1569 results about "Topography" patented technology

The invention relates to the technical field of wind power prediction. The invention provides a wind power prediction method and system. The method comprises the following steps: acquiring multi-dimensional meteorological time series data, three-dimensional elevation data and unit operation data of a target wind power plant; constructing a spatial-temporal feature fusion network, extracting time sequence dynamic features, and performing weighted fusion on the spatial correlation features and the time sequence dynamic features to obtain a fusion feature vector; establishing a hybrid prediction model, and taking the fusion feature vector as input to obtain a wind power initial prediction result; introducing a terrain correction factor, constructing a turbulence intensity compensation function, and performing micro-terrain disturbance correction on the wind power initial prediction result; and outputting a final power prediction curve and a confidence interval. The problems that in an existing wind power prediction method, a physical model is insufficient in complex terrain microclimate modeling precision, high in calculation complexity and difficult to meet the real-time requirement, a statistical learning method is limited in high-dimensional nonlinear time sequence feature expression capacity, and prediction errors are remarkably increased under the abnormal working condition are solved.

The invention discloses a mine safety risk prevention and control method and system based on multi-source data fusion, and particularly relates to the technical field of mine safety monitoring, and the method comprises the steps: obtaining surface topography, an underground geologic structure and real-time monitoring parameters through remote sensing images, drilling data and dynamic monitoring equipment, and constructing a mining area geologic database with consistent time and space; fusing geologic feature data, integrating earth surface and underground feature data by using a three-dimensional geologic modeling technology, and mapping dynamic monitoring parameters into a model to generate a dynamic geologic feature field; performing clustering analysis on the abnormal feature points based on a spatial clustering algorithm, and calibrating a potential safety hazard region; calculating a regional risk comprehensive index by combining the risk values of the dynamic features, the geological features and the spatial features; early warning is triggered in a graded mode according to the comprehensive index, prevention and control measures are put forward, and the evaluation model is dynamically updated; comprehensive support is provided for mine potential safety hazard area monitoring and safety management decision making, and the method is suitable for risk management scenes of complex mining areas.

The invention relates to the technical field of flood early warning, and discloses an urban flood disaster early warning method and system based on artificial intelligence, and the method comprises the steps: collecting five types of information, i.e., meteorological perception, hydrological monitoring, geographic space, urban operation and social perception in real time, and obtaining multi-source data with precise space-time coordinates; through preprocessing, gridding space-time alignment and key feature screening, rainfall accumulation and confluence evolution related features are extracted; constructing a physically constrained space-time fusion deep learning model, and outputting a future ponding depth prediction result in combination with a multi-head attention mechanism; environmental changes such as urban terrains and drainage facilities are adapted through incremental updating and transfer learning; and fusing the ponding depth, the influence range and the regional vulnerability characteristics to generate multi-level early warning, and synchronously outputting a spatial distribution map, a time evolution trend and affected object evaluation information. According to the invention, urban flood control and disaster reduction decision making and public accurate risk avoiding can be effectively supported.

The invention provides a metal material defect identification and analysis method and system based on a multiple detection technology, and relates to the technical field of metal defect detection, and the method comprehensively utilizes microscope detection and ultrasonic detection technologies to obtain surface topography data and internal structure data of a target metal material. And performing feature alignment and fusion processing on the two types of data through a multi-grid method to generate a unified feature distribution model, and establishing a mathematical solution model of ultrasonic wave field propagation based on the model. And determining the position, shape and size information of the potential defect by using the solved data, and generating defect positioning data containing three-dimensional coordinates and contour features. And extracting key defect information in combination with an edge detection algorithm, judging defect types by adopting a classification algorithm, and generating a detection result. According to the method, the problems of insufficient detection precision, high data fusion difficulty and low classification efficiency in the prior art are solved, and the applicability and reliability of a defect detection technology are improved.

