36 results about "Thermocline" patented technology

The invention relates to the field of ocean observation data processing, and discloses an ocean salinity data correction method based on space-time gradient adaptive filtering, which comprises the following steps of: calculating a motion compensation salinity gradient and a motion compensation temperature gradient; constructing a double-gradient driving filtering window, introducing a gradient sensitive weight distribution strategy, and carrying out adaptive dynamic filtering on the salinity data; generating an initial hyper-parameter combination of the GBDT model; inputting salinity data subjected to adaptive dynamic filtering into the model, optimizing an initial hyper-parameter combination of the model by using a grey wolf optimization algorithm, obtaining an optimal hyper-parameter combination through a dynamic search strategy, and obtaining a final salinity correction value at the same time; and carrying out index verification on the final salinity correction value, and when the salinity does not reach the standard, correcting a model hyper-parameter or a self-adaptive dynamic filtering parameter until the salinity reaches the standard. According to the method disclosed by the invention, the physical abrupt change signal of the spring layer region is reserved to the greatest extent while the noise is suppressed, and the accuracy of salinity profile correction is remarkably improved.

The invention discloses an underwater communication method and system based on adaptive data compression, which is applied to the field of underwater communication, and comprises the following steps: constructing a thermocline change curve of a target communication water area based on multi-source environment data of the target communication water area; an underwater communication path is constructed according to the position information of the data transmitting end and the data receiving end and the multi-source environment data, and attenuation characteristic change curves of the underwater communication path at different depths are simulated through a thermocline change curve so as to calculate a refraction loss value between the data transmitting end and the data receiving end. And determining a high-loss depth interval in the underwater communication path and setting relay nodes, carrying out differential compression parameter configuration on communication segments of the underwater communication path among the relay nodes, and carrying out compression transmission on underwater communication data of the target communication water area based on differential compression parameters. According to the method, the signal transmission problem under different depths and environment conditions can be better solved, and the data compression effect is optimized, so that the communication efficiency is remarkably improved.

The invention relates to the technical field of ocean current data analysis, in particular to a multi-scale modeling and verification method and system based on ocean current spring layer structure analysis. And obtaining the thermocline and halocline parameters of the target sea area and carrying out abnormal value elimination and spatial interpolation to form a thermocline data set. A convolutional neural network is used to extract spring layer space structure features, and based on Gaussian curvature quantification boundary complexity, a thermocline and halocline equivalent geometric model is constructed. On the basis, taking the equivalent geometric model as a boundary condition, and performing multi-scale decomposition on the Navier-Stokes equation set to generate a dynamic approximate equation; and then inputting the approximate equation and the equivalent geometric model into a physical information neural network for constraint training to obtain a multi-scale flow field prediction model, and comparing the multi-scale flow field prediction model with actually measured flow field data to complete verification. According to the method, automation, refinement and multi-scale coupling of spring layer structure modeling are achieved, and scientificity and engineering applicability of ocean current modeling are improved.

The invention discloses a marine environment spring layer characteristic diagnosis data processing method, and aims at complex dynamic characteristics of a land frame edge sea spring layer to realize accurate diagnosis through multi-source data cooperation and an intelligent algorithm. The method comprises the following steps: acquiring and preprocessing field observation, remote sensing, sonar, terrain and tidal ocean current data; extracting spatio-temporal characteristics based on a CNN-LSTM hybrid network, and generating a dynamic spring layer threshold; fusing multi-source data by adopting an improved D-S evidence theory, and constructing a three-dimensional spring layer characteristic field; predicting an internal wave in combination with an attention mechanism model, and optimizing a preorder model by using sonar data. The method breaks through the limitation of a fixed threshold value, realizes spring layer dynamic identification, three-dimensional reconstruction and internal wave prediction, improves the diagnosis precision of a complex sea area, and provides key technical support for underwater detection, engineering safety and environmental research.

