1645 results about "Information repository" patented technology

The invention provides a management method and system for hazardous chemicals in a laboratory, and relates to the technical field of hazardous articles, and the method comprises the steps: obtaining hazardous article operation video data of an operator through an image collection device, extracting key node coordinates and skeleton movement track information, and mapping the information into standardized operation behavior sequence data; and a time sequence behavior evaluation model constructed based on a long and short term memory network is used to identify the non-standard operation fragments, a risk level coefficient is calculated in combination with a dangerous goods attribute information base, and a multi-dimensional evaluation report is generated. And according to the evaluation report, calling a correction strategy library to generate an improvement suggestion containing characters, videos and three-dimensional models, and pushing the improvement suggestion to an operator. By monitoring the behavior of the operator after executing the improvement suggestion and dynamically updating the risk score and the time sequence behavior evaluation model, the dynamic optimization of the evaluation standard is realized, and the safety of the laboratory hazardous chemical substance operation is effectively improved.

The invention relates to a work order material intelligent tracking and dynamic updating system based on multi-source data fusion. The system comprises an acquisition module, a tracking module, an updating module, a man-machine interaction module and a storage module, the acquisition module is used for acquiring work order information from a bill of material, scheduling information and inventory and supplier data, and constructing a material data model; the tracking module monitors material inventory, consumption and material shortage risks based on the model, and realizes automatic state updating and graphical path recording in combination with bar code recognition and ambiguity analysis; the updating module predicts material requirements through a machine learning algorithm, optimizes a distribution plan and outputs a dynamic report; the interaction module supports multi-format data import, unstructured field classification and interrupted operation control; the storage module ensures credible synchronization and tamper-proofing performance of data among different systems through a block chain technology; according to the invention, high-efficiency management and dynamic allocation of work order materials can be realized in an environment without an MES system, and the production transparency and the resource utilization efficiency are improved.

The invention relates to the technical field of management and control systems, in particular to a digital intelligence system applied to collaborative management and control of water-power engineering construction participating units, which comprises a project data management module covering water-power engineering construction full life cycle management, extracting multi-source information data from various subsystems, and constructing a project view and a project management information base; the project risk analysis module is used for constructing an intelligent risk analysis model for risk analysis and generating a dynamic evaluation result, a graded early warning notification and an auxiliary decision scheme; the project collaborative management module is used for processing graded early warning notification and auxiliary decision-making schemes by using a multi-layer perceptron model, and generating finalizing service achievements and management process records; and the project document management module is used for performing compliance automatic checking and processing on the electronic documents needing to be archived, and dynamically updating and optimizing the project management information base. Through the closed-loop management and control system, the cooperative management and control efficiency of water-power engineering construction participation units is improved.

The invention relates to the technical field of energy scheduling, and discloses a smart city energy dynamic scheduling system and method based on big data analysis, and the method comprises the following steps: the operation state of a transformer substation, the basic parameters of a charging pile and regional load prediction data are collected in real time, data cleaning and abnormal value filtering are carried out; constructing a complete power grid-charging facility dynamic information base; calculating the power supply margin of each region based on the capacity loss of the faulty transformer substation, establishing a weight scoring system of charging pile power adjustment in combination with the charging demand urgency, and determining the reduction or recovery priority of each charging load; and generating a charging pile power adjustment instruction through a multi-target optimization model, and iteratively correcting a power distribution scheme and generating a final scheduling instruction set by taking minimization of user satisfaction loss as a target while meeting the power grid capacity. According to the invention, by constructing a dynamic response mechanism and a multi-target collaborative optimization model, accurate and rapid regulation and control of the traffic load are realized in the scene of sudden power shortage of the power grid.

The invention discloses a dangerous rock falling motion feature prediction method based on multi-source data fusion, and belongs to the technical field of engineering geology. Comprising the steps of collecting dangerous rock multi-source data to construct a basic information base; processing dangerous rock multi-source data based on a CNN algorithm, identifying a dangerous rock contour and calculating geometric features; the dangerous rock multi-source data is processed through multiple algorithms, and the terrain is reconstructed to generate a digital elevation and terrain model; analyzing a vibration signal frequency spectrum, quantifying dangerous rock multi-source data features and determining a fusion weight; fusing the multi-source data of the dangerous rock to construct a three-dimensional real scene model and construct a physical and mechanical model; establishing a historical database, selecting a machine learning algorithm to construct a data driving model, and adopting an optimization algorithm to predict a rockfall movement track and state; and determining a two-dimensional simulation key section, establishing a two-dimensional numerical model, and dynamically simulating and calculating rockfall movement and rock-soil body response. According to the scheme, the defects in the aspects of dangerous rock falling motion feature prediction and protection design in the prior art are overcome, and the prediction accuracy and efficiency are improved.

