534 results about "Oil spill" patented technology

The invention discloses an emergency prediction and early warning method for an overwater oil spill and hazardous chemical substance leakage accident. The method comprises the following steps: establishing an inland river basic database; constructing an environmental ecological effect model of the oil spill event; biological population changes under the influence of the oil spill event are identified; evaluating the influence of the oil spill event on the ecological system by using an eDNA macro stripe code technology; based on a biostatistics method, analyzing the relationship between the microbial community and the environmental elements; multi-dimensional real-time monitoring and early warning are carried out on an oil spill event; and a targeted sewage disposal scheme and ecological restoration measures are provided. According to the method, aerial remote sensing, ship and shore-based radar, video monitoring and buoy data are combined, multi-dimensional real-time monitoring and early warning of oil spill events are achieved through a multi-source data fusion technology, a traditional method usually only depends on a single data source, the monitoring accuracy and timeliness are improved, and the method is suitable for popularization and application. And after an oil spilling event occurs, a response can be made more quickly, and the damage of the accident to the environment and the economy is effectively reduced.

The invention relates to the technical field of marine oil spill pollution monitoring, in particular to an oil spill monitoring method and system combined with an image analysis processing technology. The method comprises the following steps: S1, acquiring an initial oil spill diffusion path through remote sensing monitoring equipment, extracting a floating ice distribution image in a path coverage area, selecting a floating ice image at the tail end of the path as a reference image, and establishing an adjacent floating ice image matching model; s2, based on the adjacent floating ice image matching model, determining a minimum feature floating ice image through an adaptive pixel threshold algorithm; and establishing an oil-ice complex edge feature matching matrix. According to the method, the recognition precision is improved through multi-feature fusion and a self-adaptive threshold value, oil film permeation and streaming laws are analyzed through multi-scale analysis, a spatio-temporal evolution model is constructed to realize diffusion path closed-loop tracking, phase change nodes are accurately captured in combination with a dynamic verification formula, the environmental adaptability of a complex ice region is remarkably enhanced, and the method is suitable for popularization and application. And real-time early warning and ecological protection decision support is provided for polar region oil spill accidents.

The invention provides an oil film detection method and system based on a hierarchical self-organizing network and scale adaptation, and relates to the technical field of oil film detection. According to the technical key points, the method comprises the following steps: preprocessing an obtained original radar image; performing oil film region identification on the preprocessed radar image by using a trained oil film identification model based on the improved growth layered neural gas network to obtain an oil film candidate region; and segmenting the oil film candidate region by using an improved multi-scale threshold segmentation algorithm to obtain a final oil film detection result. According to the method, a local feature enhancement mechanism, dynamic level adjustment, adaptive error attenuation, sparse constraint optimization and a real-time adaptive learning mechanism are introduced, so that the adaptivity, robustness and calculation efficiency of the detection model are remarkably improved. The method can be integrated in a shipborne radar system, is high in calculation efficiency, can meet the real-time processing requirements of shipborne equipment, and is suitable for practical application scenes such as marine oil spill monitoring and emergency response.

The invention discloses a big data platform system for emergency disposal of overwater oil spill and hazardous chemical substance leakage accidents, and the system comprises a data integration module which is used for collecting and integrating remote sensing data and environmental data from satellites, unmanned aerial vehicles, oceans and meteorological stations in real time; the monitoring module is used for dynamically displaying real-time diffusion conditions and affected areas of spilled oil and hazardous chemical substance leakage; the analysis and prediction module is used for predicting future diffusion paths of oil spilling and leakage based on the collected data by adopting an artificial intelligence algorithm; and the risk assessment module assesses the event risk and provides an emergency response strategy and a resource allocation suggestion. According to the invention, the multi-source data real-time acquisition and integration capabilities of satellites, unmanned aerial vehicles, ocean sensors, meteorological stations and the like are utilized, the data updating speed and the information integrity are improved, the real-time diffusion conditions of oil spill and hazardous chemical substance leakage are dynamically displayed through a map engine and a real-time data processing algorithm, and rapid decision making and resource allocation are supported.