The invention relates to the technical field of aircraft structure detection, and discloses an aircraft structure crack intelligent identification method based on deep learning. The method comprises the following steps: acquiring original vibration response signals and electromagnetic field distribution data on the surface and inside of an aircraft structure in parallel through a multi-source sensor network; synchronously processing the data by using a multi-scale convolutional neural network, and extracting time-frequency domain abnormal fluctuation features and space magnetic field distortion features; constructing a cross-modal correlation model, analyzing a topological dependency relationship of the two types of features through a graph attention mechanism, and generating a fused damage sensitive feature vector; inputting the vector into a pre-trained deep belief network to obtain a probability distribution mapping relation for different crack types; and according to the mapping relation, carrying out adaptive weighted fusion on original multi-sensor data, inhibiting environmental noise and structural background interference, and separating and reconstructing an accurate three-dimensional morphology map of the target crack. According to the method, multi-source data information can be effectively fused to improve the accuracy of aircraft structure crack identification.

The invention provides a photovoltaic power station operation state monitoring method based on unmanned aerial vehicle inspection, and the method comprises the steps: carrying out the surveying and mapping of the geographic position, landform and photovoltaic array layout of a photovoltaic power station through employing a surveying and mapping technology and a geographic information system, so as to build a digital photovoltaic power station model; acquiring technical parameters of each component of the photovoltaic power station, and mapping the technical parameters to the digital photovoltaic power station model; based on a preset inspection plan and the digital photovoltaic power station model, automatically generating an unmanned aerial vehicle inspection path; obtaining monitoring data obtained by the unmanned aerial vehicle according to the unmanned aerial vehicle inspection path, wherein the monitoring data comprises an appearance image of a photovoltaic array, temperature distribution of a photovoltaic module and illumination intensity data of different areas of a photovoltaic power station; vectorizing the monitoring data to obtain an input vector; and the operation state monitoring model performs feature extraction on the input vector so as to analyze the operation state of the photovoltaic power station.

The invention discloses a zinc coating shedding performance detection method and system, particularly relates to the technical field of metal surface treatment quality detection, and is used for solving the problems of high misjudgment rate and insufficient detection precision caused by coating surface pseudo defect interference in the existing method. The method comprises the following steps: synchronously acquiring a multispectral reflection image and three-dimensional morphology data of the surface of a zinc coating through an industrial vision imaging device, extracting grain boundary distribution information based on multispectral data, and identifying radial pseudo defects in combination with a curvature manifold geodesic line energy gradient direction of the three-dimensional morphology; and further performing micro-crack topology analysis and grain boundary spatial correlation verification on the candidate region, eliminating texture interference and grain boundary overlapping regions, and finally outputting a high-confidence fall-off defect detection result, so that the identification capability of real defects under a complex galvanized surface is remarkably improved, and the method is suitable for automatic detection requirements of a high-speed continuous production line.

The invention discloses an end-to-end underwater three-dimensional reconstruction method and system based on an underwater imaging model, and belongs to the technical field of underwater image processing. According to the method, deep learning pose estimation is combined with an underwater imaging model; firstly, a multi-frame underwater image sequence is collected as input, a deep neural network is constructed, and the network mainly comprises two core sub-modules: a pose estimation network; secondly, a three-dimensional reconstruction network is adopted, dense point cloud or voxel reconstruction is completed according to the predicted pose and image content, pose estimation and the three-dimensional reconstruction process are integrated in the same system, and overall joint optimization is achieved; and in combination with a self-adaptive underwater imaging model, modeling is performed on physical processes such as underwater illumination attenuation and scattering, so that the reality sense and the accuracy of a reconstruction result are improved. According to the method, high-quality three-dimensional reconstruction of images in a complex underwater environment is realized, and the method can be widely applied to ocean engineering, underwater robots, submarine topography surveying and mapping and underwater cultural relic protection.

