43results about How to "High practical application value" patented technology

The invention discloses a method for inverting key parameters in an underground water pollutant biodegradation numerical model based on a neural network algorithm. Carrying out preprocessing and refined dimension reduction on the data, and processing high-dimensional multi-scale data; building a multilayer neural network architecture under a physical information neural network framework, embedding a related reaction equation of a pollutant natural attenuation process, and coupling a biochemical reaction mechanism and a data driving model; a neural network model is trained, errors in the training process are calculated, and the accuracy of an inversion result is improved by using a sub-when optimization algorithm; integrating observation data and a model prediction result, determining final parameter setting of a numerical model, and carrying out underground water damage real object quantification; comparative verification of a neural network parameter inversion model is carried out, and feasibility and accuracy of the parameter inversion method are ensured. According to the method, the problem that the key parameters of the biodegradation numerical model are difficult to accurately invert in the real object quantification process of underground water pollution under complex geological conditions is solved.

The invention relates to the technical field of fault detection for a wireless communication network, and discloses a fault detection method for the wireless communication network. By collecting data of base station signal strength, network delay, data packet loss rate and user equipment signal quality, the problem of insufficient fault detection caused by a single index is solved. Through multi-dimensional data acquisition, the system can comprehensively evaluate network performance, the fault detection accuracy is improved, and different fault types can be effectively identified especially in a complex fault mode. By storing the data according to the time sequence, the problem of time sequence chaos is avoided, and accurate detection of time-varying faults is ensured. The comprehensive data vector generated by each time of sampling comprises a plurality of network performance indexes, so that the fault detection and positioning capability is improved. Abnormal values are eliminated through data preprocessing, the data quality is ensured, an accurate basis is provided for subsequent analysis, and the reliability of a detection result is ensured.

The invention discloses an airport pavement engineering three-dimensional model modeling method, system and device and a storage medium, and the method comprises the steps: obtaining elevation characters, terrain grids and flatness range boundary geometric information in an airport pavement engineering CAD two-dimensional drawing, and creating a three-dimensional terrain based on Revit; configuring road surface structure design parameters in the three-dimensional terrain; obtaining all region filling conforming to a specific layer naming rule, and based on Boolean operation, performing region filling in the three-dimensional terrain to generate a pavement structure; obtaining pavement sign information, and projecting in the three-dimensional terrain to generate a pavement sign; the method comprises the following steps: acquiring geometric information of a plate seam line, generating a closed outer contour of each pavement plate according to a pavement structure, generating pavement blocks in a three-dimensional terrain, and obtaining angular point positioning points of the blocks; generating a slab joint according to the projection of the block corner positioning points in the three-dimensional terrain; and according to projection of the block corner positioning points in the three-dimensional terrain and calculation, a dowel bar is generated, and establishment of the airport pavement engineering three-dimensional model is completed.

The invention discloses a 3D target detection method and system based on binocular vision and open vocabularies, and relates to the technical field of target detection. The method comprises the following steps: calculating pixel features of each image by adopting an open vocabulary 2D detection model; pixel features of the left view and the right view are aggregated to each three-dimensional point; obtaining a parallax estimation map based on the pixel features of the left and right views; introducing a time aggregation guide parallax consistency constraint to obtain a depth parallax estimation map; converting the depth parallax estimation map into a 3D point cloud, and extracting features to obtain 3D features; and carrying out correlation integration on the text features, the 2D fusion feature vectors and the 3D features by utilizing object-level image guide detection loss, object-level cross comparison alignment and object-level self-comparison learning to obtain a three-dimensional target detection model, realizing three-dimensional target detection and distinguishing different target objects. According to the invention, accurate detection and distinguishing of the target can be realized, so that the flexibility and universality of 3D target identification are improved.

The invention belongs to the field of data mining in deep learning, and particularly relates to a time series prediction system based on a causal relationship. The time series prediction method comprises a causal inference and enhancement algorithm suitable for time series data; a causal-frequency domain attention module based on a graph attention mechanism and Fourier transform; the invention discloses a decoder based on a multi-layer perceptron. According to the method, the modeling capability of the existing multivariable time sequence prediction method on the dependency relationship between the sequence variables and the feature extraction capability on the long-time sequence data can be improved, and the error of the prediction result is effectively reduced.

