1861 results about "Underwater" patented technology

The invention provides an underwater target identification method and system based on multi-source sensor data fusion. The method comprises the following steps: firstly, synchronously acquiring an original sound wave reflection signal and original optical image data of a target underwater area, then carrying out acoustic compensation processing on the original sound wave reflection signal to generate a target sound wave reflection signal, and meanwhile, carrying out optical compensation processing on the original optical image data to generate target optical image data; performing dynamic weighted fusion on the reliability measurement of the target sound wave reflection signal and the reliability measurement of the target optical image data through an adaptive fusion module to generate an enhanced multi-modal data set; and finally identifying the specific category of the underwater target through a multi-modal feature matching and decision-making mechanism. According to the technical scheme provided by the invention, the limitation of a single sensing mode is overcome, the quality of collected information is improved, the direct confirmation efficiency of common target recognition is also improved, and high accuracy and data reliability of target category recognition in a complex scene are ensured.

A system for three-dimensional spatial perception underwater that includes a primary submersible vehicle. Frontward facing projectors are used to scan beams of light across a selected field of underwater view. Further, event cameras with pixels triggered by events are used to detect corresponding spots of the scanned beams that are reflected from underwater objects or surfaces. Circuitry is configured to determine positions of the objects based on the pixels that are triggered. Additionally, pilot submersible vehicles the projectors and event cameras are tethered to the primary submersible vehicle to provide extend detection of spots corresponding to reflections from underwater objects or surfaces.

A method for simultaneous localization and mapping underwater. A robot is equipped with an IMU inertial unit and a sonar unit. When the robot submerges underwater, a buoy connected to the robot floats on the water surface, and the buoy moves in coordination with the movement of the robot. The position and observed velocity of the buoy are obtained by a shore-based lidar. During motion estimation in a SLAM algorithm, when an angular velocity is below a preset angular velocity threshold, the observed velocity of the buoy is decomposed into x-axis velocity and y-axis velocity, and updated as the two-dimensional operating velocity of the robot. The polar coordinates of an obstacle in a map under the coordinate system of the robot are associated with the polar coordinates of sonar data of a current frame by using the Mahalanobis distance. The polar coordinates of a new obstacle are converted to the world coordinate system and added to the map. The present invention has the advantages of not relying on underwater visibility, not requiring pre-installed devices, and possessing good generalization and stability.

The invention relates to the technical field of data processing, and discloses an intelligent monitoring method and system for cyanobacterial bloom outbreak. The method comprises the following steps: collecting a water surface spectrum and underwater particle size data, carrying out atmospheric correction, calculating a normalized algae index and a blue-green wave band ratio, inputting the normalized algae index and the blue-green wave band ratio into a U-Net network to obtain a water bloom coverage area, carrying out integral interpolation on the particle size data to obtain a vertical section distribution curve, and calculating a surface layer enrichment degree and a floating trend index, and establishing a water surface-underwater association relationship through random forest regression training, and inputting the multi-dimensional features into a CNN-LSTM model to predict a water bloom outbreak probability and determine an early warning level. According to the method, the problem that the cyanobacterial bloom three-dimensional structure cannot be comprehensively described due to the lack of effective fusion of the water surface spectral data and the underwater vertical section data is solved, the problem that the early warning timeliness of cyanobacterial bloom outbreak is insufficient due to the lack of a multi-source data time sequence analysis model is solved, and the spatial integrity and early warning advance of cyanobacterial bloom monitoring are improved.

The invention relates to the technical field of underwater detection, and discloses an underwater comprehensive detection system. The system collects multi-dimensional acoustic data including sound wave reflection intensity, propagation time delay and frequency dispersion characteristics of a target water area through an underwater sonar array; dividing the detection area into a plurality of layered units according to a water attenuation coefficient and a substrate reflection characteristic of the acoustic data, and extracting an environment intrinsic parameter of each layered unit; constructing an acoustic propagation path model based on the environmental intrinsic parameters, and generating adaptive filtering parameters in combination with a preset noise suppression strategy; calling sonar array hardware configuration data, matching filtering parameters with an array beam forming mode, and calculating a detection sensitivity threshold value of each layered unit; and integrating the sensitivity threshold and the acoustic data, generating a three-dimensional acoustic characteristic spectrum of the target water area, and marking the space coordinates and confidence level of the abnormal area. The system can improve the comprehensiveness and accuracy of underwater detection, and meets the requirement of high-precision detection.

