134 results about "Data archival" patented technology

The invention relates to a copper-clad plate layering defect diagnosis method based on pattern recognition, and the method comprises the steps: forming a rich input sample set through spatial multi-channel imaging, variable illumination and time sequence synchronous sampling in order to solve the problems that the recognition capability of tiny layering defects is weak, and the recognition is easily influenced by noise and environment interference in the existing detection; according to the method, an attention mechanism and small sample discrimination are combined, high-confidence-coefficient defect identification is realized, region self-adaptive re-detection is further triggered in real time to reduce the missing detection risk, and finally defect distribution mapping is automatically generated and data archiving and traceability analysis are supported.

The invention relates to the technical field of bridge engineering construction, in particular to a bridge deck concrete flatness detection and correction method, which comprises the following steps: synchronously acquiring bridge deck point cloud, elevation and crack data through a three-dimensional laser scanner, a laser profiler and an ultrasonic sensor, and fusing to generate a three-dimensional digital model; defects such as local protrusions and wave deformation are recognized based on an intelligent analysis algorithm, causes are analyzed, and correction process parameters such as milling, cladding, grouting or ultrathin layer pouring are generated in a targeted mode; operation is executed through equipment such as a finish milling machine, closed-loop control is realized by combining real-time monitoring of a laser profiler, and finally, a traceable digital file is formed through laser detection, inspection and acceptance of an unmanned aerial vehicle and data archiving. By means of the method, the pass percent of the flatness of the bridge floor can be increased to 94% or above, the maximum height difference is controlled within 3 mm, the maintenance period of the bridge is prolonged, and the maintenance cost is reduced.

The invention relates to the technical field of power grid load prediction, in particular to a power grid load prediction and dynamic scheduling optimization method based on big data. Comprising the following steps: preprocessing power grid multi-source data; constructing an attention enhanced load prediction model, extracting time sequence load features through an LSTM network, and screening key influence factor features through a random forest; generating a layered constraint improved whale optimal scheduling scheme; real-time closed-loop adjustment is carried out; and data archiving and tracing. According to the method, the attention enhanced load prediction model is constructed, the time sequence load features are extracted by using the LSTM network, the key influence factor features are screened by using the random forest, the attention mechanism is introduced to highlight the power consumption peak period feature weight, and the Adam optimizer training and precision verification are combined, so that the load change rules of different periods can be more accurately captured, and the load prediction accuracy is improved. And the adaptability of the load prediction result and the actual power grid operation condition is improved.

The present disclosure proposes a liquid cooling system with leak protection and method for cooling liquid leak protection. The liquid cooling system is adapted to a server system including a rack and a server. The liquid cooling system includes: a cooling distribution unit (CDU), a liquid detector, a local leak management device and a central leak management device. The CDU distributes coolant to a cold plate disposed inside the server through a manifold and a water valve. The liquid detector is disposed inside the sever and configured to generate a server leakage event. The local leak management device is disposed inside the rack and configured to control the sever to shutdown after data archiving, close the water valve and output a server leak notification after receiving the event. The central leak management device controls the CDU to reduce a flow rate distributed to the cold plate based on the notification.

The invention discloses a multi-modal sensing edge intelligent monitoring system, which relates to the field of edge intelligent monitoring and comprises a multi-modal data acquisition module for acquiring multi-modal data; the edge intelligent processing module performs space-time registration, feature extraction and feature level fusion on the multi-modal data to generate a multi-modal feature vector; performing joint reasoning on the multi-modal feature vector by adopting an intelligent analysis model, outputting a structured analysis result, and generating a local early warning instruction when the danger level indicated by the structured analysis result exceeds a threshold value; and the central control module carries out early warning information issuing, data archiving and model iteration training according to the structured analysis result. Localized feature level fusion and intelligent analysis are carried out on multi-modal data through an edge intelligent processing module, and low-delay risk identification and early warning are realized. Meanwhile, continuous optimization and global situation awareness of the model are realized through a cloud edge coordination mechanism, and the defects of the traditional architecture in real-time performance, reliability and intelligent level are effectively overcome.