The invention discloses a property scene perception and decision-making method, device and equipment and a storage medium, and the method comprises the steps: carrying out the preprocessing and format specification labeling of a target detection data set, and obtaining a property data set containing a plurality of images; performing label alignment on the property data set and the public data set to obtain a common label set; fusing the common label set through data screening to obtain a fused data set; converting the fusion data set into a visual question and answer data set, fusing professional knowledge of a property scene, constructing a visual-text multi-modal data set, and performing model training by using the visual-text multi-modal data set to obtain a multi-modal large model; performing fine adjustment on the multi-modal large model by adopting a pre-trained visual model; and deploying the multi-modal large model after fine tuning into a property service system. The problems that an existing multi-modal large model is high in training cost, context semantics cannot be understood and the like are solved, and the practical application value of the multi-modal large model is improved.

The invention relates to a method for modeling a photovoltaic power station for relay protection by using fault recording data. The method comprises the following steps: step 1, acquiring a fault recording file by a fault recording analysis system; 2, processing voltage and current data based on the fault recording file obtained in the step 1, and then calculating the short-circuit current of the photovoltaic power station; 3, obtaining a latest short circuit calculation model based on the voltage and current data processed in the step 2, and obtaining a final short circuit calculation model through multiple times of model correction; and 4, performing short-circuit calculation by using the short-circuit calculation model corrected in the step 3. According to the invention, simulation and actual short-circuit tests can be avoided.

The invention provides an organic chemical fertilizer for preventing and treating asparagus stem blight and a preparation method thereof, and relates to the field of organic chemical fertilizers. The organic chemical fertilizer for preventing and treating the asparagus stem blight is prepared from, by weight, 50 parts of organic matter base materials, 15 parts of natural mineral substances, 8 parts of microbial agents, 4 parts of plant extracts, 2 parts of stabilizers and 1 part of growth promoting factors, and the organic matter base materials are prepared from, by weight, 30 parts of decomposed chicken manure, 15 parts of humic acid and 5 parts of straw powder. The organic matter base material is used for providing rich nutritional ingredients, improving the soil structure, increasing the soil organic matter content and enhancing the soil microbial activity. The microencapsulation technology is adopted to wrap the microbial agent, so that the activity of the microbial agent is effectively protected, the influence of competition of other microorganisms and environmental factors on the microbial agent in soil is reduced, and the effectiveness of the microbial agent is improved.

The novel beacon vessel comprises a base and further comprises a water flow power generation device and a solar power generation device which are installed on the base, the base is arranged to be cylindrical, a notch is formed in the middle of the base, an impeller of the water flow power generation device overhangs in the notch to rotate, and the cylindrical base rotates in real time in the water flow direction. A solar power generation device is mounted on the top surface of the base at the rear part of the notch, and is provided with a foldable turnover mechanism, so that a solar panel of the solar power generation device is always positioned at the optimal sunlight receiving angle; multi-source power generation is achieved through the water flow power generation device and the solar power generation device, redundant electric energy is stored for standby application and delivery while power is supplied to the beacon light and other electric equipment on the device, real-time data acquisition is achieved through the camera and the light induction sensor, and the device is simple and compact in structure, reliable in operation, low in cost, convenient to install and high in practicability. Power generation is stable and efficiency is high.

The invention discloses a distributed power generation maintenance arrangement optimization method and system considering multiple uncertainties, and belongs to the technical field of electrical engineering, and the method specifically comprises the steps: arranging maintenance conditions of a sea wind turbine unit; the method comprises the following steps: acquiring sea wind overhaul arrangement data information based on set sea wind unit overhaul arrangement conditions, including sea wind unit parameters with overhaul requirements, an operation and maintenance ship rental price, the number of maintainers, work time salary and overtime time salary; and according to the obtained sea wind maintenance arrangement data information, a wind turbine generator maintenance mode arrangement plan considering multiple uncertain conditions is carried out. And various changing scenes can be coped, and the maintenance cost of the offshore wind turbine generator is reduced.

