220 results about "Sea level" patented technology

The invention belongs to the technical field of ocean observation, and discloses an ocean wave field reconstruction method and device based on binocular vision. An ocean wave field reconstruction method based on binocular vision comprises the steps that internal parameters of a camera are calibrated through a Bouguet calibration algorithm, a binocular camera provided with an IMU sensor is used for collecting images and pose information, feature points are extracted through an SURF algorithm, feature matching is completed under a game theory framework, and abnormal points are removed through an RANSAC algorithm. Then, camera parameters are calculated based on an eight-point method, and the camera parameters and three-dimensional point coordinates are optimized through an SBA algorithm; thirdly, generating a disparity map by adopting epipolar correction and an SGM algorithm, and performing morphological processing on the disparity map; and the processed image is subjected to triangulation to generate a three-dimensional point cloud, and filtering is carried out. And finally, estimating a sea level position through an RANSAC algorithm, and optimizing a result through a least square method to complete three-dimensional reconstruction of ocean waves.

The invention discloses an ozone concentration forecasting method based on peak value perception and influence factor analysis, which utilizes continuous online observation data and meteorological observation data of multi-site pollutants, processes abnormal and missing data, and combines with boundary layer height, radiation and sea level air pressure provided by an ECMWF meteorological forecasting product to forecast ozone concentration. Building a high-quality Yunnan region large database for supporting deep learning according to hour-scale meteorological numerical simulation data of vertical wind speed, and building an ozone forecasting model based on influence factor analysis and peak value perception; capturing a global dependency relationship among historical meteorology, pollutant data and an ozone long-time sequence and a nonlinear relationship between ozone and an influence factor, so that the model can better understand context information and a related mechanism influencing ozone generation; the defect of long-time sequence dependence of a traditional deep learning method is overcome, the influence of influence factors on ozone concentration prediction is ignored, and the accuracy of ozone prediction is improved.

The invention provides a high-temporal-spatial-resolution full-profile real-sea accurate corrosion test method and system, and the method comprises the steps: dividing the sea level into three layers of monitoring regions, namely an atmospheric near-sea-level layer, a sea-gas boundary layer and a seawater mixing layer, deploying corresponding sensor arrays in each monitoring region, and synchronously collecting the environmental parameters of each layer in real time; a standard corrosion coupon and a corrosion monitoring sensor for monitoring the local corrosion state of the sample are arranged in each monitoring area; performing space-time alignment on the acquired data to form an environment-corrosion strong association data set; an atmosphere-ocean coupling forecasting system is constructed, simulation and prediction of future environmental parameters are achieved, simulation results serve as input variables of a corrosion prediction model, and a material corrosion life prediction model is established in combination with historical test data. According to the invention, synchronous monitoring of multi-dimensional environmental parameters and material corrosion data within a range of 30 meters above and below the sea level can be realized, and an accurate basis is provided for material selection and corrosion prediction of marine equipment.

The invention provides an island shoreline erosion risk prediction method based on computer vision, and belongs to the technical field of island shoreline erosion risk analys.The island shoreline erosion risk prediction method comprises the steps that firstly, a high-resolution remote sensing image is obtained, island contour information is extracted, and a shoreline initial model is constructed through a small grid approximation method; generating multi-level grid representation through grid merging operation and storing the multi-level grid representation as a shoreline feature matrix; then collecting a multi-time sequence remote sensing image, calculating a change matrix set of adjacent time points, and analyzing a shoreline evolution mode; establishing a coast erosion kinetic equation model by combining the wave action intensity, the tide amplitude, the sea level rising rate, the geological structure coefficient and the shoreline slope angle; a shoreline change rule is analyzed by applying a map attention grid evolution model, and finally, an uncertainty analysis module is introduced, a multi-scale erosion risk assessment map is generated, a high-risk area is identified and output as a prediction result, so that the technical problem that the complicated island shoreline erosion risk is difficult to accurately predict is solved.

