3205 results about "Underwater" patented technology

The invention discloses a multi-modal data fusion-based high dam underwater defect measurement method, which comprises the following steps of: obtaining water flow velocity data, water pressure data and water quality turbidity data, performing preprocessing by adopting a self-adaptive median filtering algorithm, and constructing a hydrodynamic field feature model; then generating an initial trajectory based on the hydrodynamic field feature model and detection target area data, and performing trajectory optimization and stability evaluation in combination with dynamic constraint conditions; adjusting sonar parameters according to the turbidity influence and the trajectory parameters to perform data acquisition; carrying out space-time alignment through extended Kalman filtering, and carrying out feature fusion and optimization by adopting an attention mechanism; and finally, performing multi-scale consistency verification and accurate positioning mapping to obtain a final defect detection result. According to the invention, the problems of defect detection precision and reliability in a complex underwater environment are solved.

The invention discloses a deep sea underwater electro-hydraulic actuator (EHA) and a control system thereof. The system provides power through the power source module, balance of system oil pressure and pressure of external seawater is controlled through the pressure compensation module, oil circulation and oil pressure control are conducted through the integrated valve set module, a control instruction of the control module is executed through the execution mechanism module, and the control module conducts cooperative control over the whole system. According to the control system, the unbalanced pressure between the system and the deep sea high-water-pressure environment is compensated through the pressure compensator so as to reduce the influence of the deep sea high-water-pressure environment, meanwhile, the pressure compensator serves as an oil tank to supply oil, miniaturization of the system is achieved, and the reliability of the system during underwater work is improved; according to the deep-sea underwater electro-hydraulic actuator, the mounting positions and internal flow channels of all elements of the integrated valve bank are optimized, the pressure loss of fluid in the flow channels is reduced, and the energy utilization efficiency of the deep-sea underwater electro-hydraulic actuator is improved; the asymmetric hydraulic cylinder can operate in four working conditions of deep sea, and underwater high-precision movement can be completed.

The invention discloses an underwater binocular positioning method and device based on target assistance and a storage medium, and belongs to the technical field of underwater environment perception, and the method comprises the following steps: obtaining internal and external parameters of a binocular camera; solving to obtain refraction parameters of the binocular camera; the binocular camera is controlled to shoot and collect the target image, an initial underwater cooperative positioning target image is obtained, the initial underwater cooperative positioning target image is corrected, and a corrected underwater cooperative positioning target image is obtained; a YOLOv8 model is adopted to detect a target, and an area where the target is located in the underwater cooperative positioning target image is selected; feature points are extracted and matched through an ORB algorithm, and matched feature points are obtained; and calculating to obtain the three-dimensional coordinate of the target in the camera coordinate system. According to the invention, accurate positioning of the underwater target can be realized through a binocular vision method, and working requirements in a complex underwater environment are met.

The invention relates to the technical field of three-dimensional imaging, and discloses a high-precision underwater structured light three-dimensional point cloud imaging method and system, and the method comprises the following steps: deploying a plurality of sensor nodes, monitoring the temperature, salinity and turbidity key parameters of a water body in real time, selecting proper light source wavelength and power according to the collected data, and carrying out the three-dimensional point cloud imaging of the underwater structured light. It is ensured that the optimal signal-to-noise ratio is obtained under the current condition, and meanwhile the exposure time and gain setting of the camera are initialized. According to the method, the optimal signal-to-noise ratio is obtained by monitoring water body conditions in real time and dynamically adjusting light source characteristics, the optimal structured light pattern is predicted by using a machine learning model, scattering noise is removed, advanced registration and fusion algorithms and an accurate phase unwrapping method are applied, and a high-quality comprehensive structured light pattern is generated. Point cloud gaps are filled through a geometric correction algorithm and an interpolation / filtering algorithm, so that a reconstruction model is closer to the surface of a real object.

