172 results about "Dimensional analysis" patented technology

The invention discloses an intelligent management system for energy consumption optimization and fault self-diagnosis of cleaning equipment, and relates to the field of intelligent maintenance of the cleaning equipment, and the system comprises the steps: obtaining three groups of core parameters, i.e., a historical vibration spectrum, a motor current harmonic component and a bearing temperature gradient, constructing a dynamic failure mode knowledge graph, performing time sequence correlation analysis on the historical fault data to obtain failure mode analysis data; establishing a multi-dimensional analysis platform, identifying a high-risk component, and updating a fault threshold value; introducing a service time attenuation factor and a working condition correction coefficient, establishing an aging degree quantitative model, and calculating an aging coefficient; and constructing and developing an energy consumption-reliability joint optimization module, and adjusting equipment operation parameters. The method has the advantages that the dynamic knowledge graph and the time sequence analysis model are constructed by integrating multi-source sensor data, precise diagnosis and self-adaptive threshold adjustment of the coupling fault of the cleaning equipment are achieved, aging evaluation and task scheduling optimization are combined, the energy consumption efficiency is improved, and the maintenance cost is reduced.

The invention belongs to the technical field of atomized liquid component analysis, and discloses an intelligent analysis system and method based on atomized liquid components, and the method comprises the following steps: carrying out multi-parameter sampling on atomized liquid to obtain pyrolysis data; performing temperature gradient analysis to generate a pyrolysis spectrogram; identifying trace markers to generate a feature library; analyzing the component evolution track to generate a dynamic evolution spectrum; carrying out partition demarcation processing to generate an atomization characteristic spectrum; performing thermodynamic analysis to generate a reaction map; analyzing component diffusion to generate quantized data; constructing a sensory response prediction engine; performing intelligent analysis to generate response feature data; evaluating and generating a quality report; and performing optimization processing to generate formula suggestions and executing accurate blending. According to the method, accurate analysis and evaluation of atomized liquid components are achieved through multi-dimensional analysis, a scientific basis is provided for product optimization, and safety and taste experience are effectively balanced.

The invention relates to the field of underground powerhouse construction risk identification, and provides an underground powerhouse construction risk identification and disposal method, system, device and medium, and the method comprises the steps: collecting multi-source heterogeneous data in real time, obtaining historical risk case data, and carrying out the preprocessing to obtain structured time-space correlation data; constructing a multi-dimensional analysis model based on a parallel computing algorithm, and performing multi-scale risk analysis on the structured time-space associated data to obtain multi-level risk feature data; performing risk feature recognition through a multi-modal machine learning model to obtain risk quantitative indexes, and performing recognition based on a fuzzy comprehensive evaluation algorithm to obtain construction risk levels; and matching emergency strategies of construction risk levels, carrying out parameter expansion through a combinatorial optimization algorithm, generating a plurality of candidate disposal schemes, carrying out weight calculation and sorting on the candidate disposal schemes by adopting a multi-criterion evaluation model, and outputting an optimal disposal scheme. According to the invention, efficient identification and accurate emergency decision-making of the construction risk of the underground powerhouse are realized.

The invention discloses a dynamic feeding speed adjusting method self-adaptive to production line takt, and relates to the technical field of production line automation control, and the method comprises the following steps: 1, constructing a production line takt sensing system, setting sensing units at all key stations of a production line, and setting a plurality of monitoring points on a material transmission path of the production line; according to the invention, various sensing assemblies are arranged at key stations, various state information of materials in the process from station entering to transmission can be captured in real time in combination with monitoring points on a transmission path, and information reliability is ensured through data screening; therefore, the central processing unit can comprehensively master the actual operation condition of the production line, and firm data support is provided for follow-up adjustment. On the basis of characteristic parameters of multi-dimensional analysis, continuous correction is carried out in combination with historical data, and the defect that a traditional fixed model cannot adapt to beat fluctuation is avoided; in this way, the feeding speed can be adjusted on the basis of the current real production line takt all the time, and timeliness and pertinence of adjustment are ensured.

