1165 results about "Ecosystem" patented technology

The invention relates to the technical field of forestry informatization, in particular to an ecological public welfare forest monitoring and intelligent management system and method. The method comprises the steps of collecting multi-dimensional ecological data in real time and performing data fusion; based on a data fusion result, establishing an ecological behavior evolution graph and a multi-layer state inversion network by adopting a graph attention mechanism, forming a dynamic ecological twinborn body, and realizing ecological system state prediction, historical disturbance inversion and future behavior simulation; a risk tensor map is constructed in combination with state abnormality, trend instability and intervention ineffectiveness in a three-dimensional mode, a dynamic grading thermodynamic diagram is generated, and a personalized regulation and control strategy is recommended through reinforcement learning; and finally, sensing an actual regulation and control effect through a feedback mechanism, dynamically correcting twin model parameters by using deviation analysis, and constructing a knowledge base based on historical strategies and effects to drive strategy self-optimization. According to the method, a sensing-modeling-regulation-feedback closed loop is formed, and the accuracy and adaptability of ecological management are improved.

The invention relates to the field of water conservancy and hydropower engineering, in particular to a multi-objective optimized hydropower ecological scheduling decision-making system and method, and the system comprises a data collection module, an ecological model module, an intelligent decision-making engine module, a scheduling execution module, an effect evaluation module and a knowledge base module. The data acquisition module collects multi-source data, the ecological model module generates a training data set, the intelligent decision engine carries out ecological process modeling and probability prediction based on a deep learning architecture and spatial-temporal feature extraction, and generates a scheduling decision, the scheduling execution module controls hydropower engineering operation, and the effect evaluation module monitors ecological and economic effects. The knowledge base module stores historical experience and provides optimization suggestions, and the system improves the simulation accuracy of the ecological system, especially when the flow changes suddenly; and through uncertainty quantification, the system reliability and the ecological safety guarantee rate are enhanced, and high efficiency, accuracy and sustainability of ecological scheduling of the hydropower engineering are realized.

The invention relates to the technical field of port planning and construction, and particularly discloses a port planning and construction environment feasibility assessment method and system, and the method comprises the following steps: S1, obtaining planning parameters, real-time environment monitoring data, a historical ecological data set and social economic data of a target port; s2, constructing a dynamic coupling model of environmental bearing-ecological disturbance-pollution diffusion-social economic influence; and S3, based on the dynamic coupling model, adopting multi-scene space-time prediction simulation, and outputting an environmental feasibility comprehensive index, a key constraint factor and a social economic influence evaluation result. A dynamic coupling model of environment bearing, ecological disturbance, pollution diffusion and social economic influence is constructed, the four sub-models interact in real time through bidirectional data flow, full-dimension dynamic coupling evaluation of natural environment, ecological system, pollutant migration and social economic factors is achieved, and compared with traditional single-factor evaluation, the comprehensive evaluation accuracy is improved.

The invention discloses a sewage denitrification dosing method and system based on machine learning and a storage medium, and belongs to the technical field of sewage treatment.The method includes the steps that data are collected and preprocessed, and variable data influencing biochemical pool carbon source dosing behaviors are obtained; and lagging influence of carbon source input on the denitrification amount index is analyzed, and the duration time range of the drug effect is determined. And adopting the trained prediction model, and based on the denitrification amount index and the prediction variable of the future t + X period, obtaining the dosage of the (t + 1) th period. Through a correlation analysis method, the correlation rule of nitrogen conversion in the future X period after the carbon source is added is analyzed, the duration time of the drug effect is determined, the lag effect is accurately quantified, and the problem of mismatching of regulation and control opportunities is avoided. The hysteresis effect is captured and subjected to multi-factor coupling analysis based on the prediction model, the carbon source adding amount and time are optimized, system load fluctuation caused by excessive carbon sources or incomplete nitrogen removal caused by insufficient carbon sources are avoided, and the stability of an original sewage ecological system is gradually improved.