The invention relates to the technical field of network security, in particular to a dynamic access blocking method based on zero trust. Comprising the following steps: step 1, collecting whole network flow data in real time in a bypass monitoring mode through a flow mirroring function of a network switch, performing deep packet inspection analysis on the collected original flow data, and extracting network flow characteristic parameters; 2, maintaining a dynamic identity information base; 3, performing real-time behavior analysis on each network session; 4, according to the risk assessment result and the real-time security context, generating a dynamic access control strategy based on a minimum permission principle; 5, implementing access control at the network execution point; and 6, continuously monitoring the network flow and the strategy execution effect, collecting feedback data, optimizing the risk assessment model and the strategy generation algorithm based on the feedback data, and forming closed-loop control. By dynamically updating the identity and asset information, the system can identify new assets or changes in real time, so that the adaptability and response capability of a network environment are improved.

The invention relates to a visual target tracking method utilizing time sequence prompting and track guiding, and discloses a visual target tracking method utilizing time sequence prompting and track guiding. Firstly, a historical information prompt network is provided, a Mama module is adopted as a feature extractor, fine-grained features of a predicted target are extracted from a current frame and stored in a historical information base, and comprehensive and accurate historical information prompts are provided for subsequent frames to assist target matching. Secondly, proposing a trajectory regression network, constructing a unified coordinate system by fully utilizing trajectory information of a target in a previous frame through a trajectory regression decoder, and assisting a current frame to complete prediction of a bounding box; by fusing the static appearance information and the dynamic trajectory clues, the matching precision and prediction robustness in the target tracking task can be effectively improved.

The invention provides an industrial Internet of Things security authentication method and system based on zero-knowledge proof, and relates to the technical field of security authentication, and the method comprises the steps: sending the identity information of terminal equipment to an authentication server through an edge computing node, generating an equipment certificate, and building an identity management information base; and the authentication server detects a computing resource occupancy rate of the terminal equipment according to the equipment authentication key, generates a zero-knowledge proof request, performs parallel verification, updates an equipment reputation score and predicts a next authentication session state. And selecting main and standby communication channels based on the prediction state, and triggering channel switching when the health degree is lower than a threshold value. And the authentication server determines a dynamic time slice allocation strategy according to the equipment reputation score, the service priority and the prediction state, and the edge computing node adaptively adjusts the size of the time slice to complete authentication request processing. According to the method, the authentication efficiency and security are improved, the computing resource consumption is reduced, and the system robustness is enhanced.

The invention relates to the technical field of chemical material detection, and discloses an AI-based chemical material detection information library retrieval and standard spectrum comparison system. The system comprises a data acquisition module, a spectrum preprocessing module, a feature extraction module, a retrieval matching module and a dynamic comparison module. The data acquisition module uses a multispectral sensor to acquire real-time spectral data covering ultraviolet, visible light and infrared bands, and the real-time spectral data is denoised by the spectrum preprocessing module. The feature extraction module adopts a deep residual convolutional network to extract spectral fingerprint feature vectors. The retrieval matching module inputs the feature vectors into a graph structure retrieval model to screen candidate standard spectrums. And the dynamic comparison module compares the candidate standard spectrums in multiple dimensions based on an improved quantum particle swarm optimization algorithm to obtain an optimal result. The system can accurately acquire and process spectral data, quickly retrieve and accurately compare standard spectrums, improve the efficiency and accuracy of chemical material detection, and have wide application prospects in the fields of chemical material research, production quality control and the like.

The invention provides a task scheduling method and system based on an unmanned aerial vehicle, electronic equipment and a storage medium, and relates to the field of task scheduling. The method comprises the following steps: acquiring tasks, resources and user behavior data from a user side and a cloud server through an information collection module, and storing the tasks, the resources and the user behavior data into an information base; the task evaluation module analyzes the data and generates a task value score; the scheduling strategy generation module formulates a preliminary execution scheme in combination with a preset rule, and optimizes through a reinforcement learning algorithm to obtain a dynamic optimal scheduling decision; the task redundancy analysis module is used for identifying mergeable redundant tasks and generating a report for further optimizing a scheduling decision; the dynamic priority adjustment module adjusts task priorities and resource allocation according to the real-time monitoring data; and the scheduling execution module is responsible for performing specific execution and generating a state report. The multi-module collaborative design realizes the intellectualization and adaptivity of task scheduling, and improves the utilization rate of system resources.

