11 results about "Water mass" patented technology

The invention discloses a typhoon influence distinguishing method and system based on seawater CO2 partial pressure data, and the method comprises the steps: obtaining sea area situation monitoring data in a target sea area typhoon transit period through a multi-source observation platform, and constructing a standardized data set and a climate state background field; a DBSCAN clustering algorithm is adopted to perform water mass division, and the typhoon characteristic water mass distribution is determined in combination with a Manchester-HuitiniU test and correlation analysis. And calculating a seawater carbon dioxide partial pressure abnormal field based on the climate state background field, constructing a typhoon influence index sequential sequence, identifying a core influence area, and generating a typhoon influence trace path. And then seawater carbon dioxide partial pressure grid point reconstruction is carried out, and a typhoon influence space map is constructed. And finally, analyzing space-time change of carbon dioxide flux of air-sea, evaluating carbon sink stability, and generating a typhoon-carbon sink sensitivity zoning map. Seawater carbon dioxide partial pressure is used as a core index, limitation of a traditional method is overcome, and reliable technical support is provided for typhoon marine environment influence assessment.

The application discloses a marine hydrological dynamic monitoring method and system based on cloud-edge collaboration, relates to the technical field of marine environment monitoring, and comprises the following steps: acquiring temperature-salinity flow time series data, constructing a three-dimensional temperature-salinity matrix, and extracting a space-time gradient vector; encapsulating and broadcasting the space-time gradient vector together with wave energy storage surplus to form a collaborative detection cluster; analyzing a message to divide an abnormal water mass area, extracting a vortex boundary topology point set according to a storage surplus distribution node, and transmitting the vortex boundary topology point set to a main network; fusing an ocean current vector field to deduce a discrete drift coordinate sequence, constructing a triangular net to sweep and generate a time series space flow form envelope of a hydrological anomaly; performing intersection testing on the envelope and a global coordinate library, extracting time evolution depth parameters corresponding to intersection nodes, and issuing an asynchronous wake-up time slot table and a variable-frequency sampling instruction to the detection nodes according to the time evolution depth parameters. The system is used for implementing the above method.

The invention provides an abnormal water mass identification method and system, a storage medium and electronic equipment. The method comprises the following steps: acquiring a sensing monitoring image of a water body in a preset area; carrying out inclined space correction on the sensing monitoring image to obtain a corrected image; performing feature extraction classification and water body flow velocity measurement on the corrected image to obtain abnormal water mass data in the current water body, wherein the abnormal water mass data comprises an abnormal water mass area, a drift velocity and a drift direction; and outputting a water quality evolution process based on the abnormal water mass data, and performing visual display. The method can assist in monitoring section pollutant source judgment by monitoring continuous large-range water quality, realizes flow efficient correction of images in different field application environments by correcting an inclined image space, and meanwhile, realizes accurate detection of abnormal water mass by detecting abnormal water mass. And rapid identification of abnormal water masses in water bodies in different application environments can be realized.

The invention relates to a water mass classification accuracy judgment method, and the method comprises the steps: obtaining target sea area CTD observation data, and carrying out the standardization processing, and obtaining the standardized data; based on a K-means + + clustering algorithm, spatial clustering analysis is carried out on the standardized data with the multi-element features, the optimal cluster number is screened out, and spatial distribution of the water mass is obtained; combining the spatial distribution of the water mass with the multi-element features, and determining the category and spatial distribution of the water mass and the three-dimensional division result of the feature range of each element according to the optimal cluster number; and according to a principal component analysis method, the separation degree and the concentration degree of each type of water mass in a principal component space are detected so as to evaluate the accuracy of a three-dimensional division result. According to the method, three-dimensional water mass classification is realized, the space structure of the water mass in the target sea area can be comprehensively disclosed, the classification accuracy is objectively judged, and the influence of subjective factors on a water mass division result is effectively reduced.

The application discloses a kind of ocean element profile classification method based on clustering analysis algorithm, belong to marine data processing technical field, for ocean element profile classification, including obtaining original ocean element profile sample and pre-processing and standardization;Covariance matrix is constructed to standardization profile, and principal component is selected using cumulative variance contribution rate, and feature vector is constructed;Expectation maximization algorithm is used to estimate Gaussian mixture model parameter;Classification result is verified based on bayesian information criterion and physical interpretability;Ocean structure partition or water mass identification is carried out based on classification result.The application combines principal component analysis with Gaussian mixture model, significantly reduces the calculation complexity while retaining the main vertical variation information of the profile, does not need artificial preset label, has strong adaptability, interpretability and generalizability, can objectively and efficiently complete ocean element profile automatic classification, and is suitable for water mass identification, acoustic environment assessment and other various marine applications.