The invention discloses an offshore oil spill emergency decision-making method based on satellite remote sensing and big data analysis, and relates to the field of offshore oil spill management, and the main scheme is that the method comprises the steps: calculating an oil spill confidence index through oil spill authenticity data, and judging whether the region is real oil spill or not based on the oil spill confidence index; analyzing the oil spill hazard data, and calculating an oil spill comprehensive hazard index; performing comprehensive analysis on the dynamic diffusion data to obtain a dynamic diffusion risk entropy; performing comprehensive analysis on the dynamic diffusion data to obtain an emergency response efficiency index; the oil spill comprehensive hazard index, the dynamic diffusion risk entropy and the emergency response efficiency index are compared with thresholds in a comprehensive evaluation threshold set, the severity level of the oil spill event is judged, and a corresponding emergency decision strategy is selected according to the severity level of the oil spill event; the technical problems of inaccurate oil spill authenticity judgment, incomplete oil spill harmfulness evaluation and insufficient dynamic diffusion data utilization are solved.

The invention discloses a multispectral petroleum leakage detection method. The method comprises the following steps: S1, acquiring a multispectral image of a petroleum leakage area by using spectral imaging equipment; s2, the multispectral image is preprocessed, and noise in multispectral data is removed; s3, reducing data dimensions of the multispectral data by using a principal component analysis method, and removing redundant wavebands; s4, extracting a potential petroleum leakage characteristic region from the multispectral image based on an optimized SAM method, and performing ROI recognition through a region growing algorithm; s5, inputting the multispectral image into the optimized YOLO model, and carrying out entry detection and classification; and S6, optimizing a detection result by using an NMS, removing redundant detection through non-maximum suppression, and reserving an optimal detection result. The invention further discloses multispectral petroleum leakage detection equipment and a storage medium. The multispectral petroleum leakage detection method provided by the embodiment of the invention has the characteristics of high precision and high robustness, and is suitable for petroleum leakage detection under a complex background.

The invention discloses a shipborne radar oil spill detection method and system based on an improved whale optimization algorithm, and relates to the technical field of image processing and mode recognition. The method is characterized by comprising the following steps: preprocessing an acquired shipborne radar image; extracting saliency boundary ratio features of the preprocessed image; extracting an ROI image based on the saliency boundary ratio feature; obtaining an optimal segmentation threshold value by using an improved whale optimization algorithm, and segmenting the ROI image by using the optimal segmentation threshold value to obtain an optimal segmentation image; and performing post-processing on the optimal segmentation image to obtain a final oil film image. According to the method, the difference between the oil spill area and the background is highlighted by extracting the significant features; by improving the whale optimization algorithm, the local search capability of the algorithm is enhanced, and premature convergence is avoided. The method achieves the efficient and accurate recognition of the oil film region, can reduce the false detection rate, and is suitable for the detection scenes of different sea conditions and oil spill types.

The invention relates to a ship oil spill emergency response decision method and system based on multi-source data fusion, and the method comprises the steps: collecting multi-source data related to a ship oil spill emergency response decision, and carrying out the preprocessing of the multi-source data, and obtaining the preprocessed multi-source data; based on the preprocessed multi-source data, calculating an environmental risk index of a ship oil spill occurrence sea area; evaluating the emergency resource allocation capability based on the environmental risk index to obtain a resource response capability index; based on the environmental risk index and the resource response capability index, constructing a multi-target route optimization model to obtain a comprehensive decision index; performing dynamic path planning based on the environmental risk index, the resource response capability index and the comprehensive decision index to obtain a path optimization coefficient; and calculating a final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, and executing an emergency response decision. According to the invention, the accuracy and efficiency of ship oil spill emergency response decision can be improved.

