150 results about "Entire life cycle" patented technology

The invention discloses a full-life-cycle-based medical equipment monitoring analysis system and method, and relates to the technical field of medical equipment monitoring, and the method comprises the steps: collecting medical equipment data in real time, and dynamically constructing a full-life-cycle digital twin model of medical equipment; constructing a medical equipment knowledge graph based on the equipment type, the function association and the spatial distribution; when the medical equipment node detects abnormal data, an early warning signal is sent to a full-life-cycle digital twin model associated with the medical equipment in the medical equipment knowledge graph in combination with the medical equipment knowledge graph; preliminarily judging fault causes and fault location, and generating an analysis report; performing multi-dimensional verification on the diagnosis result in the digital twin environment, comprehensively evaluating the risk coefficient of the scheme, and outputting an optimal maintenance strategy; in the maintenance process, the maintenance process is recorded in real time, and maintenance data and equipment state updating are synchronously fed back to the equipment full-life-cycle digital twin model.

The invention relates to a building material mining life cycle process carbon emission improvement potential quantification method comprising the following steps: constructing a full life cycle carbon footprint digital model covering mining, transportation, processing and restoration, and integrating a digital twinning and BIM technology dynamic correlation carbon emission factor library; key carbon emission influence factors are identified through Monte Carlo simulation and regression analysis; establishing a multi-objective optimization model, generating an optimal process parameter combination by adopting an intelligent algorithm, and quantifying the emission reduction potential; model parameters are dynamically calibrated in combination with real-time data, and a closed-loop optimization mechanism is formed; space-time distribution visualization and block chain evidence storage technologies are introduced, and accurate monitoring, intelligent decision making and credible tracing of carbon emission are achieved. According to the method, the problems of data lag and single optimization in a traditional method are solved, the accuracy of carbon emission and the feasibility of an emission reduction scheme are remarkably improved, meanwhile, carbon sink offset evaluation is supported, and a whole-process technical support is provided for mine green transformation.

The invention relates to the technical field of digital management, in particular to an offshore platform component processing full life cycle quality tracing system which comprises a component unique identification code generation module, a multi-source processing data acquisition module, a quality judgment and tracing code association module, a holographic digital archive construction module and a three-dimensional visual tracing module. Wherein the component unique identification code generation module is used for generating a unique identification code; the multi-source processing data acquisition module is used for acquiring processing process data associated with the unique identification code of the component in real time; the quality judgment and traceability code association module is used for generating a quality judgment result based on a preset quality rule base; and the holographic digital archive construction module is used for generating a full-life-cycle data chain of the component. According to the method, the whole life cycle data chain with the unique traceability code as the index is constructed and mapped to the BIM model, and structural management and space-time visual traceability of the quality information of the offshore platform component are achieved.

The invention discloses a battery full life cycle intelligent management method and system based on a large model, and the method comprises the following steps: S1, collecting the operation data of a battery, and carrying out the preprocessing; s2, inputting the pre-processed sample into a pre-trained Transform encoder model, and extracting a time sequence and cross-stage characteristics; s3, executing model reasoning, outputting a state index, and generating a battery state vector; s4, identifying an abnormal category and a position in combination with the working condition information; s5, generating a dynamically optimized battery management strategy based on the battery state index and the abnormity identification result; s6, deploying a lightweight model at the edge device, executing local reasoning and uploading data; s7, the cloud updates the model through self-supervised training and issues the model; and S8, repeatedly executing the steps S1 to S7, and carrying out optimized closed-loop management. According to the invention, large model modeling and an edge cloud cooperation mechanism are fused, and intelligent sensing and dynamic management of the whole life cycle of the battery are realized.

