424 results about "Oil spill" patented technology

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 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 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 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 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 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 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.

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 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.

The invention discloses a marine unmanned aerial vehicle multi-source data intelligent mining and early warning decision-making system, and relates to the technical field of unmanned aerial vehicles, and the system comprises an unmanned aerial vehicle control module which controls a marine unmanned aerial vehicle group to execute a monitoring task according to a preset inspection route; the multi-source data collection module is distributed on each marine unmanned aerial vehicle and is used for collecting various types of marine data in a target sea area; and the multi-source data integration module is used for integrating various types of ocean data obtained by the ocean unmanned aerial vehicle group and extracting valuable information. According to the invention, comprehensive monitoring and accurate analysis of the oil leakage condition of a target sea area can be realized through cooperation of the modules, potential risks can be found in time, and early warning can be generated; and effective decision support can be provided for countermeasures, and the efficiency and scientificity of petroleum leakage monitoring and processing are improved.

The embodiment of the invention relates to the technical field of computer vision, in particular to a water surface oil spill detection method based on infrared polarization imaging and polarization characteristic enhancement, which comprises the following steps: shooting a target area within a specific observation angle by using an infrared polarization camera to obtain an infrared polarization mosaic image, the polarization information difference between the spilled oil in the target area and the water surface is maximized; inputting the infrared polarization mosaic image into a polarization feature enhancement network for denoising and demosaicing processing to obtain a multi-dimensional polarization information image so as to enhance the contrast ratio of spilled oil of the target area to the water surface; and inputting the multi-dimensional polarization information image into a detection backbone network, firstly extracting oil spill characteristics through a middle layer of the detection backbone network, then carrying out oil spill detection through a detection head of the detection backbone network, and finally obtaining and outputting an oil spill detection result of the target area. According to the method, the precision and speed of water surface oil spill detection are greatly improved.

The invention discloses an underwater oil spill imaging detection method and device based on a polarization correlation algorithm, and relates to the technical field of underwater target detection imaging, and the method comprises the steps: calculating a polarization correlation image based on the horizontal polarized light intensity and the vertical polarized light intensity of a reflected laser signal; obtaining a polarization image based on the polarization correlation image, and calculating linear polarization degrees of different areas; based on the polarization correlation image and the linear polarization degree of the oil spill detection area and the background area, the light intensity value of the reflected laser signal and the light intensity of background scattered light are obtained; calculating a correction factor of the reflected laser signal based on the polarization correlation image and the background scattered light intensity; determining a transmission function based on the polarized light intensity, the background scattered light intensity, the linear polarization degree of the background area and the correction factor; and based on the transmission function, the light intensity of the background scattered light and the light intensity value of the reflected laser signal, determining an image after scattering removal and restoration. According to the invention, the image quality and reliability of sea surface oil spill detection imaging are improved.

The invention relates to the technical field of marine oil spill monitoring, in particular to a seawater oil concentration detection method and system based on a near infrared absorption spectrum. The method comprises the following steps: acquiring spectrum samples with different concentrations of different oil samples; original near infrared spectrums of the spectrum samples under different concentrations are collected; selecting a characteristic wave band based on intensity differences of near infrared spectrums with different concentrations, and extracting spectral data in the characteristic wave band; performing normalization preprocessing on the spectral data in the characteristic wave band; training a deep learning model by using the spectral data in the characteristic wave band to obtain a concentration result; the method can effectively invert the concentration of the oil contained in the seawater, and provides a new method for marine oil spill monitoring and concentration detection of ship oil-containing seawater discharge.

The invention discloses a novel unmanned intelligent sea surface oil spill detection and recovery system based on GPRS network navigation, and relates to the technical field of offshore oil spill recovery, and the system comprises an accident preprocessing module which is used for simulating oil spill by adopting a particle method, predicting the oil spill position and the oil film thickness, marking the probability of oil spill in a nearby sea area and giving out a possible expansion speed, an alarm is given; the spilled oil recovery detection module is used for monitoring and identifying spilled oil on the water surface so as to monitor whether the spilled oil on the water surface in the area is completely cleaned or not; the spilled oil recovery route design module is used for planning an oil spilling ship route according to the oil spilling possible expansion speed; and the spilled oil recovery ship is used for recovering spilled oil in the region based on the route of the spilled oil ship. The oil spill recovery efficiency is greatly improved, and the emergency capacity of ship oil spill accident treatment is improved.