The invention relates to the technical field of marine environment monitoring, in particular to a marine aquaculture environment water temperature monitoring system which comprises a dynamic depth adjusting module, a sensor unit, a multi-parameter fusion analysis module, a passive heat shielding module, a heat compensation algorithm module and a central control unit. The passive heat shielding module is used for inhibiting parasitic heat conduction to an internal probe under a strong sunlight condition and comprises a heat flow sensing unit, a composite layer and a heat lag compensation subunit, the heat flow sensing unit collects shell surface temperature rise gradient data in real time, and the heat hysteresis compensation subunit transmits shell surface heat flow data to the thermal compensation algorithm module in real time. Through the synergistic effect of the dynamic depth adjustment module and the thermal compensation algorithm module, the problems of thermocline misjudgment and evaporative cooling pseudo signal interference caused by biological activities are solved, and accurate monitoring of the temperature of the aquaculture water layer and environment regulation and control are achieved.

The invention belongs to the technical field of ocean thermocline prediction, and discloses an ocean thermocline space-time prediction method and system based on thermodynamic constraint. The method comprises the following steps: constructing and preprocessing a data set; constructing an ocean thermocline spatio-temporal prediction model based on thermodynamic constraint, completing extraction of thermocline spatio-temporal features, model training and application, and completing spatio-temporal prediction of future underwater different depth temperatures from a sea surface layer to underwater; and completing thermocline multi-feature space-time extraction according to different underwater depth temperatures obtained through prediction by combining a quasi step function approximation method QFA and a vertical gradient criterion GC sub-region identification strategy. According to the method, physical mechanism constraints are introduced, so that the accuracy of thermocline prediction is improved, the interpretability of the model is enhanced, and space-time prediction from sea surface data to underwater thermocline multi-key features is realized.

The invention relates to the technical field of water distribution regulation and control, and discloses an ecological pond water distribution method based on the Internet of Things and a regulation and control system. The method comprises the following steps: collecting water quality parameters of different depths of an ecological pond through a vertical layered sensor to form a depth gradient data set; quantitatively analyzing the layering state of the water body by using a thermocline recognition algorithm to obtain thermocline position, dissolved oxygen vertical gradient and nutritive salt layering state dynamic variables; comparing the dynamic variable with a preset threshold value, and generating a layering abnormal trigger signal and a target water distribution depth; cooperatively scheduling the multi-depth water distribution equipment, and generating a water distribution execution instruction; executing directional water distribution treatment to obtain water quality improvement effect data and updating the parameter optimization database. The problems that in ecological pond water quality management, the water layering state cannot be accurately recognized, targeted water distribution control is lacked, and the water distribution effect is difficult to quantify and optimize are solved.

The invention relates to the technical field of water quality detection, in particular to a water quality sampling and detecting device for large-water-surface ecological fishery. According to the technical scheme, the device comprises a basic sampling device, a thermocline sampling device and a bottom layer sampling device which are fixed to a table top, the thermocline sampling device is composed of the basic sampling device and at least one telescopic pipe sleeve, and the basic sampling device is movably arranged in the telescopic pipe sleeve in a sleeved mode; the bottom layer sampling device is composed of a thermocline sampling device and at least one telescopic pipe sleeve, and the telescopic pipe sleeve of the thermocline sampling device is movably arranged in the telescopic pipe sleeve of the bottom layer sampling device in a sleeved mode. Through arrangement of the basic sampling device, the thermocline sampling device and the bottom layer sampling device, simultaneous sampling of different water layers of a large water surface is realized, mutual interference is avoided during simultaneous sampling, the risk of mixed pollution is reduced, and each sampling process is actually independent.