The invention discloses a method for completing an autonomous deep-sea exploration task by a deep-sea cross-domain unmanned aerial vehicle. The method comprises the following steps: determining a target area; taking off to a specified height from the sea level, receiving a task execution command and then flying to a target area; when the relative distance between the current position and the coordinates of the target area reaches a preset value, descending; when it is detected that the device is contacted with seawater, the device dives through gravity; when it is detected that the set depth is reached, the propeller is restarted, and the detection task is executed; after the detection task is completed, the standby battery is rejected and ascends; after leaving the water surface, rising to a specified height and switching to a homeward flight mode; and when the deep-sea cross-domain unmanned aerial vehicle is within the sight distance range, a manual landing task is executed. The invention further discloses the deep-sea cross-domain unmanned aerial vehicle. According to the unmanned aerial vehicle and the method, autonomous switching operation between an air medium and an underwater medium can be realized, and the unmanned aerial vehicle has the capability of autonomously completing detection and water body sampling in an extreme deep sea environment.

The invention discloses a GNSS (Global Navigation Satellite System) water level inversion model, which belongs to the technical field of water disaster prevention and marine environment monitoring, and comprises the following steps: S1, acquiring original data: an SNR (Signal to Noise Ratio) observation value and a GNSS observation value; s2, setting parameters: determining cut-off elevation angle information and azimuth angle information according to the surrounding environment of the shore-based GNSS monitoring station; s3, direct reflection signal separation: selecting IMF components containing main water level information to perform water level inversion and addition output; and S4, solving h by utilizing spectral analysis: analyzing the IMF component segment containing the water level information by utilizing a Lomb-Scargle algorithm to solve a main frequency f, and converting according to a formula to obtain a required vertical reflection distance h. The GNSS water level inversion model has the advantages of global coverage, no need of manual intervention, economy, effectiveness and simplicity and convenience in maintenance, and is suitable for monitoring tides, rivers, lakes and sea level; the accuracy of water level inversion can be improved, and key water level information is prevented from being lost in traditional denoising.

The invention relates to the technical field of mariculture, and discloses mariculture equipment and an offshore wind power system.The mariculture equipment comprises a mounting frame, a net cage and a lifting assembly, a containing cavity is formed in the mounting frame, an opening is formed in the top of the mounting frame, the bottom of the mounting frame is suitable for being arranged in water, and the top of the mounting frame is exposed out of the water surface; one end of the lifting assembly is fixed to the mounting frame, the other end of the lifting assembly is connected with the net cage, and the lifting assembly has a first state for driving the top of the net cage to sink into the sea and a second state for driving the net cage to float out of the sea surface. The distance between the top of the net cage and the average sea level exceeds the maximum wave height, the impact of stormy waves on the net cage can be reduced, the net cage is prevented from being damaged, and after the typhoon is finished, the net cage is driven to restore the original position through the lifting assembly and lifted to the second state of floating out of the water surface through the lifting assembly so that the net cage can be maintained conveniently.

The invention discloses a PM2.5 forecasting method based on weather circulation and a stability index, and relates to the technical field of air pollution prevention and control, and the method comprises the steps: carrying out the calculation according to the monitoring data of a target region, obtaining a sea level air pressure distance flat field of the target region, carrying out the clustering, and obtaining a weather type; calculating the circulation index value of each meteorological station, and determining the circulation type of the target area; calculating an atmospheric stability index of the target area, and determining a K index interval of the target area; according to the PM2.5 concentration time sequence of each monitoring point position in the target area, establishing a PM2.5 concentration historical data set by matching weather typing, circulation typing and a K index interval of corresponding time; and according to meteorological observation data of a future time period, calculating a weather type, a circulation type and a K index interval of the future time period, and searching a PM2.5 concentration historical data set to obtain a PM2.5 concentration prediction result. The prediction time can be shortened, and the interpretability of the prediction result can be improved.