The invention relates to the technical field of education informatization, in particular to a multidisciplinary-oriented intelligent homework reviewing management platform and method, and the platform comprises the following steps: an image structure subdivision module, a behavior path recognition module, a rule execution monitoring module, an error cause structure labeling module, and a data label filing module. According to the method, stroke path analysis is combined with corner frequency and closed region detection, the handwritten character recognition precision is improved, the misjudgment rate of interdisciplinary symbol hybrid scenes is reduced, the structural expression ability of the problem solving process is enhanced by means of sequential construction of writing paths and logic nodes, and the problem solving efficiency is improved by combining parameter linkage of scoring frequency and scoring fluctuation. According to the method, the dynamic adaptive capacity of the scoring rule is optimized, the sequence comparison of a causal chain and knowledge nodes is adopted, the logic integrity of error cause positioning is improved, label clustering and distribution statistics are used, homework data archiving has the multi-dimensional screening and teaching backtracking capacity, and the collaborative efficiency of a homework reviewing system is promoted.

The invention discloses a hydroelectric generating set data acquisition and analysis method, system, equipment and medium, and belongs to the technical field of data acquisition and analysis, and the method comprises the steps: obtaining various original data of the operation of a hydroelectric generating set, and achieving the information collection of the set and the operation environment; performing multi-level structured modeling and node feature extraction on the acquired data by adopting a mode of combining a knowledge graph and a graph convolutional neural network, and analyzing an operation state and a future trend of a unit; according to a data analysis result, comparing a historical working condition with a scheduling task, judging whether the operation of the unit is in a reasonable interval, and triggering a corresponding regulation and control measure when the operation is abnormal; by monitoring the state and operation data of key equipment in real time, actual and reference parameters are compared, potential fault risks are identified, early warning information is generated, and data archiving and statistical analysis are carried out; and carrying out visual display on data acquisition, analysis, scheduling and early warning results. Collected data are effectively utilized, and scheduling decision and early warning maintenance are powerfully supported.

The invention relates to the technical field of ship data management, and particularly provides a ship inspection data intelligent management system and method based on structured storage, and the method comprises the following steps: obtaining a ship number, an inspection item and an inspection number, and constructing a data positioning layer; obtaining an inspection document, performing content analysis on the inspection document, and constructing a data structure layer; obtaining multi-source inspection data, associating the multimedia inspection data in the multi-source inspection data with the data content of the data structure layer, and constructing an association mapping layer; constructing a three-dimensional data storage structure based on the data positioning layer, the data structure layer and the association mapping layer; based on table cell index description, binding the multi-source inspection data to table cells with corresponding semantics, and performing cell data fusion to obtain a plurality of assembly cells; and dynamically reconstructing the inspection document based on all the assembly cells to obtain an interactive inspection document, so that the structural data storage of the inspection data is realized, and the inspection efficiency and the traceability positioning efficiency after data archiving are improved.

The invention relates to the technical field of numerical control machine tool monitoring, in particular to a monitoring method and a monitoring system for an intelligent machining machine tool, and the method comprises the steps: collecting static data information of the numerical control machine tool and dynamic data information in an operation process according to a plurality of collection devices arranged on the machine tool, and summarizing the static data information and the dynamic data information into multi-source data, obtaining state data of the numerical control machine tool; constructing a digital twin model corresponding to the numerical control machine tool based on a digital twin system, and transmitting the state data to the digital twin model, so that the digital twin model is matched with the actual state of the machine tool; according to the method, real-time collection of multivariate data signals is carried out, accurate and comprehensive machine tool operation state information is further obtained in real time, and the recognition and prediction precision of the machine tool health state is improved by constructing a data twin model, carrying out data archiving and optimized storage, constructing machine tool health state classification and establishing an incidence relation between degradation characteristics and the health state; the production accident rate is reduced.

