77 results about "Dimensional analysis" patented technology

The invention discloses a data leakage early warning method, device and equipment based on buried point collection and a storage medium, and relates to the technical field of system exception monitoring, and the method comprises the steps: obtaining exception log information and historical data information sent by a buried point collection service node; performing aggregation counting on the abnormal log information according to preset time granularity to obtain abnormal quantity statistical data of each time granularity; performing transverse and longitudinal analysis on the abnormal quantity statistical data and the historical data information according to a preset transverse and longitudinal analysis strategy to obtain a comparison deviation value; and performing data leakage early warning according to the comparison deviation value. According to the method, time-sharing processing and multi-dimensional analysis are carried out on the abnormal log data of the system, so that real-time early warning and service subdivision monitoring of buried point data leakage are realized, and the reliability and fault positioning efficiency of the system are improved.

The invention relates to the technical field of software testing, and discloses an agent-based multi-dimensional test sample automatic generation method and system.The agent-based multi-dimensional test sample automatic generation method comprises the steps that code changes are captured, interface definitions are extracted, and multi-source data are fused for consistency verification; constructing a multi-dimensional dependency graph and analyzing the change influence to obtain an associated interface list; generating a multi-dimensional test scene; performing parameter traceability and consistency derivation, and initializing test data and environment to obtain a complete test data set; generating a use case code, and performing hierarchical optimization and executable verification; test arrangement optimization and automatic execution are carried out, and faults are monitored and diagnosed in real time; carrying out multi-dimensional analysis and defect identification, dynamically evaluating the value of a test case and optimizing a test strategy to obtain a comprehensive test report; according to the invention, full-process automation of test case generation is realized, the test efficiency and quality are improved, and the test maintenance cost is reduced.

The invention discloses a blasting construction harmful effect control method and system, a medium and a product, and relates to the field of engineering construction. The method comprises the steps that a three-dimensional analysis model is constructed according to geologic structural plane data of a to-be-blasted area and spatial orientation data of a protected object, and a target area where the flying stone main throwing direction conflicts with the orientation of a vibration sensitive area is recognized based on the three-dimensional analysis model; constructing a blasting sequence according to the spatial range of the target area, the geologic structural plane occurrence and a preset safe throwing sector area; coupling simulation is conducted on the blasting sequence through the blasting dynamics simulation model, whether the flying stone throwing track and the vibration distribution meet the preset safety requirements or not is verified, and if not, blast hole grouping or detonation time difference is adjusted, and iterative optimization is conducted till a final blasting scheme meeting the flying stone throwing track and the vibration distribution at the same time is obtained; and outputting a final blasting scheme. By implementing the technical scheme, the harmful effect of blasting construction can be effectively controlled.

The invention discloses a graded blasting construction method for a shallow-buried soft rock tunnel sensitive section. The method comprises the steps that measuring points are arranged in a tunnel chamber, a ground surface non-cavity section and a cavity section, and blasting vibration data are obtained; peak vibration velocity prediction models are established in a partitioned mode, an attenuation model is adopted in a chamber, a correction term is introduced into a non-cavity section of the earth surface to correct the attenuation model, and a multivariable model is established for the cavity section through dimensional analysis by integrating the horizontal distance, the elevation difference, the explosive quantity, the rock mass density and the tensile strength; determining a ground surface vibration velocity safety threshold, and quantifying a cavity vibration velocity amplification coefficient and an influence range thereof; based on the peak vibration velocity probability distribution and a preset safety level, establishing a safe dose prediction model and a safe range model; and dividing control areas according to the model, and implementing graded construction. According to the method, the vibration propagation law can be accurately described, the cavity amplification effect can be quantified, dynamic prediction of the blasting safety explosive quantity and range is achieved, and disturbance of blasting vibration to surrounding rock is effectively controlled through hierarchical management and control.