The invention belongs to the technical field of smart city construction and intelligent construction management, and particularly relates to an intelligent scheduling and cooperation system and method for the whole life cycle of city reconstruction. The system comprises an edge sensing layer, a digital twinning network module, a space-time brain module, a block chain collaborative trust layer and an XR collaborative interaction layer. The system collects multi-source data of a construction site in real time through a 5G edge device, realizes fusion modeling of BIM, GIS and TIN models by using a graph convolutional neural network, and performs multi-target scheduling optimization in combination with meta reinforcement learning and a dynamic graph neural network; and meanwhile, construction task verification and fund payment linkage is realized through a block chain smart contract, and immersive cooperation and visual acceptance are provided in cooperation with an AR / VR platform. According to the method, the problems of model splitting, scheduling response lagging, low data collaboration efficiency, insufficient credibility of the performance process and the like in the urban reconstruction project are solved, and the intelligence, transparency and automation level of the construction process is remarkably improved.

The invention discloses a document review method and device based on the full life cycle of science and technology projects and a medium, belongs to the technical field of document review, and solves the problem of how to improve the accuracy of normative review of science and technology project documents. According to the method, project document content is sequentially decomposed into field type analysis, specification requirement analysis and content specification analysis on the basis of the thinking chain technology, each item of analysis depends on the result of the previous item of analysis, and a complete path of conventional review is constructed step by step; the method comprises the following steps: analyzing whether a conflict and a logical conflict exist between a current to-be-audited project document and a historical document or not by utilizing a retrieval generation enhancement technology, and obtaining a plurality of fragments associated with to-be-audited fragments of the document from the documents in different life cycles; and ranking of possible useful fragments is provided for the large language model, an examination result is given, logic conflicts and contradictions among the documents are identified and solved, and the examination accuracy is improved from the aspects of consistency and logicality of the documents to be examined and historical documents.

The invention discloses an intelligent networked battery full life cycle optimization system and method, and relates to the technical field of energy management, the system comprises a sensor array module, temperature data and voltage data in the battery operation process are continuously collected through a sensor array, an initial multi-dimensional time sequence data set is formed, and the initial multi-dimensional time sequence data set is stored in the sensor array module; the alarm and adaptive adjustment module is used for obtaining an alarm log record aiming at the initial time sequence data set, triggering the adaptive adjustment module to dynamically optimize battery operation parameters according to the alarm log record, generating a temporary control instruction, reducing the influence range of temperature or voltage abnormity and obtaining adjusted operation state data; according to the intelligent networked battery full life cycle optimization system and method, risk monitoring of the battery full life cycle is realized, and the battery operation safety and reliability are effectively improved.

The invention provides a leasing equipment full life cycle monitoring method and system based on the Internet of Things, and belongs to the technical field of equipment operation and maintenance monitoring, and the method comprises the steps: obtaining real-time state data of leasing equipment in an operation process through a multi-source sensor; performing feature extraction on the real-time state data to obtain various feature vectors, and constructing a multi-dimensional feature vector set; inputting the multi-dimensional feature vector set into a random forest model, and judging whether the leasing equipment is in an abnormal state or not in combination with a space-time clustering algorithm; if yes, fault prediction is carried out on the leasing equipment in combination with an abnormal detection result, historical operation data and a baseline model, and a fault probability value of the leasing equipment is obtained; the future position of the leasing equipment is predicted based on the position data, an electronic fence boundary is set for the leasing equipment, if the future position exceeds the electronic fence boundary, an early warning notification of trajectory deviation is generated, and the system finally realizes trajectory and fault visual presentation in a thermodynamic diagram mode, so that the equipment operation and maintenance intelligence and management precision are improved.

The invention provides a solid waste recycling full life cycle environmental impact evaluation method, which belongs to the technical field of solid waste recycling, and evaluates environmental impact by constructing a system boundary and time dynamic list including solid waste collection, transportation, pretreatment, recycling and product use stages and applying a time weighted characterization model. A time discount rate is introduced to quantify future environmental influence, a multi-scene influence prediction function is adopted to construct a simulation matrix, and an environmental influence time distribution curve is calculated. A four-dimensional index system of resource recovery efficiency, energy substitution efficiency, pollutant emission reduction and environmental impact mitigation is established, a system dynamics and Envi rPred ictor deep learning model is combined to predict a solid waste long-term environmental behavior, an environmental impact comprehensive evaluation matrix is constructed, characterization factors are dynamically adjusted, an iterative optimization mechanism is formed, and the environmental impact mitigation efficiency is improved. Scientific evaluation on the solid waste recycling full life cycle environment influence is realized.

