full convolutional neural network by using the arch dam overall deformation data samples at different moments to obtain an arch dam overall deformation coordination monitoring model; and S5, for arch dam deformation at any moment, constructing overall deformation data according to the measuring points of the deformation monitoring network, and performing deformation coordination detection by using the trained full convolutional neural network to realize arch dam overall deformation coordination monitoring. According to the method, manual data annotation is not needed, and intelligent judgment on the overall deformation coordination of the arch dam can be realized based on historical operation data.

The invention belongs to the field of water conservancy and hydropower engineering, discloses a finite element grid construction method for free grids of a regular grid foundation of an arch dam in complex geology, and aims to realize high-precision regular grids of a dam body and flexible, diversified and quick free grids of a dam foundation so as to improve the reasonability and effectiveness of stress and overall stable calculation of the arch dam. According to the scheme, firstly, according to arch dam shape design data, a regular arch dam geometry is established; secondly, a dam foundation geometric block is built in the dam foundation near the foundation building surface, and a dam foundation foundation building surface thin layer is obtained; secondly, according to a foundation building surface, a dam foundation foundation building surface thin layer, a terrain surface, a dam foundation lithologic stratum boundary line and a fault structural surface, a geometry of the complex foundation is built; and finally, model mesh generation is carried out on the arch dam geometry, the dam foundation construction base plane thin layer and the geometry of the complex foundation in sequence, specifically, hexahedron mapping mesh generation is carried out on the arch dam geometry, then transition mesh generation from hexahedron to tetrahedron is carried out on the geometry of the dam foundation construction base plane thin layer, and model mesh generation is carried out on the geometry of the complex foundation. And finally, carrying out free mesh generation on the geometry of the complex foundation.

The invention discloses a global horizontal displacement monitoring method for an arch dam. The global horizontal displacement monitoring method comprises the step of calculating global horizontal displacement of the arch dam through arch end vector displacement obtained through an arch ring of the arch dam and linear displacement of strain of any point of the arch ring of the arch dam. The linear displacement of any point is calculated through the strain distribution of the full length of the arch ring of the arch dam; arranging inverted pendants at two ends of the arch dam arch ring to obtain arch end vector displacement; the position of any point after deformation is obtained according to the fact that the macroscopic shape of the arch dam is unchanged and continuous, vector displacement can be obtained and further decomposed into radial displacement and tangential displacement, and then monitoring of the global horizontal displacement of the arch dam is achieved.

The invention discloses a strain field reconstruction test device of an arch dam structure, which comprises an arch dam physical model, a temperature compensation gypsum block, an optical fiber and an optical fiber demodulator, a first end of the optical fiber is connected with the optical fiber demodulator, a second end of the optical fiber is not connected with other equipment, and a plurality of arch dam physical model strain gauges are arranged on the upper surface of the arch dam physical model. The arrangement path of strain gauges of the arch dam physical model is consistent with the arrangement path of the first section of optical fiber; a strain gauge for the temperature compensation gypsum block is also arranged on the upper surface of the temperature compensation gypsum block; the optical fiber demodulator is also connected with the computer; a connector of the gravity load simulation device is connected with the interior of a dam body of the arch dam physical model, and a lifting sleeve of the oil jack is attached to the surface of the upstream side wall of the arch dam physical model. The device can quickly acquire the surface strain data of the arch dam physical model through the distributed optical fibers. The invention further discloses a strain field reconstruction test method of the arch dam structure and a strain field reconstruction test system of the arch dam structure.