The invention discloses a road slope modeling method based on an unmanned aerial vehicle inspection route, and relates to the technical field of unmanned aerial vehicle inspection. The method comprises the following steps: measuring the road slope length, the landform and the geological complexity, and selecting an adaptive unmanned aerial vehicle type and sensor combination according to the road slope length, the landform and the geological complexity; planning unmanned aerial vehicle surface inspection and shallow geological exploration routes, ensuring space matching, and synchronously obtaining high-resolution images and ground penetrating radar data; and processing image data through a photogrammetry technology, generating a digital elevation model and an orthophoto map, and combining to construct a three-dimensional model of the earth surface. Geophysical inversion is carried out on the ground penetrating radar data, reflection features are extracted and projected to the ground surface three-dimensional model, and space correlation between the ground surface and a shallow layer structure is established; the reflection features are digitalized and geometrically reconstructed into three-dimensional surface elements, the three-dimensional surface elements are embedded into an earth surface model to form a three-dimensional geologic body model, time dimensions are introduced, and a dynamic evolution model is constructed. According to the dynamic evolution model, the dynamic analysis of the slope stability is realized.

The invention provides a part surface efficient three-dimensional reconstruction method based on adaptive octree sampling, and belongs to the field of surface reconstruction. The part surface efficient three-dimensional reconstruction method based on self-adaptive octree sampling comprises the following steps of performing multi-stage filtering and denoising on collected point cloud data; octree nodes are adaptively divided according to local point cloud density and curvature features, the curvature of each node is calculated, feature region marking is carried out, voxel downsampling processing is carried out on non-feature regions, curvature weighted random sampling processing is carried out on feature regions (such as cracks and recesses), and high resolution of the regions is reserved; a multi-resolution space grid is generated based on octree hierarchy, a hierarchical symbol distance field is constructed, and the Poisson surface reconstruction process is accelerated. The method can be used in the fields of surface topography analysis, process optimization, quality control and the like, is particularly suitable for scenes requiring efficient and accurate surface topography detection, and has a wide application prospect.

The invention discloses a lake terrain prediction method based on machine learning fused multi-source satellite data, and relates to the technical field of machine learning, and the method comprises the steps: extracting the optical features of a target lake from an optical satellite image; extracting water features of each water body pixel in the target lake from the SWOT satellite data; performing space-time alignment and fusion on the optical features and the water features to obtain a fusion feature vector; the actually measured water depth point of the real water depth is matched to the geographic position of the corresponding pixel, and then the real water depth and the fusion feature vector of the corresponding pixel form a training sample; selecting a machine learning model and initializing the structure or parameters of the machine learning model; training the initialized machine learning model by using the training sample; utilizing the trained machine learning model to predict the water depth value of the corresponding pixel according to the fusion characteristic vector of each water body pixel; and determining the terrain of the target lake according to each water depth value. According to the method, the terrain of a large-scale lake can be efficiently predicted at low cost.

The invention discloses a storm surge water increase prediction method and device, electronic equipment and a storage medium, and relates to the technical field of seawater monitoring, and the method comprises the steps: obtaining multi-source observation data of a target sea area, the multi-source observation data comprising satellite remote sensing data, near-shore monitoring data, meteorological mode data and drainage basin data; performing space-time alignment and exception processing on the multi-source observation data to generate standardized space-time grid data; performing hybrid prediction modeling on the standardized space-time grid data through a physical data dual-drive modeling layer to obtain a target probability water increasing field; and dynamically correcting the target probability water increasing field by using real-time observation data to obtain a storm surge water increasing predicted value. A physical mechanism model and a probability generation model are combined, limitation of a single model is overcome, and the nonlinear evolution process of the storm surge is effectively captured; the time-space dual-drive architecture is adapted to complex coast terrains and changeable meteorological conditions, and the risk of missing report or false report is reduced.

The invention discloses an additive manufacturing parameter optimization method using machine learning. The method comprises the following steps: acquiring a first cladding layer surface topography constructed by powder layers with different powder characteristics under different powder laying parameters, and establishing a first database at least mapping a relationship among the powder laying parameters, the powder characteristics and the first cladding layer surface topography; and according to the first database, a first machine learning model is constructed and trained to generate a first application model used for powder laying parameter prediction, and then the first application model is used for predicting input powder characteristics to output optimal powder laying parameters used for additive manufacturing so as to optimize the additive manufacturing quality.

