546results about How to "Improve visualization" patented technology

The invention belongs to but not limited to the technical field of fault diagnosis and maintenance of power equipment, and discloses an intelligent diagnosis and maintenance system and method for power equipment based on a knowledge graph. A data acquisition and preprocessing module acquires real-time operation data and historical data of the power equipment; the knowledge graph construction module associates various kinds of information of the power equipment to construct a knowledge graph; the intelligent diagnosis module performs association analysis on power equipment faults based on a knowledge graph and a machine learning algorithm, identifies fault modes and potential faults, and predicts possible faults of the equipment; the maintenance suggestion module automatically generates a detailed maintenance scheme according to the diagnosis result; the operation and maintenance visualization module provides visual fault diagnosis results and maintenance suggestions, supports multi-level data display, and helps operation and maintenance personnel to clearly understand the equipment state. The operation safety of the power equipment is improved, the operation and maintenance cost is remarkably reduced, and the overall efficiency of equipment management in an intelligent power grid environment is improved.

The invention provides a three-dimensional geological modeling parameter optimization method and system based on deep learning, and relates to the field of geological prospecting and modeling.The method comprises the steps that drilling data and remote sensing data of a geological prospecting area are obtained, and multi-source geological data of three-dimensional geological modeling are formed; generating geological profile map data of the geological features according to the drilling data, generating landform profile map data corresponding to the topographic features according to the remote sensing data, and extracting boundary information of the geological exploration area; carrying out gridding processing on a three-dimensional space, dividing a geologic body of the geological exploration area into a plurality of small grid units, and defining geological modeling parameters; the preliminary three-dimensional geological grid model is constructed according to the geological profile map data, the landform contour map data and the boundary information, the size and the resolution of the grid are dynamically adjusted according to the geological change area, the three-dimensional geological model is obtained through optimization and adjustment, the modeling precision is improved, manual intervention is reduced, and computing resources are saved.

The invention relates to the technical field of intelligent manufacturing, in particular to a manufacturing industry digital twinning three-dimensional visual management and control method and system, and the method comprises the following steps: collecting manufacturing equipment operation data, converting the data into a time sequence, analyzing the trend characteristics of each dynamic subsequence in the time sequence, and generating a dynamic operation state sequence set. According to the method, the time sequence characteristics in the operation data of the manufacturing equipment are dynamically analyzed, so that the trend change of the operation state of the equipment can be accurately captured in multiple time dimensions, and potential abnormal states are deeply mined and predicted. In combination with prediction of future operation state parameters and comparison of a normal state range, an abnormal trend region and a corresponding fault level can be clearly marked, and the risk assessment capability of the equipment health state is effectively improved. And carrying out three-dimensional space mapping on the marked risk area, and accurately positioning an abnormal part and a deviation area in combination with gradient change and deviation distribution analysis of three-dimensional coordinates of equipment.

The invention relates to the technical field of medical data management, in particular to a medical data document classification and marking system which comprises a document structure analysis module, a semantic information identification module, a classification and marking module and a document intelligent label module. According to the method, document visualization and retrieval efficiency is improved by analyzing document content and extracting titles, texts and appendixes, analytic performance and operability of data are enhanced by identifying key information and semantic relations and accurately extracting and labeling medical terms, medicine research data and medical record records, storage is optimized according to priorities in combination with classification and marking, and the method is high in practicability and easy to popularize and use. Clinical values and application scenes of documents are clarified, document management processes are refined, management compatible with clinical data formats is formed through structured storage of marked data and classification label generation, storage normalization and retrieval efficiency are improved, the requirement for accurate information calling in clinical tests is met, document management capacity is improved, and the document management efficiency is improved. And support is provided for improvement of clinical decision-making and research efficiency.

The invention relates to the technical field of surface defect detection, and discloses a metal surface defect detection method and device, equipment and a storage medium. The method comprises the following steps: performing multi-frequency eddy current scanning on the surface of a metal workpiece to obtain a four-dimensional original data set containing space coordinates, excitation frequency and impedance response; performing adaptive filtering and compensation on the four-dimensional original data set to obtain target signal data; performing adaptive imaging and frequency fusion on the target signal data to obtain a two-dimensional image; inputting the two-dimensional image into a lightweight adaptive convolutional neural network for multi-dimensional feature extraction to obtain a multi-dimensional feature map; performing texture analysis and anomaly detection on the multi-dimensional feature map to obtain a comprehensive anomaly score map; and carrying out multi-modal data fusion and decision making on the comprehensive abnormal score graph to obtain a metal surface defect detection result, and improving the detection accuracy of the metal surface defect.

