218results about How to "Accurate analysis" patented technology

The invention relates to the technical field of intelligent ship control, and particularly discloses an area control integration method and system based on an intelligent ship engine room, original operation data and multi-source communication data of equipment in each area of the engine room are collected, a unified real-time state vector is generated through protocol analysis and standardization processing, and a plurality of redundant processing nodes are processed in a unified mode. Synchronizing and verifying state data through a high-speed channel, constructing a global consistent state synchronization set, disassembling composite logic into atomic operation units with state constraints according to an upper-layer instruction and the synchronization set, packaging the atomic operation units into a private instruction sequence bound with the state, executing the instruction sequence by a main node, and executing the state synchronization set by a slave node; seamless switching to a standby node is realized through independent hardware monitoring when a fault occurs, and the standby node continuously executes based on the continuity of a state synchronization set, so that high-reliability uninterrupted operation of area control is realized; according to the method, the problems of instruction semantic distortion and single-point fault risk in heterogeneous equipment integration are solved, and the control accuracy and the intelligent level are improved.

The invention provides a rock mineral micromechanical evolution characterization method based on a convolutional neural network. The rock mineral micromechanical evolution characterization method comprises the following steps: step 1, obtaining rock sample micromechanical properties through a nanoindentation experiment; 2, performing deconvolution statistical analysis by using a Gaussian mixture model, and obtaining mechanical and volume fractions of each phase through a nanoindentation experiment; step 3, utilizing a Mori-Tanaka scale upgrading method to understand a convolution result, and performing rock macromechanical property prediction in combination with a convolutional neural network; and step 4, performing precision checking calculation on an output result of the convolutional neural network model until the prediction precision meets a preset requirement. According to the method, the microscopic mechanical parameters of the rock sample are obtained through the grid nanoindentation, statistical analysis is carried out on the nanoindentation test result by utilizing a deconvolution method, the mechanical property of the macroscale of the rock is obtained in combination with machine learning and a scale upgrading model, and a bridge for connecting the macroscale and the microscale is established; the method can effectively solve the problem of inaccurate prediction of rock micromechanical parameters on the macroscale and the problem of mechanical property characterization caused by scale difference.

A method for constructing a damage constitutive model to analyze the damage evolution of easily argillaceous rocks includes: preparing ore specimens; conducting acoustic emission tests on the ore specimens under uniaxial compression; obtaining the displacement, load, and acoustic emission parameters of each specimen; calculating and analyzing the characteristic stresses of easily argillaceous rocks under uniaxial compression; revealing the evolution characteristics of acoustic emission parameters under uniaxial compression; defining the damage variables at different characteristic stress stages; and constructing a damage constitutive model of the entire stress-strain process of easily argillaceous rocks. This method can accurately and comprehensively quantitatively analyze the strength evolution characteristics of easily argillaceous rocks under uniaxial compression, monitor the damage evolution characteristics and damage degree of easily argillaceous rocks in real time, and provide a reference for maintaining the stability of underground goaf areas in mines.

The present application relates to the technical field of smart grid, especially to a kind of intelligent power distribution cabinet with fault detection function and detection method.The present application can accurately obtain state data and analyze state data by obtaining unit and data analysis unit;Multiple AI analysis models in edge computing unit can accurately analyze equipment state results, and can improve the efficiency of power distribution cabinet fault detection;Through the decision unit, multiple equipment state results are fused using the preset rules to obtain accurate fault information, and the execution module in the control unit is driven based on the accurate fault information to act;Finally, the analysis unit determines the fault detection state based on the fault suppression success rate within the preset period, and adjusts the corresponding parameters based on the fault detection state, so as to more accurately analyze the fault.The present application improves the fault detection efficiency of power distribution cabinet.

The invention relates to the technical field of organoid culture, in particular to a pulmonary fibrosis organoid model and a construction method and application thereof. The pulmonary fibrosis organ-like model is obtained by co-culturing lentivirus stably transfected alveolar epithelial cells, human embryonic lung fibroblasts MRC-5 and macrophages. According to the invention, macrophages are innovatively introduced, a ternary co-culture system of lentivirus stably transfected alveolar epithelial cells, human embryonic lung fibroblasts MRC-5 and macrophages is constructed, and a key'epithelial injury-immune infiltration-fibroblast activation 'pathological triangle in a pulmonary fibrosis pathogenesis process can be more comprehensively simulated; the finally obtained pulmonary fibrosis organ-like model provides an efficient tool for pulmonary fibrosis mechanism research and research, development and screening of anti-pulmonary fibrosis drugs.

