70 results about "Contamination index" patented technology

The invention discloses a cleaning path planning method and a cleaning device, and belongs to the technical field of automatic control, and the method comprises the steps: collecting the point cloud data of a to-be-cleaned region, constructing an initial composite map, setting a perception marking method, dividing the point cloud data into sub-regions, and marking a sudden change region after the sub-regions are matched with historical map features. Locally updating the composite map by using map optimization; constructing a safety buffer zone at the edge of the to-be-cleaned area, setting a buffer adjustment method, performing trajectory prediction on the abrupt change area, and dynamically adjusting a safety buffer distance according to a prediction result; calling a basic cleaning path, generating a layered path, setting a planning adjustment method, updating the layered path according to the abrupt change area in the cleaning process, calculating a pollution index of the to-be-cleaned area, constructing a time sequence prediction model, pre-judging a pollution diffusion trend, and performing dynamic adjustment; and after the to-be-cleaned area is cleaned, decision iteration is carried out to adapt to user habits.

The invention relates to the technical field of environmental pollution monitoring, and discloses an intelligent monitoring and tracing method and system for groundwater pollution, and the method comprises the steps: arranging a first monitoring well at the periphery of a target pollution source, obtaining data, calculating a comprehensive pollution index, dividing a risk area, and obtaining second monitoring data based on the optimized point distribution of the risk area, a four-dimensional space-time distribution model and a three-dimensional dynamic migration diffusion model are constructed, and pollution traceability analysis is carried out by combining the two models; according to the method, accurate monitoring of groundwater pollution is realized through a risk classification-driven differentiated point distribution strategy, and the temporal-spatial resolution and traceability precision of pollution plume migration simulation are remarkably improved through fusion of monitoring data and dynamic traceability analysis of a geologic model.

The invention relates to the technical field of electric energy quality monitoring and treatment, and discloses an electric energy quality abnormity traceability and purification strategy generation system, which comprises an electric energy acquisition module, a feature analysis module, an abnormity traceability module, a pollution evaluation module, a parameter optimization module and a strategy generation module. The electric energy acquisition module acquires waveform data of key nodes of a group network in real time and sets a monitoring interval; the feature analysis module decomposes the spectrum features to generate pollution feature vectors; the abnormity traceability module extracts a core index to establish a traceability rule; the pollution evaluation module identifies a propagation path and calculates a pollution index; the parameter optimization module deduces an optimal parameter generation deviation sequence; and the strategy generation module integrates the sequence to form a purification strategy. The system realizes accurate traceability and dynamic management of abnormities, improves analysis comprehensiveness and strategy intelligence level, and is suitable for power grid electric energy quality management and control.

The invention discloses a farmland soil health evaluation method and system, and relates to the field of soil health evaluation. The method comprises the following steps: acquiring remote sensing image data in a target area, decomposing color features of a remote sensing image by using an HIS model, acquiring a hue value, a saturation value and a brightness value of a unit grid, constructing a color feature vector set, clustering elements in the color feature vector set of the unit grid into K unit grid types, corresponding the unit grid types to a soil type, and constructing a soil model. Soil in a target area is divided into K categories, adjacent unit grid areas of the same type are combined into independent areas, the number of sampling points in any independent area is determined, soil sampling is conducted at the sampling points, the concentration value of all pollutants in soil samples of the independent areas is measured, and the distribution situation of all the pollutants in the target area is obtained. And calculating a single pollution index of the pollutant in the independent area according to the obtained concentration value of the dyed object, and dividing the pollution degree grade of the independent area.