The invention discloses a special-shaped steel pipe concrete pipe section hoisting dynamic pose control method, relates to the technical field of ocean engineering underwater pipeline installation, and mainly solves the problems of insufficient dynamic response and low space pose control precision when a special-shaped pipe section is hoisted in a complex water flow environment. The method comprises the steps that pipe section space pose design parameters are obtained, the pitch angle and the rolling angle of a pipe section are monitored in real time through an inclination angle sensor set, disturbance torque generated by real-time water flow force is calculated, sling length compensation amount is generated, and the take-up and pay-off speed of a chain block at each lifting point is independently adjusted; and meanwhile, adjusting mooring ropes moored on the two sides are pulled to control the horizontal rotation angle of the pipe section, the height of a lifting hook and tension of the mooring ropes are fed back and adjusted in cooperation with a floating crane positioning system, and finally accurate underwater in-position of the pipe section to the preset position of the seabed is achieved. The device is mainly used for hoisting and sinking operation of the special-shaped concrete filled steel tube section in the marine environment, water flow interference can be effectively resisted, and accurate butt joint and installation quality of a pipe section connector are guaranteed.

The invention discloses a semi-supervised underwater image enhancement system and method based on wavelet transform and a diffusion model. The semi-supervised underwater image enhancement system comprises an image decomposition module used for obtaining a low-frequency component and a high-frequency component of an image to be enhanced by using discrete wavelet transform; the low-frequency diffusion module is used for gradually and sequentially denoising the randomly generated pure noise image by using a trained neural network model in a semi-supervised underwater enhanced image model through taking the low-frequency component as condition guidance to obtain an enhanced low-frequency component; the high-frequency repairing module is used for obtaining an optimized high-frequency component; and the inverse discrete wavelet transform module is used for fusing the optimized high-frequency component and the enhanced low-frequency component through inverse discrete wavelet transform to obtain a reconstructed enhanced image. According to the method, the wavelet transform is fused into the diffusion model, and the image enhancement process is optimized by utilizing the semi-supervised learning model and cooperatively utilizing the annotated data and the annotated data, so that the problem that the data scale is limited is solved, and the calculation efficiency in the image enhancement process is improved.

The invention relates to the technical field of underwater desilting robot cruise control, in particular to an underwater desilting robot intelligent cruise control method based on environmental perception, and the method comprises the steps: determining a track deviation distance by measuring the position distance of an underwater desilting robot between each moment and all moments within a preset duration before; and determining a second gain adjustment coefficient based on the variation trend of the track deviation distance at all moments within a preset time period before the current moment, and determining a gain adjustment coefficient in combination with the first gain adjustment coefficient so as to optimize the gain coefficient of the sliding mode controller and control the attitude of the underwater dredging robot. According to the method, the problem of hysteresis course errors of the underwater dredging robot caused by fixed gain in traditional sliding mode control is solved, gain adaptive optimization is realized by dynamically fusing multi-source trend data, and the dredging efficiency of the underwater dredging robot is improved.

The invention discloses a deep sea underwater integrated electro-hydraulic actuator system adopting pump and valve combination. The deep sea underwater integrated electro-hydraulic actuator system comprises a hydraulic cylinder, a pump control assembly and a valve control assembly. The pump control assembly comprises a metering pump, a first switch valve and a second switch valve; the valve control assembly comprises a large-flow proportional valve, a small-flow proportional valve, a deep sea compensation energy accumulator and a third switch valve. The metering pump, the first switch valve and a rod cavity of the hydraulic cylinder are sequentially connected through a pipeline, the metering pump, the second switch valve and a rodless cavity of the hydraulic cylinder are sequentially connected through a pipeline, the metering pump, the third switch valve and the deep sea compensation energy accumulator are sequentially connected through a pipeline, and the rodless cavity of the hydraulic cylinder is connected with the large-flow proportional valve and the small-flow proportional valve through pipelines. Two control modes of the actuator can be completed, large-flow control is achieved through the pump control assembly, high efficiency and energy conservation are achieved, flow needed by maintenance is supplied to a rodless cavity of the actuator through the valve control assembly via the large-flow proportional valve and the small-flow proportional valve, and posture keeping and emergency action are achieved.