The invention relates to the technical field of three-dimensional reconstruction, in particular to a three-dimensional reconstruction method for the peripheral topography and landform of an electric power facility based on a three-dimensional laser point cloud. The method comprises the following steps: performing electric flight laser scanning on the periphery of an electric power facility through an unmanned aerial vehicle, and synchronously collecting near-field point clouds around the electric power facility for space-time synchronous registration and morphological filtering denoising to obtain preprocessed three-dimensional point cloud data around the electric power facility; obtaining a point cloud geometric feature set corresponding to the periphery of the electric power facility through the electric power facility periphery preprocessing three-dimensional point cloud data, and performing electric power facility ground feature point classification and surface triangulation network dense and uniform reconstruction to generate an electric power facility periphery topography three-dimensional initial model; and performing reconstruction smoothing and triangular mesh simplification processing on the three-dimensional initial model of the topography and the landform around the electric power facility to obtain a three-dimensional optimization model of the topography and the landform around the electric power facility. According to the invention, the high-precision three-dimensional reconstruction process of the electric power facility and the surrounding landform thereof can be realized.

The invention discloses a visual precise plastic mold surface milling system and method, and the method comprises the steps: obtaining and analyzing the surface topography data of a milling region and a tool displacement track in real time through an optical sensor, and extracting wear-related micro-deformation features through multi-band filtering processing; generating a deviation vector matrix through three-dimensional mapping of the deviation vector matrix and a reference curved surface, and realizing dynamic calculation and path correction of the cutter offset; the high efficiency and stability of the compensation cutting process are ensured by combining the self-adaptive adjustment of the rotating speed and the feeding rate of the main shaft; meanwhile, the compensation effect is projected to a visual interface in real time to form a comparison layer, hardware acceleration is started to maintain the system response speed when the frame rate fluctuates, and finally the material removal volume is evaluated according to the deviation vector matrix to intelligently control the machining cycle termination time. Therefore, the problem of microtopography deviation caused by tool abrasion in the milling process of the complex curved surface mold is effectively solved, and the machining precision and efficiency as well as the robustness and the automation level of the system are remarkably improved.

The invention relates to the field of weather forecasting, and discloses a marine meteorological coupling refined forecasting method and system, which are used for improving the precision and reliability of marine meteorological coupling forecasting. Comprising the following steps: based on a non-exchangeable geometric vortex equation and an external differential form, constructing a conservation manifold dynamic field in combination with submarine topography data, and realizing strict conservation of mass flux under a complex terrain; an additional pressure item caused by vacuum fluctuation is quantified, and an interface energy field of quantum correction is generated; the recognition precision of the mesoscale vortex and the frontal surface structure is improved; a spectral element method and lattice Boltzmann method mixed solver is combined, and high-precision coupling of ocean vertical layering and the atmospheric process is achieved. According to the method, the defects of conservation, interface energy transmission, initial field non-physics and grid adaptive capacity of a traditional method are overcome, refined forecasting of 72-hour typhoon paths, ocean frontal surfaces and energy flux is supported, and key technical support is provided for extreme weather early warning and climate change research.

The invention discloses an irregular particle three-dimensional shape measurement device and method based on speckle imaging, and belongs to the field of irregular particle three-dimensional shape measurement, and the irregular particle three-dimensional shape measurement device comprises an irregular particle shakeout device which is used for enabling irregular particles to fall in a sparse free falling body form, and is used for forming lamellar laser vertical to the falling direction of the irregular particles, the laser sheet generating module is used for forming complete speckle distribution on the surfaces of the irregular particles; the laser sheet generating module is used for generating a laser sheet, the multi-view image collecting module is used for collecting speckle distribution on the surfaces of irregular particles in a multi-view mode and forming speckle images, the synchronous control system is used for controlling the laser sheet generating module and the multi-view image collecting module and synchronizing the time of the laser sheet generating module and the multi-view image collecting module, and the three-dimensional reconstruction processing unit is used for obtaining three-dimensional shape data of the irregular particles according to the speckle images. According to the invention, the irregular particles can be rapidly, non-destructively and in-situ measured so as to meet the requirements of aeroengine erosion research on the precision, efficiency and integrity of irregular particle data.