The invention discloses a terrain-level real-scene three-dimensional entity and element dynamic updating method, which comprises the following steps: S1, data acquisition and preprocessing: acquiring data of a target area by an acquisition mechanism based on entity and element type priorities, and preprocessing the acquired data to obtain model data of the target area; s2, change detection: comparing newly collected model data with historical model data, and identifying a change region and type; s3, entities and elements are extracted and updated, wherein the entities and the elements of the change area are processed to obtain updated models; s4, model fusion and optimization: fusing the updated entity and element model with the original model, and realizing efficient acquisition and preprocessing of target area data by using the multi-source surveying and mapping equipment and an acquisition mechanism based on entity and element type priorities; by dividing the small regions according to the region characteristics and correcting the acquisition frequency, the resource allocation is optimized, and the pertinence and efficiency of data acquisition are improved.

The invention relates to a knowledge-enhanced large model data analysis agent visualization method, which comprises the following steps of: performing syntactic analysis by using a PCFG algorithm, identifying syntactic components and relationships of sentences, and splitting the sentences into sub-sentences with complete logic; extracting keywords and entity words of the sentences by combining a word segmentation technology with a business word segmentation library; recommending and summarizing candidate segmented words through a recall strategy, carrying out rough arrangement, fine arrangement and fine arrangement on the candidate segmented words, and correcting and complementing a segmented word result; splitting and analyzing the natural language problem based on the fine-tuned large model, and generating SQL statements meeting business requirements; analyzing the data set generated by the SQL, extracting field information and business meanings, and identifying an association relationship between fields; and automatically recommending chart styles according to data features and user preferences, assembling an analysis report and distributing the analysis report according to a specified frequency. According to the method, knowledge enhancement and large model technologies are combined, so that the efficiency and effect of data analysis and visualization are remarkably improved.

The invention discloses an automatic penetration test method, system and device based on deep reinforcement learning, and a medium, and the method comprises the steps: carrying out the vulnerability scanning and baseline verification of a device through employing a vulnerability scanning and baseline verification tool, and obtaining the vulnerability information of a tested system; generating an attack graph according to the obtained vulnerability information, determining a vulnerability utilization probability according to the vulnerability information, and assigning values to edges of the attack graph to obtain a Bayesian attack graph; designing an attacker target node reward value on the generated Bayesian attack graph, simulating a possible attack behavior of an attacker, and calculating an attack strategy of the attacker by using a deep reinforcement learning method; simulating potential attack behaviors of an attacker in the attack graph according to an attack strategy, and generating a penetration attack path which is most likely to be adopted by the attacker; and performing an automatic penetration test to generate a penetration test report. According to the invention, the penetration test scheme can be intelligently generated according to the vulnerability of the system, and the precision and efficiency of network security evaluation are greatly improved.

The invention provides a semiconductor data analysis and visualization method and device based on a large model, and relates to the technical field of data processing. The method comprises the steps that demand information input by a user is analyzed through a large language model, and key information corresponding to the demand information is obtained; the key information comprises time information, industry information, index information and geographic information; determining a target data set most relevant to the key information from a preset database by utilizing a data set automatic selection algorithm; determining a visualization strategy of the demand information according to the demand information and the target data set; and according to the visualization strategy and the large language model, generating a visualization code corresponding to the visualization strategy, and executing the visualization code to automatically generate a visualization chart. According to the scheme, the problems of automatic analysis and visualization of complex data in the semiconductor feasibility research report are solved, dynamic data display is supported, and the data visualization effect is improved.

The invention discloses a capillary image evaluation method, device and equipment and a medium, and the method comprises the steps: obtaining IQ data of a to-be-detected region, and carrying out the beam forming of the IQ data; performing clutter filtering processing on the IQ data of each continuous data frame after beam forming, and extracting a blood flow signal; removing background noise from the blood flow signal to obtain a blood vessel structure image, and segmenting the blood vessel structure image to obtain a distribution position of a blood vessel region; screening a peak region based on the distribution position of the blood vessel region, and determining a peak center position; trajectory tracking is carried out based on the peak value center position, and all trajectories are superposed and displayed to generate a capillary image; and analyzing the generated capillary image, and extracting related parameters of the capillary. Therefore, the method is not limited by image resolution, and can be applied to microvascular images with limited resolution and super-resolution microvascular images, and vascular morphology and hemodynamic parameters can be extracted from the microvascular images with limited resolution and super-resolution.

