19 results about "Thermocline" patented technology

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 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.

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 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 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.

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.

This invention provides a method for monitoring thermal discharge from nuclear power plants based on unmanned aerial vehicles (UAVs), belonging to the field of nuclear power plant thermal discharge monitoring technology. This invention uses a UAV equipped with a far-infrared thermal imaging payload and a lidar payload to acquire dual-band thermal infrared images and underwater thermocline depth data. Multi-scale spatial texture features are extracted and temporally compressed. The initial supplementary intensity coefficient is determined by calculating the jitter function value of the feature patterns. The compression retention rate and supplementary intensity coefficient are dynamically adjusted through adaptive balancing iteration. After three-level supplementation processing of the temporally compressed features, they are input into the three-branch structure of a streaming temperature field inversion model for weighted fusion. The three-dimensional temperature field distribution is inverted by combining the underwater thermocline depth data, and the monitoring sampling frequency is adjusted according to the temperature gradient value. This solves the technical problem of balancing temperature field inversion accuracy and data transmission efficiency under streaming transmission conditions.

This invention provides a method for analyzing the dynamic changes of the nearshore thermocline. Based on temperature profile data of a nearshore sea area obtained from profiling buoys over a period of time, noise reduction is first performed. By comparing the magnitudes of two adjacent depth data points, the depth range of the observed sea area can be extracted. Then, the rising profile data is extracted. Further filtering and processing are then performed to complete the data downsampling and interpolation process. Historical data is matched for temporal and spatial characteristics to obtain corresponding threshold conditions. The thermocline is extracted based on the slope changes of the temperature data and the threshold judgment. Dynamic changes in the thermocline are extracted and stored. Based on the index values ​​of the time and thermocline data, the dynamic changes of the thermocline are visualized. This method realizes the analysis and visualization of the dynamic changes of the nearshore thermocline, solving the problems of accurately calculating the thermocline and conducting dynamic changes analysis of the nearshore thermocline.