The invention relates to the technical field of data processing, in particular to an engineering geological survey data processing method and system, and the method comprises the following steps: obtaining hole site space positioning and lithologic boundary information, collecting a structure segment sequence, extracting resistance change direction classification disturbance behaviors, recognizing node sequence conflicts, and judging hydrological turning positions. Identifying the corresponding relation between the structural section and the water level track, and generating a structural section water level merging mapping table. According to the method, the spatial information, the lithology identification, the sampling level and the penetration resistance of the drilling structure sections are collected and serialized, disturbance identification and non-sampling section classification are performed based on the resistance change trend between the sections, and node conflicts are identified in combination with the numbering relation and the lithology combination; continuous modeling and classified merging of geological information on the spatial level are achieved, the linkage adaptability of data in a multi-dimensional analysis scene is enhanced, misjudgment interference caused by information isolation is avoided, and dynamic recognition and hydrological response analysis of a geological structure are supported.

The embodiment of the invention provides a vehicle queuing duration prediction method and device, and the method comprises the steps: obtaining target attribute data corresponding to a target vehicle, and a time sequence related to the entering behavior of the target vehicle, the target attribute data refers to attribute data which is related to the target vehicle and affects the queuing duration of the target vehicle, and the time sequence comprises multiple pieces of historical change data which affects the queuing duration of the target vehicle; based on the target attribute data, analyzing an association relationship between the target attribute data and the queuing duration of the target vehicle, and predicting a first queuing duration; based on the time sequence, analyzing a change rule of the plurality of pieces of historical change data, and predicting a second queuing duration; and determining the target queuing duration of the target vehicle according to the first queuing duration and the second queuing duration. According to the invention, multi-dimensional analysis of the data is realized, and the accuracy of queuing duration prediction is improved.

The invention provides an intelligent equipment operation and maintenance method and system based on an industry large model technology, equipment and a medium, and belongs to the technical field of intelligent equipment operation and maintenance. Inputting the equipment operation data into a multi-agent cooperation engine, and analyzing time domain, frequency domain and working condition parameters; the diagnosis agent generates diagnosis result information in combination with the diagnosis intelligent knowledge graph; the diagnosis result information is converted into a work order text, and the work order text is synchronized to a monitoring system; after fault processing is completed, the processing process and result are fed back to the monitoring system and supplemented to the diagnosis intelligent knowledge graph based on a supplement mechanism, and knowledge iteration updating is achieved. A multi-dimensional data fusion and analysis method is adopted. Information of different types of data is utilized, and the accuracy and reliability of fault diagnosis and operation and maintenance decision are improved through a multi-dimensional analysis perspective.

The invention relates to a blasting vibration rule prediction method and device, electronic equipment and a storage medium. Comprising the following steps: determining main factors influencing the blasting vibration speed and dimensions thereof based on monitoring data of a target blasting site; based on the main factors and the dimensions of the main factors, analyzing a Sadgowski formula by using a dimension analysis principle to determine target factors influencing the blasting vibration speed in the Sadgowski formula; constructing a function form of a blasting vibration rule, and taking the target factors as basic dimensions to obtain a common form of a Sadgowski formula; and based on a common form of a Sadgowski formula, fitting and constructing a new-form blasting vibration law prediction model so as to predict a propagation law of blasting vibration speeds in different directions. Therefore, the method solves the problems that a traditional Sadgowski formula cannot be suitable for complex engineering projects with consideration of influence factors such as a charging structure and a free surface, and cannot guide blasting near-area construction, and improves the effectiveness of blasting vibration prediction.