The invention relates to an early warning method and system based on marine ranch pollution, and relates to the technical field of signal processing, and the method comprises the steps: building a three-dimensional biosensor network matrix, and dynamically adjusting the sensor deployment density of a marine ranch; a biological indicator response function is constructed according to the sensor deployment density, and a comprehensive response value is calculated; performing multi-source fusion on the sensor network data, the biological response data and the traditional monitoring data through a spatial weight kernel function to obtain a fused pollution index; calculating and evaluating the risk index of the comprehensive pollution risk of the marine ranch by combining the fused pollution index and the space-time parameter; dynamically optimizing the early warning threshold according to the change rate of the risk index and the historical data entropy to obtain a dynamic threshold; and based on the logarithmic relationship between the risk index of the marine ranch and the dynamic threshold, generating a multi-stage early warning signal for marine ranch pollution early warning. The accuracy of marine ranch pollution early warning can be improved.

The invention relates to the technical field of soil pollution detection, and discloses a soil pollution assessment method and system based on artificial intelligence. The artificial intelligence-based soil pollution assessment method comprises the following steps: step S101, determining a sensitive wave band and a contribution degree value of a pollutant; s102, judging whether the pollutants are included in a pollutant list or not according to the second characteristic value; step S103, constructing an incidence matrix; step S104, correcting the hyperspectral data of the pollutants in the pollutant list; step S105, obtaining the concentration of the pollutants through the pollutant concentration prediction model; and S106, judging whether the soil is polluted or not according to the comprehensive pollution index. According to the method, the enhanced absorption effect between the pollutants is converted into incidence matrix representation by utilizing the characteristics of the sensitive wave bands of the pollutants in the hyperspectral data, and the precision of pollutant concentration measurement is improved by utilizing the nonlinear learning capability of the pollutant concentration prediction model.

The invention relates to the technical field of soil pollution analysis, and discloses a soil heavy metal intelligent evaluation method, system and terminal, and the method comprises a multi-source heterogeneous data fusion and preprocessing step, a dynamic spatial interpolation modeling step and an intelligent visualization and decision support step. The system corresponds to the method, and the terminal equipment corresponds to the system. According to the method, comprehensive data support for soil heavy metal pollution is realized through multi-source heterogeneous data fusion and preprocessing; through dynamic spatial interpolation modeling and a dynamic parameter adjustment mechanism, high-precision grid surface layer generation is realized, and the fitting precision of pollution spatial distribution is improved; intelligent pollution grading and multi-factor dynamic calculation of pollution indexes are realized through self-adaptive grading and pollution index calculation, and the accuracy of an analysis result is improved; through intelligent visualization and decision support, a dynamic and visual decision basis is provided for multi-department collaborative governance and risk early warning.

The invention relates to the technical field of soil remediation, and provides a soil pollution remediation process which comprises the following steps: distributing points in grids of an area to be remediated, measuring the content of heavy metals and the concentration of organic pollutants, applying multi-frequency microwave radiation, synchronously applying ultrasonic treatment, and injecting a complex microbial inoculant containing sphingomonas, aspergillus niger spores and a nitrogen and phosphorus nutrient solution. A direct-current electric field is applied, pH, oxidation-reduction potential Eh and temperature parameters are monitored and measured in real time through an embedded sensor, a repair by-product recovery system is arranged, the purity of recovered metal is not lower than 98%, and mobile repair equipment is used in a matched mode. According to the method, the pollution degree is accurately quantified by constructing the pollution index PI, and dynamic regulation and repair are realized in combination with real-time monitoring parameters of a sensor. The pollutant removal efficiency is improved through the synergistic effect of multiple technologies, metal resource recovery is achieved through a repair by-product recovery system, traditional problems are solved, and efficient and environment-friendly repair is achieved.

