339 results about "Computational analysis" patented technology

The embodiment of the invention discloses a life omics research method and device based on artificial intelligence, and the method comprises the steps: carrying out the preprocessing of a project according to the intelligent interaction between a user and a system, and generating standardized data; and meanwhile, carrying out transfer learning on the large language model to construct a life science large language model. And according to the standardized data, decomposing a research target by adopting a life science big language model in cooperation with an intelligent agent, and generating an analysis plan. And based on the analysis plan, the intelligent agent is scheduled through the coordinator, and a hierarchical task is generated. And calling a multi-omics analysis tool by the intelligent agent to calculate and analyze the grading task, and outputting an analysis result. And based on data features, integrating analysis results through an integrated advanced model, and outputting a final report to complete the research of life omics. According to the embodiment of the invention, full-process automation and natural language interaction are realized, the standardization of data analysis and the repeatability of results are ensured, the research efficiency is remarkably improved, and the technical threshold is reduced.

The invention relates to the technical field of fault prediction and health management, in particular to a primary and secondary fusion complete ring main unit fault diagnosis method and system. Comprising the following steps: acquiring three-phase instantaneous voltage and current signals in real time, and converting the signals into digital transient data; performing time window preprocessing on the digital transient data, and executing wavelet packet decomposition to generate a transient feature vector; calculating and analyzing the transient feature vector through a transient zero-sequence power direction method and a support vector machine model to generate a local diagnosis result; when the local diagnosis result is that cooperative positioning needs to be started, a transient current similarity coefficient and a transient waveform intensity difference coefficient are calculated based on the digital transient data, and a comprehensive positioning result is generated; determining a fault line according to the comprehensive positioning result, and generating a remote control command; and executing a fault isolation operation based on the remote control command, and executing a PHM process. According to the method, the double local transient diagnosis and the cross-terminal cooperative positioning are deeply fused, so that the high-precision determination of the boundary of the fault section is realized.

The invention discloses an intelligent-based abnormal carbon emission data automatic identification early warning system, which belongs to the technical field of intellectualization and comprises a data acquisition preprocessing module, a high-precision space-time analysis module, an intelligent analysis module, an automatic abnormal identification module, a carbon footprint tracing module, a self-adaptive adjustment module and an intelligent emission prediction module. A carbon emission source and time-space distribution characteristics are accurately positioned through spatial positioning and time sequence analysis of the high-precision time-space analysis module, a spatial distribution diagram is more detailed and accurate through the optimized sensor position and an interpolation algorithm, and time sequence analysis is more accurate through timestamp correction and power spectrum density analysis. The method effectively evaluates the periodic intensity of the signal, analyzes a hidden mode and an association rule in the data through the intelligent analysis module integrating the spatial-temporal characteristics and the related information of the data acquisition and preprocessing module, analyzes the spatial-temporal association between variables through the calculation of a clustering center and the association intensity, and facilitates the discovery of a potential abnormal mode.

The invention discloses a character recognition method and system based on a large model and an OCR technology, and relates to the technical field of character recognition, and the method comprises the steps: extracting picture information, carrying out the unified preprocessing, generating a text detection box of a character region through a DBNet lightweight text detection model, and obtaining a text position; quickly identifying characters in the textbox by using a lightweight OCR model to obtain text content, and generating an identification information group; carrying out average value calculation on the confidence coefficient of the lightweight OCR model result, and analyzing the overall confidence coefficient; and for the result with low confidence coefficient, inputting the corresponding identification information group into the multi-modal large model, and carrying out secondary identification. According to the method, the text position set and the text character string sequence are combined into the identification information group, so that the effect of structured storage of detection and identification results is achieved, subsequent information retrieval and multi-modal fusion analysis are facilitated, and the effect of optimizing the subsequent processing efficiency and precision is achieved through the combination of the confidence coefficient screening step.

The invention discloses a tire finite element modeling and multidirectional rigidity optimization method and system based on characteristic lines. The method comprises the following steps: extracting tire section characteristic lines from a three-dimensional digital model; introducing the tire section characteristic line into a finite element analysis environment, generating a three-dimensional tire geometric model by rotationally scanning the characteristic line, and performing grid division on the model; setting tire material attributes, performing zoning setting on the model according to a tire crown, a tire shoulder and a tire side wall, and setting tire thickness based on zoning; applying a constraint boundary condition at the center of the tire, and establishing a contact form of the tread and the ground; a progressive inflation pressure load is applied, the deformation state of the inflated tire is calculated, and longitudinal rigidity, radial rigidity and lateral rigidity calculation and analysis steps are set; the tire elasticity modulus and the cord fabric thickness are used as design variables, and an optimization algorithm is adopted to solve a multi-objective optimization function. The method has the advantages of being simple in modeling method and high in practical operability, the tire modeling threshold can be lowered, and the fund and time cost of refined modeling is reduced.

