202 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 flood disaster early warning and deduction, and relates to a power grid flood disaster early warning dynamic deduction system and method. According to the method, the physical relevance of power grid damage probability analysis is improved by accurately simulating the flood spreading path and the submerging parameters of the sub-regions of the flood spreading path, a multi-dimensional analysis basis is provided for the equipment damage probability by quantifying the risk level, and the misjudgment rate is reduced; an upstream power failure area and a downstream influence range of threatened equipment are identified through dynamic deduction, a load transfer path is optimized in real time, a power supply gap is reduced, time-space dynamic prediction and management of power failure influence are realized, and power supply continuity of a key area is guaranteed; by displaying the flood inundation animation, the equipment state icon and the first-aid repair progress bar in real time, high-risk equipment can be quickly positioned, resources can be scheduled, the first-aid repair response time is shortened, a whole-process closed loop of'monitoring-early warning-response-feedback 'is formed, and the emergency efficiency is improved.

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 relates to the technical field of road maintenance management, and particularly discloses a novel digital road maintenance management method and system based on multi-source data, and the method comprises the steps: carrying out the multi-dimensional analysis of a road crack image through employing an image processing technology based on deep learning; the method comprises the following steps of: identifying a crack type and quantifying key parameters such as width, length and area of the crack, simultaneously, capturing a time sequence change trend and a periodic rule of road traffic flow by performing time sequence analysis on historical traffic flow data of a road, and further fusing a static crack detection result with a dynamic traffic load mode through a time sequence derivation algorithm to obtain a dynamic crack detection result. The expansion trend of the crack under the action of the future traffic load is predicted, and long-term crack development prediction is formed, so that road maintenance management is performed based on the long-term prediction result of the road crack. According to the method, accurate diagnosis and active intervention of the road state can be effectively realized through multi-dimensional data collaborative analysis, so that the efficiency and effect of road maintenance are remarkably improved.

The invention relates to the technical field of electric power system fault risk diagnosis, and particularly discloses an electric power system fault risk diagnosis method and system, and the electric power system fault risk diagnosis method is implemented based on an electric power system fault risk diagnosis system by building the electric power system fault risk diagnosis system. A time-space dynamic model based on time change is established, node states and line states obtained in real time serve as input, the state of the system at the next moment is predicted through the time-space dynamic model, and then multi-dimensional analysis is conducted on system faults. And finally, the intelligent decision-making and feedback adjusting unit calculates the fault risk probability of the power system, discriminates and accurately compares and divides fault levels, so that the problem that a traditional risk diagnosis model lacks general mathematical modeling for different disaster situations and is difficult to comprehensively reflect multiple influences of disasters on the power system is solved.

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 provides a grouting curtain parameter design method for structure protection under the blasting vibration effect, and relates to the technical field of underground engineering and blasting engineering, and the grouting curtain parameter design method comprises the following steps: S1, determining main factors influencing the vibration velocity of a protection structure, and constructing a vibration velocity prediction model containing an undetermined coefficient by adopting a dimension analysis white golden-han theorem; s2, establishing a finite element blasting numerical model, and obtaining structural vibration velocity data under different parameter combinations; s3, fitting the structural vibration velocity data by using the vibration velocity prediction model, and determining an undetermined coefficient in the vibration velocity prediction model; and S4, a relational expression between the structural vibration velocity and stress is established, and grouting curtain design parameters meeting structural safety requirements are determined in combination with engineering conditions. By means of the method, the problem that the grouting curtain damping effect and grouting curtain parameters are difficult to determine in actual engineering is solved, the blasting vibration peak value of the protection structure under the blasting vibration effect is effectively reduced, and a guarantee is provided for underground and ground structure protection and blasting engineering safety construction.

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.

The invention discloses a multi-dimensional analysis building construction backtracking responsibility determination method and system, and relates to the technical field of multi-data fusion analysis. Obtaining construction standard data and constructors corresponding to each construction stage in the building engineering, constructing a standard responsibility model of the construction stage according to the construction standard data, and constructing a responsibility chain according to the standard responsibility model of each construction stage and the constructors corresponding to each construction stage; building questions are set, and keywords, influence factors and influence coefficients corresponding to the building questions are set; acquiring real-time data of each construction stage regularly, and inputting the real-time data into the standard responsibility model corresponding to the construction stage to generate an error value; setting an input port, obtaining question details input by a user, obtaining a building question corresponding to the question details according to the keyword, and marking the building question as a target question; and generating a responsibility investigation group according to the influence factor, the influence coefficient, the error value and the responsibility chain corresponding to the target problem.

The invention relates to the technical field of land utilization change evaluation, in particular to a land change degree evaluation method and system based on gradient division and two-dimensional analysis and a storage medium. Dividing the to-be-evaluated land into a plurality of target sub-regions with different target gradients by adopting topographic position indexes; wherein the terrain position index is obtained by calculating an elevation value and a slope value of the land; and analyzing the target sub-regions from two evaluation dimensions including a terrain gradient effect dimension and a land gradient utilization characteristic dimension, and determining a land change degree evaluation result of the to-be-evaluated land based on the obtained terrain gradient effect evaluation result and the land gradient utilization characteristic dimension evaluation result of the plurality of target sub-regions. The objective of the invention is to solve the problem of how to carry out land utilization change evaluation on areas with obvious vertical zone performance and altitude gradient performance.

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 low-efficiency sea use comprehensive evaluation method based on multi-dimensional analysis, and relates to the technical field of marine resource management and evaluation, and the method comprises the steps: collecting sea use benefit data, and processing the collected data through a superposition analysis method; performing percentage assignment on the processed sea utilization benefit data; constructing a multi-level index system through an analytic hierarchy process, and calculating a target data weight value through a Delphi method; calculating a dimension score according to the assignment and the weight value of the sea utilization benefit data; and calculating a comprehensive score according to the dimension score, and performing grading evaluation on the sea use project. According to the technical scheme, efficient and accurate low-efficiency sea use evaluation can be made for sea use projects, and the method has high application value in the aspects of enhancing sea area space management and control and promoting ocean resource conservation and utilization.

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 provides an evaluation method and system for blasting disturbance induced time-lag rock burst, and relates to the technical field of tunnel engineering, and the method comprises the steps: selecting a basic dimension from a plurality of physical factors based on a dimension analysis method, and constructing a universal model of blasting impact stress by using the basic dimension and a basic model; establishing a numerical analysis model of the tunnel according to the parameter information of the to-be-blasted tunnel, and simulating vibration acceleration data and blasting impact stress data of surrounding rock mass points of adjacent tunnels under the conditions of different explosive loads and different blasting center distances in the numerical analysis model; substituting the acceleration data and the blasting impact stress data into the general model for fitting to obtain a blasting impact stress calculation model of the to-be-blasted tunnel; an evaluation model of the probability of inducing the time-delay rock burst of the adjacent tunnels during blasting of the to-be-blasted tunnel is built through the blasting impact stress calculation model, a systematic evaluation system is provided for evaluating the time-delay rock burst risk, and scientific guidance and early warning are provided for construction.

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.