The invention discloses an ecological restoration effect evaluation and simulation system after polluted soil restoration, and relates to the technical field of soil restoration, and the system comprises a soil feature generation module which generates an ecological feature data set; the ecological restoration evaluation module is used for establishing a multi-dimensional evaluation model by using an analytic hierarchy process and a fuzzy comprehensive evaluation method based on the ecological characteristic data set, and generating an ecological restoration effect index; the dynamic simulation prediction module is used for constructing an ecological restoration dynamic simulation model and simulating the evolution trend of a soil ecological system under different environment conditions; and the restoration strategy optimization module is used for generating a targeted ecological restoration optimization scheme by combining a preset restoration strategy library according to the ecological restoration effect index and the dynamic simulation prediction result. According to the method, a closed-loop system integrating multi-source data acquisition and processing, multi-dimensional evaluation, dynamic simulation prediction and stepped strategy optimization is constructed, and accurate evaluation of the ecological restoration effect after contaminated soil restoration and scientific optimization of the restoration strategy are achieved.

A method for delineating an ecological corridor based on a maximum similarity model determines ecosystem type according to the determined ecological source, and assigns a habitat suitability index; and according to a maximum similarity matrix between different ecosystems, assigns the habitat suitability index to peripheral pixels of the selected ecological source, to obtain a similar value of the habitat suitability index. The habitat suitability index is corrected according to the surface curvature data and population density data, and resistance surface data is calculated according to the corrected value. Based on the resistance surface data, an ecological corridor is delineated comprehensively to find one or more paths corresponding to a minimum cost distance as ecological corridors. The influence of ecological environment on ecological corridor establishment is considered more comprehensively, so that the ecological corridor is delineated more accurately, and applied into practice to maximum extent.

The invention relates to the technical field of data analysis, in particular to a territorial space planning data analysis system for ecological restoration, which comprises an interference parameter acquisition module, an ecological disturbance calculation module, a restoration area identification module, a priority level judgment module and a site selection stability screening module. According to the method, the accuracy and efficiency of ecological restoration are improved by capturing various disturbance factors of an ecological sensitive area and dynamically evaluating ecological degradation, and the signal of ecological degradation can be recognized earlier by comprehensively monitoring the change trend of earth surface coverage and the dynamic state of a water body and quickly responding to the subtle change of an ecological environment; ecological service function indexes are adopted for inter-year comparison, a long-term view angle about the health state of an ecological system is provided, prediction accuracy is improved, ecological restoration work can be implemented in a more targeted mode, and the lasting effect of the ecological restoration work is ensured through continuous monitoring of land utilization changes.

The invention provides a seaweed farm ecosystem prediction method, system, device and medium, and belongs to the technical field of seaweed farms, and the method specifically comprises the steps: collecting basic data of a seaweed farm ecosystem, and forming an ecological data set; preprocessing the ecological data set; determining a seaweed field prediction index, using a DMD mode to decompose and extract a time-delay main mode, then using convergence cross mapping to quantify causal intensity, constructing an environmental factor and biological index space-time diagram, and learning a causal edge weight through a graph attention network; predicting index change in combination with the incidence relation, and performing hybrid prediction by adopting a pulse disturbance-recovery coupling model and digital twinborn reinforcement learning; and visually outputting the prediction result. According to the method, a seaweed field ecological system monitoring and predicting system of data, information, knowledge and decision is constructed, the ecological system state characterization capability and risk early warning perspectiveness are improved, and scientific and efficient technical support is provided for marine ecological protection and management.