The invention discloses an unmanned ship underwater obstacle avoidance system based on distributed wide-beam sonar, and the system collects original environment information through a wide-beam sonar group, carries out the dynamic noise reduction processing through adaptive filtering, and obtains environment detection information. And acquiring the motion state of the unmanned ship through a navigation compensation module, and performing motion error compensation on the environment detection information to obtain environment correction information. And constructing an ellipsoid space safety area based on the environment correction information, and calculating a safety navigation boundary in real time to obtain safety navigation information. The obstacle avoidance decision module generates a multi-level obstacle avoidance strategy according to the real-time navigation state and the safe navigation information, and the execution control module converts the strategy into an obstacle avoidance instruction and dynamically adjusts the output frequency to adapt to different navigation working conditions. The system effectively solves the problems that a traditional obstacle avoidance system is insufficient in detection precision and lags behind in response in a complex underwater environment, all-directional and high-precision control over underwater obstacle avoidance of the unmanned surface vehicle is achieved, and the real-time performance and environmental adaptability of the obstacle avoidance system are remarkably improved.

The invention provides a water surface and underwater heterogeneous cooperative control method and device based on a preset time disturbance observer. The control method mainly comprises the steps that a water surface unmanned ship controller calculates an expected control torque according to a specified expected trajectory, the actual state information of an unmanned ship body and a compensation value obtained by the observer; the underwater unmanned vehicle controller calculates an expected control moment according to the expected trajectory obtained by the guidance method, the actual state information of the water surface unmanned ship, the actual state information of the underwater unmanned vehicle body and a compensation value obtained by the observer; and heterogeneous cooperative control of the water surface unmanned ship and the underwater unmanned vehicle is realized. According to the method, guidance of water surface and underwater heterogeneous cooperative control is completed by fusing vertical projection and a sight line method; according to the improved self-adaptive integral terminal sliding mode control method, the external interference is estimated by using the preset time interference observer and is compensated in the controller to improve the anti-interference capability of the system, and the robustness and rapidity of the system are improved while the tracking precision of the system is improved by the provided improved self-adaptive integral terminal sliding mode control method.

The invention relates to the technical field of underwater leveling machines, in particular to a transverse and longitudinal walking mechanism, a multi-degree-of-freedom adjusting underwater leveling machine and a construction method. The transverse and longitudinal walking mechanism comprises an end part structure, and a first hole is formed in the end part structure in a penetrating manner; a first hole is formed in the end structure in a penetrating manner; at least part of the transverse moving frame is located in the first hole, and the transverse moving frame is in sliding fit with the end structure in the radial direction of the first hole; the walking longitudinal beam penetrates through the transverse moving frame in the length direction of the first hole and is in sliding fit with the transverse moving frame. The first vertical lifting supporting leg is connected with the end part structure; and the second vertical lifting support leg is connected with the walking longitudinal beam. According to the transverse and longitudinal walking-pedrail walking mechanism, the mode that the walking-pedrail longitudinal beam is sleeved with the transverse moving frame, the transverse moving frame is sleeved with the end structure, the transverse moving frame is used for replacing a transition frame of an existing walking-pedrail type leveling machine, and therefore the overall weight of the transverse and longitudinal walking-pedrail walking mechanism is effectively reduced.

The invention discloses a health assessment method for a long-distance underground culvert structure, and the method comprises the steps: carrying out the fusion processing based on acoustic and optical detection data, so as to recognize a structure defect; based on underwater rebound and coring test data, carrying out underwater-dry conversion and correction on a strength value, and determining corrected structural strength and material degradation parameters; in combination with defect, degradation and historical monitoring data, carrying out structure evolution modeling and mutation risk identification to obtain evolution characteristics and mutation risks of the structure; and integrating the corrected structural strength, evolution characteristics and abrupt change risks, performing full-field state assessment, and generating a structural health assessment and risk early warning result. According to the method, accurate, dynamic and full-field evaluation of the health state of the culvert can be realized, and the reliability and early warning capability of an evaluation result are improved.

The invention discloses a multi-sensor fusion underwater SLAM system and method based on adaptive weight adjustment, and the system comprises a multi-modal sensor module, a data preprocessing and synchronization module, an adaptive weight adjustment module, a multi-sensor data fusion module, an SLAM calculation and map updating module, and an SLAMS result output module. And the adaptive weight adjustment module monitors the data quality of each sensor of the multi-modal sensor module in real time, and automatically adjusts the weight of each sensor according to the change of the underwater environment. The underwater positioning and navigation system can realize stable underwater positioning and navigation in an environment with insufficient light, complex obstacles or turbid water, and is especially suitable for tasks such as underwater exploration, detection and complex terrain modeling. Compared with the traditional SLAM technology, the method provided by the invention overcomes the limitation of a single data source by adjusting the weight of the sensor in real time, and significantly improves the adaptability and precision of the SLAM system in different underwater environments.

