113 results about "Smoke plume" patented technology

The invention discloses an automatic control system and method for sludge treatment, and relates to the technical field of sludge treatment, an environment state feature vector F is collected in real time through an integrated sensor, an odor concentration prediction result vector Cpred at different time points in the future is calculated based on a dynamic odor diffusion prediction model, and then the concentration trend is predicted in combination with the prediction result vector Cpred. The decision vector D of the addition amount of the additive is dynamically adjusted, the limitation that in the prior art, addition control is conducted only depending on real-time odor concentration feedback is broken through, and the problem of addition lag is effectively solved through combination of the Gaussian plume diffusion model and the time sequence prediction method. Meanwhile, benefit index E evaluation is carried out through the adjusted concentration vector Cafter and the odor concentration change vector Gafter, so that the addition strategy is optimized based on the concentration change trend, factors such as the use cost of an auxiliary agent and the odor diffusion stability are fully considered, and the defect that the deodorization effect and the cost are difficult to balance by the addition amount in a traditional method is overcome.

According to the spectrum-to-mass concentration imaging method and device based on physical mechanism deep learning provided by the invention, the actually measured spectrum and the reference spectrum of the pollution gas smoke plume are collected, the spectrum data set is constructed after differential processing, the meteorological data and the online mass concentration label are synchronously collected, and meanwhile, the spectrum-to-mass concentration imaging method and device based on physical mechanism deep learning are provided. A high-resolution gas absorption section is obtained and is convolved into a matrix; and constructing a deep learning model fusing a feature extraction module, an expanded least square module and a full connection module, taking the spectral data set, the meteorological data and the absorption cross section matrix as input, performing training in combination with labels to obtain an optimization model, and predicting the mass concentration of the target gas. According to the method, the problems of error accumulation, low calculation efficiency and poor interpretability caused by dependence on a complex physical model in a traditional method are solved, and high-precision, high-efficiency and interpretable real-time imaging of the mass concentration of the smoke plume of the pollution gas is realized.

The invention discloses a pollution source dynamic tracing method and equipment for industrial park hidden gas leakage. Comprising the following steps: acquiring meteorological monitoring data at each observation point through fixed monitoring equipment and / or mobile monitoring equipment; correcting the coordinates of the observation points; predicting a first gas pollutant predicted concentration corresponding to each observation point after coordinate correction according to a Gaussian plume diffusion model; inputting the first gas pollutant predicted concentration and meteorological monitoring data into a CatBoost model to obtain a second gas pollutant predicted concentration; taking the difference between the actual gas pollutant concentration at each observation point and the second gas pollutant predicted concentration as a target function, and solving the target function to obtain the pollutant source intensity and the source position; completing one iteration; and setting the observation point near the current predicted pollutant source position, and so on, and obtaining the final pollutant source intensity and source position after n iterations.

The invention provides an off-site full-range radiation risk evaluation method and system under a severe accident of a nuclear power plant, and the method comprises the steps: S1, building a radioactive accident risk evaluation basic model architecture, adapting to a model demand, and building a corresponding basic database; s2, constructing radioactive smoke plume characteristics after the accident; s3, calculating accident site space gridding and smoke plume transmission discretization; s4, sampling meteorological conditions, and simulating smoke plume transmission; s5, calculating the radiation dose in the early stage of the grid domain, and carrying out risk assessment; s6, performing risk assessment on the health effect in the early stage of the grid domain; s7, calculating the medium-and-long-term stage radiation dose in the grid domain, and performing dose risk assessment; and S8, performing health effect risk assessment and accident consequence assessment in the medium-and-long-term stage. According to the method, the whole transportation process of the radioactive smoke plume under a serious accident is simulated, loss effects such as dry and wet settlement and radioactive decay of the smoke plume are considered, and the activity of the radionuclide deposited on the ground and retained in the air in the off-site space range is determined.

The invention relates to the technical field of forest fire monitoring and power grid safety prevention and control, and discloses a fire scene spreading time sequence reconstruction method based on Doppler weather radar mountain fire echoes, which comprises the following steps: acquiring original data of the Doppler weather radar mountain fire echoes and carrying out quality control processing to obtain radar echo data; performing automatic segmentation of a smoke plume area on radar echo data by adopting an optimized Otsu-Unet network model, and extracting a centroid coordinate of a mountain fire echo area; a Kalman filtering algorithm is used and combined with external three-dimensional wind field data to predict a future motion trend of centroid coordinates of a forest fire echo region so as to reconstruct a continuous fire scene spreading time sequence voxel sequence; performing 3DTiles slicing processing on the fire scene spreading time sequence voxel sequence, and performing real-time rendering display on a power grid monitoring platform by using a WebGL technology; and obtaining an external expansion boundary of fire scene spreading based on the fire scene spreading time sequence voxel sequence, and calculating the distance between the external expansion boundary and the power transmission line GIS data in real time. The fire prevention and control capability of the power transmission line of the power grid is improved.