The invention relates to a centralized heating balanced regulation and control method, device and equipment and a medium. The method comprises the steps that firstly, the heat supply area of a user and the heat use state of a neighbor are collected, the basic flow of the jet device is calculated according to an industrial standard formula, and final flow containing resistance characteristic data is obtained through secondary correction by combining a neighbor heat use state correction coefficient and an environment temperature influence factor. Extracting flow and inlet and outlet pressure difference from jet device parameters, adjusting a valve to enable the resistance proportion to reach a preset interval, calculating parameters such as unit area heat consumption by combining real-time flow and supply and return water temperature difference, generating regulation and control basic data through coupling analysis, adjusting the jet device when the regulation and control basic data reach the standard, and generating a dynamic scheme by combining a thermal load prediction model. And finally, capturing the flow pulse signal according to a fixed period to calculate a difference value, generating a valve control signal according to a threshold value, acquiring the water supply and return temperature after execution, and coupling with a dynamic scheme to generate a regulation feedback signal. By adopting the method, accurate regulation and control can be realized through multi-dimensional analysis, and the flow distribution accuracy and the heat supply balance are improved.

The invention relates to the technical field of intelligent warehousing, and particularly discloses a warehouse material identification method based on data analysis, and the method comprises the steps: collecting operation event data and material coordinate information in real time through a UHF-RFID reader-writer array and a visual positioning system, and generating an operation event time sequence; calculating a material mixing risk value, an access frequency factor and an access confusion degree index, analyzing coordinate data to detect a displacement sudden change and a boundary crossing event, generating a position anomaly degree index, fusing multiple indexes to obtain a goods allocation inspection priority score, generating an anomaly inspection instruction when the score exceeds a threshold value, and marking anomaly types such as mixing, deviation and boundary crossing. According to the invention, real-time acquisition and multi-dimensional analysis are carried out on the operation event data and the material coordinate position information of the warehouse goods allocation, and the operation event time sequence characteristics and the position dynamic change are combined to construct a quantitative index system to identify the abnormity of the goods allocation, so that accurate identification of warehouse materials and timely early warning of the abnormal state are realized, and the working efficiency is improved. Therefore, the refinement level and the operation efficiency of warehouse management are improved.

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 diffusion testing, in particular to a water-rich sand layer permeation grouting diffusion effective distance formula determination method, which comprises the following steps: building a water-rich sand layer grouting model test platform, carrying out an orthogonal model test by virtue of the test platform, obtaining test data, and determining the effective distance of permeation grouting diffusion of a water-rich sand layer according to a dimensional analysis theory in combination with the test data of the orthogonal model test. Deriving a calculation formula of the permeation grouting diffusion distance of the water-rich sand layer, drilling holes at different diffusion distances of a stone body formed in the grouting test platform to obtain a stone body rock core, and constructing a relational expression between the slurry filling rate and the actual diffusion distance of the corresponding slurry according to the slurry filling rate in the drilled core at different positions; and the corresponding diffusion distance is obtained through the relational expression of the grout filling rate and the corresponding diffusion distance, the corresponding diffusion distance is compared with the actual diffusion distance of the grout to obtain a reduction coefficient, and the reduction coefficient is substituted into the calculation formula of the permeation grouting diffusion distance of the water-rich sand layer to obtain the calculation formula of the effective permeation grouting diffusion distance of the water-rich sand layer.

Method and device for celestial timekeeping that synchronizes independent object-relative cyclic time and displays each unique temporal interval on a single user display system. Multi-celestial cyclic time is displayed based on a user's frame of reference by aligning with recurrent and unique cyclic start / stop signals and the local reference frame timekeeping system. For example, using the Coordinated Universal time (UTC) for a user on Earth to equate the duration of independent cyclic time of Lunar18, Mars24, and so on. The method uses dimensional analysis and equates a single cyclic, non-cyclic (zero-time; start / stop non-dimensional instant of a cycle), and linear continuous time [T] from an observer frame of reference for displaying one or more temporal cycles on the user's device. Each independent cycle is consistent with temporal counts of a whole cycle (equated to SI units) displayed as either a discrete geometric shape (spatiotemporal units) and / or algebraic numbers on the device.