The invention provides a sea level rise influence risk assessment method based on multi-source data fusion, a medium and a system, and belongs to the technical field of marine disasters. Basic feature data are obtained by constructing a multi-dimensional data acquisition network, nonlinear time series decomposition is performed by applying multi-scale wavelet analysis, and the risk assessment result is obtained by analyzing the nonlinear time series; establishing a prediction model based on a deep learning neural network; determining key vulnerabilities by using a minimum cut maximum flow algorithm; establishing a regional vulnerability scoring system; generating a comprehensive risk assessment matrix by using a Bayesian network ensemble analysis method; and finally, generating an evaluation report by using the coastline adaptability gating model. According to the model, a multi-head time sequence attention mechanism and bidirectional autoregression coding are fused, parameters are dynamically adjusted by adopting a regional adaptability gating weighting function, and accurate evaluation and dynamic tracking of sea level rising influence risks in a complex geographical environment are realized.

The invention discloses a cooperative control simulation system for an underwater robot and an umbilical cable system, belongs to the technical field of ocean engineering simulation and automatic control, and is used for analyzing system dynamic characteristics in the research and development stage of deep sea operation equipment. Comprising an environment initialization and marine environment construction module, a mother ship model construction module, an underwater robot and umbilical cable coupling module, an instruction generation module, a man-machine interaction control module and a data acquisition and storage module. According to the method, an external interference source with physical authenticity is provided for a control algorithm by combining an energy density function and simulating a composite environment modeling method of a sea level height field and an LOD dynamic grid, and a distributed model prediction control algorithm for uniformly optimizing underwater robot trajectory tracking and umbilical cable tension safety maintenance is constructed; data such as the motion state of the underwater robot and the tension of the umbilical cable can be output in real time, algorithm performance testing is completed in a virtual environment, and dependence on high-cost sea testing is not needed.

The invention relates to the field of slope foundation trench excavation, is used for solving the problem that a square grid method has a large error in earthwork excavation amount evaluation of a complex terrain, and particularly relates to a BIM model-based hydraulic reclamation foundation slope foundation trench excavation engineering amount evaluation system. Comprising a scanning generation unit, an elevation analysis unit, an engineering quantity calculation unit, a grid adjustment unit and a result output unit. According to the method, when the earthwork excavation volume is estimated, modeling analysis is carried out on the seabed surface and the excavation position on the basis of the scanned and measured seabed surface through the BIM technology, so that the earthwork volume needing to be excavated is obtained, estimation of the earthwork excavation volume is achieved, and meanwhile, when the earthwork excavation volume is estimated, the earthwork excavation volume is accurately estimated. Different sizes of the square grids are determined according to different flatness degrees of the seabed surface, so that the sizes of the square grids can actively adapt to the flatness degree of the sea level, the convenience of square grid earthwork volume evaluation is ensured, and the accuracy degree of earthwork excavation volume estimation under the complex terrain is improved.

The invention discloses a navigation radar guided photoelectric unmanned ship horizontal plane target detection and positioning method, which comprises the following steps: carrying out zero calibration on a pose measurement device, a navigation radar and a photoelectric device which are deployed on an unmanned ship, and establishing an unmanned ship body coordinate system; obtaining the pose data of the unmanned ship based on the pose measurement equipment; adjusting the pitch angle of the photoelectric equipment based on the unmanned ship rolling data or adjusting the azimuth angle of the photoelectric equipment based on the unmanned ship pitching data, so that the sea level is located in the middle of the picture of the photoelectric equipment; the optoelectronic device receives the orientation of the to-be-tracked target detected by the navigation radar, the navigation radar guides the optoelectronic device to adjust the azimuth angle, and a photoelectric target detection module of the optoelectronic device detects the to-be-tracked target; the photoelectric device locks a to-be-tracked target, and the distance between the unmanned ship and the to-be-tracked target is measured through laser ranging; and determining the longitude and latitude of the to-be-tracked target based on the distance and the unmanned ship pose data. According to the method, the detection accuracy of the unmanned ship on surrounding targets is improved.