The invention provides a marine oil spill emergency resource scheduling method and system based on an improved ant colony algorithm, and relates to the technical field of data processing.The method comprises the steps that on the basis of a modified path transition probability function, multi-target ant colony collaborative optimization is executed on a dynamic resource scheduling architecture, a population is initialized to construct a scheduling path solution, and the scheduling path solution is optimized; calculating a time consumption target and an ecological loss target, iteratively updating pheromone distribution until convergence, and generating a multi-agent non-dominated scheduling strategy; according to a multi-agent non-dominated scheduling strategy, calculating a resource scheduling failure condition probability and an ecological sensitive area damage expected value; and if the scheduling failure conditional probability exceeds a risk tolerance threshold value, an ecological damage expected value is taken as a nonlinear penalty weight, and an anti-disturbance rescheduling mechanism is triggered to generate a flexible scheduling strategy. According to the method, the timeliness and accuracy of emergency resource transportation are improved, and collaborative optimization of'emergency efficiency-ecological protection 'is realized.

The invention discloses a marine oil spill path planning system and method based on multi-source data fusion, and belongs to the technical field of marine environment protection. According to the marine oil spill path planning method, real-time image data of an oil spill area is obtained through a multispectral camera carried by an unmanned aerial vehicle, oil spill thickness, flow velocity and oil contamination component data are collected through multiple sensors carried by a ship, meteorological data such as wind speed, wind direction and sea wave height are obtained, multi-source data are input into a reinforcement learning model, and a marine oil spill path is planned. And data fusion is carried out through dynamic weight distribution, a global optimal path is generated based on fused data, and ship-unmanned aerial vehicle cooperative operation is realized to execute an oil spill recovery task. The system comprises an unmanned aerial vehicle module, a ship module and a ground control module. Experiments show that compared with a ship oil cleaning method which does not adopt multi-source data fusion, the system and the method have the advantages that the path planning efficiency can be improved by 25%, the oil spill diffusion area can be reduced by more than 20%, the recovery efficiency can be improved by 30%, and the response time is less than or equal to 10 minutes.

The invention discloses an oil spill diffusion prediction method and device for realizing dispersant response, relates to the technical field of sea surface oil spill simulation, and aims to solve the problems that oil spill diffusion simulation of an existing oil spill model is not fine enough and cannot support the dispersant response. The method comprises the following steps: acquiring simulation parameters of an oil spilling area and dispersant action parameters; determining a target entrainment probability of the oil spilling area through an entrainment algorithm according to the dispersant action parameters and the simulation parameters; determining the target particle diameter of each oil particle in the oil spilling region by adopting an oil drop particle size formula and a logarithmic normal distribution probability density function according to the dispersant action parameter and the simulation parameter; determining the target position of each oil particle based on the initial position, the simulation parameter, the target entrainment probability, the target particle diameter and an oil spill model; determining a prediction result of oil spill area diffusion based on the target position; according to the oil spill diffusion prediction method provided by the invention, prediction of oil spill diffusion under response of the dispersant can be realized, and the accuracy of a prediction result is improved.

The invention provides an oil spill monitoring system and method capable of automatically adjusting the angle of a light source. The oil spill monitoring system comprises an MCU controller, an ultraviolet light source arranged on the bottom surface of the oil spill monitoring equipment, a light source adjusting mechanism, two groups of fluorescence sensors, a distance sensor and an illumination intensity sensor, the illumination intensity sensor is located between the two fluorescence sensors, and the distance sensor is arranged between the two fluorescence sensors. The distance sensor is located between the light source and the illumination intensity sensor; the light source adjusting mechanism comprises a motor and a transmission mechanism, and the motor is connected with a lamp holder of the ultraviolet light source through the transmission mechanism and controls the ultraviolet light source to rotate; the MCU controller controls the motor and the light source, and in the monitoring process, the motor controls the emission angle of the ultraviolet light source to reach the deflection angle alpha. According to the invention, the illumination intensity is effectively utilized, so that the photoelectric sensor obtains the maximum illumination intensity; the light-emitting ultraviolet LED can be automatically adjusted according to the distance to the water surface, and the oil spilling condition on the water surface can be monitored more accurately.