The invention discloses a gas-liquid two-phase flow measurement method based on a bent pipe and an acoustic emission technology, and belongs to the field of gas-liquid two-phase flow measurement. The method comprises the steps that the average liquid holdup HL of two-phase flow in a pipeline is measured, and the instantaneous speed Vc of a gas phase and a liquid phase passing through the 45-degree section of the bent pipe is calculated; identifying a gas-liquid two-phase flow pattern in the pipeline; taking the Vc, the HL, the apparent liquid velocity VSL and the apparent gas velocity VSG as variables, and adopting a dimensional analysis method to propose a correlation between the Vc and the VSL and between the HL and the VSL and between the VSL and the VSG according to different flow patterns; calculating an effective voltage value RMS of the acoustic emission signal, and establishing a correlation between the RMS and the VSL and VSG; fitting parameters in the correlation formula; newly collected Vc, HL and RMS are input into the fitted correlation formula, VSL and VSG are output, and therefore measurement of the gas-liquid two-phase flow is completed. Compared with a single-phase metering method after separation commonly used in the oil and gas industry, the device has the advantages of being simple in structure, low in measurement cost, capable of achieving real-time measurement, non-invasive and the like.

The application discloses a kind of lake total phosphorus concentration spatio-temporal evolution and driving factor identification method, and the application relates to water environment monitoring technical field, constructs water body, sediment and in and out lake river multi-medium linkage analysis system, carries out multi-scale spatio-temporal evolution analysis and multi-path mechanism quantization, realizes the accurate identification of scene main control driving factor, and the standardization analysis process is formed by verification solidification, the application has the advantages that by constructing water body, sediment and in and out lake river multi-medium linkage full-dimensional analysis system, simultaneously integrate multi-source spatio-temporal data covering full lake area function partition, complete hydrological year cycle, carry out the coupling analysis of multiple time scales and multiple spatial dimensions, break through the industry common defects that the evolution law of total phosphorus concentration is not comprehensive, data is insufficiently representative, and the whole chain variation characteristics cannot be clarified, caused by the fact that the prior art only focuses on single medium of water body, uses scattered point position low-frequency monitoring data.

This disclosure proposes an evaluation method and system for auxiliary coal blending, relating to the field of coal blending technology. The evaluation method for auxiliary coal blending includes the following steps: collecting basic blending data, which includes at least coal blending information, combustion parameters, environmental parameters, and equipment status data; establishing a multi-dimensional analysis model based on the basic blending data, and analyzing the basic blending data through the multi-dimensional analysis model to obtain analysis results; generating visualization charts based on the analysis results at a preset cycle; establishing an A / B comparison analysis mechanism; inputting the blending scheme verified by the A / B comparison analysis, along with the applicable conditions of the blending scheme, into a dynamic knowledge base; and establishing a review mechanism to analyze long-term data trends and continuously optimize the multi-dimensional analysis model and the dynamic knowledge base. This disclosure achieves closed-loop management of the entire process of blending schemes, from data collection, multi-dimensional evaluation, visualization, comparison verification to knowledge accumulation and continuous optimization.

The invention provides a method and device for carrying out cost optimization prediction through multi-dimensional business travel behavior analysis, and belongs to the technical field of enterprise business travel management.The method comprises the steps that business travel data are collected, cleaning, duplicate removal and entity alignment operation are carried out, and a business travel behavior data set is constructed; executing a preset query script on the business travel behavior data set, extracting characteristic indexes from preset dimensions, executing descriptive analysis, diagnostic analysis and clustering analysis, and generating a business travel behavior analysis report; and inputting the business travel behavior data set and the business travel behavior analysis report into a cost optimization prediction model to carry out business travel demand prediction, business travel price prediction and business travel travel optimization, generating an optimal travel travel scheme set, pushing the optimal travel travel scheme set to the employee user, collecting a feedback result of the employee user on the optimal travel travel scheme set, updating the business travel behavior data set, and obtaining a business travel result. And incremental training and iterative optimization are carried out on the cost optimization prediction model. Through multi-dimensional analysis and prediction, the travel cost is optimized, and the management efficiency is improved.