This invention belongs to the interdisciplinary field of marine remote sensing technology and artificial intelligence, specifically relating to a deep learning-based method for reconstructing a three-dimensional marine temperature field. The method includes: acquiring multi-source, multi-resolution satellite data and reanalysis data; constructing a sample library after preprocessing; building a three-branch MAUS Transformer model using a U-Net network as the framework, replacing convolutional blocks with Swing Transformer modules embedded in the encoding and decoding paths, and embedding a CBAM attention module to adaptively optimize feature representation. The three-branch model can extract and fuse features at resolutions of 1 / 100°, 1 / 8°, and 1 / 4° respectively; simultaneously, an adaptive loss function is designed to fuse horizontal partitioning and vertical layering, and a weighted constraint based on the real temperature gradient is introduced to reconstruct the thermocline. This invention can output a high spatiotemporal resolution three-dimensional marine temperature field, improving the accuracy, stability, and robustness of the reconstruction, and is of great significance for marine environmental protection, marine data development, marine engineering construction, and marine environmental safety assurance.

The application belongs to the technical field of ocean thermocline prediction, and discloses a thermodynamic constraint-based ocean thermocline space-time prediction method and system. The method comprises the following steps: data set construction and preprocessing; constructing a thermodynamic constraint-based ocean thermocline space-time prediction model, extracting the space-time characteristics of the thermocline, training and applying the model, and completing the space-time prediction of the temperature at different depths from the surface layer to the underwater future; combining the quasi-step function approximation method (QFA) and the vertical gradient criterion (GC) regional identification strategy, and completing the space-time extraction of the thermocline multi-features according to the predicted temperature at different depths. By introducing the physical mechanism constraint, the application not only improves the accuracy of the thermocline prediction, but also enhances the interpretability of the model, and realizes the space-time prediction of the multi-key features of the underwater thermocline from the sea surface data.

The present application relates to a kind of marine Lidar signal noise removal method, device, equipment and medium, method includes: the information sampling of the sea area to be measured generates airborne laser radar signal, through pre-processing eliminates background noise and corrects sea surface fluctuation error, based on fast fourier transform extraction underwater depth profile frequency domain feature, to the amplitude replacement and spectrum reconstruction of electric noise concentrated frequency band, generate noise reduction radar signal, the method provided in the present application overcomes the vertical resolution loss caused by traditional vertical sliding average algorithm and weak signal error filtering problem, by frequency domain filtering replacement technology retains the original data of non-noise frequency band, while removing electric signal clutter, maintain original vertical resolution, effectively capture the microscale marine dynamic information such as thermocline, suspended solids concentration mutation interface and thin layer phytoplankton aggregation, improve marine environment monitoring precision.

The present invention discloses an underwater communication method and system based on adaptive data compression, which is applied to the field of underwater communication. The method comprises constructing a thermocline change curve of the target communication water area based on multi-source environmental data of the target communication water area, constructing an underwater communication path according to the location information of the data transmitter and the data receiver and the multi-source environmental data, simulating the attenuation characteristic change curve of the underwater communication path at different depths through the thermocline change curve to calculate the refractive loss value between the data transmitter and the data receiver, determining the high-loss depth interval in the underwater communication path and setting relay nodes, configuring differential compression parameters for the communication segments of the underwater communication path between each relay node, and compressing and transmitting the underwater communication data in the target communication water area based on the differential compression parameters. The present invention can better cope with the signal transmission problem at different depths and environmental conditions, optimize the data compression effect, and thus significantly improve communication efficiency.

This invention relates to the field of lake and reservoir water environment management and aquatic ecological restoration technology, and particularly to a stratified, ex-situ synergistic ecological restoration system and method for mountainous lakes and reservoirs. The ecological restoration system includes a multi-level exogenous nutrient capture and mineralization system, an endogenous release active inhibition and water quality stratified regulation system, a structure-function synergistic restoration system for water level fluctuation zones, and an intelligent decision-making system based on multi-source data fusion. The ecological restoration method includes exogenous nutrient interception and morphological transformation, stratified, ex-situ synergistic algae control, ecological reinforcement and pollutant blocking in water level fluctuation zones, and robust adaptive regulation of the system. This invention achieves full-chain synergistic restoration of mountainous lakes and reservoirs, especially deep-water lakes and reservoirs, through a multi-integrated synergistic mechanism encompassing "pollution source interception—morphological transformation—thermocline dynamic tracking and targeted oxygenation—long-term regulation of slow-release oxygen-releasing ecological substrates—gradient plant quantitative configuration—composite geotextile impermeable blanket chemical fixation—coupled model predictive proactive regulation," demonstrating promising prospects for widespread application.