The application discloses a block data archiving method and device for a blockchain and a medium. The method comprises the following steps: determining a block start number and a block end number corresponding to to-be-archived block data, constructing a to-be-executed archiving application through a private key of a to-be-archived blockchain node corresponding to the to-be-archived block data; publishing the to-be-executed archiving application on a chain, auditing the to-be-executed archiving application by an archiving smart contract in the blockchain, and publishing an archiving audit result; in the case that the audit is passed, packaging the to-be-archived block data by the to-be-archived blockchain node to generate a to-be-archived block data file and uploading the to-be-archived block data file to a preset storage area; after receiving a message notification of successful uploading, constructing a successful archiving notification based on an archiving application transaction Hash corresponding to the to-be-executed archiving application and a storage address of the to-be-archived block data file contained in the message notification, and publishing the successful archiving notification. The application avoids the risk of data loss or leakage and ensures that the archiving behavior is traceable.

The invention relates to the technical field of supply chain management, in particular to a supply chain multi-source heterogeneous data integrated filing and management method, which comprises the following steps of: 1, acquiring multi-source heterogeneous data; 2, data preprocessing; step 3, carrying out data normalization; step 4, semantic annotation: semantic tags are added to the normalized data set, the semantic annotation comprises ontology construction, tag generation and context association, the ontology construction is based on a supply chain domain ontology, the tag generation adopts a rule matching or machine learning method, and the context association associates data with a supply chain context; step 5, data archiving; step 6, index construction; and 7, data management: performing continuous management on the archived data. Through the combination of semantic annotation and dynamic indexing, the data access efficiency can be ensured, and meanwhile, the querizability and interpretability of the data can be improved.

A dynamic cadastral data updating and management method based on a space-time sequence specifically comprises the following steps: S1, collecting dynamic cadastral data, preprocessing the dynamic cadastral data, and outputting a standardized space-time sequence database; s2, performing dynamic modeling on the standardized space-time sequence database, adjusting granularity, and outputting an optimized space-time model; s3, performing space-time sequence comparison by utilizing the optimized space-time model, automatically identifying data change, and outputting a cadastre change incremental data set; s4, constructing a relation chain according to the change incremental data set, writing change data into a current potential library, and archiving historical data into a difference file library; s5, performing space-time consistency verification and efficiency optimization on the current potential library and the difference file library, and outputting a quality inspection passing library; and S6, performing service packaging on the quality inspection passing library, and deploying the quality inspection passing library to a cloud service platform. The method dynamically adapts to change features of different regions, reduces storage cost and update time consumption, improves verification efficiency, and provides dynamically updated spatial basic data support for smart city construction.

The invention relates to the technical field of evaluation, and particularly discloses an RLHF-based AI evaluation auxiliary system, and the system comprises a field evaluation module which is used for recording key data of each evaluation item, and carrying out the data archiving and processing, and obtaining field evaluation data; the unit evaluation module is used for processing and feeding back based on the evaluation text; the level evaluation analysis module is used for acquiring a plurality of unit evaluation records, performing classification analysis according to the safety control level to which the unit evaluation records belong, and performing evaluation feedback on each level; the overall evaluation module is used for carrying out feedback, modification and adoption or regeneration based on overall evaluation result analysis; the report compiling module is used for combining the overall evaluation results to generate an evaluation report first draft and auditing the evaluation report first draft; and the report auditing module is used for carrying out learning adjustment based on an RLHF mechanism to generate an evaluation report, strengthening the precision and controllability of a model generation behavior under the RLHF mechanism, reversely optimizing an AI behavior through the RLHF mechanism, and improving the accuracy of the AI model in a subsequent evaluation process.

The invention relates to an astronomical observation data archiving method and system, the method is applied to the astronomical observation data archiving system, the astronomical observation data archiving system comprises a first server, a second server and a third server, the first server is deployed in a field station, the third server is deployed in a data center, and the second server is deployed in the data center. The first server and the third server are both connected with the second server, and the method comprises the steps that astronomical observation data to be filed are divided into a plurality of data blocks, the first server packages each data block into an AMQP message and then sends the AMQP message to the second server, the second server forwards the AMQP message to a queue in the second server, and the AMQP message is sent to the third server; and pushing the AMQP message in the queue to a third server subscribing the queue so as to realize transmission of the astronomical observation data to be tested from the first server to the third server.