The invention belongs to the technical field of oil pipe monitoring, and discloses a cruise ship oil pipe oil spill monitoring system and method based on machine learning, and the system comprises a data obtaining module which is used for obtaining cruise ship oil pipe state monitoring data; the data processing module is used for preprocessing the acquired cruise ship oil pipe state monitoring data to obtain an oil pipe state comprehensive feature data set; the oil spill risk prediction module is used for training according to the oil pipe state comprehensive feature data set to obtain an oil spill risk assessment model, and predicting an oil pipe oil spill risk rate based on the oil spill risk assessment model; judging whether the cruise ship oil pipe has an oil spilling risk or not according to the oil pipe oil spilling risk rate; if the cruise ship oil pipe has the oil spilling risk, the oil spilling early warning module carries out graded early warning on the oil spilling risk and triggers a corresponding alarm instruction; the oil spilling source tracking module is used for acquiring oil pipe space position data and positioning an oil spilling position in combination with oil pipe video monitoring data; and comprehensive monitoring and efficient management of the cruise ship oil pipe state are realized.

The invention discloses a marine pipeline leakage point and oil leakage accurate detection system and method, a focused ultrasonic detection module of the system emits ultrasonic focused sound beams to a pipeline wall, a signal acquisition and analysis module is used for receiving an ultrasonic echo signal and performing feature extraction, a fluid noise elimination and compensation module filters and corrects the signal, and a detection module is used for detecting the leakage point and oil leakage of a marine pipeline. The sensor array attached to the pipe wall can monitor the temperature, pressure and environment change of the marine pipeline in real time, the control and feedback unit automatically adjusts the focus depth and acoustic beam energy according to an analysis result, fine scanning and enhanced detection of a target area are achieved, and finally leakage point space coordinates and leakage rate estimated values are output. The system can stably operate for a long time in a high-noise and high-pressure marine environment, is high in detection sensitivity and strong in anti-interference capability, can achieve millimeter-level leakage point positioning precision, and is suitable for online health monitoring and intelligent safety management of marine oil and gas conveying pipelines, offshore wind power cooling systems and deep sea energy channels.

The invention discloses a non-contact coaxial remote water surface oil spill monitoring method and device. The oil spill monitoring device comprises an aircraft and a coaxial optical system arranged on the aircraft. The coaxial optical system comprises a laser emitting mechanism, a telescope mechanism and a reflected signal receiving mechanism. According to the invention, an optical system for oil spill monitoring is optimized, so that the weight of the optical system is reduced, remote monitoring carried by an aircraft is facilitated, the monitoring performance is improved through automatic focusing, and the signal strength is ensured.

The invention discloses a shipborne GNSS-R polar region ice region environment oil spill detection method. The method comprises the following steps: establishing a scattering transmission model of a polar region ice region on seawater, sea ice and oil film surfaces based on a GNSS-R signal; based on a coherent signal and incoherent signal accumulation processing method, an oil film existence area is identified; and carrying out feature extraction on the GNSS-R signal of the sea surface ice-oil mixture, and determining whether the polar region ice region environment spills oil or not. The shipborne GNSS-R polar region ice region environment oil spill detection technology provided by the invention has a wide application prospect. According to the ship-borne GNSS-R polar region ice region environment oil spill detection technology based on the dual-polarized antenna, the problem that targets such as sea ice blocks or oil spill are difficult to recognize can be solved, the detection and recognition accuracy of polar region navigation ice region oil spill can be improved, normalized monitoring of polar region navigation ice region oil spill and self-monitoring of navigation ships can be achieved in an assisted mode, and the detection and recognition efficiency of the polar region navigation ice region oil spill is improved. Technical guarantee is provided for polar region shipping safety, ice region strategic resource development and green and safe development of oil and gas storage and transportation in China, and the method has very important research value and popularization significance.

The invention discloses a satellite-borne synthetic aperture radar marine oil spill detection method and device, a medium and a product, and relates to the field of oil spill detection, and the method comprises the steps: obtaining a satellite-borne synthetic aperture radar image of a marine oil spill region; based on a Faster R-CNN model and a UNet + + model, constructing a marine oil spill detection model; in the marine oil spill detection model, according to a satellite-borne synthetic aperture radar image, a Faster R-CNN model is adopted to determine a candidate frame containing a marine oil spill area; according to a spaceborne synthetic aperture radar image corresponding to the candidate frame, a UNet + + model is adopted to detect the marine oil spill area, and a detection result is obtained; and according to the satellite-borne synthetic aperture radar image of the marine oil spill area, adopting a marine oil spill detection model to obtain a detection result of the marine oil spill area. According to the invention, more efficient and accurate detection of spaceborne SAR marine oil spill can be realized.