The invention relates to the technical field of data processing, and provides a resistance line-associated underwater bench blasting numerical simulation error correction method, which is characterized in that land and underwater measured data are matched through the same resistance line and similar material parameters, and the resistance line and the water depth are used as basic input of an error prediction model; a reference basis is provided for error correction of subsequent numerical simulation; calculating a target result in combination with a prediction error after initial simulation, comparing a simulation result with the target result during iterative simulation to generate an iterative error, and analyzing and determining sensitivity coefficients of different error classifications in a resistance line and the iterative error so as to adjust material parameters to reduce an invalid iterative process; simulation results are processed according to stress areas in a zoning mode through an equidistant slicing method, adjustment precision is verified in combination with the root rate and the damage area, and the reliability of the simulation results is improved; and meanwhile, parameter data passing verification are input into a back propagation neural network, a correction parameter mapping library is constructed, and the design efficiency of an underwater blasting scheme is improved.

The invention discloses an underwater delta erosion and deposition evolution analysis method based on water depth data, and relates to the technical field of ocean engineering, the underwater delta erosion and deposition evolution analysis method comprises the following steps: collecting section actually measured water depth data, remote sensing data and hydrological data over the years of an underwater delta in a research area, and preprocessing to unify a coordinate system and an elevation datum; and establishing a water depth database of the underwater delta of the crossheading petals by utilizing the preprocessed actually measured water depth data, and covering all stages of the construction period and the discarding period. According to the method, multi-temporal remote sensing data and section actually-measured water depth data over the years are integrated, a space-time continuous database covering the whole period from the construction period to the discarding period is constructed, seven-parameter coordinate conversion and the Kriging interpolation technology are combined, a data missing area is effectively filled up, a continuous water depth surface with the spatial resolution smaller than or equal to 50 m is generated, and the method is suitable for large-scale popularization and application. Dynamic monitoring limitation caused by data faults in traditional research is broken through, erosion and deposition evolution analysis is changed from fragmented observation to systematic tracking, and data support is provided for accurate evaluation of seabed stability.

The invention discloses a light-moisture dual-curing underwater epoxy coating with a self-repairing function as well as a preparation method and a construction method of the light-moisture dual-curing underwater epoxy coating. The epoxy coating comprises a component A and a component B, wherein the mass ratio of the component A to the component B is (1.5-3.5): 1; the component A is prepared from the following raw materials: bisphenol F type epoxy resin, dynamic disulfide bond modified polysulfide rubber, boron nitride nanosheet and silicon carbide nanowire hybrid filler, a photoinitiator and a silane coupling agent; the component B is prepared from the following raw materials: moisture-cured polyether amine, a boric acid ester bond cross-linking agent and hydrophobic modified graphene oxide. According to the invention, a light-moisture dual-curing mechanism is adopted, ultraviolet irradiation initiates rapid surface curing, and then environmental moisture permeates to complete deep curing. The material provided by the invention has the advantages of rapid curing, excellent self-repairing function, significantly improved underwater adhesion and good thermal conductivity, and provides a new solution for rapid repairing and long-acting protection of underwater structures.