The invention discloses a multi-source remote sensing ecological production environment assessment system, and belongs to the field of ecological environment assessment. The system is composed of a data acquisition module, a data processing and fusion module, a generative artificial intelligence core engine, an ecological evaluation and decision support module and a user interaction interface, and all the modules are connected with one another, so that the overall function of the system is realized. According to the method, through a'representation-cognition-semantics' three-layer fusion architecture, the system can surpass traditional data piling, deep integration is carried out on multi-source information from bottom-layer features and spatial relationships to high-layer semantics, so that a complex interaction mechanism among ecological elements is more accurately understood and described, and the system is more efficient and efficient. And the overall cognitive ability and evaluation accuracy of the complex ecological system are remarkably improved. The system is based on a generative artificial intelligence core engine, not only can analyze the current situation, but also can simulate future scene evolution under different ecological management strategies.

The invention discloses a desert region water resource recycling method based on ecological restoration coupling, and the method comprises the steps: building a moisture-vegetation coupled spatial dynamic model through obtaining soil humidity distribution, vegetation coverage and regional microclimate data, and recognizing a suspected water resource retention region; the water resource circulation potential is evaluated in combination with microclimate fluctuation characteristics and earth surface characteristics, and an actual water resource optimal utilization area is screened; according to the water resource circulation potential, the vegetation planting density, variety and irrigation mode are dynamically adjusted, the ecological restoration gain coefficient is calculated, and collaborative optimization of the water resource utilization efficiency and the ecological restoration effect is achieved. Water resource management and ecological restoration are organically coupled, accurate utilization and efficient circulation of water resources are achieved, and the restoration capacity and sustainability of an ecological system in the desert area are remarkably improved.

The invention relates to the technical field of regional ecological risk assessment and space management and control, in particular to a regional ecological risk assessment and partitioning method based on a multi-system spatio-temporal dynamic relationship, which comprises the following steps: collecting and preprocessing multi-source spatio-temporal data; a natural ecological risk index and a human social risk index are fused, and a comprehensive ecological risk assessment model based on a social-ecological system is constructed; divariate spatial autocorrelation analysis and cold and hot spot analysis are adopted, and a region is divided into three-level subareas including a management and control area, a monitoring area and a prevention area and six types of subareas; and analyzing the partition dominant driving factor by using the optimal parameter geographic detector, and generating a differentiated control strategy. The method realizes quantitative coupling of natural ecology and human social system risk spatio-temporal dynamic relationships, solves the problems of strong subjectivity, insufficient system comprehensiveness and lack of dynamic association mechanisms of a traditional method through multi-dimensional index fusion and spatial analysis technologies, and provides systematic technical support for accurate management of regional ecological risks.

The invention relates to the technical field of reservoir ecological management, in particular to a reservoir ecological scheduling method and system and a storage medium. The method comprises the following steps: carrying out vertical section multi-source parameter acquisition on a reservoir through a sensor array to obtain an original section data set; carrying out bottom mud-water body substance exchange strength characterization on the original profile data set to obtain an exchange flux comprehensive index; layering the reservoir according to the exchange flux comprehensive index to obtain a reservoir horizon structure chart; performing season-depth partition according to the reservoir horizon structure chart to obtain a partition statistical feature set; performing ecological safety response association on the partitioned statistical feature set to obtain an ecological safety domain map; and performing exchange flux and scheduling constraint analysis according to the ecological security domain atlas to obtain an exchange flux deviation table and a scheduling constraint condition set. According to the invention, a scientific scheduling method is provided for health of the reservoir ecosystem through collaborative optimization of water level regulation and control and layered drainage.

The invention provides a wetland ecosystem health evaluation method based on multi-source remote sensing data, and belongs to the technical field of wetland ecosystems, and the method comprises the steps: carrying out the dense dark pixel and Kalman filtering cooperative atmospheric correction of a multi-spectral remote sensing image to obtain a surface reflectance image, and achieving the precise segmentation of a wetland landscape through a graph cut theory, a spectral unmixing model based on an improved Gaussian kernel is utilized to embed physical constraints to invert water quality parameters, a laser radar canopy height priori constraint three-dimensional radiation transmission model is combined to invert vegetation parameters, and a mixed pixel decomposition result is optimized through a Markov random field. A water quality, vegetation and landscape three-dimensional comprehensive health evaluation system is constructed, degradation dominant factors are identified, and the technical problem that it is difficult for multi-source remote sensing data to cooperatively invert wetland ecosystem multi-dimensional health state parameters is solved.