The invention discloses a high-formwork optimization design method and system based on BIM and finite element analysis, and the method comprises the steps: S100, building a three-dimensional BIM model of a main body structure, and creating an intelligent parameterization frame body family which is mapped with a main body structure family and has a self-verification function; s200, importing a parameterized family and linking the main body model, generating a plurality of groups of frame body arrangement schemes through spatial topology analysis, and performing a three-dimensional collision test after optimization; s300, setting dynamic boundary constraints and construction loads in stages, and generating a geometric and mechanical integrated data packet; s400, data packet parameters are automatically mapped to finite element software through a plug-in, models are built in stages, multi-working-condition analysis is carried out, if the parameters exceed the limit, frame body parameters are modified, iterative optimization is carried out until the parameters meet the standard, and a result is synchronized to a three-dimensional BIM model; and S500, a construction drawing is automatically generated, and visual disclosure and high formwork monitoring point selection are carried out. According to the method, design, computational analysis and construction application data linkage and closed-loop management from design to construction to monitoring are achieved, and the high formwork design efficiency and safety are improved.

The invention provides a flying dust management system for composite low-carbon construction. The flying dust management system comprises a multi-source sensing acquisition module, an edge calculation analysis module, a dynamic decision control module, a resource optimization scheduling module and a carbon emission quantitative evaluation module, the multi-source sensing acquisition module completes original data preprocessing and local calibration; the edge calculation and analysis module identifies a main pollution source and generates a concentration distribution thermodynamic diagram; the dynamic decision control module generates an optimal control strategy of the dust suppression equipment; the resource optimization scheduling module optimizes hydroelectric resource distribution, and dynamically schedules fog gun and spray tower equipment combination; and the carbon emission quantitative evaluation module calculates the net carbon emission reduction of the dust suppression measures and generates a low-carbon construction report. According to the invention, turbulence diffusion and fuzzy control are combined to realize predictive dust suppression; double-loop control of edge computing and cloud feedback is adopted, so that communication delay is reduced; and through hydroelectric constraint optimization, the carbon strength of the dust suppression system is reduced.

The invention relates to the technical field of edge computing, and provides an edge data acquisition and processing device for a power plant unit, which comprises a data receiving module, an edge processing module, a data compression module and a communication module, the data receiving module is used for receiving data input by the access equipment and carrying out frame decoding processing on the data input by the access equipment to obtain data after frame decoding; the edge processing module is used for calculating and analyzing the deframed data to obtain preprocessed data; the data compression module is used for performing data compression processing on the preprocessed data to obtain compressed data; and the communication module is used for transmitting the compressed data to a preset target system. The efficient edge calculation and data compression mechanism not only improves the real-time performance and accuracy of data processing, but also enhances the adaptability of the system to the constantly changing operating environment and technical upgrading requirements of the power plant unit, and provides powerful support for safe operation and stability of the power plant unit.

The present invention relates to the technical field of electrodeposition, and relates to a simulation method for flow field distribution and deposition morphology in ultrafast laser-assisted electrochemical deposition. The steps of the method comprise: constructing, in multiphysics simulation software, a two-dimensional axisymmetric multiphysics coupled field model for heat transfer, solid and fluid heat transfer, tertiary current distribution, and laminar flow; constructing a geometric model of a deposition cell and a substrate, and setting laser properties, material physical parameters, and electrodeposition properties in the multiphysics simulation software; constructing an ultrafast laser heat transfer model on the basis of a two-temperature equation; setting initial and boundary conditions of the ultrafast laser heat transfer model, and constructing an electrodeposition field; coupling the ultrafast laser heat transfer model with the electrodeposition field to construct an ultrafast laser-assisted electrochemical deposition model; delineating a grid; and performing calculation and analysis. In the present invention, ultrafast laser is incorporated to perform multiphysics coupling of a thermal field, a flow field, an electric field, etc., and a two-temperature equation and tertiary current distribution are incorporated to the model, thereby achieving the accuracy and comprehensiveness of prediction models.