The invention discloses a multi-dimensional analysis house building health monitoring and early warning system and method, and relates to the technical field of monitoring and early warning. During operation of the system, various sensors are deployed to monitor the physical states of different materials in a building, collect surrounding environment data and transmit the data to a central processing unit in real time, and through a data fusion algorithm, real-time monitoring and early warning are achieved; the method comprises the following steps: integrating sensor data from different materials into a unified data set, preprocessing and normalizing the data, constructing a multi-material interaction mathematical model, calculating an effective stress sigma eff of a building structure, constructing a building overall health assessment model, and calculating a building health comprehensive index HI; according to the building health comprehensive index HI and the comparison result of the health index of each material and the safety threshold value, the health change of the building is detected in real time, an intelligent decision support system is provided, and building management personnel are helped to carry out long-term maintenance planning and resource optimization distribution.

The invention discloses a vibroflotation pile composite foundation quality evaluation method based on an AHP-entropy weight method. The method comprises the following steps: constructing a multi-dimensional analysis model; four master control influence factors of quality evaluation are obtained based on the multi-dimensional analysis model; weighting the influence factors based on an AHP subjective weighting method and an entropy weight objective weighting method, and obtaining a combined weight; obtaining a normalized thematic map of each influence factor evaluation index based on a Kriging interpolation method; superposing the normalized thematic maps based on a GIS superposition coupling function to obtain a quality quantification index type partition evaluation map of the whole area of the composite foundation; and carrying out partition evaluation on the quality of the vibro-replacement stone column composite foundation in the whole region. According to the method, the multi-dimensional analysis model is constructed to obtain the combination weight of each index, so that the evaluation is comprehensive, and the error of the evaluation result is greatly reduced; the influence factors are coupled in the same graph and are subjected to partition evaluation, so that the evaluation precision of the processed foundation is improved.

The invention relates to the technical field of operation index analysis, in particular to an operation index multi-dimensional analysis optimization method based on AI large model dynamic weight adjustment, which comprises the following steps: acquiring a market fluctuation index, an operation efficiency index, a financial health index and a supply chain elasticity index of an enterprise; four-dimensional index data of enterprise operation are input into a hypergraph tensor decomposer, the hypergraph tensor decomposer maps four-dimensional indexes into mutually orthogonal hypergraph nodes through orthogonally constrained Tucker decomposition, a decoupling hypergraph is generated, the decoupling hypergraph is injected into a dynamic weight modeling model, and an optimization strategy chain is generated based on a real-time event stream; and the orthogonal constraint condition of the decoupling hypergraph is corrected through tensor gradient back propagation after execution of the optimization strategy, and closed-loop optimization is formed. According to the method, the optimal response action with business semantics and timeliness can be generated according to unexpected situations such as market abnormal fluctuation, supply chain breakage or financial pressure.

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 DEM landform analysis method based on a large language model, and relates to the technical field of DEM data analysis, and the method comprises the steps: loading a DEM semantic mapping tool set, and achieving system initialization; after the system receives user input, questions are divided into single-tool questions, multi-tool collaborative questions and non-tool answerable questions through a question classification Agent on the basis of a pre-training model; respectively processing a single tool question, a multi-tool collaborative question and a non-tool answerable question; and performing existing memory retrieval on each problem based on a bidirectional knowledge evolution memory iteration mechanism, and performing multi-dimensional analysis in combination with the large language model to realize DEM landform analysis based on the large language model. The technical problems that in the prior art, LLM is difficult to directly and effectively analyze the spatial topological relation contained in DEM raster data, and iteration updating of geographic knowledge in a complex dynamic analysis task is difficult are solved.

The invention discloses a hydraulic engineering management and control system and method based on digital twinning, and relates to the technical field of digital twinning, and the method comprises the steps: firstly collecting and preprocessing channel condition data in real time, then comprehensively processing the data to obtain a sediment deposition factor and a congestion prediction factor, and analyzing whether sediment deposition exists according to the sediment deposition factor and the congestion prediction factor; if yes, whether the channel is congested or not is predicted according to the latter, if congestion is predicted, a congestion early warning is given out, and if no deposition exists or congestion does not exist, the process is ended correspondingly or prediction continues. The method combines flow velocity and flow direction abnormal parameters to form sediment deposition factors, bypasses underwater direct detection bottlenecks by means of digital twin modeling and simulation algorithms, improves sediment deposition judgment accuracy through multi-dimensional analysis, constructs congestion prediction factors based on a standard and actual water flow difference value and the flow direction abnormal parameters, and performs threshold exceeding early warning. The blocking risk is recognized in advance, and time is won for hydraulic engineering maintenance regulation and control.