The invention discloses a sea-land interaction zone chemical industry park groundwater pollution early warning index determination method and system, and the method comprises the steps: building a pollutant directory according to the hydrogeological conditions of a chemical industry park, and dividing the pollutant directory into inorganic pollutants and organic pollutants; constructing an entropy weight method-mathematical fuzzy evaluation model to carry out comprehensive evaluation on the inorganic pollutants to obtain an index sequence of the inorganic pollutants; evaluating the exposure potential EP and the toxicity potential HP of the organic pollutants according to the actually measured data of the organic pollutants and considering various evaluation parameters of the organic pollutants; obtaining final organic pollution indexes according to the EP and the HP of the organic indexes, and sorting the final organic pollution indexes; and according to the sorting result of the inorganic pollution indexes and the organic pollution indexes, determining the early warning indexes of the inorganic and organic pollutants in the underground water in the chemical industry park by combining the underground water quality standard. According to the method, objectivity and scientificity of pollutant identification are improved, and the problems that current pollution index selection is high in subjectivity, single in evaluation dimension, poor in regional applicability and the like are solved.

The invention belongs to the technical field of regional soil pollution evaluation and risk management, and particularly relates to a pollution grading evaluation and point source pollution identification method based on a regional soil environment background. The method comprises the following steps: determining a target area range and soil target pollutants; obtaining a current-stage soil environment background concentration data set of the target area, and calculating a statistical index of the data set; arranging regional soil pollution monitoring points, and monitoring the target pollutant content of the soil sample; and finally, the constructed pollution index evaluation model based on the soil environment background is adopted to calculate the single or combined pollution index of the soil at each point, the regional soil pollution grade and the environment quality are quantitatively evaluated, and the soil pollution point source is further identified. According to the method provided by the invention, based on the soil environment background content, the uncertainty of overestimation of non-point source pollution in a traditional soil pollution evaluation method is optimized, and the point source pollution point location can be accurately positioned.

The invention provides an ecological risk assessment method and system for heavy metal contaminated soil, and relates to the technical field of soil pollution treatment. The method comprises the following steps: acquiring a soil sample set of a target area; constructing a space grid model of the target area according to the soil sample set; determining a comprehensive pollution index of the grid unit according to the concentration distribution information of the heavy metal; performing time sequence analysis on the space grid model, and predicting the dynamic migration trend of the heavy metal concentration corresponding to the grid unit; determining exposure threshold values of different ecological receptors in the grid units, and generating an ecological risk thermodynamic diagram of the target area according to the comprehensive pollution index, the dynamic migration trend and the exposure threshold values; and determining a risk position and a safety position from the target area according to the ecological risk thermodynamic diagram and a preset threshold value. Therefore, according to the scheme, the ecological risk of the target area can be evaluated more comprehensively and accurately, and the accuracy and reliability of risk evaluation are greatly improved.

The invention discloses an unmanned aerial vehicle air pollution detection method and system, relates to the technical field of unmanned aerial vehicles, and solves the technical problems that it is difficult to carry out key monitoring on a pollution area according to the characteristics of different grids in a supervision area, it is difficult to dynamically evaluate and adjust the task load of an unmanned aerial vehicle, and the reliability of the whole system is affected. The unmanned aerial vehicle adjusts an air pollution monitoring strategy according to a real-time analysis result of the edge node; adjacent grids are combined into a calculation task area, so that unmanned aerial vehicle resources are utilized more efficiently, repeated monitoring is avoided, and the overall working efficiency is improved; the data of the adjacent grids are analyzed in a centralized manner, so that the pollution condition in the region can be comprehensively evaluated, and the accuracy of the pollution index is improved; unmanned aerial vehicle detection is dynamically adjusted, and a flight path and a grid monitoring strategy are optimized; the task load of the unmanned aerial vehicle is dynamically evaluated and adjusted, faults or failures caused by overload of a single unmanned aerial vehicle are prevented, and the reliability of the whole system is improved.

The present invention relates to the technical field of soil pollution detection, and discloses an artificial-intelligence-based soil pollution assessment method and system. The artificial-intelligence-based soil pollution assessment method of the present invention includes the following steps: Step S101, determining the sensitive bands and contribution degree values of pollutants; Step S102, judging whether the pollutants are included in the pollutant list according to the second eigenvalue; Step S103, constructing an association matrix; Step S104, correcting the hyperspectral data of the pollutants in the pollutant list; Step S105, obtaining the concentrations of the pollutants through a pollutant concentration prediction model; Step S106, judging whether the soil is polluted according to the comprehensive pollution index. The present invention utilizes the characteristics of the sensitive bands of pollutants in hyperspectral data to convert the enhanced absorption effect between pollutants into an association matrix representation, and utilizes the nonlinear learning ability of the pollutant concentration prediction model to improve the accuracy of pollutant concentration measurement.