The invention discloses a street space gene recognition and extraction method based on ancient customs drawings, which comprises the following steps: collecting the ancient customs drawings related to a to-be-studied regional range, and screening and classifying the ancient customs drawings; dividing a characteristic space scene in the ancient custom picture in combination with the space scene conversion marker; performing extraction on the spatial features of the street by combining the divided spatial scenes, and performing clustering on each street space; extracting space elements of each street space in the street space image and converting the space elements into text labels; based on the street space in the scene, analyzing to obtain the configuration relationship of the space elements, and combining with the function interaction relationship in the ancient customs drawing to form a combination relationship and performing screening; verifying a spatial element configuration relationship in the screened combination relationship to obtain a final street space gene; according to the method, the suitability of the path flow of space gene recognition extraction and the technical method is effectively improved.

The invention belongs to the technical field of groundwater reserve prediction, and particularly relates to a physical logic driven groundwater reserve intelligent prediction method and system. Comprising the following steps: performing complementation and physical verification on multi-source heterogeneous observation data related to groundwater reserves in a target area to obtain a physical verification complete data set conforming to physical logic; performing space-time decoupling causal contribution analysis on the physical verification complete data set to generate a causal contribution matrix; according to the causal contribution matrix, constructing and training a physical constraint emergence type space-time prediction model; applying a physical anchoring adversarial migration strategy to adapt the trained emergence type prediction model to the target new region to obtain a region adaptive prediction model; and inputting the future scene conditions into the regional adaptation prediction model for simulation, and generating a groundwater reserve prediction result. According to the method, intelligent prediction with high precision, high robustness and physical interpretability on groundwater reserves can be realized, and scientific decision support is provided for water resource management.

The present invention provides a molecular marker related to the water-power trait of pork and its application. The molecular marker is a g.152858710C>T polymorphic site on chromosome 6 of the pig reference genome Sscrofa11.1, specifically the 160th site of the nucleotide sequence shown in SEQ ID NO.1, and the Y of the site is C or T, with C / T polymorphism. The present invention also provides a method for screening pigs with excellent water-power, which can screen pigs at an early stage, effectively solving the problem that muscle drip loss in actual production cannot be screened by live measurement, reducing breeding costs, and the method has high accuracy, low detection costs, and can realize automated detection, and has high practical application value in pig breeding.

An anti-falling self-locking climbing operation ladder comprises a ladder body, the ladder body is a herringbone ladder, an anti-falling mooring device is arranged on the upper portion between two supporting legs of the herringbone ladder, the ladder body and the anti-falling mooring device are connected and fixed together through a lock catch, a locking device is arranged in the middle of the anti-falling mooring device, and the two supporting legs are locked when the herringbone ladder is unfolded. Self-alignment devices are arranged at the bottoms of two supporting legs of the herringbone ladder to adapt to low-lying and uneven ground; the anti-falling mooring device is arranged and is locked and fixed with a safety belt worn by an operator, so that the operator is prevented from falling during climbing operation; a locking device is arranged in the middle of the ladder body, so that the ladder body can be effectively prevented from being folded and toppled in the climbing operation process of an operator, the operation risk caused by the ladder body can be effectively prevented, the operation safety of the operator is further protected, and meanwhile, the ladder is conveniently folded, stored and carried after the operation is completed; and a self-alignment device is arranged at the bottom of the ladder body, so that the device is suitable for uneven ground, and the application range of the operation ladder is further widened.

The invention discloses a gravity dam face crack cause analysis method and device, relates to the field of water conservancy projects, and aims to improve the accuracy and efficiency of dam body crack cause analysis. The method comprises the following steps: establishing a nonlinear finite element model of a gravity dam body, and confirming a load applied by simulation; analyzing the stress influence of the downstream facade crack part of the dam body under the action of a single load, and analyzing the stress change rule of the downstream facade crack part of the dam body under the combined action of multiple loads; analyzing the influence of excessive highest temperature of concrete at the crack part of the downstream facade of the dam body on stress; analyzing the influence of reinforcing bars of a guide wall and a surface hole overflow surface on the stress of the crack part of the downstream facade of the dam body; and finally, comprehensively analyzing the cause of the dam body downstream facade crack. According to the method, the accuracy, reliability and efficiency of fracture cause analysis are improved.