The invention discloses a multi-source fusion detection and formation recognition system for an unmanned aerial vehicle cluster. The multi-source fusion detection and formation recognition system comprises a radar detection system, a photoelectric detection system and an information processing module. The invention further discloses a multi-source fusion detection and formation recognition method for the unmanned aerial vehicle cluster. The method comprises the steps that the radar detection system obtains the initial azimuth information of the unmanned aerial vehicle; the information processing module generates guidance information according to the initial azimuth information; the photoelectric detection system tracks the unmanned aerial vehicle according to the guidance information to obtain an image of the unmanned aerial vehicle; and the information processing module obtains the three-dimensional position information of the unmanned aerial vehicle according to the initial azimuth information and the unmanned aerial vehicle image, carries out the recognition of the unmanned aerial vehicle cluster formation pattern, and obtains a formation pattern structure. According to the method, accurate identification and three-dimensional coordinate acquisition of individual targets in a long-distance high-resolution unmanned aerial vehicle cluster and feature identification of the formation of the unmanned aerial vehicle can be realized, and high-reliability information support is provided for command, control and strike decisions.

The invention relates to the technical field of communication interaction, in particular to a data interaction method based on an intelligent control platform. The method comprises the following steps: acquiring multi-dimensional data of production equipment, performing anomaly marking and format unification processing, generating a production line data stream, performing long and short term dependency analysis on the data stream, and constructing a time-space association network, thereby realizing prediction of an anomaly situation, generating an anomaly intelligent analysis model by using a multi-modal fusion modeling technology, and performing data analysis on the anomaly intelligent analysis model. And through the model, abnormity traceability is carried out, and abnormity reasons are clarified. According to the method, a corresponding correction strategy is constructed based on an abnormal reason, tree-shaped interaction sharing is performed through an intelligent control platform, a sharing correction instruction is formed, abnormal correction processing is performed on a production line according to the sharing instruction, feedback is collected through the intelligent control platform, an effective data interaction mechanism is formed, and the reliability and efficiency of the production line are improved. The data interaction method based on the intelligent control platform is more accurate and more comprehensive.

The invention discloses a distributed architecture of an intelligent emergency command and dispatch system and a collaborative decision-making method. A distributed architecture comprising a basic resource layer, a support service layer and an application layer is constructed, and functions of multi-type alarm access, accurate alarm positioning, intelligent power dispatching and the like are realized by using multiple technologies. And establishing a collaborative decision-making mechanism which covers problem modeling, communication protocol design, negotiation mechanism development, dynamic adjustment and decision-making execution. The system is deployed after integration testing and security testing, personnel training, daily hardware maintenance, software monitoring, data backup and security component updating are carried out. The emergency commanding and dispatching efficiency, accuracy and collaboration are improved, the method adapts to complex emergencies, and public safety is guaranteed.

The invention relates to the technical field of biological information mining, in particular to a multi-omics data optimization method and system for intestinal flora matching and a medium. The method comprises the following steps: acquiring historical intestinal tract multi-omics data and integrating the historical intestinal tract multi-omics data to obtain host intestinal tract multi-omics data; performing multi-omics data fusion based on the host intestinal multi-omics data to obtain microbial flora fusion data; performing pattern classification according to the host intestinal tract multi-omics data to obtain host intestinal tract physiological pattern data; carrying out physiological pattern influence factor calculation on the microbial flora fusion data to obtain host intestinal tract physiological pattern influence factors; and performing host intestinal flora matching on the microbial flora fusion data and the host intestinal physiological data according to the host intestinal physiological pattern influence factor, thereby obtaining intestinal flora matching data. According to the method, the accuracy of flora matching prediction can be improved.

The invention relates to the technical field of solid waste sorting scheduling, in particular to a real-time monitoring optimization method and device for a solid waste collection, transportation and sorting ERP system. The method comprises the following steps: obtaining a real-time solid waste sorting log based on a solid waste collection, transportation and sorting ERP system; solid waste carrying vehicle tracking is carried out on the real-time solid waste sorting log, and a carrying track distribution visual view is constructed; acquiring an omnibearing monitoring image of a real-time sorting site; equipment sorting behavior visual identification is carried out on the real-time sorting site omnibearing monitoring image, dynamic sorting evolution is carried out, and a dynamic sorting twinborn model is constructed; carrying out multi-time-point solid waste sorting simulation on the dynamic sorting twinborn model, carrying out sorting load demand prediction, and generating a sorting load demand prediction value; and carrying out vehicle load calculation on the sorting load demand prediction value one by one, and then carrying out dynamic vehicle scheduling decision making to obtain a dynamic vehicle scheduling strategy. According to the invention, efficient and real-time solid waste sorting scheduling optimization is realized.