The invention provides a method for predicting the working failure rate of a railway vehicle relay, and the method comprises the steps: classifying data according to a preset dimension to generate a structured feature set, constructing a time sequence feature matrix, and defining a multi-dimensional analysis coordinate system based on the classification dimension of the feature set; determining an initial prediction constraint condition according to the relay life distribution model and the fault mode library, executing dynamic prediction simulation on the feature set based on the time sequence feature matrix, simulating degeneration behaviors of the relay under various working conditions through a state transition simulation engine, generating an initial fault rate curve, and calculating the fault rate of the relay according to the initial fault rate curve. And finally, carrying out iterative correction on the initial fault rate curve by adopting an integrated optimization algorithm to generate a multi-dimensional fault rate prediction model. The invention further provides a system for predicting the working failure rate of the railway vehicle relay. According to the method, the adaptability and accuracy of prediction are greatly improved, and the degeneration behavior of the relay under the actual complex working condition can be simulated more truly.

The invention discloses a geological comprehensive information analysis system and method for gold mine exploration, and relates to the technical field of information analysis, and the analysis method comprises the following steps: extracting the geological type and geological features of an exploration region, and generating a corresponding collection record; carrying out quality evaluation on the geological information which is randomly collected and recorded; performing comparative analysis on any two acquisition records with the same geological type to obtain difference features, and performing deviation degree analysis on each difference feature; constructing an anomaly evaluation model and setting an anomaly identification standard; performing geological feature extraction on geological information acquired in real time in the exploration area to generate a real-time acquisition record; performing anomaly identification on the presentation condition of each geological feature; by performing multi-dimensional analysis on the geological information collected in the exploration process, errors existing in traditional single index judgment can be eliminated, quality judgment can be more accurately and effectively performed on the geological information, and the exploration efficiency is improved.

The invention relates to the technical field of geotechnical engineering monitoring, in particular to a coal mine soft rock roadway surrounding rock argillization degree multi-dimensional index analysis method. The method comprises the following steps: extracting a plurality of analysis index data from a rock sample, listing an index matrix based on each analysis index data, then carrying out quantitative processing on all the rock sample index data according to the matrix, determining objective weights of all the rock sample index data through a CRITIC method, and finally determining the objective weights of all the rock sample index data according to the objective weights of all the rock sample index data. And according to the quantified roadway surrounding rock index data and the corresponding weight, calculating the evaluation score of the argillization degree of the surrounding rock, then establishing a specific grading table of the judgment value Q of the argillization degree of the roadway surrounding rock, and according to the comprehensive evaluation score of the argillization degree of the roadway surrounding rock, analyzing the grade of the argillization degree of the rock sample, and establishing a comprehensive and multi-dimensional analysis framework. Comprehensive data support can be provided for analysis of the argillization degree of the roadway surrounding rock, and multidimensional analysis of the argillization degree is guaranteed.

The invention discloses an automatic project cost review method based on big data, a medium and equipment, and the method comprises the steps: generating a dynamically adjusted data collection strategy through project information, and enabling the data collection strategy to trigger an updating mechanism according to a preset condition; collecting heterogeneous cost data based on a data collection strategy and performing normalization processing to form a first data set; the first data set is input into a cost prediction model, a risk prediction model and an expected income model, the cost prediction model is constructed through fusion of ARIMA and LightGBM, and the risk prediction model adopts an XGBoost model with auditing entries as adjustment parameters; and finally generating a review report by integrating the output cost prediction coefficient, the risk level, the avoidance suggestion and the expected income range. According to the method, dynamic optimization of data acquisition and collaborative decision of a multi-dimensional analysis model are realized, and the automation level and the result reliability of project cost review are improved.