The invention relates to a tunnel toxic gas detection method, device, equipment and system and a storage medium, and belongs to the technical field of information detection.The method comprises the steps that concentration measured values of multiple toxic gases collected by multiple gas sensor nodes in a tunnel are obtained; inputting the concentration measurement values of the various toxic gases into a linear minimum mean square error estimation model, and outputting the position of a gas leakage source and an estimated value of a gas release rate; inputting the estimated value of the gas leakage source parameter into a gas diffusion model, and outputting a gas diffusion parameter; the gas diffusion model is a static smoke plume gas diffusion model based on turbulence diffusion, and the gas diffusion parameters comprise the diffusivity of a gas leakage source; and inputting the estimated value of the gas leakage source parameter, the gas diffusion parameter and the standard-exceeding concentration threshold value of the toxic gas into a finite element prediction model, and outputting a toxic gas standard-exceeding prediction result. According to the invention, continuous monitoring and dynamic early warning of the toxic gas in the tunnel can be realized.

The invention discloses a background spectrum accurate acquisition method for infrared remote measurement in a complex scene, and the method comprises the steps: carrying out the division of sky and ground object backgrounds for an input background image, and selecting different radiation spectrum generation modes based on a division result; if yes, sky radiation spectrum extraction is carried out based on an MODTRAN radiation transfer model; if the background is judged to be a single ground object background, performing background spectrum extraction by adopting ELM-EMD (Extreme Learning Mode-Empirical Mode Decomposition) which is extracted in real time based on a measurement spectrum and changes slowly at low frequency; and if the background is not single, fusion of the two spectrum extraction modes is adopted. The method has the advantages that the background classification method with the visible image as the reference is adopted, the difference of infrared radiation characteristics of the sky background and the ground feature background is analyzed, different spectrum extraction modes are selected according to the difference, and therefore accurate obtaining of the target smoke plume transmittance spectrum is achieved.

The invention relates to a pollutant monitoring method, device and equipment based on multi-point source superposition diffusion, and belongs to the technical field of atmospheric pollutant diffusion analysis. The latitude and longitude coordinates of the emission source, the evaluation point and the evaluation area are represented by a geographic coordinate system, and the latitude and longitude coordinates are converted into plane coordinates under a projection coordinate system; a two-dimensional rectangular grid is adopted to cover an evaluation area, and a continuous space is discretized into a plurality of grid units; establishing a reference coordinate system and a diffusion coordinate system; the constructed Gaussian plume diffusion model is adopted to calculate pollutant concentration data of each emission source to each grid point, concentration contributions of the multiple emission sources are superposed, and total concentration data of the grid points are obtained; and enabling the pollutant concentration data of the evaluation point to be equivalent to the function output of the total concentration data of one or more grid points in the grid unit where the evaluation point is located, so as to obtain the pollutant concentration data of the target position. The invention provides a refined technical scheme for pollution diffusion simulation of complex multi-point sources.

The invention relates to the field of data processing, in particular to a smart city data processing method and system based on big data, and the method comprises the steps: dividing a city region into a plurality of sub-regions, and setting a plurality of monitoring points in the city region; the diffusion fluctuation degree in each sub-region is calculated, wherein the diffusion fluctuation degree represents the influence degree of the sub-region buildings on pollutant diffusion; adjusting diffusion parameters in the Gaussian plume model by using the influence degree to obtain an optimal diffusion coefficient, and obtaining the monitoring concentration of each monitoring point; setting the initial position of a pollution source, calculating the estimated concentration of pollutants at each monitoring point by using a Gaussian plume model, and calculating the difference between the estimated concentration and the monitored concentration; and updating the initial position of the pollution source, and taking the position of the pollution source when the difference is minimum as the final position of the pollution source. According to the invention, precise positioning of the gas pollution source is realized.