The invention discloses an asset management system based on a full life cycle, relates to the technical field of asset management, and comprises centralized management, real-time monitoring, intelligent analysis and scientific decision of asset data. The asset management system based on the full life cycle comprises an asset information management module, an Internet of Things data acquisition module, a data analysis and intelligent maintenance module, an intelligent decision support module, a visual management module, a risk early warning and compliance management module and a block chain evidence storage and traceability module. Through the asset information management module, basic information of assets is intensively recorded, updated, audited and cleaned, data formats are unified, meanwhile, the Internet of Things data collection module collects asset operation data in real time, the data are subjected to cleaning, conversion, feature extraction and other processing in the big data analysis and intelligent maintenance module, and the data are stored in the storage module. Effective integration of multi-source data is achieved, the system further provides an intelligent analysis function, and deep mining is carried out based on the integrated data.

The invention relates to the technical field of geotechnical engineering, and discloses a soft soil foundation full-life-cycle intelligent electro-osmosis maintenance system which comprises a field control system. And the intelligent monitoring regulation and control system transmits a feedback signal to the power supply system, and the field control system and the spraying humidification system perform corresponding actions, so that active prevention and control of foundation diseases are realized. Dynamic management is carried out on the anode boundary through real-time monitoring data, regular or on-demand starting is carried out through intelligent decision, the physical and mechanical properties of a foundation soil body are dynamically improved through the electroosmosis effect of a field control system, and the durability and long-term stability of the foundation soil body are improved; according to the intelligent electroosmosis maintenance system, the efficiency of an electroosmosis reinforcement system can be improved, the environmental adaptability is enhanced, and long-term stable operation is achieved.

The invention relates to a monitoring method and system for the full life cycle of a transformer substation project, and the method comprises the following steps: deploying an unmanned plane automatic airport to collect environment data, and selecting a transformer substation project construction site according to the actual construction demands and the environment data; modeling the power generation and transformation project based on the monitoring data of the power generation and transformation project construction site, and constructing a hidden danger sample library; constructing an intelligent monitoring system which comprises a hidden danger recognition module, an expert rechecking module and a decision generation module; wherein the hidden danger identification module performs hidden danger identification by using an improved YOLOv8n network to obtain a hidden danger target; the improved YOLOv8n network is specifically characterized in that a convolution attention module and an adaptive feature fusion module are embedded in a backbone network; the hidden danger target passing through the expert rechecking module is input into a decision generation module, and a hidden danger decision is generated and issued to an unmanned aerial vehicle automatic airport; the unmanned aerial vehicle automatic airport receives and controls the unmanned aerial vehicle to execute the hidden danger decision.

The invention discloses a shale gas full life cycle yield prediction method, and relates to the field of shale gas development. According to the shale gas full life cycle yield prediction method, the production stage of a shale gas well is divided into six stages of stable yield, continuous decreasing, intermittent production, pressurization decreasing, pressurization intermittent opening and fracturing effect receiving; in the stable production stage, the gas production rate is predicted by adopting a productivity coefficient method based on unstable linear flow, in the continuous decline stage, the gas production rate is predicted according to the ARPS decline model analogy partition decline rate, and in the intermittent production stage, the gas production rate is predicted by combining the ARPS decline model and the intermittent efficiency; in the pressurization decline stage, the gas production rate is predicted according to the gas well decline rate of the corresponding decline stage by adopting monthly production data; the gas production rate is predicted in combination with a decline model and the intermittent opening efficiency in the pressurizing intermittent opening stage; and predicting the gas production rate by using the effected ARPS model in the fracturing effected stage. According to the shale gas full life cycle yield prediction method, the corresponding yield prediction method is established according to the production rules of different development stages of the shale gas full life cycle, and the yield prediction efficiency and accuracy are improved.