The present invention provides a single crystal furnace thermal field insulation effect detection system based on thermal image analysis. Compared with the prior art, the present invention also includes a first thermal imager for monitoring the thermal distribution of the furnace side wall and generating thermal images, a second thermal imager for monitoring the thermal distribution of the furnace bottom and generating thermal images, a third thermal imager for monitoring the thermal distribution of the furnace top and generating thermal images, a cooling module for at least high temperature protection of the second thermal imager, a processing module for processing the image of the thermal distribution monitoring and imaging of the thermal imager, an evaluation module for evaluating the thermal field insulation effect of the single crystal furnace based on the image processed by the processing module, and an alarm module for triggering an alarm when the evaluation module determines that the thermal insulation effect of the single crystal furnace is lower than the expected thermal insulation effect. The present invention adopts multi-parameter comprehensive analysis and dynamic adaptive adjustment to greatly improve the accuracy, flexibility and industrial application value of monitoring the thermal field insulation performance of the single crystal furnace.

The present invention provides an automatic conversion method from a building 3ds Max geometric model to a Revit information model. Based on 3ds Max and Revit software platforms and using the secondary development of Maxscript and Revit API, an automatic conversion method from a building 3ds Max geometric model to a Revit information model is proposed through algorithms for component type recognition, component parameter classification, geometric information extraction, and parameter automatic modeling, so as to realize the automatic conversion from a three-dimensional geometric model to an information management model, reduce the repeated modeling work of the same building under different functional applications, improve the effective conversion method between the two types of models in the current construction industry, and lay a foundation for the versatility and scalability of building three-dimensional models.

The utility model relates to the technical field of rail transit, in particular to a split type logic control unit for a train vehicle. The split type logic control unit comprises a main control module, N input and output modules and a power supply, the main control module is connected with the power supply, the input and output modules are connected with the main control module, the number of the input and output modules is N (N is larger than or equal to 1), and each input and output module comprises an input channel and an output channel. And each input and output module is connected with the main control module through a controller area network (CAN) bus. According to the split type logic control unit, the main control module and the input and output module are separated, dynamic marshalling is supported, the access requirements of different vehicles can be met, and the space of vehicle-mounted equipment is saved; the split type design is adopted, problem points can be conveniently determined during later maintenance, replacement and maintenance can be carried out, and reference value is provided for popularization and application of an LCU system on a train.

The application provides a multi-joint coordinated control method of a self-reconfigurable star car, and relates to the technical field of star cars, and the method comprises the following steps: acquiring vehicle body state data, including the rotation angle of a driving rocker arm, the wheel base reduction caused by the rotation of the driving rocker arm, the angular velocity of the driving rocker arm and the rolling angular velocity of the wheel; establishing a multi-joint motion constraint model according to the vehicle body state data, including a vehicle body centroid position constraint model, a multi-joint action coordination constraint model and a vehicle body differential steering motion stability constraint model; and performing multi-joint motion control on the self-reconfigurable star car according to the multi-joint motion constraint model. By establishing the multi-joint motion constraint model on the three levels of the vehicle body centroid position, the multi-joint action coordination and the vehicle body differential steering motion stability, the motion coordinated control of the multi-joints in the vehicle body during the reconfiguration process is realized, so that the mechanical mode conversion function and the multi-motion mode switching function of the self-reconfigurable wheeled mobile star car are realized.

This invention provides a lithium carbonate price prediction method based on multimodal data collaborative driving, comprising the following steps: multimodal data source identification and data acquisition; multimodal data classification and standardization; personalized noise filtering and outlier correction of multimodal data; extraction of trend and correlation features from structured data; extraction of semantic and visual / speech features from unstructured data; extraction of key information and feature quantification from semi-structured data; weighted collaborative fusion and feature optimization of multimodal features; construction and training of a two-branch collaborative prediction model; model prediction and preliminary verification of prediction results; optimization and dynamic correction of prediction results; interpretability analysis and visualization of prediction results; and method effectiveness verification and continuous improvement. This method, based on multimodal data collaborative driving, addresses the pain points of existing lithium carbonate price prediction technologies, forming a comprehensive, high-precision, and highly practical prediction solution.

The present invention relates to a walking mechanism of an intelligent robot, comprising a frame, a gear box and a driving motor, wherein the gear box is arranged on the frame, the driving motor is arranged in the gear box, and the driving motor drives the walking wheels to walk through the gear box; a cutting assembly is symmetrically arranged on both sides of the frame, the cutting assembly is located between the two walking wheels on the same side, and the cutting assembly is used to clean the wheel axles on the walking wheels; the present invention arranges the cutting assembly on the frame, and utilizes the cutting assembly to move relative to the cutting assembly while walking, so as to cut off and clean the sundries wound on the wheel axles, thereby reducing the occurrence of the walking wheel jamming, playing a role in ensuring the normal walking of the robot and the safety of the people around, and improving the practical application value of the walking mechanism of the intelligent robot.