The invention relates to the technical field of electric power management and control, and discloses an electric power BIM type data GIS discount classification method and system, and the method comprises the following steps: 1, constructing an electric power industry exclusive classification system and semantic mapping, and building a three-stage classification frame based on a GIS and an electric power industry standard; 2, unifying a space coordinate reference and a topological relation, and verifying topological consistency between components and between the components and topography and roads through a GIS (Geographic Information System) tool; 3, multi-scale classification and dynamic LOD model generation are carried out, and LOD model details are automatically switched according to a GIS scale; 4, performing data format conversion and intelligent lightweight processing, performing lossless compression on key components, and performing simplified compression on secondary components; and step 5, performing classification verification and dynamic updating mechanism, and comparing whether BIM and GIS base map position classification is correct or not, thereby realizing data synchronization. According to a dynamic classification framework and an intelligent lightweight strategy in the power industry, the BIM model efficiently adapts to the spatial analysis requirement of the GIS, and the data fusion and application efficiency is improved.

The invention relates to the technical field of remote sensing landform enhancement, and discloses a remote sensing landform enhancement algorithm, which comprises the following steps of: S101, preprocessing an existing high-resolution DEM (Digital Elevation Model) image and an existing low-resolution DEM image to construct a training data set; step S102, constructing a double-domain multi-scale attention fusion super-resolution network; step S103, training the double-domain multi-scale attention fusion super-resolution network through the training data set; according to the method, the edge information and spatial continuity characteristics of the DEM image are comprehensively considered, the high-frequency and low-frequency information of the DEM image is extracted through Haar wavelet transform by utilizing the characteristic that a wavelet domain is highly sensitive to the high-frequency and low-frequency information, and spatial domain feature information obtained by a parallel branch convolutional layer is combined, so that the high-frequency and low-frequency information of the DEM image is obtained. Through fusion of the two, the network has a feature enhancement function in a shallow layer, and meanwhile, the importance relationship between different depth feature maps is obtained through the multi-scale attention fusion module group, so that the precision of DEM super-resolution reconstruction is improved.

The invention relates to a method and system for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microscopic interference, and belongs to the field of precision measurement, and the method comprises the steps: firstly, measuring a sample, scanning the surface of the sample, and synchronously collecting a white light interference image sequence containing surface contour information; adopting a bicubic interpolation algorithm to carry out interpolation processing on the acquired white light interferogram group, and constructing a high-resolution interference image sequence; analyzing the time-frequency domain interference signal through fast Fourier transform, effectively inhibiting noise interference in combination with a filtering technology, and accurately extracting an envelope curve of the interference signal; and carrying out Gaussian fitting on the envelope peak by adopting a least square method and positioning a peak value coordinate, and finally reconstructing a high-precision three-dimensional surface topography. According to the method, through advantage complementation of the bicubic interpolation algorithm and the fast Fourier transform method, the transverse resolution is remarkably improved while the longitudinal resolution is kept, and an effective technical means is provided for accurate characterization of the three-dimensional morphology of the metal hydrophobic surface structure.

The invention discloses a riverway longitudinal section determination method based on a riverway section terrain and related equipment. The method comprises the following steps: acquiring main groove section data of a plurality of sections in a target river reach, wherein the main groove section data comprises a main groove section area of each section under a corresponding section flat beach water level; for each section, a target water level value is determined from a plurality of preset water level values larger than the thalweg point elevation of the section, the channel range interval where the thalweg point of the section under the target water level value is located is a target interval, and the channel section area in the target interval is larger than or equal to the product of the main channel section area and a preset proportion value; taking the target water level value as the deep groove elevation of the corresponding section; and determining the longitudinal section of the river channel of the target river reach by utilizing the deep groove elevations of the multiple sections in the target river reach. Sawteeth in the longitudinal section of the riverway can be reduced, so that the longitudinal adjustment rule of the riverway can be accurately identified, and the level requirement on related technicians is reduced.