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.

The invention relates to a marine fishery breeding work ship deep water taking device and method, the marine fishery breeding work ship deep water taking device comprises a water taking cantilever, a submersible pump, a guide roller, a rolling part and a lifting device, the water taking cantilever is connected with a ship body through a rotation pair, and the water taking cantilever can stably descend underwater and keep the accurate water taking depth; the water taking method comprises the steps that the position and angle of a water taking cantilever are adjusted through a winding and unwinding winch, a temperature sensor at the water taking cantilever end monitors the seawater temperature in real time, and when the temperature reaches a preset value, a submersible pump is started to extract deep seawater; compared with a traditional method, the device has the characteristics of compact structure, simple operation, high efficiency and reliability; the problems that underwater butt joint is difficult, a hose is prone to damage and the like are solved, and operation efficiency and safety are remarkably improved; through the connection of the flexible short pipe, the flexibility and the stability in the water taking process are ensured, and meanwhile, the labor intensity of operators is reduced; the technology can be widely applied to marine fishery breeding, especially extraction of deep cold water resources, and has remarkable energy-saving, environment-friendly and economic benefits.

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 relates to the technical field of image recognition, in particular to a bridge pier underwater structure image intelligent analysis method and system, and the method comprises the following steps: obtaining RGB channel values of all pixels of a bridge underwater structure image region, converting a main color temperature, generating a color temperature map, dividing the region in a vertical direction, extracting a main color temperature track, and carrying out the linear fitting. And comparing the residual error with a continuity threshold, and marking a color temperature continuous section. According to the method, a two-dimensional map is constructed through fusion of main color temperature and space coordinates, spatial distribution expression of a structural region is enhanced, a stable region is extracted by combining residual and continuity discrimination, interval judgment and RGB finishing are introduced into gray scale lifting, image brightness balance and color consistency are enhanced, a gray scale trend model is constructed through radial chain grouping, and light attenuation interference stripping is achieved. Feature point continuous frame tracking is combined with disturbance vector mapping, structure dynamic changes are captured, abnormal behaviors are recognized through cross analysis of tension differences and response terms, and efficient recognition and interference isolation under multi-dimensional feature fusion are achieved.

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.

The invention discloses a seabed sonar image recognition system based on a graph neural network, and the system comprises the following modules: an image collection module which is used for collecting an original sonar image and constructing an original sonar image data set; the preprocessing module is used for generating a de-noised sonar image data set; the three-dimensional landform structure modeling module is used for constructing a three-dimensional landform structure diagram; the graph structure coding module is used for obtaining multi-scale landform semantic feature representation; the decoding and evaluation module is used for reconstructing a preliminary seabed landform semantic segmentation map through jump connection and calculating a fitness vector; the optimization scheduling module is used for obtaining an optimized submarine landform semantic segmentation map; and the post-processing and output module is used for generating a final segmentation result and obtaining a landform category identification result. According to the method, the problems of fuzziness and fracture of a traditional convolutional neural network on a sea ditch-sea mountain-hill complex nested landform boundary are effectively solved.

The invention provides a non-paired underwater image enhancement method based on multi-scale contrast learning and CLIP cross-modal contrast learning. The method comprises the following steps: randomly extracting degraded images and non-paired enhanced images thereof from at least two underwater image data sets to construct a training set; extracting a text through a large language model to construct an enhanced image positive sample description and a degraded image negative sample description; configuring a generative adversarial network, wherein a generator comprises: a self-calibration feature enhancement module performing a feature splitting-gating fusion operation; a transform global modeling module of cross-region dependence is established through block self-attention, and a transform global modeling module of cross-region dependence is established through block self-attention; implementing joint contrast learning: calculating multi-scale contrast loss of feature block similarity at a multi-layer feature random sampling position of the generator; constraining CLIP cross-modal comparison loss of semantic alignment of the enhanced image and the positive sample description; optimizing network parameters based on the training set and a loss function; and inputting the underwater degraded image into the optimized generator to obtain an enhanced underwater image.