The invention discloses a wide-area gas traceability method and device based on multistage sensing asynchronous cooperative triggering, a medium and a product, and relates to the field of wide-area gas leakage traceability, and the method comprises the steps: carrying out the adaptive three-dimensional grid division of a to-be-detected region; environment background information is detected; smoke plume discovery is carried out by adopting a random walk strategy and introducing a weight avoidance mechanism; determining a threshold value of binary detection according to the mean value of the environment background noise, and carrying out binary calculation on the sampled data; determining a near-field region according to a binary calculation result; performing concentration tracking according to the near-field region, and performing near-field state evaluation in real time; adjusting the size of the near-field region according to an evaluation result; continuously judging whether to exit the concentration detection of the near-field region; when the concentration detection of the near-field area is quitted and switched to the far-field area, a binary detection cycle is entered; determining a concentration peak value according to the concentration detection data of all the near-field regions; according to the invention, efficient, accurate and low-cost pollution source positioning in a complex wide-area environment can be realized.

1. The name of the design product: white smoke elimination equipment (magnetic energy white elimination). 2. The use of the design product: separate the fine droplets and particulate matters in the flue gas, thereby achieving the effect of reducing the white smoke plume in flue gas emission. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view. 5. The bottom surface of the design product is the part that is not easy to see or cannot be seen during use, and the top view is omitted.

The invention relates to the technical field of toxic gas risk prediction of electrochemical energy storage boxes, in particular to an electrochemical energy storage box toxic gas risk prediction method based on multi-model fusion, which comprises the following steps: searching a preset number of similar transportation scenes in a preset weight scene library, obtaining preset optimal weights of the box-type model, the Gaussian plume model and the machine learning model in a preset number of similar transportation scenes; performing interpolation calculation based on a preset optimal weight and the similarity corresponding to the similar transportation scene to obtain target weights of the box-type model, the Gaussian smoke plume model and the machine learning model, and performing weighted summation based on the target weights to obtain target diffusion data; and obtaining a toxic gas risk prediction result of the electrochemical energy storage box at least based on the target diffusion data. Therefore, by fusing the box type model, the Gaussian plume model and the machine learning model, the accuracy and reliability of toxic gas risk prediction of the electrochemical energy storage box are improved.

The present application relates to a kind of white plume removal energy-saving control method and system, belong to the device field of handling smoke and waste gas.By control module, the real-time change of air parameter is collected, using air saturation humidity database, air temperature-enthalpy / density calculation model, establish white plume removal system operating cost mathematical model.According to the constantly changing atmospheric conditions, slagging condition etc., with operating cost as optimization goal, determine the best exhaust point, the best operation combination, using numerical analysis to seek global optimal solution, make actual operation curve quickly approach optimal curve, to adjust air cooler fan frequency, then on the basis of not affecting white plume removal effect, maximize the energy consumption of white plume removal is reduced, and make actual operating cost minimum.

The invention discloses an emergency sampling and monitoring system and method for flue gas discharged by a torch, and relates to the technical field of flue gas collection and monitoring. A sampling control unit is installed on a detection positioning module in a sliding mode, the detection positioning module achieves movement of the sampling control unit through rotation, an infrared thermal imager is installed on a movable detection platform and used for detecting the smoke plume track, and a concentration detection unit is installed on the sampling control unit in a sliding mode and moves along the peripheral side of a torch. The PID sensors are used for detecting VOCs concentrations at different positions of smoke plume, the heat preservation collection box is connected with the vehicle-mounted analysis unit through a smoke tracing pipe, collection pipelines are arranged between the smoke collector and the concentration detection unit, each PID sensor corresponds to one collection pipeline, and the smoke collector collects smoke at an optimal sampling point into the heat preservation collection box through the collection pipelines. Through the pre-stored gas sampling monitoring mode, the influence on the smoke sampling monitoring process caused by the smoke plume track change can be effectively avoided.

The present invention provides a method, system and storage medium for monitoring urban sanitation buildings based on big data technology, including: inputting pollutant emission concentration, humidity of the area where the sanitation building is located, real-time wind speed and real-time wind direction in the area where the sanitation building is located into an improved Gaussian plume model to obtain the pollution degree of various pollutants to the area where the sanitation building is located; determining the average impact degree of various pollutants emitted by the sanitation building on the regional population in combination with the population size and pollution degree of the area where the sanitation building is located; determining the environmental impact index of the sanitation building according to the real-time weights corresponding to various pollutants in the attributes of the area where the sanitation building is located and the average impact degree of various pollutants on the regional population; if the environmental impact index of the sanitation building is higher than the set threshold, generating a maintenance work order, and sending the maintenance work order to garbage transfer equipment or maintenance equipment in the sanitation building.

