125 results about "Arch dam" patented technology

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 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 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 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 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.

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 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 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.

The invention provides a high arch dam abutment anti-sliding stability analysis and evaluation method, which comprises the following steps of: respectively carrying out adit exploration on left and right banks, and analyzing slowly-inclined and steep-inclined structural surfaces to obtain a possible block sliding combination; three-dimensional software is adopted for conducting three-dimensional modeling on the terrain of the dam site area, typical structural planes of the left bank and the right bank of the dam foundation are built into surface domains according to structural plane coordinate information obtained through exploration, and the surface domains extend to a slope table; finite element analysis is conducted through three-dimensional modeling, and multi-factor comprehensive analysis and evaluation are conducted on the anti-sliding stability of the blocks after excavation of the left bank side slope and the right bank side slope of the arch dam. According to the method, adit exploration is carried out on the two banks of the arch dam, obtained data are substituted into three-dimensional software to carry out three-dimensional modeling on the geological conditions of the two banks of the arch dam, finite element calculation is carried out according to three-dimensional modeling, and the anti-sliding stability of the corresponding position of the dam abutment of the arch dam is comprehensively analyzed and evaluated from the angle of multiple factors. Therefore, a theoretical basis is provided for design and implementation of anti-sliding measure schemes of the two banks during arch dam construction.

The invention discloses a high-altitude area arch dam deformation safety early warning index zoning drawing-up method, which comprises the steps of collecting high-altitude area arch dam deformation safety multi-source monitoring data, and determining a measured value sequence composite similarity measurement index of the high-altitude area arch dam deformation safety multi-source monitoring data; performing arch dam deformation behavior clustering analysis under the driving of multi-monitoring-point monitoring data, completing arch dam deformation homogeneous feature recognition, and realizing objective partitioning of the arch dam deformation behavior in the high-altitude area; determining marginal probability distribution of measuring points in each partition, establishing a joint probability distribution function of a strong correlation measuring point group in the partition, and estimating a multi-measuring-point joint probability density function parameter; and carrying out graded early warning index drawing-up on the deformation safety of the arch dam in the high-altitude area in the multi-dimensional probability space. According to the method, the situation that a traditional single-measuring-point deformation early-warning mode and method do not fully consider the behavior relevance between the measuring points is broken through, the high-altitude area arch dam deformation safety partition multi-point combined early-warning index is drafted under the driving of multi-measuring-point monitoring data, and the deformation behavior of the high-altitude area arch dam can be judged more comprehensively; and higher robustness and higher accuracy are shown.

This application relates to the field of arch dam casting technology, and discloses a simulation method and apparatus for arch dam casting. The method includes: acquiring dam sections that meet preset casting conditions, and identifying dam blocks that meet casting requirements from the dam sections; assigning weights and sorting the dam blocks to be cast according to casting engineering parameters and arch dam structural parameters to obtain an initial casting sequence; if a preset number of consecutive dam blocks to be cast belong to the same construction section in the initial casting sequence, adjusting the initial casting sequence to obtain an adjusted casting sequence; configuring cable crane resources for the dam blocks to be cast based on the adjusted casting sequence and cable crane information, and performing simulated arch dam casting. By integrating casting engineering parameters and arch dam structural parameters for weighted sorting, multi-objective collaborative optimization guided by structural safety and construction efficiency is achieved, and the sequence of consecutive dam blocks in the same section is adjusted, improving the concentration of construction resources and making the adjusted casting sequence more reasonable.

The invention discloses a method for analyzing dynamic response indexes of a concrete arch dam structure influenced by earthquakes, which comprises the following steps of: acquiring various displacement response and stress response indexes of a concrete arch dam in each unit time and damage indexes of a working state of the concrete arch dam in each unit time by various data acquisition sensors; the collected data is stored and sent to the engineer data centralized control center; performing normalization processing on the data, and mapping the data of different physical quantity outlines to the same numerical range; according to the structural characteristics of the concrete arch dam, the arch dam is divided into different nodes, and a node feature matrix is constructed; and if the multiple displacement response and stress response indexes and the damage indexes are not in the preset safety limit boundary conditions, generating a concrete arch dam to-be-maintained and repaired instruction, and feeding back the instruction to the concrete arch dam structure safety analysis model interface through the multi-modal data centralized control server. The to-be-maintained and repaired instruction of the concrete arch dam can be sent out in time, and the analysis efficiency is improved.