The present application relates to the technical field of dental root image processing, and particularly relates to an intelligent detection method for bone density change caused by dental root absorption area of impacted wisdom tooth. The present application constructs a coordinate system of images under different angles, obtains a gray weighted value of each pixel point in the images under each angle according to actual source image distances of the images under different angles and position distribution of preset anatomical structures, obtains a bone density change rate of each position pixel point in combination with displacement change amounts and gradient features of registered pixel points between the images under different angles, obtains a high risk degree threshold value of bone density change according to bone density change rate distribution of all position pixel points, and obtains a high risk area of bone density change of each image according to the bone density change rate of each position pixel point on each image and the high risk degree threshold value of bone density change. The present application improves the accuracy of bone density change detection by accurately analyzing the bone density change area.

This application provides a cross-application service scheduling and execution method and system in a vehicle environment, relating to the field of intelligent vehicle system technology. It acquires known service-related data of the vehicle system, as well as environmental perception data and user voice information of the vehicle environment; parses the user voice information to obtain target demand information, intent association information, and voice feature information; forms scene adaptation parameters based on environmental perception data; generates multiple second instruction transmission signals based on target demand information; detects each target demand information based on service-related data, intent association information, voice feature information, and scene adaptation parameters, obtains detection results, and combines these with the second instruction transmission signals to schedule and execute multiple cross-application services in the vehicle environment, generating service scheduling and execution results. This achieves dynamic coordination and orderly scheduling of cross-application services, improving the response accuracy and execution security of the vehicle system in complex driving scenarios.

The present application relates to the field of analytical chemistry, and provide a kind of method for detecting complex matrix of agricultural products in guanidine morpholino salt hydrochloride.The extraction solvent of the present application uses acetonitrile+acid+aqueous solution, different acid is selected according to the water content of sample, trifluoroacetic acid is used for high water content sample, and formic acid is used for low water content sample;In purification, pH value is adjusted according to the oil content of sample, ammonia is used to adjust pH to 8.5 for high oil content sample, and pH value can not be adjusted for low oil content sample.In the method, NaCl is not added to make organic phase and aqueous phase in extraction liquid stratified, through the way of extracting three times repeatedly, the recovery rate of the method is guaranteed;And using ultra-high phase liquid chromatography triple quadrupole mass spectrometry technology, guanidine morpholino salt hydrochloride in complex matrix of agricultural products is successfully detected, the extraction method is fast and simple, the quantitative limit of guanidine morpholino salt hydrochloride in tea is 0.1mg / kg, and the quantitative limit in other matrix is 0.05mg / kg, which is suitable for routine analysis, and can meet the quantitative detection requirements of guanidine morpholino salt hydrochloride in complex matrix of agricultural products.

The invention provides a spark source atomic emission spectrometry determination method for acid-soluble aluminum and inclusion aluminum, and belongs to the technical field of assessment of inclusions in steel. The spark source atomic emission spectrometry determination method for acid-soluble aluminum and inclusion aluminum comprises the following steps: establishing a calibration curve of all aluminum, then determining integral intensities of inclusion aluminum, all aluminum and acid-soluble aluminum in a sample under corresponding conditions, and calculating the intensity of the inclusion aluminum by using a difference value between the integral intensities; selecting two standard samples with adjacent strength according to the strength of aluminum inclusion in the sample, and calculating a calibration coefficient K according to the aluminum content Al% lt; the excitation rate F is calculated according to the peak integral intensity of the inclusion aluminum and the integral intensity of the total aluminum in the 0.0007% standard sample, the inclusion aluminum content Als% is equal to K * F * (IAlt-IAls), and the content of the acid-soluble aluminum is equal to the difference between the content of the total aluminum and the content of the inclusion aluminum. According to the method, the accuracy of a measurement result is effectively improved while high analysis speed, low cost and simplicity and convenience in operation are ensured.