The invention relates to the technical field of artificial intelligence, in particular to a business contract intelligent review and risk quantification method and device, and the method comprises the steps: building and maintaining a business contract key term information base; obtaining and preprocessing a to-be-rechecked contract text; processing the text based on a bidirectional long-short term memory network and a conditional random field model, and extracting semantic representation; identifying key information through a multi-level attention mechanism; executing multi-label learning to classify and identify clause types and attributes; utilizing a dependency syntactic analysis technology to extract logical association and a responsibility chain among terms, and constructing a knowledge graph; identifying risk terms and generating risk prompts; business indexes are extracted, and risk open values are calculated; generating a rechecking report; the corresponding device comprises nine functional modules such as an information base management module, a text preprocessing module and a semantic representation extraction module, risk terms in a contract can be automatically recognized, a quantitative risk assessment result is provided, and contract auditing efficiency and accuracy are effectively improved.

The invention relates to the technical field of medicine information management, in particular to a traceability method and system based on a medicine consumable traceability code. The method comprises the following steps: acquiring medicine purchasing information data; generating a unique code for the number of medicine purchasing information so as to generate a medicine warehousing traceability code; performing drug information association on the drug purchase information data according to the drug warehousing traceability code to generate a drug warehousing associated traceability code; storing the medicine warehousing associated traceability code in an information base to generate a medicine warehousing traceability code information base; performing scanning access mode division on the medicine warehousing traceability code, and generating a medicine dispensing scanning request mode and a medicine returning scanning request mode; and performing drug splitting tracing on the drug warehousing tracing code in a drug dispensing scanning request mode to generate drug splitting tracing data. According to the invention, through full-process closed-loop management, data association enhancement, intelligent scheduling optimization and drug return tracing improvement, the efficiency and precision of the drug consumable traceability code tracing method are improved.

The invention discloses an intelligent production scheduling method and device for the equipment manufacturing industry, and relates to the technical field of production scheduling, and the method comprises the steps: building an equipment file information library, and recording the information of active equipment and standby equipment of a target production line; and constructing an equipment topology network according to the equipment file information base and the process information of the production line. Configuring a lightweight prediction model for each edge equipment node, and performing equipment health state analysis and short-term maintenance demand prediction in combination with real-time equipment operation data to obtain a preliminary evaluation state; and performing evaluation state correction through data sharing of edge equipment nodes to obtain a final evaluation result of the equipment. And according to an evaluation result and an equipment archive library, generating an equipment scheduling and maintenance decision, and realizing intelligent production scheduling. The technical problem that equipment maintenance and production scheduling are lack of flexibility and predictability in the prior art is solved, and the technical effects of improving the equipment utilization rate, optimizing production scheduling and ensuring efficient operation of a production line are achieved.

The invention belongs to the technical field of graph neural networks, and discloses a personalized education resource recommendation method and system based on a graph neural network, and the method comprises the steps: extracting first coding information of a learner and second coding information of a learning resource from a coding information base; inputting the first coding information and the second coding information into a multi-interest contrast graph attention network to obtain a first feature vector corresponding to the learner and a second feature vector corresponding to the learning resource; multiplying the first feature vector by the second feature vector to obtain the preference degree of the learner and the learning resources for educational resource recommendation; the multi-interest contrast graph attention network is obtained by training sample data of historical learning records and learning resources of the learner as a training set, and the multi-interest contrast graph attention network is used for capturing and understanding interest preferences of the learner by fusing various interest information of the learner and attribute information of the learning resources. The educational resource recommendation accuracy and interpretation can be improved.

The invention relates to a work order material intelligent tracking and dynamic updating system based on multi-source data fusion. The system comprises an acquisition module, a tracking module, an updating module, a man-machine interaction module and a storage module, the acquisition module is used for acquiring work order information from a bill of material, scheduling information and inventory and supplier data, and constructing a material data model; the tracking module monitors material inventory, consumption and material shortage risks based on the model, and realizes automatic state updating and graphical path recording in combination with bar code recognition and ambiguity analysis; the updating module predicts material requirements through a machine learning algorithm, optimizes a distribution plan and outputs a dynamic report; the interaction module supports multi-format data import, unstructured field classification and interrupted operation control; the storage module ensures credible synchronization and tamper-proofing performance of data among different systems through a block chain technology; according to the invention, high-efficiency management and dynamic allocation of work order materials can be realized in an environment without an MES system, and the production transparency and the resource utilization efficiency are improved.