The invention provides an aircraft cockpit pollutant concentration monitoring and processing system and method and an aircraft, and relates to the technical field of aircraft cockpit environment monitoring, and the system comprises a monitoring subsystem which is provided with a plurality of sensors, and the plurality of sensors are used for continuously monitoring the pollutant concentration in a cockpit according to a preset time interval; the control subsystem is connected with the monitoring subsystem, and is used for receiving the pollutant concentration data from the monitoring subsystem, correcting the pollutant concentration data by using the measured sea level temperature and pressure data, comparing the corrected actual pollutant concentration value with a preset alarm threshold value, and sending the alarm to the monitoring subsystem. And determining whether to start an alarm according to the comparison result. According to the invention, accurate monitoring and timely warning of the concentration of pollutants in the aviation cockpit are realized.

An apparatus and method for predicting sea level fluctuations are disclosed. The method for predicting sea level fluctuations includes: acquiring past time-series data of past wind stress and past sea level height, determining an optimal length of a time lag of a response function representing a convolution relationship between the past wind stress and the past sea level height and a future sea level height, determining weighting factors of the past wind stress and the past sea level height in the response function to which the determined optimal length of the time lag is applied, and calculating the future sea level height using the response function to which the determined weighting factors are applied.

The invention relates to the technical field of marine litter monitoring, and discloses a digital traceability method and system for marine waste, and the method comprises the steps: dividing a target sea area according to a preset rule, and obtaining center influence data corresponding to a center detection region and edge influence data corresponding to an edge region; determining a reflection influence degree value according to the center influence data and the edge influence data, then correcting the initial detection image according to the reflection influence degree value and a color correction algorithm to obtain a target detection image, and finally inputting the target detection image into a pre-constructed garbage classification model to obtain a garbage category. Therefore, the reflection effect of the sea level is effectively identified, the detection error is reduced, the identification accuracy of the garbage target is improved, then path prediction is performed through the garbage distribution diagram and the real-time environment data, tracing processing is performed in combination with the preset path inversion algorithm, and the garbage source is accurately tracked.

The invention relates to the technical field of trestle construction platforms, in particular to an offshore lamplight trestle construction platform which comprises a supporting column, a bridge floor is detachably installed at the upper end of the supporting column, limiting seats are fixedly connected to the upper end and the lower end of the supporting column, the outer surface of the supporting column is sleeved with a movable barrel, the outer surface of the supporting column is further sleeved with a balance weight ring, and the balance weight ring is located below the movable barrel. The outer surface of the movable cylinder is sleeved with an auxiliary ring, the outer surface of the auxiliary ring is rotationally provided with a plurality of extension rods, the outer surfaces of the extension rods are sleeved with floating belts, the floating belts can float above the sea level, the movable cylinder automatically ascends and descends along with the sea level under the buoyancy action of the floating belts, and the communication cylinder is kept in isobaric communication with an external water body. The water column pressure formed in the rising process of sea waves and tides can automatically drive the turbofan in the driving barrel to rotate, so that continuous mechanical energy output can be achieved without additional power, and then the cleaning ring is driven to circularly clean the outer surface of the supporting column.

The invention provides an improved ship target distance measurement method and system, and the method comprises the steps: calculating the radial and tangential distortion parameters of a camera and the internal reference of the camera through a camera calibration technology, building a mapping relation through a distortion automatic correction algorithm, carrying out the reverse mapping calculation, carrying out the restoration and filling of vulnerability pixel points, and generating a distortionless correction image. A deep learning model is used to identify a sea level line in a camera video picture, a distortion automatic correction algorithm is used to correct the sea level line into a horizontal straight line, and according to a camera imaging principle, a proportional relation of a tangent function related to a camera lens direction and a sea level angle is constructed. Automatically calculating the installation angle of the camera by using an arc tangent function; and according to the automatically calculated camera installation angle and the pixel point coordinates of the distortionless correction image, the distance between the position of the opposite ship on the corrected sight line video picture and the world coordinate system of the camera is obtained, the ship target distance measurement improvement is realized, and the method has usability and high precision.