The application relates to the technical field of capacitance monitoring, and relates to an online monitoring system for a speed-regulating capacitor. The system comprises a capacitor parameter acquisition and cleaning module, a multi-dimensional space-time feature fusion module, an element correlation analysis module, a health evaluation module and a monitoring and early warning information mapping module. The rated parameter configuration and the operation state parameter of the speed-regulating capacitor are acquired and cleaned to obtain initial feature parameters and multi-source operation dynamic data. A multi-dimensional feature operation matrix of the speed-regulating capacitor is constructed. The real-time state information of the speed-regulating capacitor is subjected to element correlation analysis to obtain a key feature vector of the speed-regulating capacitor. The key feature vector is subjected to risk state evaluation to obtain a quantitative health index of the speed-regulating capacitor. The quantitative health index is mapped to historical operation and maintenance records to obtain monitoring and early warning information of the speed-regulating capacitor. The application can improve the efficiency of online monitoring of the speed-regulating capacitor.

A satellite remote sensing image power tower disaster damage identification method, system and related device, the method comprises collecting multi-source power tower satellite remote sensing image and constructing a data set; input the data set into the pre-constructed rotating target detection model, output the power tower spatial position and identify the orientation angle through the rotating target detection model; according to the spatial position of the power tower and the identified orientation angle, the maximum likelihood estimation model of the angle distribution of the power tower is constructed through angle specialization processing, and the maximum likelihood estimation model parameters are solved by using the expectation maximization algorithm to determine the orientation angle distribution of the power tower in the image to be measured; according to the orientation angle distribution of the power tower in the image to be measured, abnormal detection is carried out, and the objects exceeding the threshold range are screened out, that is, the power tower damaged by disaster. The present application can avoid the problem of sample scarcity, significantly reduce the data preparation threshold, realize full automation from data preprocessing to abnormal screening in the detection process, and effectively improve the disaster damage perception efficiency and accuracy.

The application belongs to the technical field of excavator working condition recognition, and discloses an excavator working condition recognition method and system based on whole machine information space-time fusion, which collects multi-dimensional running information of the excavator, takes data standardization and segmentation as pretreatment, inputs the obtained time sequence matrix into a constructed time attention module and a spatial attention module in parallel, respectively inputs the time sequence matrix into a time feature extraction network and a spatial feature extraction network, splices along a variable axis to obtain a space-time fusion feature space matrix, inputs the obtained space-time fusion feature space matrix into a designed working condition information learning module for processing to obtain a final working condition recognition result, and improves working condition classification precision; the application effectively combines space-time correlation of excavator sensing data, pays attention to intra-class and inter-class distance of classification features, enhances model recognition ability for continuous working conditions of the excavator, and improves recognition precision of action modes of the excavator.

An oil way switching device of a fan gear box is arranged to be of a hexahedron structure, the hexahedron structure is provided with a first butt joint face, the first butt joint face is communicated with an oil inlet of a filter through a first oil pipe, a right-angle face close to the first butt joint face is a third butt joint face, and the third butt joint face is communicated with an oil outlet of an oil pump through a second oil pipe. The first butt joint face communicates with the third butt joint face through a right-angle bend, a slope is arranged at the right-angle position of the right-angle bend, and a force unloading effect is generated on oil of an oil outlet of the oil pump. The oil pipe is ingenious in conception, through the right-angle bend design and slope unloading, impact force borne by the oil pipe is reduced, vibration of the oil pipe is reduced, and the stability of a gearbox filtering system is improved; the switching device is further provided with an exhaust hole used for exhausting gas in the gearbox. In an oil way system of the gearbox of the wind generating set, the switching device avoids bending of the oil pipe, reduces deformation and abrasion, improves operation reliability and power generation efficiency of the system, reduces maintenance cost, and is good in practical application effect and high in popularization value.