The invention provides a method for constructing a bearing test distortion model of an ice-resistant structure under the action of a dynamic ice load, and belongs to the field of test similar reduced scale model design under an ice breaking load of the ice-resistant structure. The problem that in the prior art, the strain rate of a fully-similar model is dissimilar due to the scale effect is solved; a traditional distortion model design method has the problem of dissimilar energy distribution. The method comprises the following steps: establishing a fully similar model from an ice-resistant structure prototype to a geometric and plate thickness equal ratio reduced scale; establishing a plate thickness distortion reduced scale model by using the same material on the basis of the geometric similar reduced scale model; preliminarily determining a collision contact position of the thickness distortion reduced scale model; a dynamic ice load similarity criterion is applied, correction factors are deduced through dimensional analysis, and ice body parameters and collision speed of a distortion model system are adjusted, so that the ice breaking capacity and dynamic structure response are similar to those of a prototype system. The device is mainly used in the field of polar region icebreaking.

The application discloses a feature warehouse feature value monitoring method and system, relates to the technical field of feature warehouse monitoring, and comprises the following steps: analyzing historical feature warehouse record data, and acquiring the review label of each historical feature value group; the label records the situation of the feature value group and explains; multi-dimensional feature performance analysis is carried out on the historical feature value group, different dimensional feature performances are determined, a multi-dimensional feature performance group is formed, and a feature performance baseline model is constructed based on the group and the corresponding review label, which is used for representing the normal performance mode of the historical feature value; real-time multi-dimensional analysis is implemented on a real-time feature value group, data comparison is carried out with the baseline model output data, a feature deviation index is calculated, and data anomaly early warning is sent for the real-time feature value group with the deviation index greater than or equal to a preset value; and the application realizes automatic monitoring of feature data, and improves the robustness and abnormal detection precision of a machine learning pipeline.

The invention relates to the technical field of down-the-hole drill ball tooth drill bit wear measurement, in particular to a down-the-hole drill ball tooth drill bit wear value real-time measurement method and system, and the method comprises the steps: carrying out the optimization and registration of an initial three-dimensional model, and obtaining an overall wear quantized value of a down-the-hole drill ball tooth drill bit; analyzing a mapping relation between the while-drilling parameters and the overall wear quantized value, and constructing a database between the while-drilling parameters and the drill bit wear value; deriving a dimensionless variable according to a dimensional analysis method and a database, and performing combined screening on the dimensionless variable, a second-order polynomial and a cross term to determine a dimensionless variable combination influenced by drill bit wear; and substituting the dimensionless variable combination into the multiple linear regression model to establish a mathematical relationship model between the drill bit wear and the while-drilling parameters, thereby realizing the real-time measurement of the wear value of the ball tooth drill bit of the down-the-hole drill. According to the method, non-dimensional variables of the while-drilling parameters are obtained based on dimensional analysis, the model is built in combination with multiple linear regression, the wear value of the ball tooth drill bit of the down-the-hole drill is measured in real time, and construction efficiency and safety are improved.

The invention relates to the technical field of power grid project cost management and business intelligence, and discloses a project cost multi-stage intelligent analysis and examination method, system, equipment and medium, and the method comprises the steps: building a power grid project cost data warehouse, and achieving the integration and standardization of multi-source cost data; establishing an OLAP multi-dimensional analysis model, and supporting general cost comparison and key index analysis in a budget calculation stage, feasibility research estimation, preliminary design budget calculation, completion settlement three-calculation comparison, first supply material check and review list consistency check in a settlement stage; designing an intelligent decision engine based on data mining, and generating review opinions through association rules, a classification algorithm and an anomaly detection technology; and a BI visual instrument panel is developed, and multi-dimensional display, real-time monitoring and interactive analysis of the power grid cost data are realized. Through systematic application of the BI technology, deep mining, intelligent decision and visual display of engineering cost analysis are realized, and the efficiency and precision of cost review are remarkably improved.

The invention relates to a data analysis technology, and discloses a city governance data quality multi-dimensional analysis method, device and equipment, and the method comprises the steps: obtaining a to-be-analyzed data block, carrying out the quantitative analysis of the to-be-analyzed data block based on preset data dimensions, and obtaining a standardized sub-score corresponding to each data dimension; obtaining a performance feedback index of the downstream large model, dynamically adjusting the distribution weight of each data dimension by using a predefined mapping rule base according to the performance feedback index, and performing normalization processing on the adjusted weight to obtain a normalized weight of each data dimension; performing weighted summation on the standardized sub-score of each data dimension and the corresponding normalized weight to generate a final comprehensive quality score of the to-be-analyzed data block; and obtaining a quality multi-dimensional analysis result according to a preset quality partition interval in which the comprehensive quality score is located, and distributing the to-be-analyzed data block to a corresponding processing path for data processing. According to the invention, the efficiency of quality multi-dimensional analysis of urban governance data can be improved.