The offshore wind power foundation with the scouring panoramic monitoring function comprises a pile foundation and a sensing device, the pile foundation comprises a first foundation section, the first foundation section is located below the sea level, the first foundation section is partially buried below the seabed surface, the sensing device comprises a plurality of sensing assemblies, and the sensing assemblies are connected with the pile foundation. The multiple sensing assemblies are distributed in the circumferential direction of the first foundation section at intervals, each sensing assembly comprises at least one of a vibration sensor, a force sensor, a position sensor and a light sensor, and the vibration sensors, the force sensors and the position sensors are attached to the circumferential wall of the pile foundation. And the light sensor is embedded below the seabed surface. Panoramic monitoring is carried out on the pile foundation through the multiple sensing assemblies distributed in the circumferential direction by adopting multiple monitoring means so that early warning can be carried out in advance, measures can be taken in time to reduce losses, and stable operation of a wind turbine generator and a booster station can be guaranteed.

The invention relates to an East India Ocean sea level height positive anomaly next year ENSO event forecasting method, and the method comprises the steps: employing the mark parameters of the sea abnormally descending Kelvin wave of the tropical East India Ocean during the India Ocean negative dipole event, such as the sea level height anomaly or the subsurface sea temperature anomaly; comprising the following steps: using near equatorial sea level height or subsurface sea temperature abnormity of Indonesian sea or Western Pacific Ocean, or Kelvin wave of East India Ocean obtained through India Ocean wind field, using a regression forecasting model, and using path change of old flow of Pacific Ocean cotton lancea in winter and spring or Western Pacific Ocean west wind outbreak index as a logic switch, and the starting process and the explosion intensity of the ENSO event can be forecasted. According to the method, spring obstacles can be broken through, and the outbreak and the intensity of the El Nino and La Nina events can be successfully forecasted.

The invention discloses a cloud gypsum rock cycle division and sea level lifting reconstruction method and system based on rock electricity response, and the method comprises the steps: carrying out the recognition of a symbiotic sequence of carbonatite and evaporite based on a logging curve, and summarizing the type of a mineral combination sequence on the logging curve; based on the logging curve and the symbiotic sequence type of the carbonate rocks and the evaporative rocks, high-frequency cycle division containing the evaporative rock sequence is carried out on the test well; based on the high-frequency cycle data of the test well, an accumulated deviation value of the high-frequency cycle data is obtained, and a Fischer diagram of the test well is drawn; and sea level lifting curve characteristic comparison data of the test well is further obtained, and cloud gypsum rock cycle division and sea level lifting reconstruction of the test well are completed. According to the method, high-frequency cycle division and strata series comparison in a small area range are completed by using logging rock electricity response characteristics, and a working basis is provided for work such as fine description, development law and reservoir prediction of the inter-salt thin reservoir.

The invention discloses a visual inertial pressure fusion underwater pose estimation method based on bidirectional pre-integration, and the method comprises the steps: employing the obtained visual observation constraint of each key frame; the optimization problem constructed by the IMU pre-integration observation constraint and the pressure gauge pre-integration constraint can efficiently and accurately realize the scale of the system state parameters, the speed of the key frame, the zero offset of the acceleration and the initial value of the distance between the pressure gauge and the sea level, realize the initialization of the system state parameters, facilitate the subsequent parameter updating, and improve the system performance. According to the method, the initial parameter is taken as a starting point, the parameter is updated through the maximum posteriori estimation problem constructed by the IMU pre-integration residual error, the pressure gauge bidirectional pre-integration residual error and the visual reprojection residual error, and the underwater pose estimation can be accurately realized.