The invention belongs to the technical field of transient analysis of a new energy grid-connected system, and particularly relates to a transient overvoltage analysis method of a direct-driven wind power grid-connected system under an asymmetric fault, which comprises the following steps: acquiring three-phase asymmetric voltage and current, and constructing a positive and negative sequence dq control model of positive and negative sequence bisynchronization of a direct-driven wind power plant station; establishing a mapping relation with a symmetric component method, and determining a positive-sequence dynamic reactive current increment and a negative-sequence current suppression coefficient according to a converter control strategy; establishing sequence network boundary conditions under various asymmetric faults; enabling the direct-driven wind power plant to be equivalent to a frequency-related controlled sequence impedance source, and obtaining equivalent sequence impedance of the wind power plant; establishing a sequence network equation considering wind power dynamic support; calculating the current and sequence voltage of the fault point, and obtaining a three-phase voltage through symmetric component inverse transformation; and an overvoltage coefficient is calculated, and a quantitative relational expression between the overvoltage coefficient and the negative-sequence current suppression coefficient is established and applied. The method provides theoretical support for parameter setting and capacity planning of the wind power integration system.

The utility model relates to the field of metal welding piece detection, and discloses a steel structure welding quality compression resistance detection mechanism which comprises a bottom plate, a mounting structure is fixedly connected to the middle of the upper end face of the bottom plate, a driving structure is fixedly connected to the middle of an inner cavity of the mounting structure, and clamping structures are symmetrically connected to the inner cavity of the mounting structure in a sliding mode. The left side of the upper end face of the bottom plate is fixedly connected with a containing structure, a lifting structure is arranged in the middle of the upper end face of the containing structure, the sliding block moves to make the clamping plate and the fixing structure slide relatively, and the steel structure makes contact with the fixing column. When interaction force is generated between the fixing column and the steel structure, the fixing column can slide towards an inner cavity of the sliding groove, the fixing spring contracts, so that the steel structures of different shapes are clamped and fixed, meanwhile, through the telescopic characteristic of the spring, it can be guaranteed that stable clamping force can be provided on the surfaces of the steel structures of different shapes, and the clamping effect is good. And the steel structure is prevented from displacement in the subsequent detection process, so that the accuracy of the detection result is ensured.

This invention discloses a method and system for predicting RNA binding protein binding sites on RNA without targeting, relating to the field of bioinformatics. The method includes the following steps: acquiring raw RNA structure data; expanding and filtering the preprocessed data; training an RNA analysis model using the filtered data; processing the RNA to be analyzed using the trained RNA analysis model, calculating the probability that each nucleotide is single-stranded, and obtaining a structure score; identifying low-accessibility regions based on the difference between the structure score output by the RNA analysis model and the structure score calculated by the original method; and identifying potential RNA binding protein binding sites by comparing the signal difference with that of the original method in a single RNA structure detection experiment. This invention utilizes the STONE method to improve the accuracy of RNA structure analysis in low-accessibility regions, and uses the improved difference to infer RBP binding sites, thereby improving the accuracy of RBP binding site identification.

This invention discloses a GIS-based risk management system and method for pollutant migration in mining area watersheds, relating to the technical field of simulating pollutant migration patterns. It includes a 3D GIS functional module, a hydrodynamic-water quality model coupling module, and a mining watershed pollution risk management module. Based on watershed hydrology theory and pollutant migration and diffusion mechanisms, it fully considers the migration of pollutants in the storage area after rainfall via surface microrunoff. By studying the formation patterns of microrunoff, it simulates the watershed migration process of pollutants in the mining area under different rainfall intensities, thereby more accurately calculating pollutant migration and diffusion fluxes and managing the risk of pollutant migration in the watershed. Based on historical and real-time data and models, it uses a 3D model to display the spatial distribution patterns and development trends of pollutants, achieving accurate pollutant identification and source tracing. It can simulate pollution control measures in mining area watersheds, predict development trends, and provide early warnings for pollution events.

The invention provides a gas chromatographic analysis method of maleic anhydride, and belongs to the technical field of maleic anhydride analysis methods. As a maleic anhydride sample to be detected contains acidic substances and has a low response value on an FID (Flame Ionization Detector), according to the method provided by the invention, the BSTFA reagent is adopted for esterification treatment, the response value of the acidic substances in the sample to be detected is increased, a weak-polarity chromatographic column is adopted for gas chromatographic analysis, a hydrogen flame detector is used for detection, and an external standard method is used for quantitative calculation. The method provided by the invention has the advantages of high accuracy of the obtained detection result, good data repeatability and high sensitivity, can accurately analyze the maleic anhydride component concentration, has important guiding significance for quality control of maleic anhydride products produced by a device, and has good popularization and application values.

