108 results about "Datafication" patented technology

The invention provides a machined part logistics transportation path planning management system, and relates to the technical field of data processing, and the system is used for reconstructing the spatial relationship of path nodes, splitting and combining the arrangement sequence and time sequence characteristics of the path nodes, and storing the path nodes in a database; calculating a dynamic quantitative index of a preset transportation path between a time dimension and a resource occupation dimension to obtain a time sequence tensor factor, identifying an offset track of a machined part between the preset transportation path and an actual transportation path, extracting transportation behavior characteristics between path nodes, calculating a time sequence disturbance degree of transportation path offset to a scheduling plan, and obtaining a scheduling result; the method comprises the steps of obtaining a scheduling influence coefficient, correcting a preset transportation path, adjusting the passing sequence and priority of path nodes, synchronously updating scheduling information, and carrying out linkage matching on path change information and a workshop plan to obtain linkage scheduling data. According to the invention, the whole-course data modeling and dynamic scheduling management of the transportation process of the workpieces are realized.

The invention relates to the technical field of space planning analysis, in particular to a land space planning analysis system based on big data, which comprises a boundary discrimination module, a purpose offset module, a coordination analysis module, a change identification module and an ownership selection module. According to the method, an efficient spatial information circulation and feedback chain is constructed by combining boundary space structure extraction, use weight distribution mapping, population use collaborative feature analysis, resource configuration change trend tracking and an ownership affiliation unit optimization mechanism; global linkage judgment of core elements such as spatial forms, purposes, population and resources in a complex territorial structure is achieved, the whole-course quantitative perception ability of planning and management is enhanced, land purpose optimization, resource allocation dynamic balance and accurate orientation of ownership relations are promoted, data transparency of a space governance link and continuity of a decision closed loop are improved, and the space governance efficiency is improved. Flexible adjustment and fine management of a spatial pattern in a multi-dimensional scene are supported, and the datamation and intelligence level of a territorial space treatment system is enhanced.

The invention provides a three-dimensional sedimentary facies modeling method and device based on planar graph constraint, and the method comprises the steps: loading a sedimentary facies graph and a thickness graph to a three-dimensional space, projecting a planar graph to an oil reservoir grid through space coordinate transformation, and coarsening the planar graph into an oil reservoir grid surface attribute; establishing a rapid sedimentary facies model by utilizing the plane sedimentary facies diagram, and establishing lithologic probability volume data by utilizing the plane thickness diagram and through coKriging interpolation; and the logging sedimentary facies data serve as hard data, the rapid sedimentary facies model serves as spatial constraint, the probability body serves as trend constraint, and a sequential indication simulation algorithm is utilized to generate the sedimentary facies model. According to the three-dimensional sedimentary facies modeling scheme based on the planar graph constraint provided by the invention, information such as the logging facies, the planar facies and the thickness graph is comprehensively utilized, the understanding of geologists can be introduced between wells, the problems of mathematics and datamation of a conventional method are solved, and the precision of a sedimentary facies model is improved.

The invention discloses a real-time acupuncture point mapping method based on a bone degree deflection method and a human body posture key point model, and relates to the technical field of traditional Chinese medicine digitization. According to the real-time acupuncture point mapping method based on the bone degree discount method and the human body posture key point model, acupuncture point coordinates are calculated by combining the standard bone degree discount proportion with the objective distance between the human body posture key points, traditional empirical positioning is converted into datamation and standardization calculation, personal errors are reduced, BMI parameters are introduced to formulate a BMI interval correction table, and the real-time acupuncture point mapping accuracy is improved. The three-dimensional coordinates of the acupoints are accurately corrected through the coordinate correction coefficient, it is ensured that acupoint mapping of users of different body types is highly matched with the actual subcutaneous position, the purpose of improving the acupoint positioning effect is achieved, a corresponding acupoint mapping template is selected according to the judgment result of the human body orientation, a real-time AR picture is generated in an AR superposition rendering mode, and the user experience is improved. And real-time mapping of human body acupuncture points is realized.