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 discloses an underwater riprap foundation bed tamping method based on a sand compaction pile ship. The method comprises a sand compaction pile ship transformation process and a tamping and leveling process. When the flow of transforming the sand compaction pile ship is carried out, sand outlet guide doors at the lower ends of the three pile sinking sleeves on the sand compaction pile ship are cut off firstly; the lower ends of the three pile sinking sleeves are each connected with a bottom flange; the three tamping plate devices are connected to the bottom flanges of the three pile sinking sleeves in a one-to-one correspondence mode, and each tamping plate device comprises a tamping sinking pipe, a top flange, a tamping sinking bottom plate, an enclosure plate, a middle plate, a plurality of upper-layer stiffening plates and a plurality of lower-layer stiffening plates; when the tamping and leveling process is carried out, underwater riprap operation on the lowest layer of the foundation bed is carried out firstly, and then the transformed sand compaction pile ship is moved to a vibrating tamping position on the underwater riprap surface of the lowest layer of the foundation bed for tamping and leveling; and then the ship is moved to the next ship position for tamping and leveling of the next vibrating tamping position. The construction efficiency in the drop hammer tamping process of the underwater riprap foundation bed can be improved.

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 relates to a multi-scale collaborative algal bloom assessment method fused with an underwater video, and belongs to the field of image recognition. The method comprises the following steps: S1, acquiring underwater, water surface and high-altitude images; s2, collecting water quality data and meteorological data; s3, aligning the data in time and space; s4, performing binary mask segmentation on the image by using an image segmentation technology; s5, vectorizing the binary mask of the image, and performing concat splicing on the vectorized binary mask, the water quality data and the meteorological data to serve as input; s6, an improved Transform model is used for prediction; and S7, fusing the binary masks of the images by using a weighted summation method to obtain a binary mask of the algal bloom area of the monitoring area and a fused algal bloom coverage ratio. The method provided by the invention can realize calculation and prediction of the binary mask of the algal bloom area and the fusion algal bloom coverage ratio of the monitoring area at multiple moments, and is beneficial to dynamic and accurate evaluation of the algal bloom phenomenon.

The invention belongs to the technical field of deep-sea mining environment assessment, and particularly relates to an autonomous multi-mode mining plume and redeposition thickness monitoring system and method, and the system comprises an autonomous underwater unmanned submersible and detection load equipment connected with the autonomous underwater unmanned submersible. The autonomous underwater unmanned submersible is used for carrying detection load equipment, providing electric energy for the detection load equipment, sending a control instruction to the detection load equipment, preprocessing received data returned by the detection load equipment, and sending an equipment state to the mother ship in real time, so that the mother ship can monitor the autonomous underwater unmanned submersible in real time; the detection load equipment is used for synchronously carrying out deep sea near-bottom mining plume and redeposition thickness monitoring in three detection modes of acoustics, optics and hydrology, carrying out multi-category data comparison and fusion in the same time coordinate system, and sending the collected data to the autonomous underwater unmanned submersible; and data support is provided for later deep-sea mining plume and redeposition simulation modeling.

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 concrete three-dimensional reconstruction, in particular to an underwater concrete three-dimensional reconstruction method and system based on linear structured light and stereoscopic vision fusion. The method comprises the steps of obtaining a depth map and a texture map of underwater concrete based on a line structured light module and a stereoscopic vision module, and obtaining a preliminary depth data sequence and a surface texture sequence; performing environment compensation and image enhancement on the depth data and the texture data to generate data after environment correction; based on the corrected data, performing registration and matching on the depth and texture data by using a multi-modal fusion algorithm to generate a fusion point cloud data model; motion compensation and deformation repair are carried out on the point cloud model, deformation and structure offset caused by water flow are corrected, and a repaired point cloud model is generated; the repaired point cloud is input into a three-dimensional model reconstruction engine, a high-precision underwater concrete three-dimensional model is generated, intelligent analysis is conducted on the surface of the model, and damage and structural integrity of the model are evaluated. The underwater concrete three-dimensional reconstruction method effectively improves the precision of underwater concrete three-dimensional reconstruction, solves the problem of model distortion in complex environments such as water flow and turbid water quality, and has efficient and accurate structure detection and maintenance functions.

The invention relates to the technical field of underwater sediment measurement, in particular to a microspur measurement device and method, and provides the following scheme: firstly, screening out an initial local selected area through overall image graying and feature extraction, and adjusting the local area through iteration to ensure that a microspur image can accurately reflect particle features in the overall image; then, decomposing and extracting high-frequency edge information by using a Laplacian pyramid, eliminating background noise through gray variance, and generating a particle region graph; further separating adjacent particles by using an adhesive particle cutting technology, and finally generating a high-quality sediment image through image correction; according to the method, the microspur image acquisition frequency can be reduced, the particle measurement accuracy is improved, the data processing complexity is reduced, and the method has relatively high measurement precision and practical value.