The invention provides a sea surface oil spill GNSS reflection signal simulation system and method, and the method comprises the steps: building an oil spill sea surface dielectric constant module, determining the effective dielectric constant of an oil spill sea surface, and obtaining a Fresnel reflection coefficient; establishing an oil spill sea surface rough spectrum module, obtaining a model of a sea wave spectrum of the oil spill sea surface according to a traditional model of the sea wave spectrum and the influence of oil spill on the sea wave spectrum, and obtaining a surface spectral density function and a surface root-mean-square height; establishing a microwave scattering module of the oil spill sea surface, and determining a microwave scattering coefficient according to the Fresnel reflection coefficient, the surface spectral density function and the surface root-mean-square height; a DDM simulation module is established, and a DDM waveform is obtained through simulation according to the GNSS signal parameters and the microwave scattering coefficients; and the DDM waveform is obtained through simulation of each module. According to the simulation system and method, a unified mathematical model is established to describe the relation between the oil film and the GNSS reflection signal, and accurate simulation of the influence of the oil film on the GNSS reflection signal is achieved.

An event chain-oriented offshore oil spill dynamic risk assessment method comprises a data preparation stage, an event chain modeling stage and a dynamic risk assessment stage, and the data preparation stage comprises the steps of A, determining a risk assessment area and a risk assessment unit; the event chain modeling stage comprises the steps of B, oil spill event chain construction and node analysis; the dynamic risk assessment stage comprises the steps that C, from the perspective of quantitative risk assessment, the risk index of a current oil spill event, the vulnerability index of a disaster-bearing body and the risk index of a native event are calculated respectively, and oil spill native event risk assessment is executed; step D, oil spill secondary / derivative event risk assessment; step E, oil spill event chain risk assessment; and step F, carrying out oil spill event chain risk early warning grade division. The evaluation method analyzes and evaluates the influence object of the oil spill event and the risk of secondary / derivative events caused by further disaster due to disaster elements contained in the influence object or the disaster event from the perspective of event evolution.

The invention provides an unmanned aerial vehicle aerial photography petroleum leakage intelligent detection method and system fused with a MobileNetV4 lightweight network, and belongs to the field of petroleum leakage detection. The method aims to solve the problems of low accuracy and high missing report / false report rate caused by excessive background interference, low resolution and noise of a data set in the petroleum leakage detection process. And the model parameter quantity is large and cannot be deployed on the unmanned aerial vehicle equipment. The method comprises the following steps: constructing a petroleum leakage data set, and carrying out data preprocessing; a MobileNetV4 network model is constructed; building an experimental environment, initializing grid parameters, and training a model; and evaluating the effectiveness of the model in petroleum leakage detection through a standard evaluation index. According to the method, the accuracy of petroleum leakage detection can be remarkably improved, the missing report rate and the false report rate are remarkably reduced, meanwhile, the parameter quantity and the calculation complexity of the model are reduced, and real-time detection tasks can be conveniently deployed and efficiently executed on the unmanned aerial vehicle.

The invention discloses a small target detection method and system, the method is specially designed for server-side processing of image acquisition of an unmanned aerial vehicle, the unmanned aerial vehicle is only responsible for image acquisition and transmission, and all image processing and target detection are completed on a server. According to the method, intrusion identification of people and vehicles and early detection of petroleum leakage are divided into two independent modules: for intrusion identification of people and vehicles, an improved YOLOv8 network is adopted; for early detection of petroleum leakage, a ResNeXt network is selected for processing. According to the technical scheme, the small target detection effect in the unmanned aerial vehicle image can be improved, the calculation resources of the model cannot be obviously increased by introducing the module, and the detection performance and the calculation resources can be better balanced; moreover, an effective solution is provided for the current situation that the petroleum leakage detection technology is deficient in the desert environment, the technical blank in the field is filled, and the accuracy of desert petroleum leakage detection is improved.