The application discloses a user dynamic activity degree calculation method, device and system based on ETC data, and belongs to the technical field of data analysis. The method comprises the following steps: obtaining toll data and associated consumption data corresponding to a unique identifier of a user under an ETC account of the user; aligning the two in time and space through a preset time-space correlation condition, constructing a toll-consumption event chain, and calculating a current dynamic activity degree value of a geographic node based on a time-space decay dynamic weight model; dividing the activity degree into levels according to double thresholds, rendering the levels in a differentiated visual style, and superimposing a consumption feature icon to realize visual dynamic updating. The application breaks through the limitation of single-dimensional analysis, integrates toll and consumption data, realizes accurate quantification of the activity degree through a time-space decay model, intuitively presents user behavior characteristics, improves the application value of ETC data, and provides data support for expressway operation analysis, high-activity-degree area identification and accurate decision-making.

The invention provides application of a tetrahedral structure to reduction of debris flow peak flow, a construction method of a peak flow reduction rate prediction model, a peak flow reduction rate prediction method and a peak flow regulation and control method, and relates to the technical field of debris flow treatment. According to the design, the tetrahedral structure is applied to reducing the peak flow of the debris flow. The prediction model construction method is obtained through a dimension analysis method, and the peak flow reduction rate is calculated through the prediction model. The peak flow regulation and control method is implemented based on the prediction result of the peak flow reduction rate. The method focuses on specific regulation and control of the peak flow of the mountain debris flow, exclusive application of a tetrahedral structure is adopted as the core, the regulation and control precision of disaster-causing key parameters is precisely improved, a peak flow reduction rate prediction model and method are constructed in a matched mode, multi-dimensional core parameters are integrated, the precise pre-estimation effect is scientifically quantified, and a closed-loop process from simulation optimization to field landing is achieved. The method is suitable for various disaster scenes, and takes prevention and control efficiency and engineering economy into consideration.

The invention discloses a power transformation loop reliability multi-source data fusion method, system and equipment based on a natural language processing technology and a medium, and belongs to the technical field of power transformation loop reliability, and the method comprises the steps: carrying out the intelligent management of machine account data and operation data of a power transformation loop, constructing a standardized data base, and outputting a data set; based on the data set, realizing association and integration of cross-system data through multi-dimensional feature matching, and outputting a fused data set; on the basis of the fused data set, a natural language processing model is adopted to study and judge a shutdown event affiliation loop and an event type; and based on the event type research and judgment result, performing full-dimension analysis on the operation data, completing loop state classification and shutdown statistics, and generating loop reliability operation data. According to the method, by fusing natural language processing and graph neural network technologies, intelligent management and deep semantic fusion of the multi-source heterogeneous data of the power transformation loop are realized, and the problems of poor data quality, weak relevance and the like in a traditional method are effectively solved.

The invention provides a general analysis method for the stability of a slope in any form based on strip-block resultant external force moment correction. The general analysis method comprises the following steps: S1, constructing a two-dimensional analysis model of the slope; s2, analyzing the stress of the strip blocks; s3, searching the gravity center position of the sliding body; s4, acquiring key geometric parameters; s5, analyzing the overall stress balance and moment balance of the sliding body; and S6, solving a stability coefficient. Double analysis of stress balance and moment balance is realized by adopting a strip-block and external force unified expression form, so that a basic mechanical framework of a stability analysis method is unified, and a famous method, an upgraded version and the like are all special cases of the method; and the huge technical limitation that some current methods can only consider mechanical preciseness or applicability in one aspect is broken through. The invention provides a brand new analysis method system, so that the stability analysis result can be obtained more scientifically, and the most essential path is provided for personnel in the field to comprehensively understand the stability analysis theory.