The invention relates to the field of environmental engineering, in particular to a refuse landfill groundwater pollution risk management and control method and system, and the method comprises the steps: obtaining a leachate sample, a single-day landfill amount and a plurality of leachate component reports of a refuse landfill, obtaining environmental data, carrying out the chemical evaluation of the leachate sample according to the plurality of leachate component reports, and obtaining a filtrate pollution index, determining an underground water monitoring mechanism, performing pollution monitoring on the plurality of underground water monitoring wells based on the monitoring time interval and the underground water monitoring mechanism to obtain a plurality of water quality data packet sets and a plurality of monitoring well coordinates, and obtaining garbage landfill coordinates; and calculating a comprehensive pollution index by using the garbage landfill coordinates, the plurality of monitoring well coordinates, the plurality of water quality data packet sets and the landfill risk weight, and completing the risk management and control of groundwater pollution when the risk management and control center receives a pollution warning signal or a safety signal. According to the invention, the automation degree and the accuracy of evaluating the underground water pollution condition near the refuse landfill can be improved.

The invention provides a river and lake water body ecological management system, and belongs to the technical field of water body ecological management, and the system comprises a data collection module which monitors key data of a preset type of a river and lake water body in real time based on a preset sensor; the index analysis module is used for determining a pollution index based on the monitoring data and further determining a pollution level and a main pollution factor of the water body; the water quality early warning module is used for carrying out water quality early warning based on the pollution index and a preset pollution index threshold value; the coefficient evaluation module is used for determining a plurality of pollution decomposition areas based on the water quality early warning result, and further obtaining and evaluating the decomposition coefficient of each pollution decomposition area by combining the pollution level of the water body; the scheme determination module determines a pollution decomposition scheme based on the evaluation result and the main pollution factors, hysteresis and artificial errors in a traditional method are reduced, and the ecological environment of the river and lake water is effectively improved.

The invention discloses a surface water pollution grade evaluation method based on multi-source data. The method comprises the following steps: acquiring underground water data, standard data and multi-source monitoring data; obtaining a comprehensive quality grade according to the standard data and the multi-source monitoring data, obtaining a dynamic environmental pollution limit value according to the standard data and the underground water data, and obtaining a single pollution index according to the multi-source monitoring data and the environmental pollution limit value; obtaining the comprehensive pollution index according to the single pollution index, clustering the comprehensive pollution index and the comprehensive quality grade to obtain a comprehensive pollution evaluation grade, and establishing a pollution grade evaluation model by adopting the comprehensive pollution evaluation grade; and optimizing the pollution level evaluation model by adopting a bat algorithm, inputting to-be-evaluated data into the pollution level evaluation model, and outputting an evaluation result. The method not only can improve the precision of surface water pollution grade evaluation, but also has good interpretability, and can be directly applied to a surface water pollution grade evaluation system.

The invention relates to the technical field of air purification, in particular to a workshop air purifier intelligent regulation and control method based on laser dust detection, and the method comprises the steps: firstly obtaining particle size grading concentration data in real time through a laser detection device, and calculating a dynamic pollution index of each monitoring point in combination with a preset weight coefficient; a pollution core area and a diffusion trend are identified according to exponential distribution, an optimal air distribution scheme is generated based on the position of the core area and the concentration gradient, meanwhile, the purifier power and the filter screen mode are adjusted in a self-adaptive mode according to the concentration change rate and the target threshold value, and control parameters are optimized regularly based on an energy consumption efficiency model and the standard reaching time; according to the invention, the concentration data of PM10, PM2.5 and PM0.5 are obtained by grading in real time through the laser dust detection device, and the comprehensive hazard index of dust is accurately quantified in combination with a dynamic weight coefficient set by a respiratory deposition medical model, so that the problem that the particle size toxicity difference cannot be distinguished in the prior art is thoroughly solved.