The invention discloses a power grid operation and maintenance service management method based on an informatization means, and belongs to the field of network operation and maintenance, and the method comprises the steps: S1, building power grid operation and maintenance service integrated data information, and generating a multi-source data flow with a timestamp; s2, constructing an operation inspection operation relation model of the hierarchical knowledge graph, and carrying out semantic modeling on equipment, personnel and operation scenes to realize task and risk matching identification; s3, executing task dynamic assignment and resource reconstruction, and performing priority optimization and cross-region scheduling; s4, carrying out digital twin operation inspection site virtual replication, synchronously mapping sensing data and operation images, and realizing track, working condition and risk node visualization; s5, performing abnormal working condition closed-loop management, pushing abnormal data through event triggering, and forming iterative optimization in combination with historical feedback; and S6, forming comprehensive performance evaluation and data archiving, and uniformly incorporating task execution, risk response and equipment maintenance into an intelligent archiving system. The method has the beneficial effects that the power grid operation inspection efficiency, accuracy and traceability are improved.

This invention belongs to the field of Chinese medicinal material acceptance technology, specifically a standardized acceptance method and electronic system for the handover process of Chinese medicinal material storage and transportation. The specific steps of this standardized acceptance method are as follows: unified data standards and cross-process equipment adaptation, real-time data management during transportation, on-site handover acceptance, post-handover data archiving and cross-process linkage. This application achieves data connectivity, technical adaptation and accountability in the handover acceptance, transportation and storage processes by constructing a standardized system covering the entire process of data collection, real-time management, on-site verification, joint maintenance and traceability archiving. This completely solves the problems of data fragmentation, cross-process disconnection and difficulty in accountability in the existing technology.

The present application belongs to the technical field of robot control, and specifically discloses a railway inspection robot laser radar anti-collision and remote video linkage control method, aiming to solve the problems of low inspection efficiency, low sensor fusion degree and missing linkage mechanism in industrial scenarios. The method comprises: performing benchmark calibration and entering inspection line data through system initialization and parameter configuration; acquiring point cloud data by high-frequency dynamic scanning using a laser radar, and real-time matching of multi-level early warning thresholds to trigger linkage response; the power control unit executes brake or speed reduction operation according to the instruction, and resets the mode to resume work after confirming safety; the system also archives the full data of linkage events to support continuous optimization of the inspection plan. Through the deep coupling linkage of the laser radar and the video imaging module, the present application can realize all-weather, high-precision and high-safety autonomous operation of the inspection robot in complex high-dynamic environments, significantly improving the inspection efficiency and risk control level.

The application provides a data asset sharing method and system, and relates to the technical field of data asset management.The data asset sharing method comprises the following steps: obtaining completed item data of a project in progress; performing data asset screening on the completed item data to obtain asset data; obtaining an archiving unit of the asset data according to the asset type of the asset data and the storage conditions of each unit; archiving the asset data according to the archiving unit; creating a search formula according to the definition word, the asset type and the archiving unit of the asset data when the asset data is archived; performing search analysis on the asset data through the search formula according to sharing request information to obtain an analysis result; and calling corresponding asset data according to the analysis result.The sharing method and system can effectively integrate and share important asset data of an enterprise, improve the project management efficiency of the enterprise and reduce the project cost.

The invention relates to the technical field of data processing, in particular to a handwritten font recognition and storage method for cold data archiving management. The method comprises the following steps: dividing a single font image into an intrinsic structure main body area and a style induction offset area based on the number of effective pixel points in each projection direction; determining a style influence degree according to the main body area and the offset area; clustering the single font images according to the style influence degree to form a cluster; according to the number of the single-font images in the clustering cluster and the style influence degree numerical range, the aggregation degree of the clustering cluster is determined; determining font structure ambiguity according to aggregation degree difference characteristics among the clusters; determining the overall font ambiguity by combining the font structure ambiguity; inputting the text image and the overall font ambiguity into a pre-training style correction model, and outputting a corrected text image; according to the method, the OCR algorithm is adopted to recognize and correct the handwritten fonts in the text image and store the handwritten fonts, so that the false recognition rate of handwritten font recognition is effectively reduced.