The invention relates to the technical field of wireless charging, in particular to an underwater magnetic coupling resonant wireless power transmission voltage stabilization control system and method, and the system comprises a transmitting end which comprises a power supply, an inverter circuit, a transmitting end compensation network and an array type orthogonal magnetic coupling device, and the array type orthogonal magnetic coupling device comprises four DD type coils, the DD type coils are alternately wound to generate a horizontal magnetic field and a vertical magnetic field; the receiving end comprises a biorthogonal coil, a receiving end compensation network, a rectification filtering module and a converter; the biorthogonal coil receives energy of the horizontal magnetic field and the vertical magnetic field; the linear active disturbance rejection control module comprises an extended state observer and a linear feedback control rate, the extended state observer is used for estimating the total disturbance of the system in real time and performing feed-forward compensation, and the linear feedback control rate realizes voltage stabilization by adjusting the duty ratio of the converter. The system adapts to a deep sea complex environment, and the cruising ability of the AUV is improved.

The invention relates to the technical field of image processing, in particular to an underwater crack segmentation-oriented color correction and texture sharpening double-branch enhancement system, which is characterized in that a data set is used for training, reasoning and analysis, and underwater crack images are stored in the data set; the system comprises an input unit used for receiving an underwater crack image; the color correction network is used for carrying out color correction on the underwater crack image and eliminating the problems of color deviation and low contrast of an underwater environment; the texture enhancement network is used for performing texture enhancement on the image after color correction; and the output unit is used for outputting the image enhanced by the texture enhancement network, and aims to recover the color and texture features of the underwater crack image through the color correction network and the texture enhancement network so as to enhance the perceptibility of the semantic segmentation model to the underwater crack.

The application discloses an underwater data center, which comprises a pressure cabin, an outer frame, a lifting structure, a pipeline structure, a server cabinet inside the pressure shell, an inspection lifting structure, a fixing and moving mechanism, and an internal state monitoring system; the pressure cabin is a closed structure formed by the pressure shell, and at least one pressure cabin entrance structure is arranged on the surface of the pressure cabin; the lifting structure comprises a hydraulic jacking oil cylinder and a lifting guide column; the server cabinet is arranged in an array in the pressure shell, and is fixed and moved by the fixing and moving mechanism at the upper end and the lower end for control. The application can realize efficient water-out and water-in actions by using the lifting mechanism; the application is suitable for high-stable underwater cooling of a large-volume high-density data center system; the pressure cabin entrance is provided, so that the inspection personnel can enter the pressure cabin for inspection without water-out, and the working efficiency and use efficiency are high; and the state monitoring system ensures high safety of the internal environment and timeliness of risk discovery.

The invention discloses an underwater image enhancement method based on dual-path feature decoupling and gating fusion. The method comprises the following steps: firstly, constructing a training data set; then, an encoder-bottleneck layer-decoder is used as a trunk, and a dual-path encoding and decoding mechanism is adopted to construct an underwater image enhancement model; the encoder is used for extracting direction encoding features and space encoding features; the bottleneck layer is used for extracting global and local features and fusing and outputting bottleneck features; the decoder is used for decoding and multi-scale refinement so as to reconstruct and obtain an underwater enhanced image; then training is carried out to obtain a trained underwater image enhancement model; and finally, the device is deployed to acquire the underwater image in real time for underwater image enhancement. According to the method, independent modeling is carried out for anisotropic scattering / edge attenuation and spatial non-uniform atomization / local brightness imbalance, and mutual interference of different degradation causes in the same feature space can be reduced.

The invention discloses an underwater in-situ fish label-free sample detection method and equipment. The method comprises the following steps: acquiring an in-situ image shot by a monocular camera of an underwater observation platform, and constructing an image-text structured knowledge base; extracting a training and verification data set of the detection model from the knowledge base, and dividing the data set into a closed set category and an open world category; receiving a natural language text instruction which is input by a user and is used for describing the to-be-detected data set, and generating a text feature vector of a target category; a targeting auxiliary model is obtained through vision-text semantic space training, dynamic interactive fusion is carried out on the visual features of the in-situ image and the text features of the category, and end-to-end joint optimization is carried out on the target model; and performing label-free detection on fishes appearing in the underwater in-situ image by using the optimized target model. According to the method, new species which are not seen during training can be effectively identified, cross-domain reasoning can be implemented on a label-free observation sample, and the retraining and maintenance cost is reduced.