The invention discloses a mangrove forest distribution information extraction method based on deep learning and remote sensing images, and the method comprises the steps: firstly, constructing a spatial diagram fusing ecological priori knowledge such as hydrological connectivity, and extracting high-dimensional features containing a complex space-time dependence relation from an irregular satellite image time sequence through employing a PG-STGT network; a physical information guided antagonism decoupling mechanism is subsequently adopted to explicitly decompose the high-dimensional feature into three subspaces. And finally, according to the method, a high-robustness distribution diagram is generated by applying the decoupled identity feature vectors, and a multi-dimensional mangrove forest health index is generated by using residual error abnormal features. According to the method, the physical mechanism and deep learning are deeply fused, the time consistency of the classification result is improved, and the ability of diagnosing the health condition of the ecological system is provided.

The invention discloses a network toughness prediction method, system and device based on digital twinning, and relates to the technical field of ecological monitoring and network toughness modeling. The network toughness prediction method, system and device based on digital twinning comprises the following steps: S1, collecting multiple types of ecological monitoring data through ecological monitoring equipment, and carrying out standardized preprocessing on the ecological monitoring data; s2, the modeling difficulty of each piece of ecological data is comprehensively evaluated, and automatic screening and grading processing of data quality are achieved; s3, performing state synchronous evaluation on the to-be-modeled data, and dynamically updating the operation state of the corresponding ecological entity in the digital twin based on a state evaluation result; and S4, identifying key fragile nodes and risk paths in each ecological entity, and outputting corresponding ecological risk levels and regulation and control suggestions. The problem that in the prior art, static threshold risk judgment is carried out only based on a small amount of observation data, and multi-source isomerism and dynamic evolution characteristics existing in an ecological system cannot be effectively handled is solved.

The invention discloses an intelligent site selection method and system for farmland occupation and compensation balance, and belongs to the technical field of intelligent site selection, and the method comprises the steps: S1, collecting and preprocessing multi-source spatio-temporal data, so as to construct a basic database; s2, constructing a spatial adjacency relation graph, inputting data in the basic database into a graph neural network model, and generating a dynamic evaluation weight vector for a to-be-selected plot; s3, calculating a final utility value of each evaluation index, and calculating a multi-scale ecological balance score of the land parcel by adopting a multiplicative aggregation model in combination with the dynamic evaluation weight vector; s4, predicting the future quality evolution trend of the land parcels by adopting a long-short-term memory network model, and the method can accurately capture and respond to the spatial-temporal dynamic characteristics of the cultivated land ecosystem, so that the evaluation result is more fit with the physical reality.

The invention provides an urban internal lake water pollution treatment method and system. Real-time water quality data are collected from a lake; processing the collected data; using the prediction model to predict a water quality trend and identify a pollution risk; according to the analysis result of the machine learning algorithm and the water quality model, the decision support module generates a targeted treatment strategy; according to the treatment strategy provided by the decision support module, specific treatment measures are implemented; and the intelligent management and control module is used for monitoring and managing the whole treatment process in real time. All the modules are linked to construct a whole-process and intelligent treatment system, the treatment efficiency of urban internal lakes is effectively improved, and continuous improvement of water quality and long-acting restoration of an ecological system are achieved.