The invention relates to the technical field of electric power iron tower full-life-cycle carbon footprint accounting, provides an electric power iron tower full-life-cycle carbon footprint accounting method and system, and aims to solve the problems of low efficiency and poor accuracy of electric power iron tower full-life-cycle carbon footprint accounting in the prior art. The method comprises the steps that an electric power iron tower component library is constructed, and a design stage carbon accounting benchmark is generated in combination with a building information model, a steel model, a welding process and anti-corrosion coating parameters; capturing assembly installation deviation and splicing gaps in real time, calculating material loss caused by construction errors, and converting the material loss into carbon emission increment; loading data by using a digital twinning technology, adjusting a material loss early warning threshold value, and updating design data; based on the corrected data, icing load deformation and corrosion expansion in the operation and maintenance stage are analyzed, and a full-life-cycle carbon footprint report is generated in combination with the updated stress distribution data. According to the technical scheme provided by the invention, the efficiency and accuracy of the full-life-cycle carbon footprint accounting of the electric power iron tower can be improved.

The invention provides an energy storage battery full life cycle management method, system and device and a medium, and belongs to the technical field of energy storage battery management, and the method comprises the steps that an edge node collects energy storage battery operation parameters, power grid operation parameters and environmental data in an energy storage battery box and provides the parameters to a cloud node; the cloud node solves an energy storage battery charging and discharging power instruction and an energy storage battery thermal management set value by taking the minimum energy storage battery full life cycle cost function as a target and taking an energy storage battery SOC constraint, a power constraint and a power grid power balance constraint as constraint conditions, and issues the energy storage battery charging and discharging power instruction and the energy storage battery thermal management set value to the edge node; and the edge node adjusts the operation parameters of the energy storage battery according to the charging and discharging power instruction of the energy storage battery and the thermal management set value of the energy storage battery, inputs the operation parameters into the battery health state prediction model, and performs early warning and reminds operation and maintenance personnel when the energy storage battery is predicted to have a fault. The full-life-cycle closed-loop management of the energy storage battery is realized, the safe operation of the battery is ensured, and the operation efficiency is improved.

The present application belongs to the field of carbon emission statistics, and particularly relates to a carbon emission statistical tracking system based on the whole life cycle of products, which can effectively track the total carbon emission of each product in the whole life cycle after being sold out through the cooperation of a detection module, a remote recording module and a terminal receiving module; meanwhile, the time t less than the threshold t1 is not included in the total amount, so that the situation of carbon emission caused by the operator's accidental touch to start or the start for a few minutes and the discovery of problems requiring timely stop can be reduced, the accurate calculation of the carbon emission amount is improved; through the setting of the influence coefficient u, the problem of the increase of the carbon emission amount caused by the insufficient treatment of raw materials in the same use time due to the increase of the service life of the product, the aging of parts and the accumulation of residues in the product can be corrected.

The invention discloses a scientific and technological achievement full-life-cycle traceability tracking management system, and relates to the technical field of scientific research management, and the system comprises a data fusion collection module which is used for collecting data of all stages of a scientific and technological achievement full-life cycle, and carrying out the format conversion and protocol adaptation of the data; the safe and credible storage module is used for storing the collected data by adopting a mixed framework combining distributed storage and blockchain storage; the intelligent analysis and decision module is used for analyzing the stored data based on an artificial intelligence model, mining data values and generating decision suggestions; and the dynamic interaction application module provides visual achievement traceability query, real-time state monitoring, intelligent early warning and decision support functions for different user roles. A semantic mapping rule is dynamically learned by using a reinforcement learning algorithm through the adaptive protocol translation unit, a heterogeneous protocol is automatically adapted, and seamless joint of multi-source data is realized.