The application discloses a kind of low-voltage distribution cabinet arc fault whole cycle management and control methods, belong to low-voltage distribution and industrial internet of things technical field, solve the defects of existing technology early warning lag, false alarm rate is high, emergency disposal network failure, no whole cycle closed-loop management and control.This method uses the double redundancy architecture of edge local priority and cloud platform bottom, including six steps of preposition system configuration and grid responsibility binding, multi-source data acquisition and edge preprocessing, super-early three-stage early warning and preposition intervention, fatal arc fault cloud edge collaborative emergency disposal, fault closed-loop operation and management and control, whole cycle data archiving and model iteration optimization, supporting working condition feature distinguishing rule and multi-source composite verification logic.The application can realize arc fault early identification for 1 to 3 weeks, false alarm rate is controlled within 0.1%, completes local emergency disposal within 100ms and network failure is not invalid, forms arc fault whole life cycle closed-loop management and control, and greatly reduces electrical fire and equipment damage risk.

The application relates to a data archiving method, a system, an electronic device and a storage medium, wherein the data archiving method comprises the following steps: obtaining to-be-archived data after database and table division and shard element information of the to-be-archived data; inserting a streaming service into the to-be-archived data, performing streaming processing on the to-be-archived data according to at least the shard element information and unique identifier information corresponding to the streaming service, obtaining first synchronization data; creating a distributed database according to the shard element information and synchronizing the first synchronization data to the distributed database for distributed storage, obtaining second synchronization data; and taking the second synchronization data as a data archiving result. Through the application, the problem that archived data cannot be quickly queried and the high maintenance cost are solved, and quick storage and query of data archiving results are realized.

The invention provides a glass batching data filing management interaction method based on multi-stack dynamic allocation, and relates to the technical field of glass production data management. A dynamic in-stack / out-stack mechanism corresponding to a special calibration stack and a multi-class process parameter stack is respectively adopted, so that classified isolated storage and ordered archiving of calibration data and batching process parameters are realized; according to the method, the real-time performance and reliability of data writing and archiving are improved, a prompt mechanism can be actively triggered to guide user intervention in an abnormal state, and meanwhile, efficient retrieval and archiving result exporting according to multi-dimensional conditions are supported, so that the data integrity, traceability and man-machine interaction efficiency in the glass batching process are remarkably enhanced.

The invention discloses a multi-field coupling robot self-adaptive inspection method and system based on a creative technology stack, and the method comprises the steps: reading a fixed historical parameter set in a previous inspection period, collecting the environment data of a current operation region, generating a control parameter set, calling thermal control and propulsion parameters in the control parameter set, and outputting real-time flow field data and attitude control quantity. Based on real-time flow field data and attitude control quantity, navigation speed and propulsive power are optimized, energy consumption data and path tracking data are synchronously recorded, a real-time signal-to-noise ratio is calculated by using environment real-time parameters, communication states are adjusted by combining communication bandwidth parameters in a control parameter set, and the environment real-time parameters and communication state data are synchronously received. Summarizing the data to complete data archiving; through heat-flow coupling control and multi-mode sensing fusion and environment adaptive communication and parameter iterative optimization cooperation, stable inspection in a complex flow field, zero-visibility defect identification and reliable return of noisy environment key data are realized.

The invention relates to a data archiving method and device, a storage medium and electronic equipment, and relates to the technical field of power transaction and data archiving, and the method comprises the steps: firstly obtaining archiving data corresponding to different business systems and archiving indexes corresponding to the archiving data; in response to a received data archiving instruction corresponding to the archived data, verifying the archived data according to the archiving index, and obtaining a data verification result corresponding to the archived data; and if it is determined that the data verification result is that the data verification is passed, executing an archiving operation of the archived data according to the archiving index, and generating an archiving verification result of the archived data. Through the scheme of the invention, the data archiving service can be provided for different business systems, the archiving index verification of the archived data is realized, the conditions of incomplete archiving, missing archived data, wrong archiving data and the like are reduced, and the data archiving quality is further improved.