The invention provides a large-scale water body underwater terrain inversion method and device and a medium, and the method comprises the steps: carrying out the partitioning of a to-be-inverted water body region, and obtaining a deep water region and a land-water conversion shallow water region; based on a spatial interpolation method, carrying out inversion on the land-water transformation shallow water area to obtain a land-water transformation shallow water area topographic image; a deepwater area water depth inversion model constructed based on the wave band reflectivity information and the underwater topographic elevation data performs inversion on the deepwater area to obtain a deepwater area underwater topographic image; and carrying out image splicing fusion on the land and water transformation shallow water region topographic image and the deep water region underwater topographic image to obtain the underwater topography of the water body to be inverted. In the face of a complex and changeable water body environment, a water body area to be inverted is divided into a deep water area and a land and water conversion shallow water area, and different and more targeted inversion methods can be adopted according to the characteristics of water bodies in different areas.

The invention discloses a marine surveying and mapping system based on deepwater exploration robot intelligent navigation, and belongs to the technical field of marine surveying and mapping. Comprising a data acquisition module for synchronously acquiring navigation positioning data and submarine topography data through multi-source navigation equipment carried by a deepwater detection robot and submarine measurement equipment; the navigation fusion module is used for realizing self-adaptive fusion of multi-source data and outputting initial pose estimation; the quality control module is used for carrying out quality evaluation and abnormity identification on the real-time surveying and mapping data; the path planning module is used for planning an optimal surveying and mapping path in real time and carrying out online adjustment according to the re-measurement requirement of the quality control module; the fault-tolerant control module is used for realizing multi-level navigation source fault diagnosis, starting a degraded navigation strategy when navigation is abnormal or fails, and ensuring that basic navigation and surveying and mapping functions can still be maintained; and the topographic surveying and mapping module is used for compensating and splicing submarine topographic data in real time by using the pose information provided by the navigation fusion module.

The invention provides a precision injection mold data monitoring system, and relates to the technical field of data processing, and the system comprises a monitoring point positioning module which is used for setting a casting region monitoring point in an annular region with the radius of 5mm at the casting tail end of a mold, setting an ejection contact monitoring point in a circular region with the center diameter of 10mm of the contact surface of an ejection part, surface topography images of the area monitoring points and the ejection contact monitoring points are collected through an industrial camera, and contact pressure gradient data and high-frequency vibration energy signals are obtained. According to the method, the mold state is cooperatively analyzed, intelligent monitoring of the mold state and precision of maintenance decision are achieved, and the precision and efficiency of injection molding production and the mold life cycle management level are improved.

The invention relates to the technical field of ocean engineering construction, and discloses a construction positioning and SCADA visualization integrated intelligent arrangement method for an arrangement ship, which comprises the following steps: synchronously acquiring coordinates and attitude parameters of the arrangement ship through a Beidou positioning terminal and an inertial navigation device, and constructing a three-dimensional digital twinborn model of a construction scene in combination with submarine topography surveying and mapping data; analyzing boundary and gradient characteristics of the target arrangement area based on the model, and generating an initial arrangement path planning scheme; position deviation and ocean current flow velocity data are monitored in real time in the operation process, and the laying path is dynamically adjusted; and the position of the laying ship, the path adjustment record and the submarine topography change are displayed in real time through a visual interface of the SCADA system. According to the method, high-precision positioning, dynamic path optimization and full-process three-dimensional visual monitoring of the laying operation are realized, the problems of large positioning deviation and response lag of a traditional method are solved, and the construction precision and efficiency are remarkably improved.

The invention relates to the technical field of photovoltaic power prediction, in particular to a photovoltaic power station cluster power prediction method and system based on multi-task learning, and the method comprises the following steps: obtaining the three-dimensional position and shielding characteristics of a power station, constructing a sun incidence vector, recognizing the array shielding relation and space illumination distribution, and extracting the wind speed disturbance characteristics. And deducing a propagation path and a response time sequence, and executing multi-task prediction dynamic adjustment output. According to the method, a three-dimensional space shielding relation is established by combining topographic features and a solar radiation path, space shielding characteristics are measured and calculated through an earth surface inclination angle, an orientation angle and a shielding angle, the influence of the topography on illumination distribution is effectively captured, the interference of landform differences on photovoltaic output is reflected, and meteorological and space cooperation features are fused; the prediction precision is improved, non-linear errors caused by terrain and space distribution are considered, the adaptive capacity of power prediction to dynamic disturbance is enhanced, and steady-state operation guarantee of a photovoltaic power station cluster under the complex terrain condition is achieved.