The invention belongs to the field of bioinformatics, and relates to a protein post-translational modification prediction method based on multi-modal deep learning. The method comprises the following steps: firstly, performing multi-modal feature extraction by inputting a protein sequence and three-dimensional structure data to obtain a sequence feature vector and a structure feature vector; secondly, carrying out feature fusion by adopting a cross-modal attention mechanism and a self-adaptive gating network; then, combining the fusion features with the disease type information, and performing fine adjustment on the prediction probability through a disease specific coding network; then, using a multi-task learning framework to predict the locus probabilities of various protein post-translational modification types in parallel; finally, feature importance is calculated through a gradient back propagation technology, and a comprehensive report is output in combination with variation influence analysis. According to the method, high-precision and explainable protein post-translational modification prediction with disease perception capability is realized, and an important calculation and analysis tool is provided for revealing a disease molecular mechanism and finding accurate drug targets.

A portable golf putting green putter multi-parameter intelligent training system is characterized by comprising a support (1) used for installing an electromagnetic induction type sensing device (2) and an electric control element and enabling the whole training system to be convenient to carry and move; the sensing devices (2) are installed on the two supporting legs of the support, and at least two sensing devices (2) are installed on each supporting leg; and the electric control element (3) is used for receiving the signal intensity and the time difference obtained by the sensing device (2), transmitting the signal intensity and the time difference to a computer system (4) in real time in a wired or wireless manner, calculating and analyzing the signal intensity and the time difference, displaying the speed and the angle of the push rod in real time, and comparing the speed and the angle with preset standard values, so that a coach or a practicer can improve the speed and the angle. The utility model has the advantages of simple structure, convenience in carrying, low cost and wide application range.

The invention relates to the technical field of hydraulic engineering, and discloses a gate station-based flow coefficient calculation and analysis method, which comprises the following steps of S1, synchronously acquiring flow, gate opening and upstream and downstream water level parameters from a gate station; s2, performing dimensionless processing on the acquired real-time monitoring data; s3, constructing a three-dimensional feature tensor according to the preprocessed data; s4, decomposing the three-dimensional feature tensor by using a weighted constraint tensor decomposition technology; s5, on-line parameter identification is carried out based on the flow calculation model; and S6, flow prediction is executed according to the real-time flow parameters, and the corresponding gate opening degree is output to control the water flow of the gate station. By performing dimensionless processing and logarithmic binning method preprocessing on the acquired real-time monitoring data, the influence of different dimensions and measurement errors on model establishment is eliminated. Compared with a traditional data processing method, according to the technical scheme, the consistency and reliability of the data are ensured, and the accuracy of model analysis is improved.

The invention discloses a computational analysis method applied to high-power power electronic networking equipment, and relates to the technical field of power systems. According to the method, broadband power grid impedance, equipment state and device working condition data are acquired through a sensing layer, and accurate input is provided through layered compression and priority transmission; the cooperative calculation layer introduces a power grid impedance correction coupling interference matrix, establishes an electrothermal coupling loss mapping relation, and realizes coupling interference quantification, loss real-time calculation and full life cycle prediction; the linkage optimization layer constructs a multi-objective optimization function, an optimal control parameter is solved through an efficient algorithm, and a segmented execution strategy is adopted to adapt to different working conditions; the closed-loop feedback layer collects operation feedback data, dynamically updates the model and optimizes the weight, and links fault black-start support and optimal power supply recovery path planning. According to the invention, multi-target collaborative optimization of system stability, operation efficiency, equipment service life and power supply reliability is realized, and technical support is provided for large-scale safe and efficient operation of high-power networking equipment.

This invention discloses a method for calculating the vibration response of a delaminated composite laminate, belonging to the field of structural defect calculation and analysis. The method includes: dividing the composite laminate with delamination defects into delaminated and intact regions based on the damage condition; decoupling the delaminated regions dynamically; describing the vibration characteristics of each component in both the delaminated and intact regions using elastic waves based on elastic wave propagation theory, and establishing vibration state vector expressions for each region; determining the compatibility relationship based on the displacement continuity and internal force equilibrium conditions at the coupling point between the delaminated and intact regions, and establishing structural dynamic equilibrium equations in wave space based on the boundary conditions of the composite laminate; solving the structural dynamic equilibrium equations to obtain the amplitudes of elastic waves of each order; and calculating the vibration response of each region of the composite laminate based on elastic wave theory and amplitude calculation. This invention solves the problem of low computational efficiency in existing methods.