The invention discloses an electric power material supply management and control system and a method thereof. The electric power material supply management and control system comprises a master control center, a sub-control center, a material warehouse, a mobile control terminal and a data processing platform. The electric power material supply management and control method comprises the following steps: S1, material demand prediction; s2, intelligent scheduling; s3, performing real-time monitoring; s4, risk assessment and early warning; and S5, emergency response is carried out. The electric power material supply management and control system and the method thereof can improve the material supply efficiency, enhance the decision support capability, make the decision more accurate and efficient, help to optimize resource configuration, improve the overall operation efficiency, improve the transparency and visualization of a supply chain, enhance risk management, guarantee the safe and stable operation of a power grid, improve the emergency response speed, and improve the power supply efficiency. The resource allocation is optimized, the inventory cost is reduced, the fund utilization efficiency is improved, the optimal allocation of resources is realized, and the electric power material requirements of each region can be better met.

The invention belongs to the technical field of rock and soil mechanics, and particularly discloses a method and system for analyzing and predicting a rock failure process based on discontinuous deformation. Comprising the following steps: performing regional discretization modeling on rock, applying parallel spring units between adjacent discrete blocks based on an elastic theory, and establishing a nonlinear failure criterion based on a fracture mechanics theory; inputting a time step, calculating normal phase and tangential deformation of the cemented spring, and updating stress-strain information of the block in real time; a damage coefficient is calculated, the damage degree of the cemented spring is judged, a damaged cemented spring unit is removed, and the rigidity of the undamaged spring is updated; and the rock damage process is visualized. According to the method, the stress softening behavior in the rock fracture process is considered, the problem that an existing discontinuous deformation analysis method (DDA) is insufficient in precision in the aspect of simulating the nonlinear stress softening behavior of the rock is solved, the damage process and the stress evolution process of the rock under the tension-shear action can be predicted more accurately, and the strength and fracture characteristics of the rock can be predicted.

The invention discloses a data processing system and method for three-dimensional real estate surveying and mapping, and relates to the technical field of intelligent surveying and mapping, and the system comprises a multi-source data fusion module, a model generation module, a spatial relationship analysis module, an efficient rendering module and a data security module. The multi-source data fusion module converts the original surveying and mapping data in different formats into a unified three-dimensional point cloud data set; the model generation module generates a parameterized three-dimensional building model based on the point cloud data; the spatial relation analysis module constructs a relation graph of the building model and generates a surveying and mapping index report; the efficient rendering module processes large-scale three-dimensional data and generates an interactive three-dimensional scene; and the data security module controls the data access authority and generates an operation log. According to the method, the processing efficiency and precision of the three-dimensional real estate surveying and mapping data are improved, efficient analysis and visualization of large-scale three-dimensional data are realized, the security of sensitive data is ensured, and advanced technical support is provided for modern city planning, real estate management and real estate development.

The invention relates to an inter-satellite link communication simulation system and method based on a satellite constellation. The system comprises a satellite orbit simulation module, a satellite attitude simulation module, an inter-satellite communication link simulation module, a visualization and interaction technology module and a data interaction and system test module. The satellite orbit simulation module is used for calculating a movement track of a satellite in an earth gravitational field; the satellite attitude simulation module is used for accurately simulating a satellite attitude; the inter-satellite communication link simulation module is used for evaluating inter-satellite communication quality; the visualization and interaction technology module is used for presenting real-time states of satellite orbits, attitudes and inter-satellite links; and the data interaction and system test module is used for smoothly exchanging data, and comprehensively testing and checking the correctness and performance of satellite orbits, attitudes and communication functions. The method has the beneficial effects that the real-time states of the satellite orbit, the attitude and the inter-satellite link are efficiently presented, so that a user can easily monitor and control the simulation process.