The invention discloses an oil spill detection method and system based on reinforcement learning and an improved optimization algorithm, and relates to the technical field of offshore oil spill detection. The method comprises the following steps: preprocessing a collected sea surface radar image; performing interest region extraction on the preprocessed sea surface radar image by using a Q-learning reinforcement learning algorithm to obtain an oil film region map; obtaining an optimal segmentation threshold value by using an improved intelligent optimization algorithm, and segmenting the oil film region graph by using the optimal segmentation threshold value to obtain a segmented image based on the optimal segmentation threshold value; and post-processing the segmented image based on the optimal segmentation threshold to obtain a final oil film segmented image. According to the method, the segmentation result of the oil spill image is more accurate, and a reliable foundation is laid for subsequent oil film recognition.

The invention discloses a petroleum pollutant diffusion dynamic tracking simulation method, device and equipment, and relates to the technical field of pollutant diffusion simulation, and the method comprises the steps: determining a multi-dimensional simulation working condition of pollutant diffusion in a target water body region; establishing an unstructured grid hydrodynamic model of the target water body area according to the multi-dimensional simulation working condition; an oil spill prediction model is constructed based on the unstructured grid hydrodynamic model, and the diffusion process of pollutants is simulated according to the oil spill prediction model; if the pollutants are non-soluble petroleum pollutants, the oil spill prediction model is a four-process coupling model including diffusion motion, wind-induced drift, turbulent diffusion and weathering degradation, and if the pollutants are soluble petroleum pollutants, the oil spill prediction model is a convective diffusion model. The simulation precision of the diffusion process and the influence range of the petroleum pollutants can be improved, the simulation precision is improved by 30% or above, and the method is particularly suitable for emergency decision support of closed water bodies such as reservoirs.

The utility model relates to the field of overwater oil spill treatment, and discloses an overwater oil spill robot which comprises a main hull unit, and a camera unit, a radar unit and a mechanical arm unit are arranged on the main hull unit. The camera unit is used for acquiring image data in a preset range of the main hull unit in real time and sending the image data to the control center; the radar unit is used for receiving an echo signal of an electromagnetic beam actively emitted by the radar antenna to obtain an object identification and analysis result and sending the object identification and analysis result to the control center; the mechanical arm unit is used for extracting a detection target when receiving an instruction of allowing extraction of the monitoring target from the control center. The mechanical arm unit comprises a front end claw, a server, a hexagonal linkage wheel, a connecting rod piece, a supporting arm, a disc connecting piece and a right-angle fixing base. According to the technology, people do not need to directly relate to a dangerous water area, the monitoring and cleaning work efficiency is greatly improved, oil contamination can be rapidly and accurately positioned, and larger environmental damage caused by oil contamination diffusion is avoided.

Systems and methods for tracking and remediating oil in a body of water include monitoring the data from the satellite for indications of an oil spill. In response to determining that the indications of oil spill are present, assessing whether criteria for triggering a forecasting process are met. In response to determining that criteria for triggering a forecasting process have been met, running a forecasting process including: (i) delineating polygons where oil is determined to be present based on the data from the satellite; (ii) receiving meteorological and hydrodynamic data for the body of water; (iii) running a trajectory model using the polygons as initial conditions for the oil spill to forecast future locations of the oil spill; and sending instructions to a vessel in the body of water.

The invention provides a sea surface oil spill monitoring system based on a GNSS-R receiver. The sea surface oil spill monitoring system comprises an unmanned aerial vehicle platform, the GNSS-R receiver, a signal processing module, an oil spill feature extraction module, a data storage and transmission module and a ground station data processing module, wherein the GNSS-R receiver, the signal processing module, the oil spill feature extraction module and the data storage and transmission module are installed on the unmanned aerial vehicle platform and connected in sequence. According to the system, the GNSS-R receiver acquires the GNSS scattering signals on the surface of the ocean by acquiring the reduced polarization, the requirements of independent inversion and application of parameter inversion of typical disasters of the ocean can be effectively met, the GNSS-R receiver supports multi-band and multi-polarization GNSS scattering signal receiving, the oil spill detection precision and reliability are improved, and the reliability of the system is improved. And high-precision oil spill detection can be realized under complex meteorological conditions.