This application provides a method and system for the intelligent transformation of an existing arch dam. The method includes: diagnosing, evaluating, optimizing, and supplementing the existing monitoring system of the arch dam, and outputting standardized and fused multi-source monitoring data; constructing and refining a simulation model based on the multi-source monitoring data to build a digital twin reflecting the current operational status of the arch dam; analyzing the operational status of the arch dam over a future period based on the digital twin, performing hydrological-hydraulic integrated diagnosis and dynamic simulation, and generating decisions for routine or emergency scheduling; and executing closed-loop control actions on the arch dam gates through a gate control system integrated with safety interlocking and remote communication capabilities, according to the control instructions or emergency plan.

The application discloses an arch dam valley amplitude deformation risk quantitative early warning method and system based on plastic effective stress evolution, and the method comprises the following steps: S1, acquiring deep site monitoring data; S2, calibrating the plastic effective stress coefficient and the rock mass or structural plane strength parameter, and determining the value range of different rock masses; S3, removing the elastic volume deformation component, and directly constructing the plastic effective stress tensor for controlling the shear yield; S4, constructing the dimensionless plastic approximation degree index K, and quantifying the approximation degree of the stress state to the failure envelope surface; S5, introducing the displacement rate and the cumulative deformation for double control verification, and intelligently identifying the critical yield locking, limited plastic damage and continuous structural plane rheological mode. The application solves the mechanism paradox between the traditional theory of 'water thrust causes deformation widening' and the actual monitoring of 'valley amplitude narrowing', and realizes the accurate quantification and grading early warning of the rheological risk of the deep rock mass of the high arch dam.

The present invention discloses a high-pressure airflow uniform disturbance device for anti-freezing ice arch dams in high-altitude cold areas, which relates to the technical field of anti-freezing ice for arch dams, and comprises a fixing frame, wherein a plurality of the brackets are rotatably connected to sleeves inside, support plates are fixedly connected on both sides of the bottom of the brackets, and the bottom ends of the two support plates are fixedly connected to connecting plates, a threaded rod is slidably connected inside the sleeve, the bottom end of the threaded rod is rotatably connected to a rotating plate, the bottom of the rotating plate is fixedly connected to a support plate, the support plate is rotatably connected to a rotating tube, the top of the rotating tube is fixedly connected to a nozzle, and a plurality of blades are fixedly connected to the outside of the nozzle in a ring array. The high-pressure airflow uniform disturbance device for anti-freezing ice arch dams in high-altitude cold areas forms turbulence in water, further enhances the disturbance effect of the high-pressure airflow, thereby improving the anti-icing effect of the water surface, causes the rubber elastic strip to stir the water surface, and causes the water flow near the water surface to surge, thereby improving the anti-icing effect.

The invention provides an intelligent arch dam deformation monitoring system based on a rail robot, which belongs to the technical field of hydraulic engineering and comprises an arc-shaped guide rail, a rail moving device, an automatic leveling base, an intelligent total station, a driving device and a data processing module. The intelligent total station is used for collecting deformation data of a plurality of rearview reference points arranged on the top of the arch dam; the driving device is used for driving the rail moving device to slide along the arc-shaped guide rail; the data processing module is used for receiving, analyzing and processing the deformation data, the data processing module adopts a multi-station automatic networking adjustment algorithm to carry out error correction and data adjustment on the deformation data and outputs a deformation monitoring result of the arch dam, and the multi-station automatic networking adjustment algorithm comprises a least square method, a Kalman filtering algorithm and resection adjustment. The arch dam deformation data are automatically collected through the rail robot, high-precision data correction is ensured in combination with a multi-station automatic networking adjustment algorithm, and the reliability and precision of deformation monitoring are improved.

This application relates to the field of water conservancy engineering safety monitoring technology, and in particular to a method and system for intelligent early warning of dam deformation based on multi-source sensor data fusion. The method includes: acquiring a multi-source information set of the dam; based on the multi-source information set, analyzing the impact of asymmetric deformation caused by differences in load transfer in a hyperbolic arch dam, obtaining a dynamic information set of the dam abutments; based on the dynamic information set of the dam abutments and a dynamic dormancy strategy, analyzing the impact of mud adhesion and freeze-thaw residue caused by seasonal freeze-thaw cycles on the deformation of drainage channels, obtaining a drainage channel assessment information set; based on the drainage channel assessment information set, analyzing the critical state of dam abutment instability precursors characterized by abnormal channel deformation, executing multi-level collaborative early warning commands for dam safety, and outputting an intelligent early warning log of dam deformation. This improves the intelligence level and emergency response capability of dam safety management, effectively ensuring the long-term stable operation of the dam.