This utility model discloses a monitoring device for accurately detecting the opening pressure of a safety valve online. It includes a base fixed to a spring safety valve, a piston chamber fixed above the base, a piston coaxially arranged with the valve stem of the spring safety valve connected inside the piston chamber, a screw coaxially fixed to the piston, and the screw and the valve stem connected to each other via a strain gauge. The piston chamber and the piston form a sealed cavity, and the piston chamber has an oil inlet communicating with the sealed cavity. The oil inlet is connected to a hydraulic device via a pipe. The strain gauge and the hydraulic device are both communicatively connected to a distributed control system (DCS), which is also communicatively connected to a pressure sensor. This utility model not only allows for remote operation of the control system to measure and calculate the spring stiffness of the safety valve, but also eliminates the need to shut down the furnace during the measurement process, offering better real-time performance, allowing for operation at any time, and without excessive limitations.

The application relates to the technical field of power distribution control, in particular to an active power distribution network fault self-healing system and a method thereof, which comprises a data sensing module, a fault positioning module, an isolation control module, a fault self-healing module and a power supply recovery module, and realizes intelligent processing of the whole process from fault detection to power supply recovery through cooperation of the multiple modules. The system can quickly position faults based on FTU layout structure and operation data, optimizes analysis efficiency in combination with a GPU computing power dynamic distribution mechanism, and realizes accurate isolation of a fault area, self-healing repair and smooth grid recovery by using intelligent strategy generation and digital twin technology. The application effectively improves the power supply reliability, system stability and operation intelligent level of the power distribution network.

The utility model relates to the technical field of geological sample sampling devices, and discloses a geological stratified sampling device for geological mining, which comprises a movable base provided with a central hole, and a limiting ring rotatably connected in the central hole; the sampling barrel selectively penetrates through the central hole; the telescopic sleeves are sequentially connected in a sliding mode from the outer side to the inner side in the vertical direction, the telescopic sleeve on the outermost side is connected with the inner side wall of the limiting ring in a sliding mode, the inner side wall of the telescopic sleeve on the innermost side is connected with the sampling barrel in a sliding mode, and the sampling barrel can drive the telescopic sleeve on the innermost side to synchronously move downwards. And then the multiple sections of telescopic sleeves from the inner side to the outer side are driven to be sequentially embedded in the drill hole. The sampling barrel can drive the telescopic sleeve on the innermost side to synchronously move downwards, then the multiple sections of telescopic sleeves are driven to be sequentially embedded in a drill hole, collapse of the drill hole is avoided, and layered multi-time sampling of stratums with different depths is achieved.

This utility model relates to the field of soil research technology and discloses an equidistant sampling device suitable for the study of soil pollutants in agricultural land. It includes a support plate with a scale fixedly connected to its top. Two I-shaped grooves are formed at the top of the support plate, and two I-shaped sliders are slidably connected to the inner walls of the two grooves. Two pedals are fixedly connected to the tops of the two sliders. The operator first determines the sampling interval according to the research requirements. Then, the operating parameters of the bidirectional motor, such as speed and direction of rotation, are set via the control panel. After starting the bidirectional motor, its output drives a bidirectional screw to rotate. Due to the bidirectional thread characteristic of the bidirectional screw, the two moving sleeves connected to the surface of the bidirectional screw will move in opposite directions at equidistant intervals along the screw. The operator can then observe the position of the pointer on the scale.

The present application relates to the technical field of crystal nondestructive testing, and particularly relates to a crystal defect nondestructive testing method and system based on pumped probe transient absorption spectrum, which comprises the following steps: detecting a target region of a crystal to be tested by using pump light and probe light; collecting a transient absorption image of the target region according to a preset time delay between the pump light and the probe light, and extracting a target risk region; focusing the pump light and the probe light, and performing point-by-point scanning on the target risk region by using the focused pump light and probe light; collecting three-dimensional transient absorption intensity distribution and defect dynamic evolution data of each scanning point in the target risk region under different time delays; performing correlation calibration based on the transient absorption image and the three-dimensional transient absorption intensity distribution to obtain defect parameters; and constructing a damage prediction model based on sample damage threshold data, and outputting damage threshold prediction results according to the defect parameters. The purpose is to realize nondestructive and rapid detection of internal defects of deuterated potassium dihydrogen phosphate crystals.