This invention discloses an online assessment system, method, equipment, and medium for visual pollution and transparency of emission plumes based on image recognition. The system includes: an image acquisition module for continuously capturing images of the plume at the chimney outlet; an image preprocessing module for receiving pollutant concentration data from a continuous emission monitoring system; an intelligent assessment module for extracting visual features of the plume from the preprocessed images and outputting plume opacity level and morphodynamic characteristics; and a correlation analysis module for receiving the plume opacity level, morphodynamic characteristics, and pollutant concentration data, performing correlation analysis by calculating correlation coefficients, and determining whether emissions are abnormal based on a multivariate model. This invention achieves real-time online monitoring of emission plumes by continuously capturing images of the plume at the chimney outlet through the image acquisition module, overcoming the limitations of manual visual inspection in terms of time and space.

The application discloses a kind of wild fire smoke cluster and its boundary vector automatic identification method, system, storage medium and electronic equipment, belong to satellite remote sensing and disaster monitoring technical field.Method includes: obtaining satellite active fire point, fire event and UVAI data;Fire source area is positioned based on fire event geographic location and initial plume pixel is marked;The spatially continuous smoke cluster connected domain is identified by iterative region growing algorithm;According to the specific distribution form of connected domain pixel in satellite pixel matrix, the accurate closed boundary vector is automatically generated using matching geometric algorithm;Finally, using multiple criteria, the spatial isolated independent smoke cluster is screened out.The application avoids the defects that traditional image method is easily disturbed by environment from physical principle, realizes fully automated processing without training data, and can output vector boundary that can be directly used for diffusion and emission evaluation, significantly improves the accuracy, automation degree and application value of wild fire smoke cluster monitoring.

The invention discloses a gas leakage concentration prediction method and system based on an improved Gaussian plume model, belongs to the technical field of data processing, and aims to solve the technical problem of how to improve the accuracy and reliability of gas leakage concentration prediction. Comprising the following steps: selecting an adaptive grading calculation strategy from a multi-modal aperture adaptive leakage speed grading calculation model based on a leakage aperture, and predicting and calculating the leakage intensity of a pipeline based on the selected grading calculation strategy; an improved intelligent Gaussian plume model is constructed by introducing a logistic time growth function, a wind speed segmented intelligent compensation mechanism, diffusion coefficient lower limit constraint and concentration physical amplitude limiting, and for a gas leakage pipeline, the wind speed and the leakage intensity corresponding to the pipeline are used as input; and the diffusion concentration and the diffusion distance of the output leaked gas are predicted through the improved intelligent Gaussian plume model.

The application discloses a forest and grassland fire smoke and fire point simultaneous detection method. The method obtains visible light and infrared band images of a target area, registers and synthesizes into multi-band synthetic data; the data is input into a pre-trained multi-modal smoke and fire simultaneous detection network for feature extraction, the network adopts a feature fidelity down-sampling module containing a fixed kernel low-pass filter and average pooling during down-sampling, and is combined with a cross-layer connected background suppression and smoke and fire focusing module, a multi-scale smoke and fire shape perception module and a smoke and fire space information rearrangement amplification module for joint processing; finally, according to the feature channel set, the smoke and the fire point area are respectively located, and a fire monitoring distribution map is generated by superposition. The application realizes the simultaneous detection and mutual verification of multi-modal features of smoke and fire, effectively overcomes the loss problem of small fire points and smoke plume details, and improves the accuracy of early fire warning.

The present application relates to the technical field of image enhancement, in particular to a remote sensing image enhancement method for forest fire monitoring, which specifically comprises the following steps: firstly, pre-processing multispectral images, digital elevation models and fire point labels to obtain multi-source training samples; then, performing differentiated enhancement on different bands in combination with terrain shadow intensity, normalized burning ratio and short-wave infrared local anomaly response; then, generating a spatially restricted fire line expansion area based on wind direction, slope direction and vegetation conditions, and performing thermal radiation enhancement and smoke plume shielding modulation to obtain physically simulated augmented samples; finally, constructing a double-branch dynamic receptive field network for decoupling fire points and smoke, and jointly training the network using focal loss and boundary consistency loss, and outputting a pixel-level fire danger probability map. The present application can improve the detection accuracy of forest fires under complex terrain and the enhanced results can be directly used for fire point detection or auxiliary manual interpretation.