The invention provides a full-life-cycle water and fertilizer management method and system for blueberry planting, and relates to the field of crop fertilization, and the method comprises the steps: obtaining water and fertilizer management experiment data of a plurality of blueberry growth stages; based on the water and fertilizer management experimental data of the plurality of blueberry growth stages, establishing a growth-related weighted undirected graph of the plurality of blueberry growth stages; determining a key growth factor and a key water and fertilizer management factor of each blueberry growth stage based on the water and fertilizer management experimental data of the plurality of blueberry growth stages and the growth-related weighted undirected graph of the plurality of blueberry growth stages; based on the water and fertilizer management experiment data, the key growth factors and the key water and fertilizer management factors of the blueberry growth stage, determining candidate water and fertilizer management schemes of the blueberry growth stage; based on the candidate water and fertilizer management scheme of each blueberry growth stage, a water and fertilizer management scheme for the whole life cycle of blueberry planting is generated, and the method has the advantages that accurate supply and intelligent regulation of water and fertilizer are achieved, and the water and fertilizer utilization rate is increased.

The invention relates to a salt cavern integrated energy system full life cycle economic evaluation method, and the method comprises the steps: obtaining electric energy supply and demand data in a target region, and building a mathematical model of a salt cavern integrated energy system based on the electric energy supply and demand data and at least one salt cavern geological parameter; based on the mathematical model, an objective function is determined with the maximum comprehensive economic benefit in the whole life cycle, and a double-layer optimization model of the salt-cavern comprehensive energy system is established; and performing multi-scene evaluation by using a double-layer optimization model to perform modeling and optimization solution on each scene to obtain economy of the system in different scenes, and determining the optimal configuration of the salt cavern integrated energy system according to the economy of the system in different scenes. Therefore, the problems that the overall value is difficult to accurately evaluate and the scientificity of investment decision and the rationality of resource allocation are influenced due to the fact that a static analysis mode is adopted in related technologies and multiple factors such as related complex technologies, economy and environment are not fully considered are solved.

The invention belongs to the technical field of road marking performance detection, and particularly discloses a road marking full-life-cycle performance detection system, which comprises the following steps of: acquiring an initial retroreflection brightness coefficient and a geographic position of a whole road in a marking construction acceptance stage to generate a road marking optical performance reference digital map; the real-time initial retroreflection brightness coefficient and the position of the marking line are collected in the daily service of a road, and the optical performance of the marking line in the service state is compared and evaluated point by point by taking the reference map as a reference, so that the real performance state of the marking line in the whole life cycle is dynamically described, and the marking line quality is improved. Meanwhile, optical sudden change event identification is carried out in service state comparison based on the reference digital atlas, and external event data are accessed for association, so that a maintenance decision is converted into an active intelligent intervention normal form with traceable causes and orientable measures from a passive response and representation repair mode; and the accuracy and timeliness of road marking maintenance are obviously improved.

The invention discloses a compliance supervision platform design method based on a full life cycle of spatio-temporal data of an intelligent networked automobile, and belongs to the field of intelligent traffic, Internet of Vehicles and data governance, and the method comprises the steps: according to behavior characteristics of data activities, determining related data life cycle links, and obtaining meta-information of each data life cycle link; based on meta-information of each data life cycle link, a risk perception module is introduced, and the risk perception module comprises a rule engine and a behavior analysis model and is used for recognizing and judging high-risk behaviors in the process in real time; fusing the preliminary risk score and the identification score to obtain a comprehensive risk score; and when the comprehensive risk score exceeds a preset alarm threshold value, automatically triggering an early warning process, and pushing the early warning process to an industry supervision department. According to the method, roles can be configured, review can be traced, and behaviors can be traced back, a landing and extensible technical path is provided for intelligent network connection automobile spatio-temporal data compliance management, and the industry compliance management level is improved.