The invention provides a wetland ecological safety early warning method and system based on remote sensing analysis, and the method comprises the steps: firstly obtaining a multi-dimensional remote sensing data set containing multi-temporal imaging, spectral radiation and microwave scattering data in a target wetland region, and carrying out the interpretation to obtain an ecological process signal set; establishing a mapping relation model of the ecological process signal and the wetland ecological safety state, and obtaining a current ecological safety state description; performing cross-process correlation analysis on the ecological process signal to form an ecological process abnormal conduction chain; constructing an early warning trigger node system and generating an early warning rule; and acquiring real-time multi-dimensional remote sensing data, interpreting the real-time multi-dimensional remote sensing data, matching the interpreted real-time multi-dimensional remote sensing data with an early warning rule, and generating wetland ecological safety early warning information containing an abnormal ecological process link, an abnormal conduction path and an early warning response node. The wetland ecological safety risk can be comprehensively and accurately pre-warned, and the stability of the wetland ecological system is guaranteed.

The utility model provides a submerged plant diversity restoration biological window which is provided with a frame structure and a supporting structure, the supporting structure is arranged on one side or two sides of the frame structure, the frame structure is provided with a through containing cavity, and one or more submerged plants are planted in the containing cavity of the frame structure. A plurality of biological windows are arranged in a combined gathering manner or are detachably removed to form a repairable submerged plant group. According to the method, an economical and efficient engineering technology path can be provided for restoration of diversity of submerged plants in the damaged aquatic ecosystem and optimization construction of the healthy aquatic ecosystem, and the method has important significance on restoration of health of the aquatic ecosystem and improvement of water environment quality.

The invention discloses a virulence factor gene relative abundance prediction model based on water quality physicochemical indexes, and relates to the technical field of ecological environment protection, and the virulence factor gene relative abundance prediction model comprises the following steps: taking a plurality of river water samples, obtaining virulence factor gene relative abundance of the river water samples, and obtaining water quality physicochemical index data of the river water samples; temperature, redox potential, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total nitrogen, total dissolved solids, pH, conductivity, chlorophyll-a, chemical oxygen demand, dissolved oxygen, total organic carbon, total phosphorus, organic nitrogen, phosphate, carbon-nitrogen ratio and organic nitrogen / total nitrogen are taken as explanatory variables, and relative abundance of virulence factor genes is taken as a target variable. And establishing a regression model by adopting a GBM algorithm in an h2o packet in R software, and predicting the relative abundance of the virulence factor gene of the river water sample to be detected by utilizing the prediction model. The research provides a brand new method for predicting the relative abundance of the virulence factor gene and analyzing the environmental response of the virulence factor gene, and the method is suitable for identification and interpretation of a high-dimensional nonlinear ecosystem with complex interaction.

The invention discloses a system and a method for quickly dividing ecological system restoration requirements, belongs to the technical field of ecological system restoration, and remarkably improves the efficiency and the accuracy of ecological problem identification. By integrating satellite remote sensing, ground monitoring and historical data, key problem areas such as severe water and soil loss areas and vegetation degradation zones can be quickly locked, and restoration priorities are automatically divided. Traditional manual evaluation needs an analysis process of several months, the system can be completed in several days, subjective judgment errors are avoided, and the scientificity of degradation grade judgment and restoration scheme matching is ensured. Besides, the dynamic tracking module monitors the restoration effect in real time and adjusts engineering parameters in time, the problem of resource waste caused by traditional'one-time treatment 'is solved, the integrity of the ecological barrier is guaranteed through the multi-dimensional balance mechanism, development space is reserved for village revitalization, and bi-directional improvement of ecological benefits and economic and social benefits is truly achieved.