The invention provides a rotary mechanical equipment fault identification method and device based on vibration data, and belongs to the field of vibration monitoring. The method comprises the following steps: acquiring a component information library of to-be-monitored rotary mechanical equipment; fault information corresponding to the component information base is determined, the fault characteristic frequency of each fault is calculated, and a fault characteristic frequency model corresponding to the component information base is established; collecting a vibration signal characteristic value of each component in the component information base in real time; extracting a vibration signal characteristic value, and matching the frequency domain characteristic value with the fault characteristic frequency based on a component information base and a fault characteristic frequency model to obtain a matching result; positioning an abnormal feature in the signal based on the time domain feature value and the geometric feature value; and identifying the fault type and degree of the mechanical equipment according to the matching result and the abnormal features. According to the mechanical equipment vibration monitoring data processing method and device, potential faults of the equipment can be found as soon as possible, and the equipment can be maintained in time.

The invention provides an SQL statement analysis method and device, equipment and a storage medium, and relates to the technical field of databases. According to the specific scheme, the method comprises the steps that SQL statements and metadata thereof are obtained, wherein the metadata comprises table names, column names and predicates of the SQL statements; target statistical information corresponding to the metadata is obtained from a preset statistical information base, and the target statistical information comprises table statistical information, column statistical information and index statistical information. And loading the statistical information to a test environment database to obtain a simulation database corresponding to the SQL statement. And based on the statistical information, determining an execution plan of the SQL statement, and executing the SQL statement in the simulation database according to the execution plan to obtain a statement analysis result. The method can effectively solve the problem of analysis distortion caused by the distribution difference of test and production environment data, and can obtain a more accurate SQL analysis result without complex data preparation.

The invention provides an intelligent number asking method for large model index query, and belongs to the field of natural language processing and database query. An auxiliary information base is constructed to store a database structure and historical question and answer examples, and key entities and fields are extracted by conducting structured format processing on natural language questions; a large language model guided by a small number of examples is utilized to generate an intermediate expression close to an SQL grammar and a plurality of SQL query candidates, and a consistency alignment mechanism is designed to verify candidate SQL in the aspects of field matching, aggregation functions, data tables and the like so as to screen out an optimal SQL query. Finally, the generated correct SQL and the corresponding question and answer pairs are fed back to the auxiliary information base, and self-learning enhancement is achieved. According to the method, under the condition that only a small number of training examples are needed, the accuracy and expandability of large language model text generation SQL query are improved.

The invention relates to the technical field of process scheme generation, and discloses an intelligent scheme reasoning generation method based on a process knowledge graph, and the method comprises the steps: firstly collecting multi-source process data, constructing a knowledge element extraction system, and outputting standardized knowledge entries through semantic analysis; establishing a process knowledge graph, and when a scheme reasoning demand is detected, positioning a target knowledge node through a logic association algorithm and generating an association relationship label; meanwhile, constructing a historical scheme case information base, and dynamically recording reasoning to generate a record; establishing a multi-dimensional weight configuration model, calculating a scheme matching degree score, and generating a recommendation priority sequence; solving an optimal scheme reasoning result by adopting an improved ant colony algorithm; and finally, outputting a result through the interactive verification platform, tracking and feeding back. The method improves the efficiency and quality of process scheme generation, and is suitable for process scheme formulation in industrial production.

The invention provides a computing power resource management and distribution method and system and a medium. The method comprises the following steps: integrating various computing power resources in a private network, establishing a computing power resource information base, analyzing a computing power resource request, establishing a service demand model, optimizing and matching a computing power resource configuration template, obtaining a computing power adaptation template, and establishing a service demand model; optimal computing power resource adaptation is carried out according to dynamic information of target computing power resources matched with the computing power adaptation template, isolation processing is carried out at the same time, monitored performance index data are processed, a load trend is predicted, a corresponding computing power resource adjustment strategy is obtained, and the computing power resources are optimized and expanded according to big data analysis; therefore, efficient utilization and elastic expansion of the computing power resources of the private network are realized by constructing the dynamic computing power resource pool and the resource scheduling model and monitoring, adjusting and optimizing an expansion mechanism, and the processing efficiency and security of big data services are remarkably improved.