The invention discloses a surface topography modeling method and particularly provides a roughness calculation formula based on Fourier series and polynomial combination, Fourier series can effectively describe periodic roughness features of a surface, a polynomial function can describe an overall deformation trend of the surface, the advantages of the Fourier series and the polynomial function are combined, and the surface topography modeling method has the advantages that the surface topography modeling efficiency is improved. The method can accurately simulate the random roughness and overall deformation characteristics of material corrosion, terrain, sea wave plane and other phenomena, and avoids the problem that the traditional surface topography modeling method is difficult to accurately describe the randomness and nonlinear characteristics of a complex surface based on simple statistical model or experimental data fitting. According to the method, the morphological characteristics of phenomena such as material corrosion, topography and sea wave planes can be simulated more accurately, and technical support is provided for analysis and prediction in related fields.

The invention discloses a multi-field sensing fusion deep sea geological environment dynamic monitoring system and an application method. The system comprises a buoy measuring platform, a multi-beam sounding system, a high-precision marine gravimeter, an external camera, a GPS, a data acquisition and transmission control unit and a power supply system. By designing a modularized and integrated multi-sensor buoy platform, various sensors are fused and integrated. A plurality of sensors are connected to the data acquisition control terminal, the steps of sensor calibration, data synchronization and clock calibration, correction and compensation, data acquisition, real-time processing, fine post-processing, data transmission and the like are completed, and multi-sensor collaborative operation is realized, so that submarine topography and ocean gravity data of a deep sea ditch area are synchronously acquired in real time; and thus, diving erosion information experienced by the area can be accurately monitored. The method can provide important support for submarine topography and landform detection and application and marine geographic information system construction, and has application value in the aspects of geological disaster early warning, resource development and the like.

The invention discloses a self-adaptive gait control method, system and device for a quadruped robot in a limited space and a medium, and belongs to the technical field of gait control. Identifying terrain categories through a classifier and acquiring initial gait parameters from a gait library; adjusting the gait parameters according to the terrain gradient and the roughness to obtain optimized gait parameters; calculating stability indexes and fusing scores; when the score is lower than a threshold value, an adjustment strategy is determined according to an instability mode to correct gait parameters; a foot end track is generated and control is executed; and the executed information is fed back to terrain perception to form a closed loop. According to the method, the terrain recognition accuracy is improved through multi-modal information fusion, the adaptive mapping from the terrain to the gait is established to achieve automatic gait switching and parameter optimization, the stability is evaluated through multi-index fusion, a targeted adjustment strategy is selected according to an instability mode, the adaptive gait control problem under the limited space and the complex terrain is solved, and the adaptive gait recognition accuracy is improved. And the movement efficiency and the stability are improved.

The invention relates to the technical field of marine surveying and mapping and submarine topography modeling, and discloses a submarine topography and landform construction method based on multi-source water depth data fusion, which comprises a multi-source data acquisition module, a data preprocessing module, a feature extraction module, a fusion algorithm matching module, a three-dimensional modeling module and an uncertainty evaluation module. A historical submarine topographic map is converted into grid data, namely, submarine topography is discretized into digital representation of regular grid units, water depths of other sources are converted into the grid data, the precision of the water depths of different sources is evaluated by adopting a superposition comparison method, and an error distribution model is established to reasonably correct and fuse the water depth data of various sources. The innovation of the method lies in that topographic feature parameters including the gradient, the curvature matrix and the bionic optimization algorithm are introduced, the defect that a single algorithm is preset in a traditional method is overcome, and the precision of coral reef and fault zone complex areas is improved.