The invention discloses a marine radar oil spill target segmentation method and system, and relates to the technical field of target segmentation. The method is characterized by comprising the following steps: preprocessing a shipborne radar image; the preprocessing comprises the step of carrying out convolution on the shipborne radar image by adopting a Laplacian operator; an Otsu algorithm is adopted to segment the image after convolution, and same-frequency interference noise is extracted; smoothing the same-frequency interference noise by means of mean filtering to obtain a preliminary smoothed image; segmenting the preliminary smooth image by using a gray threshold algorithm and a pixel area threshold method, and extracting block noise; smoothing the block noise by adopting a dynamic window and distance weighted median filtering to obtain a denoised image; and segmenting the denoised image by using an improved Phansalkar local threshold method, and extracting an oil film. According to the method, the oil spill target features are more prominent by effectively suppressing noise, so that the accuracy of oil spill detection is remarkably improved, and the actual requirements of effective region extraction in the field of oil spill detection in marine radar images are met.

The invention discloses a marine oil spill quantity estimation method and system based on image depth analysis and a medium, and relates to the technical field of image data analysis, and the system comprises a time period analysis module, an image data processing module and a diffusion analysis estimation module. The output end of the time period analysis module is connected with the input end of the image data processing module; and the output end of the image data processing module is connected with the input end of the diffusion analysis and estimation module. Aiming at still water experiment analysis of marine oil spill, a brand new analysis processing direction is provided, under different characteristic conditions, motion characteristic, rule and trajectory analysis in a related complex dynamic condition environment is achieved, prediction diffusion range estimation of marine oil spill is formed, and therefore influences are accurately judged and decisions are made in advance.

The invention belongs to the technical field of environmental monitoring, and particularly relates to a real-time marine oil spill monitoring system based on an FPGA. The system comprises an FPGA unit, and a sensor unit and a camera module which are connected with the FPGA unit. The sensor unit at least comprises a visible spectrum sensor, an ultraviolet sensor and a thermal imaging sensor; the FPGA unit performs data fusion on the monitoring data obtained by the sensor unit to obtain the state of the oil spilling area; image data acquired by the camera module are processed, the type and area of oil spilling are recognized, and oil spilling events in the ocean are monitored and recognized in real time. According to the oil spill monitoring method, visible spectrum, ultraviolet rays, thermal imaging and image data can be comprehensively utilized, the oil spill edge is recognized in real time, the oil spill area is calculated, different oil products are classified, the accuracy of oil spill monitoring is improved through data fusion and an image processing algorithm, and the real-time performance and adaptability are remarkably improved.

The invention particularly relates to a sea surface oil spill identification and oil-like film target distinguishing method based on an optical flow method. The method comprises the following steps: acquiring a plurality of frames of time sequence remote sensing images including a seawater oil spill area; based on the first coordinate corresponding to the suspected oil spill area of the previous frame of time sequence remote sensing image, using a maximum absolute value error criterion to obtain a second coordinate corresponding to the suspected oil spill area of the next frame of time sequence remote sensing image; calculating a moving vector between the first coordinate and the second coordinate to obtain an optical flow speed of the suspected oil spill area; performing adaptive clustering on each suspected oil spill area by adopting a mean shift algorithm, and outputting optical flow features of each suspected oil spill area; and analyzing the optical flow characteristics of each suspected oil spill area, and judging the actual seawater oil spill area. According to the method, the motion characteristics of the oil film and the oil film-like target in the time sequence remote sensing data are analyzed, the oil film and the oil film-like target are distinguished, false positive and false alarm during oil spill identification are effectively reduced, and the oil spill identification precision is improved.