The invention discloses a fixed asset full-life-cycle intelligent dynamic management system based on data management, and the system comprises a data collection module which obtains fixed asset full-life-cycle data; the information entropy enhancement module is used for generating fixed asset management data; the dynamic management module is used for establishing a fixed asset dynamic management model; the real-time monitoring module is used for dynamically adjusting the maintenance plan and resource configuration of the fixed assets; the mobile checking module is used for intelligently correcting the mobile checking data of which the error exceeds a threshold value; the automatic reconciliation module is used for storing an optimization result into a fixed asset resume database; and the decision support module is used for seamless connection and collaborative optimization of fixed asset dynamic management, mobile checking and automatic account checking processes. According to the invention, seamless connection and collaborative optimization of dynamic management, mobile checking and automatic account checking processes of fixed assets can be realized.

This invention relates to a method for assessing the carbon emissions of new energy vehicles throughout their entire life cycle, taking into account inter-provincial power transmission. It belongs to the field of carbon emission accounting technology and includes the following steps: S1: Calculating the carbon emissions of new energy vehicles during the production stage; S2: Calculating the carbon emissions of new energy vehicles during the usage stage; S3: Calculating the carbon emissions of new energy vehicles during the scrapping and recycling stage; S4: Calculating the total carbon emissions of new energy vehicles throughout their entire life cycle. This invention accurately reflects the carbon emission transfer effect brought about by inter-regional power transmission; achieves precise accounting of the carbon footprint of new energy vehicles during the usage stage; and realizes the assessment of carbon emissions in the three stages of production, use, and recycling of new energy vehicles, providing support for formulating locally appropriate strategies for the promotion of new energy vehicles and cross-regional collaborative emission reduction.

The invention provides a method and a device for determining full life cycle carbon emission of a skid-mounted transformer substation, and the method comprises the steps: obtaining the carbon emission of the skid-mounted transformer substation according to the obtained full life cycle information of the skid-mounted transformer substation; and determining the carbon emission in the raw material acquisition stage, the carbon emission in the manufacturing stage, the carbon emission in the construction stage, the carbon emission in the operation stage, the carbon emission in the digital operation stage and the carbon emission in the dismantling stage of the skid-mounted transformer substation, and comprehensively obtaining the full-life-cycle carbon emission of the skid-mounted transformer substation. The method comprises the following steps: establishing a boundary of a skid-mounted mobile substation carbon emission evaluation system, constructing a full-life-cycle carbon emission analysis model and a calculation process by combining production and manufacturing and construction operation characteristics of the skid-mounted mobile substation carbon emission evaluation system, and collecting, calculating and analyzing data of carbon emission at each stage of the full life cycle of a product by taking an actual project as a research object; and a scientific basis is provided for accurately mastering the carbon emission condition of the whole life cycle of the skid-mounted mobile substation.

The invention discloses an anti-seepage curtain full-life-cycle intelligent monitoring system, which comprises a sensing module, a transmission module, a data processing module and an application module, and is characterized in that high-precision sensors comprise a displacement sensor, a stress-strain sensor, a seepage pressure sensor and a temperature and humidity sensor, so that structural design data, monitoring data and operation and maintenance data are obtained; the environment monitoring sensor obtains precipitation and soil moisture, so that deformation monitoring of a curtain material is obtained, the deformation condition of the curtain is monitored in real time, efficient and accurate state monitoring and evaluation can be conducted in the full life cycle of the anti-seepage curtain, the manual inspection cost is effectively reduced, the monitoring precision and the response speed are improved, and the anti-seepage effect is improved. Through an intelligent early warning mechanism and data analysis, the system can realize early prevention and risk control of accidents, greatly reduce the manual inspection cost, and improve the monitoring precision and response speed.

The invention discloses a subsea tunnel surrounding rock full life cycle test method based on a supergravity geotechnical centrifuge technology, which comprises the following steps: firstly, constructing a model box, carrying out scale simulation on a subsea tunnel and a surrounding rock structure thereof, then putting the model box into a vacuum box for saturation treatment, finally taking the model box out of the vacuum box, putting the model box into a supergravity geotechnical centrifuge, and testing the whole life cycle of the subsea tunnel surrounding rock. And the super-gravity geotechnical centrifuge is started to rotate, and the strain sensor collects the dependent variable of the rock stratum near the tunnel reduced-scale pipeline in real time, so that the nonlinear elastic deformation of the rock stratum in the full life cycle in the running process of the train track simulation mechanism is observed. The model box is constructed to simulate the subsea tunnel and the surrounding rock structure thereof, test analysis is performed based on the supergravity geotechnical centrifugal technology, the evolution process of damage of the subsea tunnel and the surrounding rock structure thereof is remarkably accelerated, the experimental period is shortened, and the change condition of the whole life cycle is rapidly tested and determined.