The invention provides a multispectral remote sensing water quality monitoring method and system, electronic equipment and a medium, and the method comprises the steps that multispectral remote sensing equipment fixedly installed on the basis of a shore base obtains an original water body image of a target water area, and the multispectral remote sensing equipment and the horizontal plane of the shore base are arranged at a preset angle; image splicing and spatial correction are carried out on the basis of the original water body images, corrected images are obtained, and the spatial correction comprises image distortion correction based on camera parameters and oblique image correction based on a perspective transformation matrix; performing water quality parameter inversion based on the corrected image to obtain a water quality monitoring parameter image; performing abnormal water mass identification based on the water quality monitoring parameter image to obtain abnormal water mass parameter information; the abnormal water mass parameter information at least comprises the area, the position and the drifting direction of the abnormal water mass; and performing water quality monitoring based on the abnormal water mass parameter information to obtain a water quality state.

The invention discloses a seawater quality on-line monitoring device and a monitoring method, and relates to the technical field of water quality monitoring. Comprising a detection cabin, the top of the detection cabin is fixedly connected with a fixed seat in a penetrating mode, a water quality monitor is installed in a blocking cover at the bottom of the fixed seat, a first elastic telescopic rod is fixedly installed at the center of the fixed seat, and a partition plate is fixed to the movable end of the first elastic telescopic rod; a triggering assembly is arranged between the sliding rod and the inner bottom wall of the detection cabin, and a sealing plate is fixed to the right end of the sliding rod. By arranging the adjusting assembly, the detection depth can be automatically adjusted according to the flow velocity of seawater, it is ensured that obtained data can represent the real characteristics of disturbed water masses, by arranging the detection cabin, the water inlet, the sealing plate and the triggering assembly, sampling and isolation detection are conducted on a water body at the specific depth, and reading is stable; and the water quality detection sensor is in a closed dry environment in a non-detection period.

The present application relates to the technical field of marine observation and data processing, in particular to a kind of Yellow Sea cold water mass submesoscale structure observation method and its observation system, comprising the following steps: step one: data acquisition;Obtain multiple profile data by the temperature-salinity-depth instrument carried by wave energy profile float, import profile data into observation system, form profile data txt file, as raw data;Step two: feature recognition and three-dimensional reconstruction;Raw data is processed using python program, to obtain temperature-depth-time array and salinity-depth-time array;Feature recognition, analysis and reconstruction of three-dimensional structure of submesoscale phenomenon are carried out jointly, and the observation of the submesoscale structure of the Yellow Sea cold water mass is realized through the reconstructed three-dimensional structure.The present application realizes the dynamic monitoring of the boundary submesoscale process of the Yellow Sea cold water mass by integrating wave energy profile float and satellite remote sensing technology.

This invention relates to the field of reservoir ecological management technology, and more particularly to a reservoir ecological scheduling method, system, and storage medium. The method includes the following steps: acquiring multi-source parameters of the reservoir's vertical profile using a sensor array to obtain an original profile dataset; characterizing the sediment-water mass exchange intensity of the original profile dataset to obtain a comprehensive exchange flux index; stratifying the reservoir according to the comprehensive exchange flux index to obtain a reservoir stratification structure map; performing seasonal-depth partitioning based on the reservoir stratification structure map to obtain a stratified statistical feature set; correlating the stratified statistical feature set with ecological security responses to obtain an ecological security domain map; and analyzing the exchange flux and scheduling constraints based on the ecological security domain map to obtain an exchange flux deviation table and a set of scheduling constraints. This invention provides a scientific scheduling method for the health of the reservoir ecosystem through the synergistic optimization of water level control and stratified water release.

The invention relates to the technical field of ocean observation and data processing, in particular to an observation method and an observation system of a Yellow Sea cold water mass sub-mesoscale structure. The method comprises the following steps: acquiring a plurality of profile data through a temperature-salinity-depth instrument carried by a wave energy profile buoy, and importing the profile data into an observation system to form a txt file of the profile data as original data; 2, performing feature recognition and three-dimensional reconstruction; processing the original data by adopting a python program to obtain a temperature-depth-time array and a salinity-depth-time array; and carrying out feature recognition in combination, analyzing and reconstructing a three-dimensional structure of a sub-mesoscale phenomenon, and observing the sub-mesoscale structure of the Yellow Sea cold water mass through the reconstructed three-dimensional structure. By integrating the wave energy profile buoy and the satellite remote sensing technology, dynamic monitoring of the Yellow Sea cold water mass boundary sub-mesoscale process is achieved.

The application relates to a water mass classification accuracy judgment method, which comprises the following steps: obtaining CTD observation data of a target sea area and performing standardization processing to obtain standardized data; based on a K-means++ clustering algorithm, spatial clustering analysis is performed on the standardized data with multiple element characteristics, an optimal cluster number is screened out, and the spatial distribution of the water mass is obtained; the spatial distribution of the water mass is combined with the multiple element characteristics, the three-dimensional division result of the category, spatial distribution and element characteristic range of the water mass is determined according to the optimal cluster number; and the separation degree and concentration degree of each type of water mass on the principal component space are verified according to a principal component analysis method, so as to evaluate the accuracy of the three-dimensional division result. The application realizes three-dimensional water mass classification, can comprehensively reveal the spatial structure of the water mass of the target sea area, objectively judges the classification accuracy, and effectively reduces the influence of subjective factors on the water mass division result.