The invention discloses a stratigraphic range constrained sequence modeling method, which relates to the technical field of three-dimensional geologic modeling, and comprises the following steps: preparing data including drilling data, regional geologic map data and a regional DEM, standardizing the drilling data including a standard stratigraphic table, a drilling basic information table and a drilling layered information table, the format of the form is unified as. Xlsx and a standard stratum table, the standard stratum table records the lithology of the whole stratum, and arrangement is carried out from top to bottom according to the new-to-old relationship; according to the sequence modeling method based on the stratum range constraint, the modeling boundary of each stratum is subjected to forced constraint, sequence modeling is carried out by using the stratum range constraint, the distribution condition of each stratum in a modeling area can be subjected to forced constraint, and meanwhile, modeling is carried out by combining drilling data and area elevation data, so that the model is finer, and the modeling efficiency is improved. And the error between a section cut through three-dimensional analysis of a sectioning model and the like and an original section is small.

The invention discloses a blasting data multi-dimensional analysis and anomaly detection processing system, and particularly relates to the technical field of blasting intelligent analysis processing, and the system comprises a distributed data collection module, a data preprocessing module, a multi-dimensional analysis engine, a hybrid anomaly detection module, a visual interaction interface, an early warning processing module, and an extensible interface module. Aiming at insufficient multi-source heterogeneous data fusion capability in the prior art, the invention innovatively adopts a WPT-EMD combined denoising algorithm and a dynamic standardization unit to work cooperatively, and effectively overcomes the problems of mode aliasing and noise residual in the traditional method through fine frequency band division of wavelet packet transform (WPT) and self-adaptive characteristics of empirical mode decomposition (EMD); in combination with a dynamic standardization strategy based on information entropy, feature space alignment of heterogeneous data such as vibration waveforms and stress fields is realized, the signal-to-noise ratio of original data is improved, the feature dimension consistency is improved, and a high-quality data foundation is laid for subsequent analysis.

The invention discloses a unit state analysis early warning method applied to a centralized control system, and the method comprises the steps: obtaining original data of a data interface layer, carrying out the data preprocessing and parameter reconstruction of the original data after statistical classification, and calling an equipment three-dimensional model in a model layer to carry out digital twin modeling, the preprocessed data, the reconstructed feature parameters and the digital twinborn model are correspondingly output; multi-dimensional index analysis is carried out on the preprocessed data and the reconstructed characteristic parameters by calling an analysis model and a diagnosis model in the model layer, an independent scoring rule is constructed, and the instantaneous state and the risk trend of the centralized control system are comprehensively evaluated; and by calling an early warning model and an evaluation model in the model layer, dynamically analyzing unit overall risk output early warning information according to the multi-dimensional analysis result, and displaying a dynamic simulation result and an early warning result of a unit state through a digital twin model. The objective degree and standardization problems of centralized control system evaluation are effectively solved.

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 provides a hydraulic engineering prevention and control information digital management method and system, and the method comprises the steps: firstly obtaining a real-time data stream, extracting overflow risk features through employing a data fusion technology, and then screening out a core feature index from the overflow risk features through constructing a feature weight analysis logic; then, performing anomaly detection on the core characteristic indexes, and when an abnormal index is detected, generating a dynamic risk distribution diagram corresponding to the abnormal index and determining an influence range so as to predict a change trend of the abnormal index in a future target time period in a risk distribution area and lock a risk evolution time interval; and finally, carrying out comprehensive risk analysis based on the abnormal indexes and the initial characteristic indexes associated with the abnormal indexes, and generating standardized early warning information for outputting. According to the method, real-time monitoring, multi-dimensional analysis and accurate early warning of the overflow risk of the target reservoir are achieved, the response efficiency of water conservancy risk early warning is improved, and then the safety management level and the disaster prevention and reduction capacity of the water conservancy project are effectively improved.

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.