The present application proposes a method, device, equipment and storage medium for railway tunnel model review, deepening and delivery throughout the entire life cycle. Among them, the method includes: obtaining the initial model structure tree and design model corresponding to the design delivery tunnel; conducting model review on the design model based on the pre-established design delivery standards; determining that the model review is passed, and obtaining the first tunnel model through model delivery based on the design model; updating the initial model structure tree based on the first tunnel model to obtain the model structure tree corresponding to the design delivery tunnel; conducting coding conversion on the design model to obtain the corresponding model code; splitting and shearing the first tunnel model to obtain the second tunnel model; and obtaining the tunnel model corresponding to the design delivery tunnel based on the model structure tree, model code and the second tunnel model. Through the technical solution of the present application, it is possible to achieve railway tunnel model review, deepening and delivery throughout the entire life cycle.

This invention discloses a hail identification and tracking method and system for the entire life cycle of hail embryos, relating to the field of meteorological detection. The method includes: S1 acquiring dual-polarization radar volume scan data; S2 identifying hail embryo particles; S3 determining whether the hail embryo particles are new particles, and if so, creating a life profile; S4 tracking target particles in spatiotemporal correlation and updating the life profile; S5 determining whether the target particles have transformed into hail; S6 acquiring the current life profile of the hail particles; S7 determining whether hail precipitation conditions have been triggered, and if so, proceeding to S8, otherwise returning to S1; S8 analyzing the location of the precipitation area; S9 spatially clustering the precipitation area location and generating a probability map of the hail precipitation area and early warning information. By establishing a "life profile" for each hail embryo particle that includes its trajectory, phase evolution, and environmental thermodynamic conditions, the complete process of hail embryo formation from initial formation to final hail precipitation is tracked. Based on the statistical analysis of the life profile, key transformation characteristics of different hail storm types are adaptively identified, thereby achieving early hail warning.

The invention relates to the technical field of engineering suitability evaluation, in particular to a full-life-cycle comprehensive fuzzy evaluation method based on a time sequence function and a related product, and the method comprises the steps: dividing evaluation time periods of a full life cycle, and constructing an influence factor coefficient matrix and a mutual feedback effect matrix of each time period; performing function fitting on the time sequences of the influence factor matrix and the mutual feedback effect matrix by adopting a least square method to obtain a time sequence function; an evaluation matrix in each time period is constructed, a stationary point value of a time sequence function is solved, evaluation values of all schemes in different evaluation time periods are calculated, a comprehensive evaluation function is used for comparing the multiple schemes, and finally the optimal scheme is determined. According to the method, a time sequence function is adopted for modeling influence factors and mutual feedback effects of all time periods, and the dynamic change trend of all schemes in different stages can be accurately reflected; through calculation of an evaluation matrix and a correlation coefficient, advantages and disadvantages of each scheme can be systematically integrated.

The invention relates to a method for rapidly measuring and calculating carbon emission in the whole life cycle of a transformer substation, and belongs to the field of carbon emission prediction. The method comprises the following steps: S1, decomposing a full life cycle and screening influence factors; s2, carrying out influence factor characteristic analysis and sensitivity analysis; and S3, constructing a general measurement and calculation model and carrying out accounting simulation. According to the method, the carbon emission influence factors in the whole life cycle of the transformer substation are delicately decomposed, key elements are accurately screened, and the correlation analysis and sensitivity analysis technologies are combined, so that a carbon emission measuring and calculating system which is high in universality and wide in applicability is successfully constructed.