The invention discloses a multi-view underwater three-dimensional point cloud splicing method based on sparse and dense point cloud fusion, and relates to the technical field of structure underwater detection. The method comprises the steps that a binocular camera surface image of an underwater structure is received, the binocular camera comprises a left camera and a right camera, dense point clouds are generated based on stereo matching and triangulation, and the corresponding relation between the dense point clouds and image pixels of the left camera is output; and based on the received left camera image, a sparse point cloud is generated by adopting a motion structure recovery algorithm and utilizing multi-view triangulation, and a corresponding relation between the sparse point cloud and the pixels of the left camera image is output. According to the method, when the point cloud of multi-view reconstruction is spliced, the surface features of the underwater structure can be well restored, feature extraction is not needed, the method has high accuracy and robustness, and high-precision point cloud splicing can be achieved in the underwater complex environment, so that the method has good application prospects in actual underwater structure detection and image splicing tasks.

Integrated underwater rock drilling and splitting device, characterized in that it comprises: a supporting structure (1); a drilling unit (2) mounted on the support structure (1); a splitting unit (3) mounted on the support structure (1), wherein the splitting unit (3) and drilling unit (2) are arranged at intervals; and wherein the splitting unit (3) comprises a splitting rod (301) provided with a plurality of telescopic piston segments (302); a positioning and borehole alignment system comprising a positioning pin (401) and at least one auxiliary positioning device, wherein the positioning pin (401) is designed to bear against and be fixed to a rock body (7) and the auxiliary positioning device is arranged relatively fixedly on the support structure (1); a workstation switching mechanism (5), wherein the support structure (1) is arranged on the drive side at a switching end of the workstation switching mechanism (5); wherein the workstation switching mechanism (5) is configured as a rotary switching mechanism or a translation switching mechanism; wherein the rotary switching mechanism is configured to drive the support structure (1) to rotate so that the splitting unit (3) is able to move and be aligned with the drilling position of the drilling unit (2); and wherein the translation switching mechanism is configured to drive the support structure (1) to translate so that the splitting unit (3) is able to move and be aligned with the drilling position of the drilling unit (2); and a connecting rod (6), wherein the connecting rod (6) is adapted to be connected to a ship-based manipulator arm in order to adjust the underwater depth of the device.

The invention relates to the technical field of desilting control, in particular to a control method and system for underwater desilting. When the desilting operation of an underwater desilting robot is controlled, underwater environment parameters and comprehensive desilting efficiency parameters of the desilting robot are firstly collected; the desilting speed of the desilting robot is controlled according to the two parameters, the scientificity of speed control is improved, and meanwhile, during specific control, based on the special operation scene of underwater operation of the desilting robot, after the desilting speed parameter is calculated through a mathematical model controlled by the desilting speed parameter, the desilting speed of the desilting robot is controlled. The reference threshold value of the desilting speed parameter adjusting value is set, the calculated desilting speed parameter adjusting value is compared with the reference threshold value of the desilting speed parameter adjusting value to determine whether the desilting speed parameter is adjusted or not, and the situation that the speed adjustment is not expected in the speed adjustment process of the desilting robot is avoided.

The invention discloses an underwater micropterus salmoides body length and mass measurement method, and relates to the technical field of aquaculture. Comprising the following steps: 1) target detection and key point detection: performing target detection and key point detection on underwater largemouth bass by using a YOLOv8 model to obtain key point coordinate information of a fish head and a fish tail; and 2) obtaining depth information: obtaining the depth information of the underwater image through a monocular depth estimation algorithm, and calculating the body length of the largemouth bass in combination with a key point detection result. And 3) mass estimation: based on the body length information, estimating the mass of the micropterus salmoides through a power function regression model. And 4) model deployment: deploying the model in a recirculating aquaculture monitoring system, and displaying and recording the body length and quality information of the micropterus salmoides in real time. According to the method, the body length and the body weight of the largemouth bass can be obtained in real time in a non-contact mode, the method is suitable for a factory-like circulating water culture mode, data support can be provided for culture management, and the practical value and the popularization prospect are high.