The present invention discloses a construction passage structure and a construction method for the bottom gallery of a large arch dam. The arch dam is provided with a grouting gallery at the bottom layer of the arch dam and a monitoring branch gallery connected to the grouting gallery. The construction passage extends from the end of the monitoring branch gallery towards the downstream dam surface of the arch dam to form a reserved gallery as the construction passage for the bottom gallery of the arch dam. Among them: the bottom plates at both ends of the reserved gallery are smoothly connected to the elevation of the monitoring branch gallery and the bottom plate of the outer water cushion pond on the dam surface; a composite rubber water stop is arranged downstream of the intersection of the reserved gallery and the monitoring branch gallery, and a wide flat copper water stop is arranged upstream near the downstream dam surface of the reserved gallery. The passage structure of the gallery in the present invention effectively forms a passage for the bottom grouting gallery during grouting, improving the construction efficiency of grouting; by adopting the construction passage set in the present invention, the cost is relatively low, the passage is formed relatively quickly, and it can be implemented and completed synchronously with the bottom grouting gallery and the monitoring branch gallery.

The application relates to a cleaning robot and a cleaning method suitable for various dams, belonging to the technical field of dam surface cleaning, and comprising a shell, a navigation assembly, a cleaning assembly, a sensor group and a pump group for providing suction power, wherein the navigation assembly comprises a posture adjusting water tank arranged in the shell, and direction water spraying devices are arranged in the circumferential direction and the axial direction of the shell; the cleaning assembly comprises cleaning water spraying devices arranged in the circumferential direction of the shell, and the cleaning water spraying devices are provided with water pipes; and the sensor group is arranged at the bottom of the shell. The application can be applied to the cleaning of the surface attachments of different dam types, such as face slab dams, gravity dams and arch dams, the landing posture and the moving direction of the robot are determined through the sensor group, the spatial posture of the robot is adjusted through the posture adjusting water tank, and the purposes of cleaning the dam surface, driving the robot to rotate and expanding the cleaning area are simultaneously achieved through the cleaning water spraying devices.

The invention relates to an arch dam foundation typical structural surface defect analysis processing method. The method comprises the following steps: obtaining structural surface information and load information of each structural surface in the river valley arch dam; dividing the structural plane according to the steep degree of the dip angle of the structural plane to obtain a steep dip angle set, a medium-low dip angle set and a low dip angle set; randomly combining the structural surfaces in the steep dip angle set, the medium-low dip angle set and the low dip angle set to obtain a plurality of groups; based on the structural surface information of each structural surface in the group, determining whether all the structural surfaces in the group can form a block body, and if the block body can be formed, determining the formed block body as a to-be-evaluated block body; calculating a stability index value of the to-be-evaluated block based on the structural surface information and the load information corresponding to the to-be-evaluated block; and under the condition that the stability index value does not meet a preset condition, determining the structural plane corresponding to the to-be-evaluated block as a risk structural plane. According to the scheme, the accuracy of analyzing and processing the typical structural plane defects of the arch dam foundation is improved.

The invention discloses an arch dam point cloud registration method based on deep learning and multi-target feature input, and the method comprises the steps: 1), carrying out the observation station arrangement of an arch dam, scanning the surface of the arch dam through a ground three-dimensional laser scanner, and obtaining the point cloud data of the arch dam; 2) constructing an improved point cloud segmentation neural network to obtain an arch dam point cloud segmentation result; 3) designing a feature extractor, and extracting contour features of each segmented component of the arch dam; and 4) designing a rigid transformation estimation network, and performing registration by taking each component of the arch dam and the rock mass contour as input data. According to the method, dam components are extracted through a PointNet + +-based point cloud segmentation network, and contour features are obtained by using a Transform frame and a clustering plane boundary extraction method according to the surface difference between a dam body and a rock mass in combination with arch dam environment features; and inputting the contour features as guide information into the registration network, optimizing 12-dimensional feature vectors by using an attention mechanism and an improved MLP, and finally constructing a rigid registration network to calculate a transformation matrix.