2056 results about "Underwater" patented technology

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 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.

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 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 provides an underwater image enhancement method based on a water diffusion physical model, and relates to the technical field of underwater image enhancement, and the method comprises the steps: S101, inputting a local block of an underwater image to a convolutional neural network, and predicting an attenuation coefficient matrix and a diffusion matrix of a water body; s102, constructing a water diffusion control equation based on the attenuation coefficient matrix and the diffusion matrix of the water body; s103, performing multi-scale diffusion on the underwater image in a frequency domain based on a water diffusion control equation to obtain a reconstructed image; s104, recovering a color channel of the reconstructed image through a spectral transmittance model to obtain an enhanced image; and S105, outputting an enhanced image. According to the method, by estimating the attenuation and scattering coefficients of the light underwater, image enhancement which better conforms to the physical diffusion characteristics of the light underwater is achieved, color distortion and image blurring are effectively avoided, and the physical interpretability and reliability of an enhancement result are 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 invention provides an underwater ultrasonic signal analysis method based on the Doppler effect, and relates to the technical field of data processing, and the method comprises the steps: carrying out the segmentation processing of echo signal data according to a preset time window, carrying out the envelope demodulation and phase unwrapping operation of a signal in each time window, and carrying out the phase unwrapping operation of the signal in each time window; amplitude sequence, phase sequence and instantaneous frequency sequence data are extracted; extracting frequency change, amplitude change and phase change data, performing clustering processing, and distinguishing and marking different underwater target components; respectively calculating an amplitude stability index and a phase change synchronism index for each frequency track in all time windows, and screening a main frequency track according to the amplitude stability index and the phase change synchronism index; frequency shift values in the time windows are extracted, the speeds of the underwater targets in the time windows are calculated based on the Doppler effect, and the motion direction is judged in combination with frequency change data and phase change data; according to the invention, the autonomy and accuracy of underwater ultrasonic signal analysis are improved.

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 provides high-durability concrete for inducing adhesion of marine fixing organisms and a preparation method, and belongs to the crossing field of marine fixing organisms and marine concretes.The concrete is prepared by adopting a porous carrier loaded with induction bacteria, and the impregnation process of the porous carrier loaded with the induction bacteria is optimized; according to the present invention, the barnacle can be induced to adsorb to the concrete surface, the chloride ion resistance of the concrete can be improved, and the concrete has characteristics of simple component, low preparation cost, green environmental protection, and wide application prospect, and can provide more effective protection for the loaded bacteria, and can induce the barnacle to adsorb to the concrete surface. The goal of high durability of the concrete for underwater ocean engineering can be achieved.

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 relates to the technical field of underwater construction engineering, and discloses an underwater foundation horizontal bearing capacity evaluation method which comprises the following steps: acquiring the geometric dimension and material physical and mechanical properties of a foundation, geological information of a seabed soil sample, ocean current observation data and design wave elements; the maximum scouring depth around the foundation is determined according to ocean current observation data, wave elements and sediment mechanical properties; establishing a foundation-soil body three-dimensional bearing model, and substituting the foundation and soil body mechanical properties and the scouring size to obtain the foundation bearing capacity under each foundation diameter, burial depth, scouring depth and sediment property; according to the relationship between the foundation diameter, the burial depth, the scouring depth and the sediment property and the foundation bearing capacity, a correlation model is established, and the residual value of the foundation bearing capacity after scouring is calculated according to the correlation model. Based on the pile foundation bearing characteristic and the pile-soil interaction mechanical theory, the analysis method has the advantages of being clear in theory, wide in application range, high in reliability and the like. Analysis results are accurate and reliable, influence factors are comprehensively considered, and the method is more scientific.

The invention discloses an underwater leveling machine path optimization method based on foundation bed pore characteristics, and relates to the technical field of ocean engineering. The method comprises the following steps: measuring three-dimensional topographic data and pore distribution characteristic data of a to-be-leveled water area foundation bed by using a multi-source sensing and control system and a multi-beam sounding method, establishing a digital topographic model of the to-be-leveled foundation bed, and generating candidate optimized leveling paths adapted to geological characteristics by constructing an initial construction path, the engineering feasibility of the leveling operation is evaluated, and the optimal position of each path point after iterative optimization is output as an optimized leveling path in combination with an optimization algorithm, so that the leveling of the underwater leveling machine is completed; according to the method, the pore distribution characteristics and three-dimensional topographic data of a seabed foundation bed are intelligently analyzed, reliable environment data are obtained, an initial construction blueprint is formed, a basis is provided for optimization, dynamic generation and online correction of a path are achieved by fusing pore characteristic analysis and an intelligent optimization algorithm, and efficient, uniform and high-precision autonomous leveling operation is achieved.

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 provides a deepwater underwater wellhead stability real-time monitoring and early warning system, and belongs to the technical field of early warning systems. The deepwater underwater wellhead stability real-time monitoring and early warning system comprises a monitoring scheme design module, a data acquisition and storage module, a state observation module, a state early warning module, a signal wireless transmission module and a platform remote monitoring module. The deepwater underwater wellhead stability real-time monitoring and early warning system comprises the following steps that the monitoring scheme design module determines layout of sensors and a host; the data acquisition and storage module acquires signals and sends the signals to the state observation module; the state observation module fuses the mechanism model and the data driving model to form a state prediction model; the state early warning module forms a three-level early warning mechanism and transmits early warning data; the signal wireless transmission module encodes, modulates and transmits the early warning data; the platform remote monitoring module receives and processes the signals to achieve stability early warning, and the problems that in the prior art, a deepwater underwater wellhead stability real-time monitoring and early warning system lacks, and safe and efficient development of deepwater oil and gas resources is difficult to guarantee are solved.

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.