The invention discloses an ecological effect assessment method based on a pollution index method cluster and index covariance, and particularly relates to the field of pollutant ecological risk assessment. Comprising the following steps: S1, constructing a multi-element pollution index method cluster; s2, performing data standardization assignment on the multi-element pollution index in the step S1; s3, multi-element pollution index fluctuation accounting is carried out; s4, multi-element pollution index correlation degree accounting is carried out; s5, calculating an index weight value according to the volatility in the step S3 and the correlation degree in the step S4; and S6, calculating the risk value of the research area according to the standardized copy obtained in the step S2 and the weight value in the step S5. By adopting the technical scheme, the problems of single evaluation angle and non-uniform results of a traditional pollution index method are solved, and a technical support and a scientific means are provided for ecological risk evaluation of heavy metal pollution of different regional producing areas.

The application relates to an anti-pollution performance accelerated testing device and method of a hydrogen production diaphragm of alkaline electrolytic water, and belongs to the field of electrochemistry. The method simulates the process of catalyst deposition under the real working condition of an electrolytic tank by adopting dynamic addition of catalyst particles, is closer to the actual operation environment of the electrolytic tank, introduces an anti-pollution index as an evaluation index based on test data, realizes quantitative evaluation of the anti-pollution performance of the diaphragm, can reflect the stability of long-term operation, and can also be used for estimating the failure time of the diaphragm and can be used for guiding operation and maintenance and selection.

The invention discloses a pollution grade evaluation method for an urban industrial pollution site, and relates to the technical field of pollution detection, and the method comprises the steps: employing an unmanned aerial vehicle-mounted air pollution detection instrument for inspection, collecting air pollution concentration data in real time, separating a background from a hot spot through a grid mean-standard deviation model, and carrying out the weighting to generate an air pollution index, based on the air pollution index, dynamically regulating and controlling the soil sampling density, carrying out secondary gridding point distribution in a field area, measuring soil pollution concentration data, and obtaining the soil pollution index by using the same'background + hot spot 'weighting strategy; fusing the soil pollution index and the air pollution index as a comprehensive pollution index, and comparing a four-level threshold value to immediately judge the site pollution level; according to the method, air-ground multi-dimensional anomalies are taken into consideration, high-risk area encryption sampling and low-risk area economic evaluation are realized, and an accurate, efficient and visual decision basis is provided for urban brown land redevelopment, treatment and resource release.

The application belongs to the technical field of vacuum equipment maintenance, and specifically discloses a molecular pump automatic purging pre-cleaning system and method. The system comprises a detection module, a control module and an execution module. The detection module collects flow, pressure, temperature and vibration parameters in real time through various sensors, obtains a pollution index PI through normalization and weighted operation, and accurately determines the pollution grade. The control module combines PID and fuzzy control algorithms and dynamically generates cleaning instructions in combination with an adaptive learning strategy. The execution module uses high-purity inert gas to complete the purging operation. The application solves the problems of low efficiency, unstable effect, easy damage to equipment and poor universality of traditional manual cleaning, can automatically adjust the cleaning cycle according to the load of the molecular pump, and has good hardware and software compatibility. The scheme has high automation degree and good cleaning effect, can reduce operation and maintenance cost and prolong the service life of the equipment, and is suitable for high-vacuum scenes such as semiconductor manufacturing, vacuum coating and particle accelerators.