A system for delivering contextual responses through dynamic integrations of digital information repositories with inquiries, comprising a computing device configured to collect a plurality of inquiries associated with an entity, access a plurality of digital information repositories in communication with the at least a processor to retrieve a plurality of entity records pertaining to the entity, extract one or more entity features from the plurality of inquiries and the plurality of entity records, implement a nested data storage structure to store the plurality of inquiries and the plurality of entity records based on the one or more entity features, generate, at one or more process modules interfaced with the computing device, one or more contextual responses upon receipt of an additional inquiry by traversing the nested data storage structure, and display the one or more contextual responses to the entity through a user interface at a display device.

The invention discloses an intelligent literature screening method and system based on zero sample voters. The method comprises the following steps: expanding a literature set based on seed literatures, constructing a classification system comprising a plurality of zero sample voters, screening literatures related to a target topic through a majority voting mechanism, and iteratively expanding the literatures to obtain more literatures related to the target topic. The zero sample voting device integrates subject term matching, language model pre-training, multi-large language model voting and a semantic embedding vector technology, adaptively determines a threshold value in combination with an improved binary search algorithm, and realizes high-precision classification without training data. The system supports parallel processing and intelligent API management, and the processing efficiency of a large-scale literature set is remarkably improved. The method is suitable for the fields of academic research, literature retrieval and the like, can quickly construct a large-scale high-correlation literature information base, and particularly meets the retrieval requirements of emerging technologies or interdisciplinary themes.

The invention discloses a multi-modal remote sensing data-based building target damage assessment method, which comprises the following steps of: constructing a text-guided two-stage building target classification network which comprises a CLIP text encoder, a Unet image encoder and a text image fusion decoder, inputting image text description information and pre-disaster / post-disaster dual-temporal remote sensing images, and carrying out multi-modal remote sensing data-based building target damage assessment on the pre-disaster / post-disaster dual-temporal remote sensing images; a CLIP text encoder module extracts text description information features, a Unet image encoder extracts image features of pre-disaster / post-disaster dual-phase remote sensing images, a text image fusion decoder fuses the text description information features and the image features, and building target damage is classified according to the fused features; a building target damage assessment module fusing building vector data and post-disaster remote sensing image data is constructed, the building vector data is converted into a bitmap of a pre-disaster remote sensing image by using the building vector data constructed by an official geographic information base or an OSM base, the bitmap is used as a pre-disaster image in a text-guided two-stage building target classification network BCL-Unet, and the pre-disaster remote sensing image is used as a pre-disaster remote sensing image. And carrying out building target damage grade classification by using a text-guided two-stage building target classification network BCL-Unet. According to the invention, a feasible technical scheme is provided for efficient detection of post-disaster building target damage.

The invention discloses a commodity receiving method and system based on digital twinning, belongs to the technical field of industrial internet and supply chain management, and aims to solve the technical problems of non-transparent information, tedious process, low efficiency, difficult inventory management and lack of effective monitoring in traditional commodity receiving. According to the technical scheme, data collection and twinborn modeling are carried out, specifically, digital and intelligent management of commodity receiving is achieved by building real-time mapping of a physical warehouse and a virtual twinborn body, multi-source data of material information, inventory data and position information of the physical warehouse are collected through Internet of Things equipment, and after cleaning processing is carried out, the real-time mapping of the physical warehouse and the virtual twinborn body is carried out; a three-dimensional modeling technology is adopted to construct a virtual twinborn body, and the consistency of the virtual twinborn body and a physical warehouse is ensured through a dynamic updating mechanism; real-time data processing and synchronization; intelligent receiving is realized; inventory monitoring and prediction; and performing user management and authority control.

The invention discloses a method, a device, equipment and a medium for determining an investment attracting enterprise in an industrial park, and the method comprises the steps: collecting original enterprise data related to the enterprise from a data source, and building an enterprise feature information library according to the original enterprise data; constructing an industrial chain atlas based on an industrial classification standard and the enterprise feature information base, and obtaining park enterprise data corresponding to a target industrial park; and determining a target enterprise corresponding to the target industrial park according to the park enterprise data, the industrial chain spectrum and the enterprise feature information base. Based on the technical scheme, the enterprise data of the plurality of data sources are acquired, the enterprise feature database is established, and the target enterprise is determined according to the enterprise data of the industrial park, so that the accuracy of determining the investment attracting enterprises is improved, and the efficiency of determining the investment attracting enterprises is improved.