The invention provides an engineering carbon emission factor dynamic calculation and traceability analysis method and system, and belongs to the field of engineering construction. The method comprises the following steps: acquiring multi-source heterogeneous data of the whole engineering construction process, and preprocessing the multi-source heterogeneous data to form a data set supporting knowledge modeling and computational analysis; constructing a semantic knowledge structure in the field of carbon emission factors in the whole engineering construction process by utilizing a knowledge graph technology; carrying out dynamic calculation on the carbon emission factor and correcting the weight; and carrying out visual analysis on a dynamic calculation result and a correction result to complete dynamic calculation and traceability analysis on the engineering carbon emission factor. According to the method, the defects in a carbon emission accounting system in the existing engineering construction field are overcome.

Disclosed are systems and methods that provide a decision intelligence (DI)-based computerized framework for deterministically determining atmospheric data and patterns in / around locations, and leveraging such information for on-demand access and usage on similar sites. The disclosed systems and methods can provide a synergistic combination of a layered data repository, DI-based computational analysis, sensor integration and simulation capabilities, which can provide an interactive holistic system for monitoring, analyzing and managing atmospheric conditions at specific locations. The disclosed framework can provide unprecedented insights, enabling systems, sites, assets and / or users to make informed decisions, optimize asset operations and proactively mitigate environmental impacts.

The invention discloses an ALS prognosis evaluation system based on UBE2J2 gene methylation and expression level, and relates to the technical field of biomedicine and bioinformatics. Comprising a data acquisition module, a methylation detection module, an expression quantity determination module, a data preprocessing module, a preliminary survival analysis module, a multivariable Cox proportional risk model construction module, an individualized risk index calculation and grouping module and a visualization and clinical application module. By combining UBE2J2 gene methylation and expression quantity analysis, peripheral blood non-invasive detection, standardized experiment and computational analysis process and visual presentation, the method is technically and remarkably superior to the prior art, high accuracy, operability, repeatability and expandability are realized, and the method is suitable for large-scale popularization and application. And the technical defects of single molecular marker, complicated operation, inaccurate prediction and the like in ALS prognosis evaluation in the prior art are overcome.

The invention relates to the technical field of sensing, and discloses an equipment operation maintenance state intelligent monitoring system and method.The system comprises a multi-mode sensing acquisition module, an edge calculation analysis module, a digital twinborn decision module and a maintenance execution control module; when the operation state of the equipment is monitored, static parameters and dynamic operation data of the equipment are fused, multi-dimensional feature extraction and abnormal coupling analysis of the health state of the equipment are realized, early potential faults of the equipment can be accurately identified, the problems of false alarm and missing alarm caused by monitoring of a traditional single sensor are avoided, the accuracy and reliability of state evaluation are improved, and the reliability of state evaluation is improved. The method is advantaged in that continuous and safe operation of equipment is guaranteed, long-term benefits of different maintenance actions are simulated in a virtual environment based on equipment degradation state quantitative indexes during equipment maintenance strategy optimization, and a problem of non-planned shutdown caused by dependence on artificial experience and maintenance lag of a traditional threshold alarm mechanism is solved.

The invention discloses an unmanned aerial vehicle data sharing method and device based on privacy protection, and the method comprises the steps: collecting flight data, environment perception information and task state data through an unmanned aerial vehicle, combining an operation instruction, scheduling information and user authority data of a ground control end, and intelligently recognizing to-be-shared privacy data. According to the data type and the sensitivity level, the system performs protection processing on the sensitive data by adopting a privacy computing technology such as homomorphic encryption or differential privacy, generates protected data and uploads the protected data to a sharing platform through a secure channel. The platform directly executes cooperative calculation and analysis on the protected data without decryption, generates an intermediate result, and feeds back the intermediate result to a related terminal after inverse processing. The risk of data leakage caused by calculation after decryption in a traditional encryption scheme is solved, the high-efficiency multi-party cooperative calculation capability is maintained while absolute security of sensitive information is guaranteed, and a solution which gives consideration to privacy protection and data value mining is provided for an unmanned aerial vehicle system.

The invention discloses an intelligent production line packaging box detection and recognition system, which relates to the technical field of image recognition, and comprises a data acquisition module, a preprocessing module, a storage module and a central calculation module, foreign matter existence and covering parameters are obtained by processing an image, a shielding factor is calculated to judge shielding, and the acquisition module is adjusted until no shielding exists. And then information missing parameters and missing factors are obtained through comprehensive processing, and information missing is analyzed and adjusted until detection is complete. Foreign matter shielding is accurately judged and adjusted through multiple modules and algorithms, the problem of information loss caused by camera shielding is solved, the analysis accuracy is improved, after foreign matter is not shielded, information loss is calculated and analyzed, the analysis range is adjusted to be complete, and it is guaranteed that packaging box information detection is reliable.