The invention discloses a coal seam working face floor detection and analysis method, and relates to the technical field of detection and analysis. Potential change conditions of different positions and different elevations are observed through a parallel electrical method instrument, resistivity distribution conditions of different depths in a working face and a bottom plate of the working face can be obtained through three-dimensional electrical method inversion, and the resistivity distribution conditions provide technical support for objective and accurate geological interpretation. The hydrogeological condition of the working face floor rock stratum can be better understood, so that an important reference basis is provided for safe mining; the thermal effect and the electromagnetic effect existing in the environment are evaluated and corrected, so that the deviation of the measured conductivity value can be accurately corrected, and the accuracy and the reliability of conductivity measurement data are improved; and inputting the corrected conductivity value SR (xi, yi, zi) of each grid point into a three-dimensional model, and marking to construct a conductivity three-dimensional model, so as to visually display the electrical property distribution information of the underground medium.

The invention discloses a food safety data evaluation method and system based on big data, and relates to the technical field of food safety, and the method comprises the following steps: collecting and preprocessing multi-party information data related to food, obtaining standardized data, integrating the standardized data, and carrying out the weighted calculation of the integrated standardized data, the method comprises the steps of obtaining basic data, establishing a food safety index evaluation model, obtaining a safety evaluation index of target food, and establishing a traceability chain for the target food in combination with related data and the safety evaluation index. The food safety data evaluation method is realized by setting food safety data evaluation based on big data, the basic data is acquired based on data of various sources and types of food, the food safety evaluation index is calculated, the food safety quality is conveniently and visually displayed, the food safety evaluation index is acquired through the data of multiple parties, and the food safety evaluation efficiency is improved. And the authenticity of the safety evaluation index is improved.

The invention relates to an agricultural data interaction method and platform based on multi-source information, and belongs to the technical field of agricultural data processing. Comprising the following steps: processing collected data through a corresponding edge calculation module to generate a dynamic label; analyzing and processing the agricultural information data to obtain a supervision label and corresponding supervision data; all the tags and the corresponding data are imported into a geographic information system, matching is carried out according to the corresponding areas and the respective tags, and meanwhile, the monitoring tags are recognized and updated through a cloud platform computing center. The real-time data is fused and sent to the cloud computing platform through the edge computing module, the interaction prompt is generated through association with the supervision data, so that the real-time performance and the high efficiency of data processing are improved, meanwhile, the monitoring data and the supervision data are associated through the interaction prompt, and the interactivity of visual display is improved.

The invention relates to the technical field of network security, in particular to a network traffic anomaly detection method and system based on a knowledge graph, and the method comprises the steps: extracting entities in a traffic data set, relationships between the entities and entity attributes, and constructing a traffic information knowledge graph based on the extracted entities, relationships between the entities and entity attributes; storing the flow information knowledge graph into a graph database; and obtaining a feature similarity score between the to-be-detected unknown traffic and the traffic in the stored traffic information knowledge graph by adopting a collaborative filtering algorithm, and determining the type of the to-be-detected unknown traffic according to the feature similarity score. According to the method, the traffic information is stored in the graph database Neo4j, so that the relationship of characteristic values among the traffic is clearer and clearer, the operation of security personnel is facilitated, and the visualization effect is improved; through matching of intervals where flow characteristic values in the knowledge graph are located, the flow range participating in calculation of an anomaly detection algorithm is narrowed, and the calculation efficiency is improved; and by fusing the weight coefficients and comprehensively considering the two similarity results, the accuracy of the detection result is improved.

The invention belongs to the technical field of electric power engineering monitoring, and discloses a small sample power transmission line pin defect detection method based on a graph convolutional network, and the method comprises the steps: collecting a power transmission line pin image through image collection equipment; marking pins in the image based on event logic guidance to obtain a transmission line pin data set with logic association; introducing a cross-domain interaction enhanced pyramid network into the graph convolutional network to obtain an improved graph convolutional network model, and training to obtain an original target detection model; a knowledge graph relation reasoning module is introduced into the original target detection model, and a power transmission line pin defect detection model is obtained; and detecting the preprocessed power transmission line pin image by using a pin defect detection model, so as to generate a pin image with marked pin position classification and confidence. The method can effectively solve the problem that the sample size is small, and improves the recognition accuracy of the pin and the defect of the pin, thereby facilitating the improvement of the efficiency of detecting the defect of the pin of the power transmission line by inspection personnel, and guaranteeing the stable operation of a power system.