The invention discloses a ship viscous flow numerical simulation method based on a hybrid Cartesian grid, and relates to the technical field of ship CFD. The method comprises the steps that after a computational domain is constructed, a body-fitted grid is generated at the object plane boundary of a ship model; then, on the basis of the outermost-layer body-fitted grid, a full-thread tree is used for carrying out space division on a computational domain to generate a Cartesian grid, and the full-thread tree is output as Cartesian grid topological information matched with the data structure of the target viscous flow solver; and finally, assembling and coupling the body-fitted grid and the Cartesian grid by using an overlapping grid technology to obtain a mixed partition grid unit, and applying the mixed partition grid unit to a solving process of a target viscous flow solver. Therefore, the accuracy and robustness of viscous flow numerical simulation of the ship with the complex geometry are improved, and the method can be well applied to resistance and flow field numerical simulation scenes in underwater and water surface ship body motion states.

The invention relates to the technical field of ship underwater positioning, in particular to a dynamic space positioning method and system for a sensor chain body of a ship drag chain, and the method comprises the steps: dispersing the drag chain into a plurality of hinged rigid sections in a two-dimensional inertial reference system, connecting the sensor chain body to the tail end, and taking the motion of a ship as a traction point boundary; according to the given traction speed, the initial pitch angle, depth and tension distribution are obtained through static balance; calculating local speeds in the sections according to translation and rotation states of upstream nodes of all the sections, obtaining distributed hydrodynamic loads in combination with fluid parameters, establishing moment balance equations at all the upstream nodes, and forming a second-order ordinary differential equation set with a pitch angle as an unknown quantity; and numerical solution is carried out under a unified time step length, and the mass center positions of each node and a sensor chain body are obtained according to geometric recursion, so that dynamic positioning in an inertial reference system is realized. According to the invention, the precision and reliability of underwater target motion analysis and target tracking can be improved.

The invention discloses a vortex induced force calculation method and system and a computer readable storage medium, relates to the technical field of ship and ocean engineering, and is used for evaluating the influence of drifting trailing vortex on underwater movement attitude and trajectory of a wrecking target and providing a corresponding vortex induced force numerical calculation method. Based on a computational fluid mechanics method, a multi-ocean-current scene numerical model is established, the falling process of a wreck target in still water and ocean current environments is simulated, corresponding trailing vortex structural features are captured, differences of trailing vortex distribution under the still water and ocean current conditions are compared and analyzed, and the influence mechanism of ocean current on trailing vortex evolution is revealed. And the interference mechanism of the trailing vortex on the falling track of the wrecked target is clarified. According to the method, the vortex induced force is extracted from the trailing vortex distribution and is quantified into the mathematical expression, so that the influence of the trailing vortex on the underwater falling track of the target can be directly pre-judged, the prediction precision of the falling track envelope and the falling point dispersion range can be improved, and the success rate of the underwater search of the wrecked target can be improved.

The invention discloses an underwater target detection method based on dual supervision guidance. The method comprises the following steps: obtaining a data set of an underwater target; constructing an underwater target detection model based on dual-supervision guidance, wherein the underwater target detection model is used for detecting an underwater target; on the basis of a training set in the data set, a dual-supervision training mechanism of loss enhancement and loss detection is adopted for the underwater target detection model, close combination of image enhancement and a target detection task is realized, it is ensured that enhanced image features are more beneficial to target detection, and a trained underwater target detection model is obtained; and inputting the test set into the trained underwater target detection model, and outputting the position, target category and confidence information of the underwater target in the picture. According to the underwater target detection method, underwater image enhancement and target detection tasks are optimized at the same time through a dual-supervised guided joint learning mechanism, the overall performance of underwater target detection is effectively improved, and algorithm noise introduced in the enhancement process is reduced.