The invention relates to the technical field of membrane filtration, in particular to a membrane pollution state determination method based on multi-dimensional operation parameter association. The membrane pollution state determination method based on multi-dimensional operation parameter association comprises the following steps: acquiring multi-dimensional input parameters of an ultrafiltration membrane system in a current operation state; and preprocessing the obtained multi-dimensional input parameters to obtain a multi-dimensional parameter data set. And inputting the multi-dimensional parameter data set into a pre-established optimal analysis model to obtain a current membrane pollution index PI. Comparing the current membrane pollution index PI with each preset pollution grade range, quantitatively judging to obtain the pollution state grade of the ultrafiltration membrane, and determining treatment measures according to the pollution state grade. The method has the technical effects and advantages that the problem of single historical working condition data is solved, the data preprocessing process is perfected, the model design is reasonable, the adaptability is high, the operation is simple and convenient, the practicability is high, and the service life of the ultrafiltration membrane is prolonged.

This invention provides a method and system for multidimensional risk coupling assessment and dynamic prediction of environmental capacity for heavy metals in soil. It relates to the field of data processing technology. Based on remote sensing spectral data and environmental physicochemical covariates of the target area, it inverts and generates heavy metal content data covering the target area. An integrated pollution index is calculated based on the heavy metal content data. Probability distributions are configured for exposure parameters of various population groups under different exposure pathways. Random sampling is performed on each exposure parameter according to the probability distributions. Health risk probabilities are determined based on the heavy metal content data and the sampled exposure parameters. The current environmental capacity is calculated based on risk control benchmarks and heavy metal content data. The current environmental capacity is extrapolated based on a preset annual heavy metal residue rate to obtain overload risk zones. This invention can extrapolate the changes in soil heavy metal environmental capacity over multiple future years, and can delineate and issue early warnings for capacity overload areas.

The present application relates to the technical field of power quality monitoring and treatment, and discloses a power quality abnormality tracing and purification strategy generation system, which comprises power collection, characteristic analysis, abnormality tracing, pollution assessment, parameter optimization and strategy generation modules.The power collection module collects grid key node waveform data in real time and sets a monitoring interval; the characteristic analysis module decomposes frequency spectrum characteristics to generate a pollution characteristic vector; the abnormality tracing module extracts core indexes to build a tracing rule; the pollution assessment module identifies a transmission path to calculate a pollution index; the parameter optimization module deduces optimal parameters to generate a deviation sequence; and the strategy generation module integrates the sequence to form a purification strategy.The system realizes accurate abnormality tracing and dynamic treatment, improves analysis comprehensiveness and strategy intelligentization level, and is suitable for power grid power quality management and control.

The invention discloses a detection method and system for agricultural land soil heavy metal pollution, and belongs to the technical field of soil heavy metal detection.The detection method comprises the steps that a dynamic grid division method is adopted for delimiting a detection area, and the detection area is divided into a plurality of space units; carrying out adaptive filtering and noise reduction processing on the in-situ rapid spectral signal to obtain denoised spectral data, and calculating the initial content of heavy metal elements in each space unit; constructing a multi-feature data set, training the multi-feature data set, and establishing a heavy metal pollution degree comprehensive evaluation model; and inputting the spatial unit feature data of the farmland to be detected into the comprehensive evaluation model, and outputting the comprehensive pollution index and risk level of each unit. According to the method and system for detecting heavy metal pollution of agricultural land soil provided by the invention, multi-source information can be fused, rapid and accurate detection can be realized, and the method has a dynamic risk assessment capability for detecting heavy metal pollution of agricultural land soil.

The invention relates to an intelligent disinfection control method and device for an electric otoscope. The method comprises the following steps: synchronously acquiring pollution spectrum data, ultraviolet intensity reference data, disinfection temperature and humidity data and a probe insertion state signal of an endoscopic optical window at the front end of a probe before disinfection is started to obtain a disinfection initial state vector; calculating a dynamic pollution index according to the disinfection initial state vector, the historical use frequency of the probe and the adjacent use time interval; matching a basic disinfection parameter according to the dynamic pollution index and a preset disinfection mapping table, and performing parameter dynamic calibration on the basic disinfection parameter according to the index deviation degree to generate a personalized disinfection protocol; performing process protection control in the process of executing the personalized disinfection protocol; and after disinfection is finished, carrying out cumulative ultraviolet dose standard verification and pollution spectrum data comparison verification. The reliability of the disinfection process is remarkably improved, and the risk of cross infection caused by human negligence is avoided.