This invention relates to the field of fluid mechanics and transient process analysis of hydraulic systems, and discloses a method for determining the occurrence boundary and risk level of liquid column separation. The method utilizes a visual test bench to conduct multiple experiments under different combinations of test parameters, collecting data and simultaneously recording the liquid column separation state. Based on Buckingham's π theorem, dimensional analysis is used to construct multiple independent dimensionless parameter sets from the test parameter combinations. These are used as input features, with the separation state as the target variable. A machine learning algorithm is introduced for multiple batch training to calculate importance scores, selecting the dominant dimensionless parameter with the highest and most stable score. Subsequently, regression analysis is used to fit the data boundary, solving for the intersection point and outputting the critical equilibrium point as a quantitative benchmark for the occurrence boundary. After confirming separation, high-scoring dimensionless parameters are selected to construct composite judgment parameters, which are compared with preset thresholds to classify the risk level. This invention can accurately define the critical equilibrium point of cavitation occurrence and quantitatively assess its risk severity.

The application discloses a method for mapping aerodynamic force of aerodynamic elasticity of a heavy gas wind tunnel to air medium, and belongs to the technical field of high-speed wind tunnel test. The application determines key influence parameters of aerodynamic force characteristics in the heavy gas medium through dimensional analysis, derives flow similarity parameters of the heavy gas and the air medium through similarity analysis, determines the equivalent Mach number of the heavy gas medium according to the similarity condition, and finally accurately maps the aerodynamic force coefficients related to aerodynamic elasticity measured in the heavy gas medium to the air medium through mapping parameters, so that the equivalent conversion of the aerodynamic force of the aerodynamic elasticity test of the heavy gas medium wind tunnel to the air medium is realized, and then the equivalent conversion of the flutter characteristics is realized through the aerodynamic force mapping relationship. The application solves the technical problem that the aerodynamic test results cannot be directly applied due to the difference in thermodynamic characteristics between the heavy gas and the air medium, the slope error of the aerodynamic force coefficient in the small attack angle range after mapping is not more than 2%, and the application can be used for perfecting the application system of the heavy gas wind tunnel test data.

The invention discloses a planned electric quantity management and control method and system based on multi-index cooperative tracking, and the method belongs to the technical field of digital management and control of an electric power system, and achieves the collection and standardization of cross-system data through constructing a multi-index system comprising a plan type index, an execution type index, a prediction type index and a deviation type index; a cooperative tracking mechanism is established based on the multi-index system, hierarchical early warning is triggered by comparing execution type, plan type and prediction type indexes in real time, a supervision order is automatically generated and tracked to a deviation closed loop, and full-process management and control are achieved; and finally, a plan decomposition rule and an early warning threshold are optimized through multi-dimensional analysis, and a refined management and control suggestion is output. According to the method, the precision, efficiency and decision support capability of planned electric quantity management and control can be remarkably improved, and the method is suitable for multi-level (group, company and station) electric quantity management and control scenes of a large-scale electric power group.

The application provides a tetrahedron structure and a debris flow volume and density decay rate prediction method, a model construction method and a regulation method, and relates to the technical field of debris flow control. The tetrahedron structure is a regular tetrahedron solid structure, a regular tetrahedron solid frame structure or a regular tetrahedron solid sphere branch structure. The debris flow volume and density decay rate prediction method is calculated through a prediction model. The model construction method is obtained by analyzing the regulation factors of the tetrahedron structure on the volume and density of the debris flow by using the dimensional analysis method. The volume and density regulation method adjusts and optimizes the best throwing interval and arrangement mode of the tetrahedron structure based on the prediction results of the debris flow volume and density decay rate, and then throws the corresponding tetrahedron structure in the target channel by using the numerical simulation method or the debris flow dam break simulation experiment device. The application is flexible in arrangement, can effectively regulate the volume and density of the debris flow, enriches the measures and technical means for regulating the volume and density of the debris flow, and provides key parameter support and technical support for the prevention and control work.