The invention discloses a method, a system and equipment for detecting the spatial form of an underwater pile foundation of a wading bridge and the thickness of a fixing object, and a medium. The method comprises the following steps: obtaining point cloud data of the complete form of an underwater pile group foundation; processing the obtained point cloud data of the complete form of the underwater pile group foundation to obtain an underwater pile foundation axis; the inclination is calculated based on the axis of the underwater pile foundation, the service state of the underwater pile foundation is evaluated with the tangent value of the inclination as an evaluation index, and whether the underwater pile foundation has significant spatial form changes or not is judged; a pile foundation appearance model is established based on the final underwater pile foundation axis and the pile foundation radius design value, the distance from the point cloud to the pile foundation surface is calculated, point cloud data are screened according to the distance, and a hard fixing object point cloud model is obtained; and performing noise interference correction on the distance between the attachment point cloud model and the surface of the pile foundation, and calculating to obtain a hard organism attachment thickness mean value. According to the method, the service state of the underwater batter pile can be accurately evaluated, and the attachment condition of the ocean fixing objects can be quantified.

The invention discloses a modal fusion method of camera-sonar equipment under the condition of unknown external parameters, and relates to the field of underwater multi-sensor data fusion. The method comprises the following steps: firstly, acquiring synchronous underwater optical images and sonar images, and converting sonar polar coordinate imaging data into a three-dimensional point cloud under a sonar coordinate system through a geometric model; then, under the condition that camera-sonar external parameters do not need to be calibrated in advance, a spatial transformation matrix between a camera coordinate system and a sonar coordinate system is automatically estimated and calibrated through the corresponding relation between images and target features in point clouds, and alignment fusion of two kinds of modal data is achieved. According to the method, optical and acoustic information can be effectively fused in a severe water quality environment, the sensing limitation of a single sensor is made up, the robustness and accuracy of underwater dam crack and other target detection are improved, and the method has the advantages of no need of manual calibration and high adaptability.

The invention relates to the field of underwater sound signal processing, in particular to an underwater DOA (direction of arrival) estimation method based on graph nerves and a convolutional neural network, which comprises the following steps: 1, establishing a linear array, and enabling narrow-band signals to simultaneously reach an underwater sound array; 2, performing signal preprocessing to obtain a signal covariance matrix, and performing normalization processing; 3, extracting correlation between array elements and spatial features of array signals, and performing data supplementation on sparse linear array information; 4, forming a double-branch structure, enhancing the information aggregation capability, and extracting features from a space path and a time domain path; and 5, constructing an adjacent matrix, filling node features of damaged array elements, adopting a double-branch structure, extracting spatial features and time domain features, carrying out feature integration, and outputting a DOA estimation result. The spatial correlation between array elements is extracted and the array sparsity problem is processed by using the graph neural network, and the time domain features of the signals are extracted in combination with the convolutional neural network, so that more accurate and more robust DOA estimation can be realized under the conditions of low signal-to-noise ratio and array sparsity.

The invention discloses a reinforcement learning-based control modeling method for a water-air cross-medium unmanned aerial vehicle and a related device, and the method comprises the steps: carrying out the interaction of a strategy network and a simulation environment, and generating a series of trajectory data; predicting a state value according to the trajectory data through a value network, and calculating a corresponding dominant function and a target value function based on the state value; calculating a value loss item, a strategy loss item and a strategy regular item through a strategy optimization algorithm so as to construct a total loss function, and performing joint training update on the strategy network and the value network by taking minimization of the total loss function as a target to obtain the updated strategy network and the updated value network; and judging whether the updated strategy network and the updated value network meet a preset dual convergence condition, if so, taking the updated strategy network and the updated value network as a water-air cross-medium unmanned aerial vehicle control model, and guiding the unmanned aerial vehicle to realize smooth and stable autonomous control in air, underwater and transition stages. And the intelligent autonomous control level of the cross-medium unmanned aerial vehicle is improved.