The invention discloses an old building reconstruction design method and system based on BIM and real-time monitoring, and relates to the field of old building reconstruction design, and the technical scheme is that the method comprises the steps: constructing a three-dimensional observation environment, carrying out the multi-stage three-dimensional collection of a to-be-reconstructed building, and obtaining observation data with unified coordinates and time stamps; performing stage comparative analysis on the observation data, and performing space matching and data integration under BIM constraint to form three-dimensional time sequence information oriented to each building component; based on the three-dimensional time sequence information, establishing a historical memory model under component identifiers of the BIM model, and extracting a time sequence evolution rule of deviation and defects of each component; and according to a time sequence evolution rule, establishing a transformation evaluation model, comprehensively analyzing the safety, durability and use functions of each component of the building, and generating a transformation design scheme. The method has the beneficial effects that through multi-period three-dimensional acquisition and BIM fusion analysis, the whole-process datamation and intelligent management of old buildings from state monitoring to reconstruction design is realized.

The invention provides an enterprise data analysis method, a computer readable storage medium and terminal equipment, and relates to the technical field of electric digital data processing, and the method specifically comprises the steps: obtaining enterprise economic production abnormal data and related financial statement data; marking abnormal events related to process change and equipment maintenance cost to form a first screening set, and extracting additional cost data and economic loss indexes; comprehensively analyzing the cost to generate an initial loss coefficient, and collecting a benefit evaluation index to generate an initial profit coefficient; and comparing and analyzing the two, calculating a loss adjustment index, and comparing the loss adjustment index with a preset threshold value to execute a corresponding strategy. Through the three-layer system of'initial loss coefficient-initial profit coefficient-loss adjustment index ', the economic loss and profit increase degree of the abnormal event is quantified, full-dimension profit and loss comprehensive balance is realized, a datamation basis is provided for decision making of enterprise process change, equipment maintenance and the like, and fine management of economic activities is facilitated.

The invention discloses an intelligent management system and method for rubber production, and the system comprises a system user interface, a business process management module, a yield calculation service center and a resource library, and the data output end of the system user interface is connected with the data input end of the business process management module. The data output end of the business process management module is connected with the data input end of the yield calculation service center, the data output end of the yield calculation service center is connected with the data input end of the system user interface, and the yield calculation service center comprises an incoming material management module, a discharging management module, a yield calculation module and a production progress management module. And the yield calculation module is in data connection with the resource library. The invention aims to reduce the dependence on a large amount of manpower, reduce the labor cost, simplify the management process and improve the production efficiency; through real-time automatic data acquisition, storage and analysis, a complete production data chain is established, and an enterprise is helped to carry out accurate monitoring and datamation management on each link from raw materials to finished products.

The application discloses an elevator full-data simulation test system, and relates to the technical field of elevator testing.The scheme comprises a multi-source data acquisition module, a digital twin modeling module, a full-scene simulation test module, a data processing and analysis module, a closed-loop optimization module and a terminal interaction module.The application realizes full-cycle multi-dimensional data coverage of the elevator, integrates mechanical, electrical, environmental, personnel and fault data, improves the completeness of test data, constructs a full-dimensional model based on digital twin technology, realizes multi-element coupling simulation, simulates various working conditions, fits actual operating conditions, iterates the simulation model, outputs optimization schemes, improves test efficiency and optimization effect, supports custom parameters, meets the test requirements of various types of elevators, does not require a physical test platform, greatly reduces test costs and shortens the test cycle, and avoids safety risks in physical tests.

The invention relates to the technical field of water pollution treatment, and discloses a multi-scale coupled drainage basin high-resolution pollution source emission list construction method, which comprises the following steps: acquiring multi-scale administrative division statistical data, and preprocessing the multi-scale administrative division statistical data to obtain multi-scale pollution source basic data; converting the basic data space of the multi-scale pollution source into gridding space distribution data of each pollution source in a target drainage basin range by utilizing a space mapping relation between an administrative scale and a gridding drainage basin scale; calculating multi-source pollution emission data based on the gridding spatial distribution data of each pollution source in the target drainage basin range; and superposing the multi-source pollution emission data on the watershed grid scale, and constructing a watershed high-resolution pollution source emission list. According to the method, accurate description of drainage basin pollution source emission and identification of key pollution units are realized, and the scientization, refinement and datamation levels of regional water environment treatment can be effectively improved.