This invention discloses a multi-dimensional analysis and abnormal fluctuation early warning system for chassis production quality data, specifically relating to the field of data analysis and early warning. The system includes: a data acquisition and standardization module that collects three types of raw data from chassis production: geometric dimensions, mechanical properties, and surface and weld images. After preprocessing, a standardized dataset and a benchmark parameter set are formed. A multi-dimensional analysis module sequentially performs quantitative assessments of dimensional consistency, structural stability, and surface integrity, outputting three sets of single-dimensional anomaly indices. A multi-mode coupling module integrates the single-dimensional indices into three sets of comprehensive coupled indices using three methods: linear weighting, nonlinear interaction, and extreme value sensitivity. A fusion decision module normalizes the coupled indices and then uses dynamic confidence weighting to obtain a single abnormal fluctuation determination value. An early warning execution module completes the three-level early warning threshold calibration iteration and triggers graded early warning handling based on the abnormal fluctuation value, achieving closed-loop control of chassis production quality anomalies throughout the entire process.

The invention discloses a carbonate rock bottom water gas reservoir numerical simulation parameter determination method and a related method. The method comprises the following steps: obtaining each physical model parameter of a carbonate rock bottom water gas reservoir physical model and a value range of each physical model parameter; determining a plurality of experimental scale model parameters; establishing an experimental scale carbonate rock bottom water gas reservoir numerical simulation model, and determining a value range of corresponding experimental scale model parameters; selecting a plurality of influence factors; screening to obtain a preset number of main control factors; in combination with a similar second theorem and a dimensional analysis method, determining a corresponding number of carbonate rock bottom water gas reservoir similarity criteria; and establishing a single-well scale carbonate rock bottom water gas reservoir numerical simulation model by taking each main control factor as a single-well scale model parameter, and determining a value range of the single-well scale model parameter. According to the method, effective parameter selection of numerical simulation is realized, the scientificity and reliability of parameter setting are improved, the workload is reduced, and efficient simulation is facilitated.

This invention proposes a three-phase comparative analysis system and method for a main transformer. The system includes a multi-source data acquisition and preprocessing module, a three-phase characteristic multi-dimensional comparison module, an anomaly level intelligent judgment module, and a personalized operation and maintenance strategy recommendation module. The system's implementation involves: first, the multi-source data acquisition and preprocessing module collects and fuses the three-phase electrical parameters of the main transformer from multiple sources; then, the three-phase characteristic multi-dimensional comparison module constructs a dual-dimensional analysis model combining vertical and horizontal comparisons to quantify the state differences of the three-phase electrical parameters; the anomaly level intelligent judgment module quantifies the degree of difference in three-phase parameters and associated risks; and finally, a two-dimensional matrix combining comprehensive difference values ​​and parameter risk levels is used to classify four anomaly levels, enabling data-driven decision-making. Finally, the personalized operation and maintenance strategy recommendation module recommends the optimal operation and maintenance strategy based on the anomaly level, main transformer attributes, operation and maintenance resources, and a recommendation rule base combined with a machine learning model.

This application relates to the field of geological exploration technology, and in particular to an intelligent prediction system and method for complex structures that integrates geological knowledge graphs and deep learning. The method includes: acquiring a real-time exploration dataset of the exploration area; based on the real-time exploration dataset, analyzing the stress distribution trend, microseismic activity rhythm, and aquifer lithology and pore structure under roof water inrush phenomena to obtain a multi-dimensional dynamic feature information set; based on the multi-dimensional dynamic feature information set, constructing a multi-dimensional analysis framework for the direct and indirect interactions between different parameter sets within the multi-dimensional dynamic feature information set; based on the multi-dimensional analysis framework, combining geological knowledge graphs and deep learning algorithms, deriving the complex structural features of the exploration area to obtain dynamic derivation results, generating an exploration structure-water inrush association rule base. Recording roof water inrush risks provides targeted safety decision-making basis for exploration projects, reducing the probability of subsequent water inrush accidents and ensuring the safety of personnel and equipment.