The application relates to the technical field of water distribution regulation, and discloses an ecological pond water distribution method and a regulation system based on the Internet of Things. The method comprises the following steps: collecting water quality parameters at different depths of an ecological pond through vertical layered sensors to form a depth gradient data set; quantitatively analyzing the layered state of the water body by using a thermocline identification algorithm to obtain a thermocline position, a vertical gradient of dissolved oxygen and dynamic variables of a layered state of nutrient salts; comparing the dynamic variables with preset threshold values to generate a layered abnormal trigger signal and a target water distribution depth; cooperatively scheduling multi-depth water distribution equipment to generate water distribution execution instructions; executing directional water distribution treatment to obtain water quality improvement effect data and update a parameter optimization database. The application solves the problems that the layered state of the water body cannot be accurately identified, targeted water distribution control is lacked and the water distribution effect is difficult to quantitatively optimize in ecological pond water quality management.

The invention discloses a method for inversely researching a seasonal change rule of the depth of a Sailuer dome thermocline of South Indian Ocean based on artificial intelligence. The method comprises the following steps: acquiring sea surface data of Sailuer dome of South Indian Ocean and global earth-to-ocean real-time observation matrix data, and processing the sea surface data and the global earth-to-ocean real-time observation matrix data; establishing three models, and selecting and analyzing input variables by using the data; selecting a lightweight gradient lifting model, and confirming an input variable; verifying the lightweight gradient lifting model; estimating the change of the isotherm depth at 20 DEG C; and obtaining the seasonal change of the South India Ocean Sailuer dome by using the estimation result. According to the method, the problem that the 20 DEG C isotherm depth is not estimated from sea surface data obtained from satellites by using a machine learning method in the Indian Ocean region in the prior art is solved; the seasonal change of the Sailuer dome of the south India Ocean is reflected through the change of the depth of the 20 DEG C isotherm of the Sailuer dome of the India Ocean estimated by using a lightweight gradient lifting model.

The present application relates to the technical field of flow velocity prediction model construction, and particularly relates to a method for constructing a flow velocity prediction model based on a thermocline adaptive loss. The method comprises the following steps: in the process of shipborne sailing, low-frequency full-water-depth flow velocity background field data and medium-high-frequency target water layer high-resolution flow velocity data are obtained by using a multi-frequency acoustic Doppler current profiler, sound velocity profile data and unified space-time reference data are synchronously obtained, and a multi-source original observation data set is formed; sound velocity gradient data is calculated based on the sound velocity profile data, a thermocline interval is identified, and thermocline structure identification information is generated; under the constraint of the thermocline structure identification information, adaptive layered three-dimensional sound ray tracking calculation is performed on each wave beam measurement unit of the preset multi-frequency ADCP; by means of adaptive layered sound ray tracking and high-frequency detail reservation, the present application overcomes the measurement distortion caused by the dramatic change of sound velocity in the thermocline in the traditional method, and obtains a high-precision flow velocity field of the key water layer.

The invention provides a reservoir thermocline feature forecasting method considering climate and hydrological condition changes, belongs to the technical field of hydrological simulation and hydraulic engineering, and is suitable for a reservoir area without main branch convergence. The method comprises the following steps: collecting and preprocessing a multi-source data set; constructing a drainage basin runoff yield model and a facade two-dimensional water temperature model; main influence factors of the vertical water temperature are screened, and a data set is constructed; on the basis of a production and convergence model, a reservoir water balance equation model and a Copula model, 27 working conditions are designed by considering climate and hydrological elements and a reservoir dispatching coupling relation, and an expansion data set is generated by utilizing a facade two-dimensional water temperature model; an LSTM-BNN neural network model is established to carry out vertical water temperature probability forecasting; the model performance is evaluated and the occurrence time, location, thickness and strength of the quantified thermocline are identified. According to the method, effective expansion of the data set is realized through physical and reasonable working condition combination, meanwhile, redundancy of the training set is avoided, and the problem that the generalization ability of the model is insufficient under a short-series monitoring data scene is solved.