A guide pipe device of a chute tube riprap system comprises a guide pipe, the top of the guide pipe is communicated with a stone supply device, the bottom of the guide pipe is provided with a discharge port, a movable bottom plate is hinged to the discharge port, a push rod is fixed to the bottom of the movable bottom plate, and the push rod pushes the movable bottom plate to rotate in the discharge port to adjust the size of the discharge port and the stone throwing direction. The push rod communicates with a remote control unit which communicates with the monitoring module. The movable bottom plate is pushed by the push rod to rotate, so that the size of the discharge port, the stone throwing direction and the falling position and speed of the stone are adjusted, the utilization rate of the discharge port area of the guide pipe device is improved, the throwing and filling range is enlarged, and the frequency of moving the guide pipe device and the workload of later supplementary throwing or leveling are reduced; the remote control unit enables operation to be convenient, and working efficiency is improved; the device is simple in structure, convenient to operate, uniform in throwing and filling, suitable for riprap treatment work of the ocean wind turbine foundation, high in practical application value and good in economic benefit.

With the construction of a national novel power system and continuous deepening reformation of the power market, the operating pressure of thermal power enterprises is larger and larger, so that the fuel purchasing management level is improved, and the fuel purchasing cost control requirement is higher and higher; a more scientific and effective method for analyzing, researching and visually and vividly expressing key elements such as fuel purchase'quantity, quality and price ', 'supply, consumption and storage' and the like is urgently needed to be explored and established, practice is scientifically guided, enterprises are helped to reduce cost and increase benefits, and high-quality development of new kinetic energy is continuously gathered. On the basis, a'quantity, quality and price 'comparative analysis and'supply, consumption and storage' total balance histogram expression method 'for monthly fuel purchase of a thermal power enterprise is created by applying a digital thinking concept through long-term tracking research and repeated thinking and exploration on the basis of a logic association relationship among internal elements of the fuel cost of the enterprise and an internal operation mechanism. According to the method, all fuel purchase key elements are pioneered to be integrated into one graph, the method has high practical application value, and particularly, an authority, comprehensiveness and instantaneity fuel purchase comprehensive index visual expression and intelligent monitoring alarm'one graph 'expression method is provided for managers at all levels of thermal power enterprises.

The invention discloses an anti-loss image processing method for digital media, which is suitable for short video frame processing and comprises the following steps: S1, through multi-algorithm preprocessing, outputting a layered feature cache library and a preprocessing feature map containing a transition area; s2, a differential elastic compression strategy is adopted for the four types of image areas, and two-stage error correction and area fusion softening are matched; s3, repairing details through an attention codec and a multi-residual network, correcting dynamic artifacts and balancing light and shadow; s4, adaptively converting a color space, and scaling the resolution to adapt to different terminals; and S5, outputting the image after verification. The method gives consideration to compression efficiency and image quality, reduces transmission loss, improves the detail reduction degree of a complex scene, guarantees the consistency of cross-device display, and is suitable for a multi-digital media scene.

The invention discloses a method for predicting soil heavy metal content by using spectral data and social environment factor data, which comprises the following steps: S1, acquiring a training sample set, each training sample comprises position information (longitude and latitude, region codes or other attributes capable of reflecting spatial positions) and spectral data and social environment data corresponding to the sample; s2, data fusion: based on the position information or other associable sample attributes, carrying out matching fusion on the spectral data and the social environment data to obtain fusion feature data; social environment factors are fused to supplement key information of pollution sources and migration, and model prediction precision and operation stability are effectively improved. By means of a spectrum dimension reduction and embedding technology, the problem of high-dimensional data colinearity is relieved, and the over-fitting risk of the model is reduced; a cross validation method based on geographic grouping is adopted, so that the model validation process is closer to a cross-regional actual deployment scene; meanwhile, the feature contribution degree is output, and the practical application value in environment supervision work is improved.

The invention relates to the technical field of data processing, in particular to a multi-source heterogeneous data real-time processing method and system. The method comprises the following steps: acquiring multi-source heterogeneous original data, synchronously extracting attribute characteristics of the multi-source heterogeneous original data and collecting process state information; performing standardized cleaning processing on the multi-source heterogeneous original data based on the attribute features to obtain standardized heterogeneous data; embedding a priority guide identifier into high-information-density data in the standardized heterogeneous data, and performing symbiotic binding on the acquisition process state information and the standardized heterogeneous data to form heterogeneous standardized bound data; through full-process automatic processing, multi-source data compatibility, large model analysis and dynamic storage, efficient standard processing of the multi-source heterogeneous data is realized, so that the processing efficiency of the multi-source heterogeneous data is improved, and reliable data support is provided for information analysis and decision making.