The invention discloses an operating system based on industrial internet equipment control, which comprises an equipment information acquisition module used for acquiring basic information and fault history of equipment; an equipment fault confirmation module and a training method selection module which are used for systematically collecting basic information and fault history of equipment so as to provide accurate data support for formulating a personalized training scheme; proper training steps are automatically selected, so that the safety and pertinence of a training scheme are ensured; the training method selection module intelligently recommends the most appropriate training method according to the specific condition of the equipment, and dynamically adjusts the training intensity through the training intensity calculation unit, so that the training is more scientific and reasonable; the virtual reality training module utilizes an immersive environment and interactive training to improve the participation degree and the training effect of the equipment, and the training effect evaluation unit unifies the judgment standard through a datamation evaluation method, does not depend on experience purely, and effectively reduces the misjudgment rate.

The invention discloses an intelligent analysis and model self-iteration psychological sand table auxiliary system, which is characterized by comprising a data acquisition device, a model training platform, a session analysis platform and a back-end server to realize intelligent psychological sand table auxiliary analysis. The data acquisition device inputs acquired sand tool multi-angle images into the model training platform to train a target detection model; and the back-end server maps the output category ID of the target detection model with a preset sandy tool psychological significance knowledge base, and generates a comprehensive analysis report for reference of a consultant by using a task-supervised fine-tuned large language model. Compared with the prior art, the method has the advantages that AI recognition results and psychological knowledge are deeply fused, real-time intelligent recognition and analysis are achieved, and an end-to-end closed-loop solution from sand tool datamation, model training, sand table process panoramic recording to analysis report generation is provided for application in psychological sand table treatment auxiliary scenes.

The invention relates to the technical field of project datamation management, and discloses an engineering project digital asset management platform. The engineering project digital asset management platform comprises an acquisition module which is connected with an enterprise database to acquire project data of an enterprise; the classification module establishes a first item set and a second item set for the item data according to the item attributes and the work types; the analysis module determines the predicted working duration of each working type by using the data in the second project set; the uploading module is used for acquiring and transmitting a to-be-uploaded project official document; and the display module not only displays data in the first item set and the second item set according to the item attribute and the working type of the selected target, but also is used for acquiring the working type of the selected target and displaying the preset working duration of the working type in the second item set based on the working type. Through cooperative work of the acquisition module, the classification module, the analysis module, the uploading module and the display module, the data processing efficiency and accuracy are improved, and an effective management tool is provided for project management.

This disclosure presents an embodiment of a method and system for address and entity recognition based on a large language model and retrieval enhancement. One specific implementation of the method includes: data processing of an acquired multi-source address dataset and a point-of-interest dataset to generate a candidate entry dataset; performing a mixed retrieval on the acquired unstructured text to be processed based on the candidate entry dataset to generate a retrieval candidate entry dataset; constructing a set of instruction prompts from the unstructured text to be processed and the retrieval candidate entry dataset; inputting the instruction prompt set into a preset entity recognition model to obtain a structured entity recognition result; generating a formatted recognition result based on the structured entity recognition result; and, in response to determining that the formatted recognition result represents a successful verification result, identifying the formatted recognition result as the target entity recognition result. This implementation improves anti-interference capability, reduces dependence on labeled data, and lowers data costs.

The invention discloses a carbonate rock distribution area soil heavy metal traceability method, and belongs to the technical field of soil heavy metal traceability, and the method comprises the following steps: (1) geological background analysis: constructing a regional association type geological background reference; (2) soil sample collection and chemical analysis: providing basic data for traceability work; (3) chemical fingerprint feature extraction: constructing a form-isotope two-dimensional fingerprint, and improving the source distinguishing precision; and (4) spatial distribution modeling and traceability: multi-dimensional data collaborative analysis is carried out, and accurate traceability is realized in combination with spatial visualization. On the basis of the geological background, the natural source reference is defined; establishing a characteristic system database by taking chemical fingerprint data as a core; the receptor model parameters are optimized, and the distinguishing ability of a natural source and an artificial source is enhanced; and the spatial distribution data is used as a carrier to verify the source spatial relevance, so that the traceability precision is effectively improved finally.