The present invention relates to the field of ocean observation data processing, and discloses a method for correcting ocean salinity data based on spatiotemporal gradient adaptive filtering, comprising the following steps: calculating motion-compensated salinity gradients and motion-compensated temperature gradients; constructing a dual-gradient driven filtering window, and introducing a gradient-sensitive weight distribution strategy to perform adaptive dynamic filtering on salinity data; generating an initial hyperparameter combination of a GBDT model; inputting the salinity data after adaptive dynamic filtering into the model, optimizing the initial hyperparameter combination of the model using a gray wolf optimization algorithm, obtaining the optimal hyperparameter combination through a dynamic search strategy, and obtaining a final salinity correction value at the same time; performing index verification on the final salinity correction value, and when it does not meet the standard, correcting the model hyperparameters or adaptive dynamic filtering parameters until it meets the standard. The method disclosed by the present invention retains the physical mutation signal of the thermocline zone to the maximum extent while suppressing noise, and significantly improves the accuracy of salinity profile correction.

The embodiment of the present application provides a temperature-salinity-depth probe and a temperature-salinity-depth detection system, wherein the temperature-salinity-depth probe comprises a probe underwater part and a probe overwater part, the probe underwater part and the probe overwater part are movably connected and exist communication transmission; the probe underwater part comprises a pressure detection module, which is used for detecting a pressure signal of a water area position where the probe underwater part is located; the probe overwater part receives the pressure signal and outputs. The temperature-salinity-depth probe in the embodiment directly detects the pressure signal of the water area position where the probe underwater part is located by additionally arranging the pressure detection module on the probe underwater part, and then calculates the corresponding depth value according to the corresponding relationship between the water pressure and the depth. Because the corresponding relationship between the water pressure and the depth is relatively constant, the accuracy of the calculated depth value can be ensured.

The present invention provides a thermocline monitoring method based on spectral technology and a thermocline monitoring device based on spectral technology. The method first pre-judges whether a thermocline exists through temperature monitoring points, and then determines whether a thermocline exists through spectral analysis of water quality monitoring points. If so, the height of the thermocline is calculated based on the coordination of temperature monitoring points and water quality monitoring points. The method has high accuracy and can timely and accurately process the thermocline according to the height of the thermocline. For example, an aerator is turned on to fully stir the water body, break the thermocline, and allow the oxygen-rich water body on the surface to be fully mixed with the oxygen-deficient water body on the bottom to increase the overall oxygen content of the water body, thereby effectively reducing the incidence of floating heads when the dissolved oxygen value in the pond is low in the early morning.

The present invention provides a method, device, equipment, and medium for visualizing ocean thermocline data based on PCA-SVM. The method includes: obtaining an initial ocean thermocline data set; performing dimensionality reduction processing on the initial ocean thermocline data based on principal component analysis, filtering the reduced dimensionality data based on a filter control method, interpolating and fitting the filtered data by establishing a BP neural network model, and finally identifying and classifying ocean thermoclines of different depths on the interpolated and fitted data using the established SVM model to obtain ocean thermocline target data; and visualizing the ocean thermocline target data to obtain a visualized ocean thermocline. The present invention greatly improves the accuracy of ocean thermocline data information by performing a series of preprocessing steps on ocean thermocline data, including dimensionality reduction, filtering, interpolation supplementation, and classification training, and solves the problems of insufficient display accuracy and data loss caused by insufficient data information accuracy during visualization.