The invention discloses a railway external environment patrol method and system based on an unmanned aerial vehicle, and the method comprises the steps: automatically planning an optimal patrol route of the unmanned aerial vehicle based on a railway electronic map and a hidden danger hotspot library; collecting along-line multi-dimensional data through a carried multi-sensor module; the data is returned to a ground center or an edge node in real time by using a 5G / 4G network; an AI algorithm based on deep learning is adopted to perform intelligent analysis on the data, various hidden dangers such as illegal construction, dangerous tree invasion and geological disasters are automatically identified, and accurate measurement and change detection are performed; then early warning information containing accurate geographic coordinates is automatically generated and pushed to a related person in charge to form a disposal closed loop; all data are archived and an analysis report can be generated. According to the invention, full-process automation and intelligentization of inspection operation are realized, the system has the remarkable advantages of high efficiency, high precision, low cost and high safety, and the discovery and disposal efficiency of potential safety hazards of the external environment of the railway can be greatly improved.

This invention discloses a distributed photovoltaic distribution network energy storage scheduling method based on cloud-edge collaboration, belonging to the field of cloud-edge collaboration technology. This method includes: S1, performing time alignment, boundary verification, and standardization processing on operational boundary data and field operational data; S2, performing cloud-based plan support analysis to generate cloud-based planned charging and discharging power and direction; S3, performing edge-end voltage flow adaptation analysis to generate adaptation markers; S4, performing edge-end correction acceptance analysis to generate corrected charging and discharging power and cloud recalculation requests; and S5, executing scheduling instructions, sending back edge-end execution receipts, and archiving data. This method solves the problem that existing methods, which focus on global power balance and energy storage access point charge state constraints, lack synchronous adaptation judgment of energy storage actions, local node voltage boundaries, and feeder flow direction before edge-end execution, easily leading to cloud-based plans being feasible but edge-end local voltage states not being compatible.

The invention provides a configurable automatic data archiving method and system based on a storage process, and belongs to the technical field of database data life cycle management.The method comprises the following processes that firstly, an archiving task is initialized, and a configuration table archiving rule is loaded; automatically judging and creating an archiving history table; secondly, dynamically calculating an archiving reference date; archiving conditions are generated, and data archiving and source table cleaning are executed in batches; abnormities are processed through log and transaction control, and data archiving and source table cleaning are completed; and finally, task circulation and exception handling are performed, and configurable and automatic historical data management is realized. The method solves the problems that an existing data archiving scheme is high in hard coding dependency, lacks unified configuration, is high in batch processing risk, is weak in fault tolerance and traceability, and is disordered in historical table management, is suitable for batch backup and archiving of historical data and source table cleaning in a core business system, guarantees the performance of a core table, and meets the requirements of data retention compliance.

The present invention relates to a computing and archiving research environment that uses multi-data integration between different information or data with high requirements for data storage and high performance computing. The invention provides a platform for easy storage, analysis and sharing of different scientific data by providing different service combinations such as high performance computing (HPC), scientific clouds and data archiving.

The invention provides an urban river channel digital management method. The method comprises the following steps: S1, acquiring heterogeneous data through equipment and uploading the heterogeneous data to a data center; s2, the data center carries out standardization processing on the heterogeneous data to obtain standardized heterogeneous data; s3, constructing a virtual asset model of the river channel according to the GIS engine, and binding the standardized heterogeneous data to the virtual asset model by the GIS engine; s4, analyzing the standardized heterogeneous data by using an AI analysis engine, identifying and positioning river channel diseases, and generating a structured disease record; s5, generating a maintenance work order according to the disease record and the corresponding responsibility unit, and pushing the maintenance work order to maintenance personnel; s6, after the maintenance work order is completed, data of the disease records are archived to a database; and S7, synchronizing the data of the disease record to the virtual asset model, and carrying out quantitative decision and supervision, so that the discovery efficiency, the disposal efficiency and the accuracy of the river channel disease are remarkably improved.

The present application relates to the technical field of industrial vision detection and intelligent manufacturing, and in particular provides a papermaking wood grading evaluation method based on 3D vision and high-resolution imaging fusion. The method comprises raw material feeding and pre-screening, and collecting front and back multi-modal information to realize heterogeneous data archiving, establish an initial digital archive of the target physical form; camera alignment and foreground segmentation are performed, and material categories and associated metadata are identified to obtain offline grading evaluation. Through hardware synchronization and algorithm cooperation, the method realizes automatic collection of front and back of wood, calculation of three-dimensional geometric parameters, material classification and grading evaluation, significantly improving detection accuracy, reviewability and automation level.