The invention belongs to the field of polarization optical transmission and detection. The invention provides a polarization transmission testing device and a polarization transmission testing method for simulating a complex sea fog environment, aiming at solving the problems of unclear seeing, undistant recognition, difficulty in testing and the like during ocean exploration and building an indoor semi-physical simulation platform to research polarization transmission characteristics in the complex sea fog environment. The device comprises a polarized light generation module, a horizontal adjustable rotating table, a complex medium optical environment module and a polarized light receiving and measuring module. The polarized light generation module is used for generating and emitting polarized light with a certain wavelength and a certain polarization state; the horizontal adjustable rotating table is used for adjusting azimuth angle information of emitted polarized light; the complex medium optical environment module is used for simulating an actual medium particle environment above the near sea level; and the polarized light receiving and measuring module is used for measuring and analyzing the received polarized light. And the parameter information is substituted into a Monte Carlo program for analogue simulation to obtain the polarization transmission characteristic of the polarized light transmitted in the complex sea fog environment, so that the simulation of the complex sea fog environment system and the test of the polarization transmission characteristic in the environment are of great significance.

The invention discloses an in-flight tide level control method and system for a drag suction dredger. The method comprises the steps that tide level data are defined based on antenna elevation data; acquiring draft data of different positions of the drag suction dredger; the sea level data and the draught data are synchronized to the unified time scale, synchronization of the sea level data and the draught data in time is achieved, further processing of the sea level data and the draught data is facilitated, and follow-up processing of the sea level data and the draught data is guaranteed. Further, ship installation data are collected, and a vertical distance is defined according to the ship installation data; according to the method, the on-line tide level of the drag suction dredger is defined based on the tide level data, the draught data and the vertical distance, overall consideration of the tide level data, the draught data and the vertical distance is compatible, multi-dimensional control over the tide level data, the draught data and the vertical distance is achieved, accurate control over the on-line tide level of the drag suction dredger is guaranteed, and the control accuracy of the drag suction dredger is improved. And therefore, the accuracy of the drag suction dredger on the sea level is ensured.

The invention discloses a sea surface temperature and sea level anomaly joint prediction method based on cross attention, and the method comprises the steps: constructing a deep neural network joint prediction model, taking collected sea surface temperature SST data and sea level anomaly height SLA data as input, and predicting future SST data and SLA data; the prediction process comprises the following steps: (1) training a prediction model by adopting a training data set; (2) after each training iteration is finished, verifying the prediction model by adopting a verification data set, and storing prediction model parameters with optimal performance; and (3) testing the trained prediction model by adopting the test data set. The prediction model adopts a double-branch structure to extract spatial-temporal characteristics of SST and SLA through a convolutional long-short-term memory network, and dynamic information interaction fusion between two variables is realized by using a cross attention mechanism, so that a coupling relationship between thermodynamics and dynamics is described. The model carries out end-to-end training through a unified loss function, and continuously outputs high-precision and high-consistency prediction results in a long period.

The invention provides an atmospheric delay correction method based on GNSS (Global Navigation Satellite System) high-order horizontal gradient and particle filtering. The atmospheric delay correction method comprises the following steps: acquiring GNSS data; gNSS ZTD is obtained by using a parameter estimation method; determining a mapping function, and correcting the mapping function by using an ETILTING method to obtain anisotropic delay; the GNSS ZTD is corrected by using the anisotropic delay, and the corrected GNSS ZTD is obtained; performing particle filtering on the corrected GNSS ZTD and gradient observation data, and constructing a linear relation model between the observed ZTD value and the height and a linear relation model between the observed GNSS delay gradient parameter and the height; after convolution interpolation is carried out on the regularly-gridded sea level ZTD, the sea level ZTD is projected to an InSAR coordinate, and a neutral atmospheric delay correction model is obtained; subtracting the neutral atmospheric delay correction model from the estimation delay models at different times to obtain a delay difference; and correcting the interference pattern through the delay difference to obtain a corrected interference pattern. The method disclosed by the invention has obvious advantages in the aspects of reducing the atmospheric delay influence and improving the ground surface infinitesimal displacement monitoring precision.