The invention discloses a deep sea temperature-salinity chain observation system suitable for ocean temperature-salinity-depth observation, and relates to the technical field of ocean observation. Comprising a sea surface positioning control module used for performing positioning, motion control and data receiving on a temperature-salt chain observation module; the temperature-salt chain observation module is used for collecting observation data and transmitting the observation data to the shore-based data center through the sea surface positioning control module; the shore-based data center is used for data processing, data storage and distribution, system monitoring, system command and task planning; the sea surface positioning control module comprises three sea surface positioning beacons, and the sea surface positioning beacons are arranged at different positions of the sea surface of an observation sea area to form a triangular positioning reference network. According to the invention, long-term, layered, fixed-depth and large-range self-adaptive observation of thermohaline of an upper layer ocean spring layer and a middle bottom layer ocean in a specific sea area can be realized, and data can be transmitted back in real time.

The invention provides a high-temperature heat storage system composed of multiple layers of different materials and a method thereof.According to the system, the interior of a heat storage tank is divided into a first heat storage layer, a second heat storage layer and a third heat storage layer, and the heat storage layers are formed by stacking different heat storage media; and heat can be more uniformly distributed in the heat storage tank due to the heat conduction performance difference between different materials, so that the formation of a thermocline in the heat storage tank is inhibited. Meanwhile, heat transfer among different layers is hindered due to material differences, so that the forming speed of the thermocline is slowed down, and the thickness of the thermocline is reduced. And by inhibiting the thermocline phenomenon, the efficiency of the heat storage system can be remarkably improved, the loss is less in the storage and release process, and the economic benefit of the heat storage system is improved.

A system for producing desalinated water from seawater or other saline water, wherein the system comprises the following equipment features or equipment items, in a typical direction of flow: a subsea seawater inlet, a subsea pretreatment stage, at least comprising one or more of a subsea filter and / or a subsea seawater pre-treatment unit and / or a subsea coarse screen unit, and / or a hydrocyclone, a subsea feed pump, fluidly coupled to, a subsea RO unit, a subsea product pump fluidly coupled to a RO unit product outlet, a product line fluidly coupled to the subsea product pump, and a RO unit reject outlet, preferably coupled to a reject line. The system is distinctive in that: the subsea seawater inlet is at a depth below or within the thermocline layer of the seawater, that is below the epipelagic zone, or as close as feasible if the local depth is insufficient to reach the thermocline layer, and wherein the system preferably is without any barrier fluid supply to the subsea pumps.

The application discloses a water body crossing pipeline water distribution system and method, and belongs to the technical field of water body heat storage. High-temperature inlet and outlet water pipes and low-temperature inlet and outlet water pipes are horizontally crossed over the water body and are supported by pipeline support foundations on both banks, and meanwhile, downwardly extending pipes from the middle of the crossing pipeline penetrate through floating heat preservation top covers into the water body to install water distributors, so that the pipeline system is completely separated from the bottom of the water body, and holes need not to be opened on a waterproof and anti-seepage bottom film or underwater concrete foundations are not needed to be built, thereby fundamentally eliminating the risk of seepage at the bottom of the pool, greatly reducing the construction difficulty and engineering cost. In addition, the water distribution mode of the water distributors suspendedly extending into the water body not only ensures that the water distributors stably distribute water in the water body according to a predetermined height to maintain the thermocline, but also effectively isolates the interference of the external environment on the water body, and the reliability, economy and temperature uniformity of the heat storage and cold storage system are improved as a whole.

The invention relates to a group collaboration and environment perception method for a lifting type culture net cage, and belongs to the technical field of lifting type culture net cages. An underwater communication local area network is configured and optimized, and a plurality of environment monitoring buoys are arranged in a culture area; environment monitoring data in the current culture area is monitored through an environment monitoring buoy, a three-dimensional water body environment model is constructed, a fish growth adaptability prediction model is constructed based on a deep neural network, and adaptability data of each depth layer in the current three-dimensional water body environment model is predicted; and finally, selecting an optimal water layer according to the adaptability data of each depth layer in the current three-dimensional water body environment model, and controlling the depth area position of the lifting type culture net cage based on the optimal water layer control cluster. Lifting is adjusted according to habits of fishes, and all the net cages can be instructed to synchronously dive to a proper water layer below a thermocline when the water temperature of the surface layer is too high after the afternoon in summer, so that the fishes are bred in a more excellent environment.