The utility model relates to the technical field of flue gas treatment, in particular to a wet-type electric precipitation energy-saving efficiency-increasing modified coupling waste heat recovery smoke plume deep treatment device. Comprising a reactor, and an emission reduction skid, a heat exchange skid and a circulating water skid are sequentially arranged in the reactor from top to bottom; a spraying device is arranged above the emission reduction skid; the circulating water skid is connected with the spraying device; a flue gas inlet is formed in the top of the reactor; and a flue gas outlet is formed in the reactor between the heat exchange skid and the circulating water skid. By integrating the waste heat utilization and water resource recycling technology, the functions of desulfurization, dust removal, denitration synergism, waste heat and condensate water resource recycling and smoke plume comprehensive treatment are synchronously achieved, an original high-energy-consumption and high-water-consumption environment-friendly device is upgraded to an energy-saving integrated facility, and the operation cost is converted from rigid expenditure to continuous earnings; the integrated design is adopted, and the comprehensive advantages of being small in occupied space, low in investment cost, small in operation energy consumption and high in energy-saving benefit are achieved.

Title of the invention: Chimney for plume reduction in a CO2 capture installation. A chimney for venting gas from a CO2 capture installation comprises an elongated hollow body open upwards to the atmosphere and means for bringing the NO2-containing gas into the elongated hollow body, the body comprising means for diluting the gas by mixing it with atmospheric air. No figure

The utility model relates to the technical field of thermal boiler production, and discloses a thermal gas-fired boiler regular-discharge steam recovery device which comprises a boiler regular-discharge flash tank. The air outlet pipe is communicated with the top of the boiler periodic blowdown flash tank, a heat exchanger is installed at the top end of the air outlet pipe, an exhaust pipe is arranged above the heat exchanger, and an extension pipe is communicated between the heat exchanger and the exhaust pipe; according to the utility model, the heat exchanger is additionally arranged at the exhaust port of the existing boiler periodic blowdown flash tank and is matched with the recycling mechanism for use, so that the waste heat of boiler blowdown dead steam is effectively recycled, the energy utilization efficiency is improved, the operation cost is reduced, and the dead steam is condensed in the heat exchanger to form high-quality condensed water; and the preheated demineralized water enters the deaerator, so that the steam demand is reduced, the deaerator operates more stably, the phenomenon of white smoke plume caused by direct discharge of dead steam can be eliminated, and the factory environment is improved.

The utility model discloses a flue gas water heat recovery and flue gas white smoke elimination device for a power plant. A centrifugal fan communicates with outside air; the flue gas heater is provided with a flue gas inlet and a flue gas outlet, and the flue gas inlet is communicated with the centrifugal fan; the steam generator is provided with a steam outlet, and the steam outlet is communicated with the flue gas outlet of the flue gas heater through the mixer; the heat exchanger is provided with a gas inlet, a gas outlet, a water inlet, a water outlet and a liquid outlet; the gas inlet is respectively communicated with the flue gas outlet and the steam outlet through the mixer; the circulating water tank is respectively communicated with the water inlet and the water outlet; and the condensation water tank is communicated with the liquid outlet. According to the device, the centrifugal fan and the flue gas heater simulate a power plant to provide high-temperature flue gas, the high-temperature flue gas is humidified through the steam generator and the mixer to form saturated wet flue gas, the saturated wet flue gas is subjected to heat exchange through the heat exchanger, and the saturated wet flue gas is dehumidified and cooled through cooling water, so that water in the flue gas is recycled; meanwhile, white smoke plume is eliminated.

The application provides a method for automatically identifying smoke plumes of global large point sources based on satellite data, which is based on the column concentration data retrieved by high-resolution satellite remote sensing, selects the region around the global large point source as the research region, and obtains the local concentration enhancement data by deducting the background concentration from the original column concentration. The best global segmentation threshold in the research region is obtained, and the median of the foreground pixels is further taken as the final threshold. The pixels greater than the final threshold in the concentration enhancement image are recorded as the final pixel group, and the information of the final pixel group is traversed to screen out the initial screening plume pixels that meet the conditions, so as to screen out the plume pixels that meet the conditions. The retrieved global large point source emission plume is artificially identified, and the false positive plume is removed, so that the global large point source pollution gas emission smoke plume is finally obtained. The application can automatically identify the emission plume of the preset global emission point source during satellite observation.