The invention discloses an agricultural knowledge base construction method based on a large language model, relates to the field of agricultural knowledge base construction, and aims to solve the problems of dependence on a large amount of manpower, poor data quality, inaccurate search and the like in existing agricultural knowledge base construction. The method comprises the following steps: firstly, collecting agricultural knowledge texts from multiple channels such as professional books and academic papers, and segmenting the agricultural knowledge texts into smaller knowledge fragments to form an original knowledge fragment information base; then, a knowledge corpus set containing questions, abstracts and keywords is generated by designing interaction between a prompt project and the large language model; and then the corpora are converted into a vector form by using an NLP technology, a problem index vector library and an auxiliary index vector library are constructed, and the retrieval efficiency and accuracy are improved. And further automatically extracting keywords by using a large language model to form a structured keyword set. And finally, forming a comprehensive and structured agricultural knowledge base, and ensuring the quality and timeliness of the knowledge base through continuous dynamic optimization and user feedback.

The invention provides an intelligent question and answer method and device based on large model multi-source information fusion and electronic equipment, relates to the technical field of computers, in particular to the fields of big data, intelligent search and the like, and can be used for application scenes such as intelligent question and answer. According to the specific implementation scheme, pre-retrieval is conducted from a data table structure information base and a data table field information base according to a user problem, and a pre-retrieval result is obtained; retrieving from a business knowledge base, a business rule base and a question number template base according to the user question to obtain a knowledge enhancement result; according to the pre-retrieval result and the knowledge enhancement result, utilizing a query instruction generation model to obtain a query statement; and querying from the data table set according to the query instruction to generate an answer corresponding to the query word. The scheme can improve the professionality of intelligent questioning and answering, and is suitable for application scenes of various industries.

The invention relates to a multimodal transport cargo tracking method and device, equipment and a medium. According to the method, a standardized data set containing time-space attributes is generated by obtaining original circulation data of different transportation modes and hub nodes; on the basis of the timestamp continuity of the data set, constructing a cargo circulation association graph marked with transportation mode switching points; performing path feature clustering according to continuity identifiers in the map, and generating a standard path template library in combination with a geographic information library; matching and identifying a common path section through a real-time cargo track and a template library to form a cargo grouping tracking label; when the transportation duration in the group exceeds a threshold value, calculating an alternative path combination and outputting a track correction instruction; and generating a track synchronization instruction based on the instruction simulation resource topological relation, updating the association graph and outputting a dynamic track report. Continuous visual tracking of goods in the whole transportation process is achieved, the track path is automatically corrected under the abnormal working condition, and the timeliness and accuracy of logistics state feedback are improved.

The invention discloses an aquatic product processing production link temperature control method, which comprises the following steps: dynamically adjusting temperature control parameters in a processing link according to temperature quality related parameters, and if the temperature quality related parameter of a certain link displays that the influence weight of temperature fluctuation on a quality index is higher than a preset threshold value, judging that the temperature control parameters are not the temperature control parameters; if yes, the temperature tolerance range of the link is reduced, and an optimized temperature control parameter set is obtained; and constructing a problem tracing path according to the abnormal feedback data monitored in real time, automatically tracing back to the corresponding data segment in the integrated temperature information base aiming at the time point and the link label of the alarm record, and extracting the temperature change sequence before and after the occurrence of the abnormality to obtain a detailed abnormality tracing report.

The invention discloses a cultural heritage file multi-dimensional storage system, which relates to the field of cultural heritage digital protection and intelligent storage and comprises a data acquisition and processing module, a double-library management module, a multi-dimensional index retrieval engine, a security and convergence module and a backup and disaster recovery module. According to the method, structured texts and unstructured files are uniformly accessed through various interfaces, a special tool chain is adopted for format standardization, audios and videos are transcoded into an H.264 / AAC format through FFmpeg, images are subjected to resolution adjustment and compression through ImageMagick, plain texts are extracted from texts through ApacheTika and are converted into UTF-8 codes, standardized data are uniformly converted into an intermediate format, and the format of the intermediate format is converted into the intermediate format. According to the technical scheme, the method comprises the following steps of: standardizing input data by adopting a three-layer duplicate removal strategy, facilitating other modules to receive data, performing refined redundancy processing on the standardized input data by adopting a three-layer duplicate removal strategy, remarkably reducing storage redundancy, partitioning a cultural heritage data main library according to three layers of ''project type-medium type-age'', and partitioning an inheritor information library according to two levels of ''province-inheritor number prefix''.