The invention discloses an unmanned aerial vehicle-mounted sea surface oil spill detection system, method, device, medium and product, and relates to the field of sea surface oil spill detection, the system comprises a polarization characteristic detection module, an image fusion module and a data processing module; the polarization characteristic detection module comprises an unmanned aerial vehicle and an image shooting unit; the image shooting unit is connected with the image fusion module; the image fusion module is connected with the data processing module; the unmanned aerial vehicle hovers at a set position according to a set navigation route; the image shooting unit shoots multi-modal images of the sea surface to be detected during hovering, wherein the multi-modal images comprise a visible light intensity image, a visible light polarization image, an infrared intensity image and an infrared polarization image; the image fusion module performs image registration processing, radiation correction processing and image fusion processing on the multi-modal image to obtain a fused image; and the data processing module determines the polarization degree of the fused image so as to determine the oil spill type according to the polarization degree. The sea surface oil spill detection precision is improved, and the false alarm rate is reduced.

The invention discloses a technology for detecting land petroleum oil spill by using a multispectral image of an unmanned aerial vehicle in combination with an artificial intelligence algorithm. According to the technology, a multi-spectral camera is carried by an unmanned aerial vehicle to collect surface oil spill data, and then an improved ResUNet algorithm is used for image processing and target detection. Under the condition of small samples, the method can effectively segment and detect the petroleum leakage area. The method has the advantages of being high in flexibility and precision, capable of rapidly detecting small local oil leakage, suitable for oil spill detection in a complex environment, low in calculation complexity, high in reasoning speed and beneficial to environmental protection and labor cost reduction.

The invention belongs to the technical field of functional material preparation, and particularly discloses a preparation method and application of magnetic super-hydrophobic graphene aerogel based on a biomass template. Loofah sponge fibers are used as a three-dimensional skeleton, and three-component molecular-level coupling of Fe < 3 + > / Cu < 2 + > ions, graphene oxide and a biological template is realized through a pH-regulated electrostatic co-assembly technology; performing solvothermal reaction at 180 DEG C to synchronously complete crystallization growth of hollow CuFe2O4 nanospheres and in-situ reduction of graphene, and finally performing freeze drying to obtain the super-hydrophobic aerogel with a hierarchical porous structure. The specific surface area is increased by 17.5 times compared with that of aerogel prepared by a traditional hydrothermal method; the super-hydrophobic / super-oleophylic characteristic is realized through the surface energy gradient design; an embedded superparamagnetic unit realizes external field driven recovery, and the adsorption retention rate gt is obtained after 20 times of circulation; 92%. The product can efficiently treat emulsified oil wastewater containing a surfactant, and is especially suitable for rapid treatment of metallurgical rolling waste liquid and marine oil spill accidents.

The invention discloses an improved offshore oil spill identification and prediction method, and belongs to the technical field of deep learning methods and neural network models.The improved method comprises the steps that a neural network model is constructed to carry out oil spill area identification, and an image processing method is adopted to divide an oil spill area boundary contour; future environmental data of the oil spill area are obtained, and a diffusion simulation result is obtained through a Lagrange model and drawn. According to the improved method for identifying and predicting the oil spill on the sea, the oil spill area can be automatically identified and segmented from the satellite image, the Lagrange particles are sown on the boundary contour of the oil spill area, the initial state of oil spill is truly simulated, data of a wind field, a flow field and a wave field are corrected, and sea temperature data are predicted; and inputting the data into a Lagrange model to obtain a more accurate oil spill diffusion prediction result.

The invention discloses an oil spill treatment ship based on a multifunctional integrated cabin and application of the oil spill treatment ship, and belongs to the technical field of water surface environment protection. The ship comprises a deck, a cabin body below the deck and a navigation bridge installed on the surface of the deck. The top face and the interior of the navigation bridge are fixedly connected with a camera and a water surface oil spill emergency treatment system correspondingly. A mechanical arm base and a mechanical arm movably connected to the mechanical arm base are fixedly connected to the surface of a deck in front of the navigation bridge, a transverse oil suction roller is fixedly connected to the front end of the mechanical arm, and outward-opening arm unfolding plates are fixedly connected to the positions, on the two sides of the oil suction roller, of the prow; the cabin body is divided into a port treatment area and a starboard treatment area by a longitudinal isolation wall extending along the direction of the cabin body keel; an oil spill recovery cabin and a garbage compression cabin are sequentially arranged in the larboard treatment area from a ship bow to a ship stern; a sand excavation monitoring cabin is arranged in the starboard treatment area; and the stern parts of the port treatment area and the starboard treatment area are isolated to form a shared power cabin, so that a cabin body structure with compact space and integrated functions is formed.