The invention provides a fluid-solid-heat dynamic simulation method for impeller blade particle impact based on multi-physics field coupling, the physics field in the method comprises a fluid field, a heat transfer field and a structure field, coupling simulation is carried out through data exchange among different software, and the process of particle impact on an impeller blade is calculated and analyzed. The method mainly comprises the following steps: importing an impeller model grid file into FLUENT software, setting a turbulence model and the like, setting parameters such as the density and the viscosity parameter of air fluid along with the temperature change, the rotating speed of a fluid domain and the like, and setting the flow speed and the temperature parameter of an air inlet; in EDEM software, parameters such as the material, the number and the particle generation of particles are set; a UDF script is read in the FLUENT software, a coupling switch of the EDEM software is turned on, and bidirectional coupling simulation of data exchange is carried out; and importing the obtained temperature change range into an elastic-plastic thermal coupling material model of LS-DYNA software, and carrying out explicit dynamic simulation by taking the obtained particle movement speed as the initial speed of the particles impacting the impeller.

A system for quantum-enhanced behavioral analysis and secure database operations includes an ACAARY Database configured to store and process quantum-verified data under multi-tiered access control; an AR Quantum Cyber-Micro Expressions System configured to analyze involuntary behavioral patterns in digital communications via computational analysis of user interaction data; AR Quantum Sequence Triplications with Quantum Operations comprising three-qubit verification circuits implemented on superconducting quantum processors that perform parallel artificial-qubit processing to achieve unbiased quantum supremacy; an AR Quantum Parallel Data Algorithm Structure and Method Specialized Encrypted Algorithmic Quantum Procedures configured to execute simultaneous perpendicular encryption processing with real-time transaction verification across multiple channels; an AR Helmsmen Quantum Transportation Management System with integrated digital licensing and frequency-based quantum routing protocols; and an AR Thermodynamics Devices System configured to perform thermal bonding and division operations while maintaining different temperatures within defined containment areas for material modification.

The invention relates to the technical field of circuit breaker detection, and particularly discloses a circuit breaker operating characteristic detection system based on artificial intelligence, which comprises a data acquisition layer, a data preprocessing layer, a data analysis layer, a decision early warning layer and a system management layer, and the data acquisition layer is responsible for acquiring operating characteristic parameters of the circuit breaker. Through filtering, normalization and feature extraction, the data quality and availability are improved, and a foundation is laid for subsequent analysis; the data analysis layer performs evaluation from multi-dimensional parameters in mechanical actions by applying comprehensive calculation and analysis to obtain a mechanical action state evaluation coefficient and accurately grasp the operation state of the circuit breaker; the decision early warning layer accurately judges the operation state according to an evaluation result and a threshold value and carries out early warning in time so as to assist operation and maintenance personnel to rapidly respond; the system management layer is used for dynamically optimizing a feedback judgment threshold, and the overall scheme effectively improves the accuracy, reliability and intelligent level of circuit breaker detection, reduces the fault risk, and guarantees the safe and stable operation of a power system.

The invention relates to the technical field of artificial intelligence, and discloses an artificial intelligence-driven multi-modal data analysis method and system, and the system comprises a data collection module which is used for setting collection nodes and terminals, collecting multi-modal data and equipment operation parameters in real time, and carrying out the format conversion; the multi-modal fusion module is used for constructing a cross-modal semantic association model, processing space-time characteristics, fusing characterization characteristics and performing association simulation; the feature extraction module is used for constructing image, text and voice related extraction algorithms to obtain corresponding features; the comprehensive analysis module is used for carrying out correlation calculation on the features after standardization processing, and comparing and analyzing semantic consistency with a preset threshold value; and the grading processing module is used for combining context calculation analysis when semantics are inconsistent, and analyzing target scene performance after secondary comparison. The system and the method can effectively process multi-modal data, improve semantic analysis accuracy and efficiency, and are suitable for various scenes.