The invention discloses a design method of an extra-high arch dam diversion tunnel structure, relates to the field of water conservancy and hydropower engineering, solves the problem that an existing diversion tunnel structure cannot overhaul a diversion tunnel lock chamber under the condition of large flow in a dry season, and determines arrangement parameters of the extra-high arch dam diversion tunnel structure. According to the technical scheme, according to the design method of the ultrahigh arch dam diversion tunnel structure, an outlet of an ecological bypass tunnel is connected with a diversion tunnel main tunnel, a diversion tunnel lock chamber is arranged at an inlet of the diversion tunnel main tunnel, and a middle partition pier dividing the diversion tunnel main tunnel into a tunnel A and a tunnel B is further arranged at the inlet of the diversion tunnel main tunnel; a front flow guide gate and a rear flow guide gate are arranged in each of the hole A and the hole B; a bypass hole lock chamber is arranged at an inlet of the ecological bypass hole, and a front bypass gate and a rear bypass gate are arranged in the bypass hole lock chamber. According to the method, the values of the arrangement parameters of the diversion tunnel structure of the extra-high arch dam are determined, so that the multiple functions of flood control, leakage control, water storage and maintenance of the extra-high arch dam are achieved. The method is used for diversion design of the extra-high arch dam.

The utility model discloses an experimental device for anti-explosion protection of an arch dam, and belongs to the field of simulation explosion tests. The experimental device comprises a fixing mechanism, an explosive module, a displacement sensor module and an acceleration sensor module, wherein the fixing mechanism is used for supporting a high polymer plate; the explosive module is arranged above the high polymer plate and is used for carrying out an anti-explosion test on the high polymer plate; the displacement sensor module and the acceleration sensor module are fixedly mounted on the high polymer plate; the shock wave sensor modules are symmetrically arranged on the two sides of the high polymer plate. According to the experimental device, shock wave sensor modules are installed on the upper side and the lower side of a high polymer plate, an explosive module is installed above the high polymer plate, the explosive module is detonated through an exploder, shock waves on the explosion facing face and the explosion backing face of the high polymer plate are detected through the shock wave sensor modules on the two sides, and displacement data are tested through a displacement sensor module. Acceleration data are tested through the acceleration sensor module, so that comprehensive anti-explosion analysis is carried out on the high polymer plate, and the method is more comprehensive and fine.

The application belongs to the technical field of arch dam shape design and artificial intelligence, and discloses a kind of arch dam shape multi-objective intelligent design and optimization method based on machine learning;Including the following steps: step 1, collect and arrange arch dam shape design data of arch dam shape;Step 2, carry out data cleaning to the collected arch dam shape design data, carry out correlation analysis based on arch dam shape design data, and utilize principal component analysis to carry out feature dimension reduction, complete the feature engineering of arch dam shape design data;Step 3, call the machine learning model of design optimization, and input the input parameter to be designed, utilize machine learning model to carry out intelligent design and optimization of arch dam shape design, output arch dam crown beam curve equation and horizontal arch ring line equation.The application realizes multi-objective intelligent design and optimization of arch dam shape design, effectively improves the efficiency of arch dam shape design.

The invention belongs to the field of concrete dam construction organization, and relates to an arch dam concrete cable crane hoisting track prediction method, which comprises the following steps: 1) constructing a space coordinate system, and determining a space positioning node of a cable crane; 2) acquiring real-time position information of a spatial positioning node of the cable crane by using a sensor; 3) performing filtering and noise reduction preprocessing on the real-time position information of the spatial positioning node of the cable crane by using Kalman filtering; 4) calculating the preprocessed real-time position information of the spatial positioning nodes of the cable crane, and obtaining time sequence motion state parameters of the cable crane; 5) constructing a cable crane trolley-lifting rope-hanging cage system dynamics model, and 6) predicting the swing angle of the cable crane hanging cage based on the cable crane trolley-lifting rope-hanging cage system dynamics model and obtaining the motion trail of the hanging cage. The arch dam concrete cable crane hoisting track prediction method can improve prediction precision.

The invention discloses a method for calculating temperature load of an arch dam adopting permanent heat preservation measures in a cold region, which comprises the following steps of: calculating a quasi-stable temperature field of a typical section of the arch dam by adopting a finite element method and combining thermal parameters of heat preservation materials and concrete of upstream and downstream dam surfaces of the arch dam according to a stable heat conduction principle; the calculation of the temperature load of the arch dam adopting the permanent heat preservation measure in the cold region is realized, a new method for calculating the temperature load of the arch dam adopting the heat preservation measure is explored, and the efficiency and the precision of temperature load calculation are improved.