The invention discloses a coupling model framework for simulating nitrogen dynamics in a flowing water ecosystem and a construction method of the coupling model framework, and relates to the technical field of environmental protection, including hydrodynamic flow, substance diffusion between environmental media and microbial metabolism, and the construction method of the coupling model framework comprises the following steps: (1) establishing a hydrodynamic model; (2) establishing an inter-environmental-medium nitrogen transmission diffusion model; (3) establishing a gene center model of metabolism of inorganic nitrogen and organic nitrogen; (4) constructing a nitrogen dynamic numerical simulation system in the flowing water ecosystem in a coupling manner; and (5) decoupling a dominant factor and a nitrogen conversion mechanism of a nitrogen dynamic state in the quantification system. By simulating the nitrogen dynamic state of the flowing water ecosystem, dominant factors and a nitrogen conversion mechanism of the nitrogen dynamic state in the water ecosystem can be accurately described, so that effective suggestions can be provided for nitrogen dynamic regulation and control and eutrophication management and control of the water ecosystem.

The invention provides a healthy plant community construction method based on an urban green land nutrition relationship, and relates to a construction method of an urban green land plant community. The construction method comprises the following steps: selecting plant communities to construct species according to urban green land types and functional requirements; according to the plant community establishment species, determining the nutrition relationship between the phytophagous arthropods corresponding to the establishment species plants and the nutrition relationship between the phytophagous arthropods corresponding to the natural enemies; and selecting functional plants according to the corresponding nutrition relationship, and configuring the functional plants around the colonized plants to construct and form a healthy plant community based on the urban green land nutrition relationship. According to the construction method, healthy growth of plants in the urban green land, nutritional relation coupling and ecological system balance of the urban green land can be realized.

The invention relates to an ecological system health space-time driven attribution analysis method based on IGTWR-XGBoost, and the method comprises the steps: obtaining an ecological system health index of a target region, calculating the ecological system health index of the target region according to the ecological system health index, and collecting a multi-source driving factor; constructing an interactive geographic space-time weighted regression model according to the multi-source driving factor, the ecological system health index and a geographic-time weighted regression model; acquiring a multi-dimensional local regression coefficient matrix according to the interactive geographic space-time weighted regression model; correcting a multi-source driving factor according to the multi-dimensional local regression coefficient matrix to form a space-time enhanced feature matrix; and inputting the space-time enhanced feature matrix into an XGBoost model, and obtaining a prediction result of the ecological system health index and global and local contribution values of each driving factor. According to the invention, the accuracy and reliability of ecosystem health driving mechanism analysis can be significantly improved.

The invention relates to the technical field of green prevention and treatment of dendroctonus valerieus, in particular to a dendroctonus valerieus repellent as well as a preparation method and application thereof. The repelling component comprises fenchone. The fenchone is found to have an obvious repelling effect on the dendroctonus resurus, and meanwhile, the fenchone can be used as a repellent for the dendroctonus resurus, and the dendroctonus resurus can be repelled in production to protect an ecological system of a pine forest. The repellent has the advantages of good repelling effect, stability, environmental friendliness and wide industrialization prospect.

The invention discloses a coupling evaluation index-based energy flow path evaluation system for a sea-mountain ecosystem, and relates to the technical field of marine ecological evaluation and management, and the system comprises an evaluation center which is in communication connection with a region deployment module, a multi-source collection module, a coupling analysis module, an energy evaluation module, a data management module and a decision support module. According to the system, systematic and standardized collection of biological and environmental data in the sea and mountainous areas is realized through gridding partition of the region deployment module and directional equipment layout in combination with layered collection of the multi-source collection module and standardized pretreatment of samples; the coupling analysis module constructs a coupling index, analyzes an energy flow key path, screens a key environment factor and provides a quantitative evaluation basis; and the energy evaluation module calculates the efficiency of the biological pump, evaluates benthic food supply and spatial change and visually presents the benthic food supply and spatial change, so that refined evaluation and management of ecological energy flow in the western pacific sea mountainous area are realized.