The invention discloses a multi-modal large model ground penetrating radar disease data intelligent interpretation method and device, and belongs to the computing intelligence and information processing technology. The method is based on a computing device of machine learning, artificial intelligence and a specific mathematical model, and an inference model of specific ground penetrating radar knowledge is fused for information processing. Comprising the following steps: acquiring underground disease data by using multi-frequency ground penetrating radar equipment, and converting the underground disease data into a serialization format adaptive to a multi-modal large model; and then sequentially executing detection, segmentation and image description tasks. Wherein a segmented label mask is generated by adopting a Bayesian optimization method based on a target detection result, and an image description data set is constructed by utilizing a segmentation result; and finally, performing intelligent interpretation on the data by using the multi-modal large model to generate an interpretation report. According to the method, through multi-task collaborative learning, full-process automatic interpretation from disease detection to semantic description is realized, the interpretation efficiency and reliability are improved, and an intelligent basis is provided for road maintenance decision making.

The application is a kind of method for remotely guiding infrared observation equipment to observe target, belonging to the technical field of remote guidance, which comprises the following steps: a remote control terminal locates the observation target and obtains target position information, and then wirelessly transmits the target information to first, second and third infrared observation equipment; the remote control terminal estimates the optimal observation distance based on the estimated size of the target and the field of view angle and resolution of the first infrared observation equipment; the remote control terminal guides the first, second and third infrared observation equipment to move to the optimal observation distance from the target position and to the positions of the three apexes of the inscribed regular hexagon in the circle for cooperative target observation; the remote control terminal remotely controls the real-time adjustment of the direction, position and focal length of each infrared observation equipment based on the video stream images returned by the first, second and third infrared observation equipment. The application is used to remotely and real-timely guide infrared observation equipment to observe the specified target.

This invention relates to a surge arrester condition monitoring system, comprising a data acquisition module, a lightning strike assessment module, a prediction module, and a threshold adjustment module. The data acquisition module collects current and voltage waveforms from multiple lightning strikes within a single lightning event, as well as the time intervals between adjacent strikes. The lightning strike assessment module calculates the intensity ratio of single lightning strikes based on the surge arrester's baseline withstand parameters, quantifies the cumulative effect of consecutive lightning strikes using a time interval-based correction coefficient, and obtains a weighted fusion index of the comprehensive impact of lightning events on the surge arrester. The prediction module uses this index, combined with the natural aging rate, to update the surge arrester's estimated remaining lifespan. The threshold adjustment module adjusts the abnormal monitoring thresholds for operating parameters such as leakage current, resistive current, and temperature based on the updated remaining lifespan. This invention achieves quantitative assessment of the surge arrester's aging state, dynamic prediction of remaining lifespan, and intelligent adjustment of monitoring thresholds, effectively improving the foresight and accuracy of condition monitoring.

The invention relates to the technical field of data processing, in particular to a multi-dimensional automobile accessory big data processing method and system based on a vertical class model, and the method comprises the steps: obtaining multi-dimensional data information of automobile accessories at regular time; according to key text information in the multi-dimensional data information, constructing a text feature vector of the automobile accessory; determining a first similarity between each attribute of each automobile accessory and the automobile accessory with the same name; obtaining the attribute importance degree of each attribute of each automobile accessory; based on a vertical class model, evaluating the similarity degree of the text feature vectors between any two automobile accessories obtained in a single time, and classifying the automobile accessories; and determining a first similarity between each attribute of any automobile accessory in the same kind of automobile accessories and the remaining automobile accessories, and calculating the automobile accessory similarity between the any automobile accessory and the remaining automobile accessories by combining the attribute importance of each attribute of the any automobile accessory so as to perform duplicate removal processing on the same kind of automobile accessories. Therefore, the duplicate removal effect of the automobile accessory data is improved.

The invention discloses an intelligent precise maintenance system and method for garden plants, and relates to the field of intelligent maintenance. The system comprises a garden plant key data acquisition module, a plant image imaging recognition early warning detection module, a plaque multi-block segmentation recognition analysis module, a plaque type comparison and diagnosis module, a medicament precise application analysis and confirmation module and an intelligent collaborative terminal, and aims to construct a garden environment data platform by using intelligent monitoring equipment. Partition precision analysis is performed on garden soil, different surfaces of garden plant canopy leaves and corresponding stems are analyzed, positions, types and serious proportions of disease spots are precisely identified, severity levels of the disease spots are analyzed, early warning is realized, precise targeted therapy is performed according to the severity levels of the disease spots, production cost is reduced, and large-scale and high-frequency plant health general survey is realized.