The invention relates to the technical field of wire production, in particular to a tension self-adaptive control method and system in enameled wire production, and the system comprises an initialization and matching module, a disturbance observation estimation module, a feed-forward compensation calculation module and a composite control output module. According to the scheme, intelligent initialization and rapid matching of the new production task control parameters are realized by constructing and querying the process knowledge graph. According to the method, historical optimal production experience is stored in a datamation mode, and a reference tension set value close to an optimal solution and controller parameters can be automatically provided under the working conditions of different wire diameter, speed and temperature combinations. Therefore, the debugging time after specification switching is greatly shortened, the production efficiency is improved, a control system is ensured to start to operate from a high-level starting point, and the quick response capability of a production line to multi-variety and small-batch orders is remarkably improved.

The invention relates to an electrical angle calibration method and system for a joint actuator. The method constructs an intelligent calibration closed loop that is deeply integrated with a production line management system (MES). The method comprises the following steps: scanning a product identification code and automatically preloading an optimal parameter; the actuator automatically detects the encoder signal, performs closed-loop adjustment on the gain, and records data at the same time; if the fault occurs, calling a rule base to perform multi-dimensional root cause pre-judgment and interception; after the signal is qualified, high-precision electrical angle compensation is executed, and a compensation value is locally stored and uploaded to a digital file; the system realizes self-learning and continuous optimization by periodically analyzing historical data; and finally, generating a uniquely bound full-link traceable file. The system comprises an upper computer, a joint actuator, a programmable power supply and a CAN communication module. According to the invention, full automation, intelligence and datamation of calibration are realized, the problems of low efficiency, poor consistency, dependence on manpower and the like are solved, and the production takt, quality and traceability are remarkably improved.

The invention discloses an intelligent management method and system for enterprise work plans, relates to the field of enterprise intelligent management, and can solve the problems of poor collaboration and nonstandard flow caused by information dispersion, low permission and progress management and control efficiency, no datamation risk pre-judgment and optimization mechanism in enterprise work plan management at the present stage. Comprising the following steps: determining a basic management environment of an enterprise according to an enterprise organization structure and authority system, cloud side end collaborative hardware and system operation parameters; determining a hierarchical task list according to the basic management environment and the enterprise strategic target; according to the hierarchical task list, allocating each hierarchical task to a corresponding execution main body and pushing a task notification message to the execution main body; and acquiring real-time progress data of each level of task, and performing closed-loop management on the execution process of each level of task according to the real-time progress data. The method and the device are used for intelligently managing the enterprise work plans.

The application discloses a similar network behavior user identification method based on an unsupervised variational autoencoder, and relates to the technical field of network security. The method is based on super-large network communication metadata, uses an unsupervised variational autoencoder model, learns deep law features of user network behaviors from massive user network flow metadata, abstracts network behaviors of users into high-dimensional vector representations of essential behavior modes, and finally identifies users by using the similarity between vectors. Specifically, the method comprises network flow metadata, network behavior statistical feature extraction, behavior feature image processing, deep learning model training, deep feature extraction and similar behavior user identification.

The application discloses a data-based integral generation and exchange management system based on equipment charging behavior, and relates to the technical field of charging management. The system comprises a data acquisition and communication module, a data processing and analysis module, an integral generation and record module, an integral exchange management module and a system management background. The application combines high-frequency charging behavior with a multi-dimensional integral rule model, realizes intelligent guidance of user habits, and significantly improves user stickiness and system operation efficiency.

The invention relates to the technical field of environmental management, and discloses an environmental protection system based on data big model training optimization, and the system comprises the steps: constructing an environmental impact evaluation report classification system; collecting standard specifications of different pollution types in the classification system, performing sample processing, and constructing a model training sample data set; a text recognition and processing module; calling a large model interface to obtain an audit result; performing preliminary verification on the auditing result; and feeding back an auditing result. According to the environmental protection system based on data large model training optimization, intelligent auditing of reports is achieved by constructing an environmental impact evaluation report classification system, collecting related standard specifications and conducting sample processing, the auditing efficiency and accuracy are improved, and manual errors are reduced through formulated labeling and datamation verification; a general quantitative evaluation formula is introduced, a more comprehensive evaluation result is provided, improvement of the consistency of the evaluation result is facilitated, and meanwhile, the comparability of the evaluation result is improved by using a unified quantitative evaluation method.