The invention discloses a zero-energy-consumption white smoke removal method and device for a primary flue gas diffusion chimney of a converter. The white smoke removal device comprises a converter primary flue gas diffusion chimney, a flue gas inlet pipeline, a water baffle, a segmented drainage system, a folded plate demister, a throat spiral fin cooler, a swirler, a water collector, an upper spiral fin cooler, an ignition device and a chimney sealing plate. Flue gas is sequentially subjected to pre-dehydration, primary white smoke removal, intensified cooling, sufficient cooling and secondary white smoke removal and then is discharged into the atmosphere, water vapor in the flue gas is sufficiently condensed and removed in a segmented mode, white smoke plume and various pollutants at an outlet of a diffusion chimney can be effectively reduced, meanwhile, consumption of external energy is not increased in the whole process, and the device is low in initial investment and low in cost. The method has good economical efficiency and is widely suitable for newly-built and reformed projects.

The invention discloses a methane smoke plume recognition and emission estimation method based on multi-constraint background selection, and belongs to the technical field of greenhouse gas remote sensing monitoring and hyperspectral inversion. According to the method, satellite-borne or airborne short-wave infrared hyperspectral observation data is subjected to preprocessing such as radiometric calibration, atmospheric correction and noise suppression, a multi-constraint background pixel screening model including same-column consistency constraint, spectrum slope consistency constraint and diffusion distance constraint is constructed, and a background spectrum library is automatically obtained; based on the background library, an enhanced matched filtering algorithm is adopted to extract the methane concentration enhancement amount, and the system deviation and the false alarm rate are remarkably reduced. A smoke plume area is accurately extracted through spatial filtering, morphological segmentation and connected domain analysis, and the methane emission flux is inverted by combining an integrated quality enhancement (IME) emission estimation model with meteorological wind field data.

The invention provides an airport ventral region identification method and system. The method comprises the following steps: acquiring airport operation comprehensive data of a target airport, and inter-region association degree data and traffic data between the target airport and each peripheral region; airport point source intensity data, the inter-region correlation data and the traffic data are input into an airport ventral region identification model, the influence degree value of the target airport on each surrounding region is obtained, and the airport ventral region identification model is constructed based on a smoke plume model; the airport point source intensity data is obtained through calculation of the airport operation comprehensive data; and according to the influence degree value, determining a ventral region range corresponding to the target airport from the plurality of peripheral regions. According to the method, the abdominal land range of the airport is identified and divided more accurately.

The application provides a method and system for evaluating the whole range of radiation risk outside a nuclear power plant in a severe accident, and the method comprises the following steps: S1, a basic model architecture for evaluating the risk of radioactive accidents is built, the model requirements are adapted, and a corresponding basic database is established; S2, the characteristics of the radioactive plume after the accident are constructed; S3, the spatial gridding of the accident site and the discretization of the plume transmission are calculated; S4, the sampling meteorological conditions are obtained, and the plume transmission is simulated; S5, the radiation dose in the early stage of the grid domain is calculated, and the risk is evaluated; S6, the health effects in the early stage of the grid domain are evaluated; S7, the radiation dose in the medium and long term stage of the grid domain is calculated, and the dose risk is evaluated; S8, the health effect risk in the medium and long term stage is evaluated, and the consequences of the accident in the medium and long term stage are evaluated. The application simulates the whole transport process of the radioactive plume in a severe accident, considers the dry and wet deposition of the plume and the loss effects such as radioactive decay, and determines the activity of the radionuclide deposited on the ground and retained in the air within the spatial range outside the scene.

The invention discloses a high-emission ship screening method based on a spectral remote sensing technology, and the method comprises the steps: carrying out the multi-azimuth angle and multi-elevation angle observation of ship plume based on shore-based spectral remote sensing equipment, and carrying out the inversion to obtain the optical path integral concentration of SO2 and NO2 at different positions of smoke plume, the mass concentration result of SO2 and NO2 in the plume and the ratio RSN of SO2 and NO2 are obtained through background concentration deduction and in combination with optical path information; the method comprises the following steps: pre-processing RSN data and ship characteristic data, then performing data grouping, performing statistics on the RSN data in each group, determining a calculation key percentile, taking the calculation key percentile as an RSN upper limit of compliant emission to calculate a fuel oil sulfur content calculation factor corresponding to the group, and sorting fuel oil sulfur content calculation factor results subjected to grouping calculation into a structured table to form a lookup table. Based on the lookup table scheme, the fuel sulfur content of the newly observed ship is further calculated, whether the ship meets the standard or not is judged, early warning information is sent out for the high-emission ship, and ship supervision is assisted. The method is used for solving the problem of high-emission ship screening.