The invention relates to the technical field of aquaculture, in particular to an aquaculture water environment repairing agent and a preparation method thereof, and the repairing agent is composed of a modified biochar composite material, chlorella microspheres, a cross-linking agent and a microbial compound inoculant. The modified biochar composite material is prepared through the steps of mixing attapulgite and biomass raw materials, performing acid activation, performing pyrolysis and the like, and tannic acid is used for further modification so as to enhance the adsorption capacity; the chlorella microspheres are prepared from sodium alginate and a CaCl2 solution, and have good suspension property and stability; the microbial complex microbial inoculant contains various beneficial bacteria, and can decompose organic matters and reduce the content of ammonia nitrogen and nitrite; the components of the repairing agent are combined through the cross-linking agent to form particles, so that the repairing agent is convenient to put and recycle. The repairing agent disclosed by the invention has efficient pollutant removal capacity, and can be used for remarkably improving the water quality of aquatic water, improving the transparency of the water, increasing dissolved oxygen and promoting the health and stability of an aquatic ecosystem.

The invention belongs to the technical field of water quality monitoring, and discloses a big data water quality dynamic monitoring and early warning method and system, a'water environment-social economy-ecosystem 'ternary data system is constructed through a cross-domain data symbiosis module, social and economic data such as enterprise pollution discharge, agricultural irrigation and the like and ecological microscopic data such as algae gene expression and the like are fused, and the water quality dynamic monitoring and early warning system is established. Implicit factor dominance is realized in combination with a dynamic weight algorithm; meanwhile, the quantum dot marking technology breaks through chemical analysis blind areas, accurately locates multi-source pollution, greatly improves the novel combined pollution identification capability, solves the problem that the traditional technology is lagged in response to complex pollution, and provides omnibearing data support for pollution traceability; in extreme weather, a parameter mutation adaptation mechanism is started, sub-models are rapidly switched, and an enhanced feature set generated by a cross-domain feature distillation step is combined, so that the model can accurately simulate the coupling effect of pollutants and a biologic chain, the long-term prediction stability is remarkably improved, and a reliable trend basis is provided for early warning decision making.

The invention discloses a water conservancy project ecological construction method and system based on artificial intelligence, and relates to the technical field of ecological system simulation, and the method comprises the steps: collecting historical ecological event data of each region of a water conservancy project, analyzing the causal association between events based on an artificial intelligence model, and calculating and dynamically updating the association degree index between any two regions; constructing a regional association network based on the association degree indexes, calculating core scores of nodes in the network to identify a core region, and dynamically improving the monitoring sampling frequency of ecological data for the core region; and when an abnormal state is monitored in a single region, predicting the abnormal risk probability of other regions, and generating and recommending an optimal coping plan. Compared with the prior art, the method has the advantages that by constructing a dynamic regional correlation analysis system, the mutual influence between ecological regions is quantified, the monitoring resources are distributed uniformly to be intelligently and optimally configured based on the network core degree, and the monitoring efficiency and the capturing capacity of key information are remarkably improved.

The invention discloses a self-cleaning device for a ballast water pipeline of a tropical scientific investigation ship, the self-cleaning device comprises the ballast water pipeline, a double-rod fixing device, rotation dampers, a screw rod and a rotary scraper, the screw rod is fixed and welded on the inner wall of the ballast water pipeline by the double-rod fixing device, the rotary scraper is fixed on the screw rod through thread engagement and limited by the rotation dampers on the two sides, and the rotary scraper is fixed on the ballast water pipeline. A silicon nitride ceramic shaft seal is arranged at the penetrating connector of the screw and the double-rod fixing device, the rotary scraper body is made of a metal alloy matrix, and the surface of the rotary scraper body is coated with an Al2O3-TiO2 coating. The invention further discloses a working principle of the self-cleaning device for the ballast water pipeline of the tropical scientific investigation ship. Aiming at the special requirements of the operation area of the tropical scientific investigation ship, the rotary scraper is driven by the kinetic energy of ballast water flow, a quickly growing biological membrane is efficiently removed through the centrifugal stripping and shearing stripping effects of the fluid, pollution of chemical cleaning to sensitive ecology such as coral reefs is avoided, and the pipeline blockage risk and the maintenance cost are reduced.