This invention discloses a method for thermoelectric power generation and eutrophication early warning linkage regulation of stratified water intake in reservoirs, relating to the fields of water environment control and synergistic utilization of renewable energy. The method includes: acquiring the upper low-temperature water body and the lower high-temperature water body of the thermocline in the reservoir, and using the temperature difference between the two types of water bodies to generate electricity to power water quality monitoring, early warning and regulation equipment; acquiring water quality monitoring data of the reservoir through water quality monitoring equipment, and outputting the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model; when the chlorophyll a peak index Ic reaches the early warning threshold, adjusting the water intake strategies of the upper and lower layers based on a bi-objective optimization algorithm, and controlling the upper and lower tailwater after power generation to be reinjected in a directional manner according to the reinjection strategy corresponding to the water intake strategy, forming controllable vertical convection and destroying the optimal growth layer for algae.

The application discloses a heavy metal pollution assessment method and system for a gulf marine environment, and relates to the technical field of computer data processing. The method is based on big data analysis, obtains environmental factors from multiple depth sampling points of the gulf water body, and performs sliding window smoothing on the temperature-salinity thermocline parameter offset, obtains a first environmental factor time sequence through feature screening and interaction, obtains the total amount of metals and separates each form component, uses a long short-term memory network for nonlinear mapping and delay alignment to obtain a first metal form distribution feature, extracts a first pollution mechanism feature through toxicity classification, historical pollution sequence time alignment and support vector machine association analysis, performs pollution degree assessment and fuses a regional risk correction term, and finally performs spatial interpolation on the assessment result and superimposes a coastline and a water depth grid to obtain a heavy metal pollution distribution map. The application can accurately analyze the heavy metal form distribution and trace the pollution mechanism under the disturbance of multiple environmental factors, and improves the assessment accuracy.

The invention relates to the technical field of data processing, and discloses a marine environment monitoring method and system based on multi-dimensional information and a storage medium. The method comprises the following steps: constructing a multi-parameter vertical coupling matrix by collecting temperature, salinity and density data of each stratification, calculating a coupling strength weight based on the coupling matrix to generate a vertical stratification observation matrix, monitoring boundary change of a thermocline, and updating adaptive stratification structure parameters. And reconstructing and outputting reconstructed ocean data by using layered structure parameter constraint compressed sensing, and finally fusing parameter layer, layering and time sequence information to output an ocean environment monitoring result. According to the method, the problem that a vertical layered structure dynamic change and a multi-parameter physical coupling relation are ignored in an existing marine environment monitoring method is solved, and a compressed sensing reconstruction method based on adaptive layered structure parameter constraint is constructed.

The invention discloses a self-adaptive frequency measurement and dual-energy management ocean temperature and pressure sensing method, and belongs to the technical field of ocean environment monitoring. In order to solve the problems that an existing ocean temperature and pressure observation device depends on battery power supply, the measurement frequency is fixed, and self-adaptive adjustment cannot be achieved according to the energy state and the environment change, the method comprises the steps that a dual-energy power supply mechanism in which a friction nano-generator and a standby battery cooperate is constructed, and a chained multi-node sensor is arranged to collect temperature and pressure data of different depths; the energy state is judged based on the output state of the energy management module and the voltage of the standby battery, and meanwhile, the vertical gradient and time sequence change of temperature and pressure data are analyzed to identify thermocline and possible ocean dynamic process characteristics; and finally, dynamically adjusting the measurement frequency and the working state of the sensing node according to the energy state and the identified environment characteristic information. According to the invention, long-term stable operation of the sensing system in an energy fluctuation environment is realized, and the energy utilization efficiency and the capture capability of a key ocean process are improved.