This invention discloses a model test device and method for simulating road collapse caused by rainfall infiltration. The device includes a load-bearing module, a rainfall control module, a particle collection module, and a parameter monitoring module to ensure the operability and accuracy of the experiment. The rainfall control module controls the rainfall flow rate through a booster pump, an inlet valve, and a flow meter to trigger piping. The particle collection module collects lost particles in layers according to depth. Combined with pre-treatment of the foundation soil particles with staining, the particle loss patterns at different depths and sizes can be accurately analyzed. This invention has a simple structure and is easy to operate. It can effectively simulate the entire process of rainfall infiltration leading to piping and subsequent road collapse. By laying reinforced sections at different heights on the embankment, it can be used to study the piping mechanism and the reinforcement effect of reinforced embankments.

The application provides a method for monitoring a contaminated soil remediation process, which comprises the following steps: adding micro-nano reactors into wet contaminated soil, transferring into a closed container, mixing uniformly, carrying out the soil remediation process, collecting samples at different time periods of the remediation process, separating the micro-nano reactors from the soil by using a flotation method or a screening method, and obtaining the micro-nano reactors with target pollutants or degradation products of the target pollutants on the surfaces of the micro-nano reactors. The surface state of the separated micro-nano reactors and the target pollutants or degradation products are analyzed by using spectroscopy technology, the distribution of the target pollutants, the element valence, the morphology of the nano metal or metal oxide, the crystal form and the change of the valence are judged, the separated micro-nano reactors are washed by using an organic solvent, the target pollutants or degradation products washed out are analyzed, and the types of the target pollutants or degradation products are judged; and the progress of the soil remediation and the interaction mode of the components in the micro-nano reactors and the pollutants in the soil are obtained according to the analysis results.

The application discloses a method and system for dynamic prediction and emergency decision of agricultural disasters based on multi-source data, and relates to the technical field of agricultural disaster prevention. The method comprises the following steps: collecting multi-source historical data and real-time data; dividing the grades of disasters; taking crop data as output, other multi-source data and prediction time as input, and establishing a crop prediction model; calculating a super prediction factor for reflecting the self-recovery effect of the agricultural ecological environment; combining the crop prediction model and the super prediction factor to establish a disaster prediction model; obtaining a prediction result, combining the disaster grade, and performing a preset emergency decision scheme. The application uses the super prediction factor to represent the subsequent disaster dynamic situation of the to-be-predicted period, quantifies the self-recovery effect of the agricultural ecological environment, combines the crop prediction model, analyzes the agricultural disaster dynamic situation after the to-be-predicted period, and improves the prediction accuracy and the effectiveness of the emergency decision.

This invention belongs to the field of power system automation and discloses a method, system, equipment, and storage medium for wide-area oscillation tracing in power grids. The method includes: acquiring oscillation characteristic information of each substation node; identifying the oscillating substation node and its oscillating current flow direction based on the oscillation characteristic information; acquiring the oscillation amplitude of each oscillating substation node; and determining the oscillation propagation direction of each oscillating substation node based on the oscillation amplitude and oscillating current flow direction; and tracing the oscillation source based on its propagation direction to obtain the oscillation source. This enables accurate analysis of the oscillation propagation path and its impact range, achieving oscillation source tracing and accurate location, thereby providing strong support for power grid operation monitoring and targeted oscillation suppression, effectively supporting dispatching and operation monitoring operations, and ensuring power grid operation safety.

The invention discloses a supervision-process-oriented multi-modal engineering document intelligent structured extraction and association system, and relates to the technical field of engineering supervision informatization. A multi-modal perception understanding module accurately analyzes texts, images and voice documents through a supervision field fine-tuning large model, multi-step chain reasoning and geometric parameter measurement; the dynamic affair graph construction module is used for defining relationships between nodes such as problems and rectification and triggering and response, establishing association according to an analysis result and dynamically updating attributes and weights; the closed-loop state tracking module determines and rectifies a flow state rule, and realizes overtime and associated risk early warning and flow evolution prediction; the interaction application module provides a visual billboard, voice interaction and automatic report generation functions; the model optimization module acquires new case data, calculates process deviation and adjusts model parameters, and the system improves supervision document processing efficiency and rectification management and control precision and supports intelligent decision making.

This invention discloses a data task orchestration method that supports end-to-end tracing and service-oriented architecture. It accesses multi-source heterogeneous data through pluggable data source adapter components and transforms the data into a unified internal data model. The process model includes start event nodes, batch processing task nodes, stream processing task nodes, gateway nodes, and end event nodes. It breaks the limitations of traditional static FGA models, supporting mixed orchestration of batch and stream processing within the same process model, as well as complex process control based on parallel and inclusive gateways. The traceId mechanism enables end-to-end task tracing, facilitating fault location and operational monitoring.