The invention belongs to a mass spectrometry technology, and particularly provides a mass spectrometer anti-pollution performance dynamic monitoring method which comprises the following steps: A1, alternately injecting samples with the same concentration and blank products, and collecting a mass spectrum full-scanning spectrogram in real time; a2, extracting a time sequence pollution characteristic index according to the spectrogram, wherein the index comprises a background noise rise rate delta Nt / N0; a3, calculating a dynamic pollution index according to the characteristic index; a4, establishing a method for predicting a future cleaning critical point based on a dynamic pollution index sequence; and A5, a pollution boundary response threshold value is set, and a pollution cleaning strategy is fed back. The method has the advantages of high pollution monitoring capability and the like.

The invention discloses a method and a system for determining heavy metal pollution characteristics of water sediment, and relates to the technical field of environment monitoring and water environment governance, the system is characterized in that surface sediment samples are regularly collected at different positions of water in a mine area and an industrial gathering area, and a metal element data set and a reference data set are established; calculating a single-factor pollution index, and judging whether single metal exceeds the standard or not; integrating the single-factor pollution indexes to obtain a comprehensive pollution index, and determining the overall pollution level; whether manual input pollution exists or not is judged by calculating the geocumulative index; according to the method, correlation analysis, principal component analysis, factor analysis and GIS space statistics are combined, multi-dimensional indexes are extracted, pollution source analysis coefficients are calculated, agricultural non-point source or industrial emission dominant pollution types are determined, and corresponding prevention and control strategies are generated. According to the method, multilevel feature recognition and source analysis of sediment heavy metal pollution can be realized, and a scientific basis is provided for water area pollution treatment and risk management and control.

The application relates to a metal contamination online monitoring method, system, electronic equipment, storage medium and computer program product. The method comprises the following steps: acquiring spectrum data in a process cavity in a semiconductor process; calculating an SPE statistic of the spectrum data according to a principal component analysis model; when it is judged that the SPE statistic exceeds a preset control limit, the spectrum data is regarded as a contamination spectrum, and a metal contamination analysis step is entered, which comprises the following steps: acquiring the closest reference spectrum based on the process time stage of the contamination spectrum, and calculating a difference spectrum of the contamination spectrum and the reference spectrum; calculating a contamination index of the metal to be measured based on the original spectrum data and the difference spectrum; matching the contamination index of the metal to be measured with a preset metal characteristic spectrum database; when a matching result meets a preset condition, it is determined that metal contamination exists in the process cavity, and an alarm signal is output. The application can realize early warning and rapid response of metal contamination, thereby improving the process control level and product yield of semiconductor manufacturing.

The application provides an ecological risk assessment method and system for heavy metal contaminated soil, and relates to the technical field of soil pollution control. The method comprises the following steps: obtaining a soil sample set of a target area; constructing a spatial grid model of the target area according to the soil sample set; determining a comprehensive pollution index of a grid unit according to concentration distribution information of heavy metals; performing time series analysis on the spatial grid model to predict a dynamic migration trend of the heavy metal concentration corresponding to the grid unit; determining an exposure threshold of different ecological receptors in the grid unit; generating an ecological risk heat map of the target area according to the comprehensive pollution index, the dynamic migration trend and the exposure threshold; and determining a risk position and a safe position in the target area according to the ecological risk heat map and a preset threshold. Therefore, the ecological risk of the target area can be more comprehensively and accurately evaluated, and the accuracy and reliability of risk assessment are greatly improved.