The invention relates to the technical field of channel monitoring and underwater topography analysis, in particular to a multi-beam sounding data driven underwater topography profile extraction method and device and a medium, and the method comprises the steps: obtaining channel region multi-beam sounding original data, carrying out the standardized preprocessing, and outputting a sounding data set; performing spatial interpolation and vectorization processing on the sounding data set to generate channel geological data, and issuing the channel geological data as a similar three-dimensional channel bottom graph through a geographic information service platform; generating a profile path, and generating interpolation points according to a preset interval; constructing a spatial index structure based on the sounding data set, and establishing an adjacent sounding point retrieval channel for each interpolation point; and in allusion to the same profile path, acquiring multiple periods of sounding data, calculating water depth difference, and dynamically and visually displaying an abnormal movement phenomenon by using a broken line graph. According to the method, efficient extraction, dynamic comparison and automatic early warning of the multi-period sounding data can be realized, and the analysis efficiency and accuracy of the channel topographic change are remarkably improved.

The invention discloses an underwater side-scan sonar target detection system and method based on an attention mechanism, and the system comprises a data collection module which collects an underwater side-scan sonar image, and obtains a side-scan sonar image data set; the network construction module is used for constructing a target detection network based on the YOLOv8n architecture, and the target detection network comprises an inattention Transformer module, a double-branch weighted multi-scale attention module and a fusion bridging attention module; the model training module is used for training the target detection neural network by using the side-scan sonar image data set to obtain a trained target detection model; and the target detection module inputs the underwater side-scan sonar image to be detected into the trained target detection model and outputs the position information of the target in the image. The problems of poor adaptability to underwater complex acoustic images, insufficient target feature extraction capability and limited background noise suppression effect are solved, and high-precision underwater side-scan sonar target detection is realized.

The invention provides a construction control system, method and equipment of an underwater leveling machine and the underwater leveling machine, and relates to the technical field of ocean engineering. The construction control system comprises a sensing subsystem used for obtaining the weight of stone in a hopper of the underwater leveling machine and the inclination angle of the hopper; the calculation subsystem is used for determining the stone mass based on the weight of the stone in the hopper and the inclination angle of the hopper and calculating the real-time material distribution mass flow rate based on the time sequence data of the stone mass; the current terrain elevation of the foundation bed is obtained to calculate the terrain residual error and the to-be-laid volume; and the control subsystem is used for generating a cloth control instruction through an optimization decision algorithm based on the real-time cloth mass flow rate, the terrain residual error, the to-be-laid volume and the predicted thickness distribution. According to the system, real-time working condition monitoring, dynamic flow calculation, terrain deviation analysis and predictive control strategies can be combined, closed-loop accurate control over the whole process from material conveying to bottom bed forming is achieved, and the control precision of underwater leveling construction is improved.

The invention relates to a UUV heterogeneous platform global task planning method and system based on full path coverage, and belongs to the technical field of underwater target exploration. According to the method, a three-dimensional environment is reduced to a two-dimensional grid plane, regions are divided according to the number of UUVs, real-time obstacle avoidance and bow-shaped path planning are realized in combination with an improved artificial potential field algorithm, and collaborative operation of A-type (detection disposal type) and B-type (detection-only type) heterogeneous UUVs is supported. The system has a dynamic scheduling mechanism, when the B-type UUV finds a target, the latest idle A-type UUV is scheduled for processing, and task duration and load balancing are optimized while full-area coverage is guaranteed. Simulation examples show that the method is high in planning efficiency, smooth in path, stable in total task time and suitable for detection tasks in complex underwater environments.

The invention provides an attitude control method, system and equipment of an underwater leveling machine and the underwater leveling machine, and relates to the technical field of ocean engineering. The method comprises the following steps: establishing a dynamic model; constructing a physical information neural network based on the dynamic model; constructing a digital twinborn body of the leveling machine, and performing simulation verification on the attitude error prediction result in the digital twinborn body; based on a simulation verification result, taking control parameters of the underwater leveling machine as optimization variables, performing parallel optimization on a plurality of control targets of the underwater leveling machine, and generating a control solution set; and determining a target control parameter combination from the control solution set, and generating a control instruction for controlling the underwater leveling machine to perform attitude adjustment based on the target control parameter combination. According to the method, the reliability of attitude control of the underwater leveling machine can be improved through prediction of the integrated physical information neural network, simulation verification of the digital twin and multi-objective optimization.