The utility model discloses a surface-mounted resistor CCD (Charge Coupled Device) detection device, which relates to the technical field of detection equipment and comprises a bottom plate, a control and calculation analysis unit, a feeding mechanism, a CCD detection camera, a discharging mechanism, a turntable and three supporting tables, the rotating disc is horizontally designed, the center of the bottom of the rotating disc is fixedly connected with the output end of the second motor, the edge of the rotating disc is rotationally connected with the bottom plate through a limiting piece, three through holes are evenly formed in the rotating disc, rotating shafts are rotationally arranged in the through holes, and a first motor is arranged at the position, corresponding to the through holes, of the bottom face of the rotating disc. According to the utility model, the CCD detection camera is used for shooting the surface-mounted resistor on the support table, and the support table can rotate by 360 degrees, so that the CCD detection camera can shoot and detect each side surface and upper surface of the surface-mounted resistor, the detection efficiency is greatly improved, the overall structure is simple, and the repair and maintenance are convenient.

The invention discloses a distributed photovoltaic power station intelligent safety operation and maintenance management system, and relates to the technical field of photovoltaic power station operation and maintenance, the system comprises a data acquisition module, a data processing module, a calculation and analysis module and a management execution module, and the calculation and analysis module comprises a component health sub-module, a potential risk sub-module and an operation and maintenance analysis sub-module. According to the invention, a comprehensive attenuation coefficient is output through the assembly health sub-module, a dust coverage rate and other multi-dimensional parameters are integrated to quantify an attenuation state, a fault risk index is output based on the potential risk sub-module through the potential risk sub-module, and parameters such as current fluctuation are fused to construct a multi-precursor early warning system. The operation and maintenance analysis sub-module integrates parameters such as a risk index and outputs an operation and maintenance priority index, and the three components cooperate to realize full-period quantitative management from attenuation evaluation, fault early warning to operation and maintenance decision making, so that the traditional limitation is broken through, and the evaluation accuracy and the operation and maintenance efficiency are improved.

The invention discloses a deep learning-driven low-altitude unmanned aerial vehicle disaster emergency surveying and mapping and real-time monitoring system, and the system comprises a data collection module which constructs a networked control architecture, and obtains a flight state and environment perception data; the data distribution module separates the key data stream to an edge computing node for processing; the permission allocation module optimizes permission allocation according to the task coordination efficiency; the cooperative control module is combined with local adjustment and a global instruction to form a cooperative control strategy; the resource allocation module dynamically allocates resources to the high-priority tasks; the parameter optimization module analyzes feedback data through edge calculation to optimize operation parameters; and the collaborative operation module adjusts the control authority to form a stable operation mode. By means of deep learning and edge computing, efficient data processing, dynamic resource allocation, quick response and stable collaborative operation of the unmanned aerial vehicle in a complex disaster environment are achieved, and the overall performance and task execution efficiency of multi-vehicle operation are remarkably improved.

The present application belongs to the technical field of nuclear power engineering design, and provides a nuclear power plant wind pipe support load automatic calculation and analysis method and system, comprising: obtaining data information of a nuclear power plant wind pipe; calling a corresponding three-dimensional support model in a preset wind pipe information library according to the data information of the nuclear power plant wind pipe; automatically calculating the wind pipe support load according to the three-dimensional support model; and automatically completing the mechanical analysis of the wind pipe support load according to the calculated wind pipe support load; the present application can realize the data information of the wind pipe support, automatically call the support model in the wind pipe information library to complete three-dimensional support modeling; according to the three-dimensional support model, the automatic calculation and automatic analysis of the wind pipe support load can be realized, the complex process of drawing, mapping, data extraction and coupling iterative calculation of the designer is cancelled, the cycle of mechanical calculation and analysis of the wind pipe support is shortened, and the accuracy of the calculation result is greatly improved.

A method for secure analysis of distributed data includes receiving a request from a user to perform a data analysis operation. The data analysis operation utilizes first data accessible by a first secure research environment and second data accessible by a second secure research environment. The method further includes authenticating the user at the first secure research environment and the second secure research environment, communicating a first query for the first data to the first secure research environment, and communicating a second query for the second data to the second secure research environment. The method further includes receiving, from a secure compute environment in communication with the first secure research environment and the second secure research environment, results from the data analysis operation.

The invention provides an alarm analysis method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring alarm information, wherein the alarm information comprises alarm time period information, alarm range information and alarm scene information; generating alarm query data corresponding to the plurality of alarm associated data sources according to the alarm time period information and the alarm range information, and sending the corresponding alarm query data to each alarm associated data source; when a query result returned by any alarm association data source based on the corresponding alarm query data is received, determining an association degree corresponding to at least one received query result according to the alarm scene information; calculating the confidence coefficient of the analysis result according to the correlation degree; and when the analysis result confidence is greater than a preset confidence threshold, analyzing the alarm root cause corresponding to the alarm information according to the at least one query result. According to the method, the alarm analysis efficiency can be improved.