The utility model discloses a portable wave monitor fixing frame, which relates to the technical field of ocean monitoring and comprises a fixing frame, a wave monitor fixing frame, a wave monitor fixing frame body and a wave monitor fixing frame body. The lower end part of the steel pipe is fixedly arranged at the monitoring point seabed, and the upper end part extends above the sea level; a mounting structure for fixing the wave monitor is arranged on the fixing frame, and the mounting structure comprises an adjustable tightening belt and a gland matched with the tightening belt; a limiting ring connected to the steel pipe in a sleeving mode is arranged on the fixing frame. According to the technical scheme, the fixing frame is firmly installed on the seabed through the steel pipe, the structural stability of the whole device is improved through the structural arrangement of the limiting rings and the inclined struts, and displacement or overturning caused by seawater flowing or external impact is effectively prevented. And the fixing frame is mounted in a detachable connection manner, so that the wave monitor can be conveniently and quickly mounted and dismounted, the mounting and maintenance processes of equipment are simplified, and the maintenance cost and time are reduced.

An apparatus and method for predicting sea level fluctuations are disclosed. The method for predicting sea level fluctuations includes: acquiring past time-series data of past wind stress and past sea level height, determining an optimal length of a time lag of a response function representing a convolution relationship between the past wind stress and the past sea level height and a future sea level height, determining weighting factors of the past wind stress and the past sea level height in the response function to which the determined optimal length of the time lag is applied, and calculating the future sea level height using the response function to which the determined weighting factors are applied.

The utility model relates to a new energy photovoltaic support which comprises a floating plate, communication pipes are fixedly arranged at the four corners of the floating plate, installation rods are arranged at the bottom ends of the communication pipes, electric telescopic supports are arranged at the top ends of the communication pipes in a sliding mode, an installation frame is jointly arranged at the top ends of the electric telescopic supports, and pressure relief structures are arranged on the side walls of the communication pipes. The utility model relates to the technical field of new energy photovoltaic supports. According to the new energy photovoltaic support, when the sea surface rises due to rising tide, the floating plate can rise along with the sea surface, the relative position of the electric telescopic support and the floating plate is always kept unchanged at the moment, and the floating plate can rise along with the sea surface, so that the relative position of the floating plate and the sea surface is always kept unchanged; and the distance between the mounting frame and the sea surface is always kept unchanged, so that the problem that seawater is easily splashed on the surface of the photovoltaic panel due to rising of the sea surface during flood tide can be effectively avoided, and the surface of the photovoltaic panel can be effectively protected from being corroded by the seawater.

The invention discloses a shore-based sonar automatic lifting support for a nuclear power station, and the support comprises a mounting support, one side of the mounting support is provided with a telescopic support, and the top end of the telescopic support is provided with a drive motor; a sonar installation hanging basket is arranged at the bottom end of the telescopic support, an ultrasonic liquid level meter is arranged on the telescopic support, a control box is arranged on the installation support, and the control box is electrically connected with the driving motor and the ultrasonic liquid level meter. The problem that when the sea level height changes, sonar cannot accurately detect marine organisms, and consequently the monitoring and early warning effect is poor is solved, the monitoring and early warning accuracy is improved, and it is guaranteed that water enters the water intake of the nuclear power plant smoothly.

The invention relates to a toughness improvement and long-acting management and protection method for maintaining and repairing a beach, and the method comprises the steps: obtaining the landform and environment data of the beach through the remote sensing of an unmanned plane, a shore-based sensor and other means, and evaluating the erosion risks under different storm scenes and sea level rising conditions through an improved model; based on key indexes such as shoreline retreating, beach shoulder elevation and vegetation coverage, the validity period and the failure threshold value of each restoration measure are measured and calculated; a multi-objective optimization algorithm is adopted to comprehensively balance ecological protection, protection efficiency, economic cost and regulatory restrictions, and the measures are deployed in a partitioned and staged manner in space and time; through periodic or real-time monitoring threshold comparison, a subsequent scheme is iteratively corrected in time. According to the invention, through real-time or regular coast power monitoring, multi-dimensional risk assessment, multi-target optimization and a rolling updating mechanism, continuous restoration and high-toughness maintenance of the beach are realized in an uncertain environment.