The invention relates to the field of ship propulsion systems, in particular to a ship propulsion system operation state diagnosis method and system based on an intelligent algorithm. The method comprises the steps that current and historical shafting data and operation plans are acquired, whether a current operation route is a specific operation route or not is determined based on the historical operation plans, the operation routes are classified and distinguished, and the specific operation route is subjected to data processing; the corresponding target historical shafting data are obtained, the ship operation state is determined in combination with the current shafting data, and the current ship state under the route can be more accurately judged by using the reference value of the historical data under the specific route; for a non-specific operation route, historical shafting data, current shafting data and a current operation plan are comprehensively considered to determine the operation state of the ship, the accuracy and reliability of diagnosis are improved through multi-dimensional analysis, abnormity of a ship propulsion system can be found in time, and safe operation of the ship is guaranteed.

The application discloses a multi-scale coupled heavy pollution weather forecasting and early warning method and system, and belongs to the technical field of weather forecasting and early warning; the method comprises the following steps: S1, receiving and standardizing multi-source heterogeneous data from each observation platform, fusing the multi-source heterogeneous data by using a data assimilation algorithm, and reconstructing a thermal-dynamic-pollution field three-dimensional analysis field; S2, based on the fused data and the analysis field, running a 'weather scale forcing W-mesoscale response M-microscale triggering mu' coupling diagnosis algorithm, quantifying key indexes of each scale, and establishing an early warning index library; S3, according to W-M-muChain concept model output, automatically generating a series of progressive early warning products from weather scale potential prediction to microscale near warning. Thus, accurate and seamless monitoring and early warning of the heavy pollution process are realized.

The invention provides a method and device for calculating the well depth of a vertical well in a low-exploration-degree complex structure area, and the method comprises the steps: predicting the first bottom boundary burial depth of a target geological layer according to a landmark stratum interface structure map constructed based on the geological related data of a to-be-researched area and the altitude of a design well; predicting a second bottom boundary burial depth of the target geological layer according to a first thickness between the target geological layer and the reference geological layer and a second thickness between the reference geological layer and the ground, which are determined based on a two-dimensional seismic profile map in the geological related data; performing multi-dimensional analysis according to the geological related data of the to-be-researched area, and determining a first weight corresponding to the first bottom boundary burial depth and a second weight corresponding to the second bottom boundary burial depth; and according to a weighted summation mode, determining the comprehensive prediction burial depth of the target geological layer. According to the scheme, the problem of well depth prediction caused by data shortage, complex structure, large error of a single method and high multiplicity of solutions in a low-exploration-degree complex structure area can be effectively solved.

Method (100) for optimizing the placement of weld spots during resistance spot welding comprises several steps that enable precise analysis and adjustment of the welding parameters. First, welding process data is acquired (102). This data is used to monitor and optimize the welding process. In step (104), geometric design data is extracted from a CAD model, including the weld spot location, material thickness combinations (MCT), and geometric features such as edge distances. This data is necessary to analyze the weld spot placement. In step (106), a two-dimensional analysis is performed, calculating distances between weld spots and component features. In step (108), a three-dimensional analysis is carried out, taking into account the spot location in relation to the geometric properties of the surroundings.Step (110) links the geometric design data with the welding process data, including the quality score, enabling a detailed analysis. In step (112), correlations between the geometric location of the weld spots and the weld quality are determined. In step (114), alternative spot locations and / or material thickness combinations are identified to improve the weld quality. Finally, in step (116), optimization recommendations for the design are generated to increase the weld quality by adjusting the spot location or material thickness combination.

The invention is suitable for the technical field of power system diagnosis, and provides a centralized control center-oriented power plant relay protection fault diagnosis method, which comprises the following steps of: reconstructing a fault event sequence with sequential logic by receiving a relay protection action alarm signal and automatically acquiring associated fault data; the method comprises the following steps of: configuring and executing multi-dimensional analysis tasks including electrical quantity analysis, protection logic check and historical case matching, automatically judging action behaviors of the protection device according to cross validation of task results, intelligently comparing and storing diagnosis characteristics and conclusions with a historical case library, and finally automatically generating a diagnosis report. According to the invention, automation of the whole process from fault data collection and intelligent analysis to report generation is realized, and the response speed and processing efficiency of fault analysis are effectively improved; through the built-in standardized judgment logic, the dependence on artificial experience is reduced, and the consistency and objective accuracy of the diagnosis conclusion are guaranteed.