The invention belongs to the technical field of water conservancy projects, and discloses an extra-high arch dam bank slope dam section concrete first bin high lift layer construction method which comprises the following steps: step 1, determining dam concrete construction layering, step 2, establishing a template support model, step 3, carrying out stress checking calculation and the like. According to the extra-high arch dam bank slope dam section concrete first bin high lift layer construction method, PKPM structural calculation software is combined with the structural form of a dam, the distance from an upstream excavation face is combined, a model is established for structural stress and stability analysis, high lift layer construction is achieved, the highest lift layer height is large, multi-bin parallel one-time pouring is achieved, the pressure of a standby bin is relieved, and the construction efficiency is improved. The construction efficiency is improved. According to the ultrahigh arch dam bank slope dam section concrete first bin high rising layer construction method, the pouring height and quality of each layer can be effectively controlled, the uniformity and compactness of concrete are ensured, and the construction precision of the whole structure is improved.

The invention discloses an arch dam shear-resistant safety evaluation method, which specifically comprises the following steps of: establishing an arch dam numerical model through ADAO software, calculating shear-resistant safety coefficients of each arch section and beam section of a dam body, and identifying and positioning the most unfavorable arch section and the most unfavorable beam section according to the shear-resistant safety coefficients; constructing an agent model by combining Latin hypercube sampling and a BP neural network method; calculating an arch dam shear resistance reliable index based on a Monte Carlo simulation method; according to the arch dam anti-shear safety evaluation method, the arch dam anti-shear safety problem is focused, the anti-shear safety level of the weakest area of the arch dam is quantitatively evaluated, the gap of arch dam anti-shear safety evaluation is filled up, anti-shear safety is accurately quantified, a scientific and efficient path is provided for arch dam engineering anti-shear safety evaluation, and through A arch dam example verification, the arch dam anti-shear safety evaluation method has the advantages that the arch dam anti-shear safety evaluation method is high in practicability. And the arch dam operation safety is effectively guaranteed.

The invention, which relates to the technical field of dam safety monitoring, discloses a concrete arch dam video monitoring system comprising a plurality of monitoring points, at least one monitoring substation and a monitoring master station. The monitoring points are distributed at key monitoring parts of a concrete arch dam and a near dam reservoir area, and each monitoring point is provided with front-end equipment for acquiring video and image information; the monitoring substations serve as regional signal convergence and transmission nodes and are connected with a plurality of monitoring points which the monitoring substations belong to through wired or wireless communication links, and industrial-grade switches are arranged in the monitoring substations. The monitoring master station serves as a system management and application center, communicates with at least one monitoring substation through a network, and is integrated with a control device, a storage device, a display device and an information management system. And the front-end equipment, the monitoring substation and the monitoring master station are sequentially in communication connection to form a closed-loop system for completing information acquisition, transmission, storage and management. According to the system, manual inspection blind areas and risks are eliminated, and dam body defect identification efficiency and data reliability are improved.

The invention relates to the technical field of building design, in particular to an arch dam three-dimensional geological model and parameterized design data fusion system and method and application, and the system comprises a data acquisition and interface module which obtains CAD data and three-dimensional geological data; the data preprocessing and feature engineering module is used for preprocessing the CAD data and the three-dimensional geological data and extracting features; the three-dimensional model data fusion engine module is used for constructing a three-dimensional digital model with uniform structural parameters; the machine learning-based analysis and evaluation module is used for carrying out performance prediction, key region identification and CAE result interpretation on the three-dimensional digital model by utilizing a machine learning model to generate performance evaluation information; and the arch dam design parameter optimization and recommendation module adopts an intelligent optimization algorithm to optimize arch dam design parameters, outputs a final design parameter combination, and improves the accuracy and decision-making efficiency of arch dam parameterization design and the intelligent level of engineering design.