The embodiment of the invention provides an intelligent GIS defect detection method, a controller, a power grid management system and a medium, and the intelligent GIS defect detection method comprises the steps: obtaining the partial discharge level of a partial discharge position under the condition that the power grid management system detects at least one partial discharge position of a gas-insulated metal-enclosed switchgear; determining a processing sequence table of partial discharge positions according to the partial discharge grade; sequentially acquiring detection data and simulation data of the partial discharge position according to the processing sequence table; determining the defect type of the partial discharge position according to the detection data and the simulation data; and generating corresponding intelligent decision information according to the defect type. The GIS defect detection efficiency is high, the detection cost is low, the partial discharge position and the defect type are displayed on the digital twin model, the visualization is good, and the defect of the partial discharge position with the high partial discharge grade is preferentially processed, so that the loss caused by partial discharge is reduced to the greatest extent.

The invention discloses an irrigation district water storage management and control system and a dynamic water storage management and control method for slope planting, and relates to the field of mountain water resource management and agricultural irrigation, and the irrigation district water storage management and control system comprises a server side which is used for deploying front and rear end codes, files, models and databases; the background management control platform is used for managing and controlling water storage stations, drip irrigation valves, soil moisture content information, crop planting information, crop fertilization information and data analysis related models in an irrigation area; the foreground statistical analysis platform is used for monitoring, analyzing and visually displaying the information in the irrigation area; and the mobile terminal management and control platform is used for checking the multi-dimensional information of the irrigation area in a portable manner and performing corresponding management and control. According to the method, the large-scale multi-point-position operation state is displayed in a partitioned, blocked and multi-dimensional manner by combining terrain and geographic information data, and the method can adapt to visual monitoring, management and control of irrigation areas in complex geographic environments such as slopes and the like.

The invention relates to the technical field of data processing, and discloses a BIM model storage system and method based on lightweight data, and the system comprises a tree segment management module which is used for constructing a tree segment structure, and taking each segment as a storage unit; the segment multiplexing creating module is used for creating multiplexing segments in the tree-shaped segment structure, realizing data multiplexing in a reference mode, and creating style segments for centralized management of drawing attribute information; the parallel rendering module is used for rendering the model primitives by adopting a parallel computing method based on the geometric information and the attribute information in the multiplexing segments; the lightweight data generation module is used for organizing the BIM model data according to a tree-shaped segmentation structure and generating a binary data file; and the data compression module is used for compressing the binary data file to generate a compressed format storage file. The technical problem that efficient storage, transmission and application requirements of the BIM model are difficult to meet in the prior art is solved.

The invention relates to a digital twin model construction method and device of a converter station and computer equipment. The method comprises the following steps: processing a visible light image of a converter station by adopting a motion recovery structure model and a multi-view stereoscopic model to obtain dense point cloud data of the converter station; fusing the dense point cloud data and the laser scanning point cloud data of the converter station to obtain geometric point cloud data of the converter station; constructing a grid model of the converter station according to the geometric point cloud data; according to the visible light image and the grid model, obtaining a visible light texture mapping relation corresponding to the visible light image, and according to the visible light image, performing registration processing on other multi-source images of the converter station to obtain other texture mapping relations corresponding to the other multi-source images; and obtaining a multi-source texture digital twin model of the converter station according to the grid model, the visible light texture mapping relation and other texture mapping relations. By adopting the method, the precision of the digital twin model of the converter station can be improved.

The invention discloses a branch coverage rate calculation method and device based on BOOL logic, and relates to the technical field of software testing. The method is suitable for the test case taking the BOOL logic expression as basic test data, the branch path diagram is generated according to the BOOL logic expression, the coverage rate condition of the test case set on the BOOL logic branches is calculated according to the covered path condition in the case execution process, covered and uncovered BOOL branch reports are output according to the test execution condition, and the test efficiency is improved. The test case executed by the black box is transparent, and meanwhile, a test case set can be completed according to uncovered branch guidance in an output report.

The invention relates to the technical field of Internet of Things data alarm threshold management, and discloses an Internet of Things data alarm threshold management method and system based on a distributed generation mode, and the system comprises a user side alarm threshold application demand identification module, a user side alarm threshold application processing module, and a user side alarm threshold application feedback adjustment module. Internet-of-things distributed client alarm threshold application program object type intelligent identification is carried out based on big data storage Internet-of-things data alarm threshold application program parameters in combination with intelligent identification algorithm client alarm threshold application demand standard keyword translation information; the intelligence and applicability of the Internet of Things data alarm threshold management system are improved; and according to the analysis information of the user-side Internet of Things data alarm threshold application program, the application execution hardware terminal is combined to autonomously and dynamically execute the user-side Internet of Things data alarm threshold application operation, so that the visualization and functional diversity of the Internet of Things data alarm threshold management system are improved.