The application discloses a neodymium-iron-boron magnet quality tracing method and system based on big data analysis, relates to the technical field of quality tracing, and solves the technical problems of high data collection missing rate, inability to support process state restoration and root cause analysis, difficult non-causal simulation error debugging, influence on new product development efficiency, and serious industrial chain information island; through isolation forest online detection of deformation anomalies, process fluctuations can be self-adapted; the deformation index quantifies the deformation severity of single-piece magnets, the Mahalanobis distance evaluates the stability of the batch relative to the historical baseline, and the mold wear or pressing pressure anomaly can be early warned, the size deviation is converted into quantifiable data labels, and the root cause is convenient to trace. The magnetic properties are preliminarily analyzed, if the risk is found, an equation dependency graph is constructed, an abnormal sensor or process parameter is located by using a graph neural network from error variables, key performance fingerprints are stored by a consortium chain, and it is ensured that the data cannot be tampered with and can be audited.

The invention relates to the field of furniture production, in particular to a furniture design and production file integrated system. The system comprises a file management module, an equipment management module, a workflow module and an object version control module. The file management module carries out datamation management on file contents and identifiers; the equipment management module manages online equipment; the workflow module combines and converts the uploaded design files into production processing programs by corresponding equipment converters according to different design files and data under corresponding production plans through editing design workflows, and stores the production processing programs into file libraries of corresponding equipment classes; and the object version control module analyzes and compares the uploaded file and the data object, and generates a lightweight incremental file when the uploaded file conflicts with the file which is being executed. According to the method and the system, the versions of the files are uniformly managed, so that the real-time performance of synchronization is greatly improved, workers do not need to actively download and push the files, and the possibility of file confusion is completely eradicated.

The disclosure provides a string-based graphical analysis method, which defines the hierarchy, layout direction, size ratio and state color of a graph by designing a nested string DSL, converts the string expression into standard structured data using an analysis engine, and finally dynamically generates a visual graph through a rendering engine; this method abstracts complex graph layout into dataable semantic templates, allowing users to quickly build and modify complex nested graphs in a minimalist text form, while relying on a color and state binding mechanism and standardized data output to achieve flexible definition, efficient parsing, dynamic rendering and real-time state updating of graph layout in server cluster monitoring, distributed system state display and other scenarios, effectively solving the problems of low development efficiency, high maintenance cost and lack of dynamics in traditional hard coding methods.

The invention discloses a cable support installation quality acceptance system, which comprises an intelligent agent pre-learning modeling system, a mobile terminal field interaction acceptance system and a defect recording and data management system, and is characterized in that the intelligent agent pre-learning modeling system is used for constructing an intelligent agent with interactive learning ability, inputting cable support core data into the intelligent agent, and carrying out defect recording and data management on the cable support core data; meanwhile, the intelligent agent completes pre-learning and training in combination with cable bracket mounting conditions in different scenes; the mobile terminal field interaction acceptance system is used for deploying a maturely trained agent; the mobile terminal field interaction acceptance system collects video information of a cable support in real time, and an intelligent agent analyzes the installation state of the support and outputs an analysis result. The defect recording and data management system is controlled by an intelligent agent and is used for collecting, storing and recording installation defect information between cables. The system has the advantages that the intelligent, efficient and datamation closed loop of the installation quality acceptance inspection process of the cable bracket is realized.

The invention discloses a triangular mesh shape-finding optimization method based on GH and fluid dynamics. The method comprises the following steps: step 1, storing a triangular mesh needing shape-finding optimization in a tool of a Grasshopper parameterization process in a datamation form; step 2, applying a force to each side of the triangular unit to homogenize the triangular unit; and 3, restoring the plurality of triangular optimization units into the triangular mesh to form the triangular mesh after shape finding optimization. The invention relates to the technical field of building external envelope engineering, and can solve the problems that in the prior art, triangular grid units are not uniform in side length, and triangular geometrical shapes are classified in multiple types.

The present application relates to a kind of based on the intelligent management and control method of physical flow direction of Internet of Things, step 1, each physical object is provided with an RFID electronic tag, RFID electronic tag receives the state signal and environmental parameter of different sensor collection physical object in real time, RFID reader-writer can read or write in the data of RFID electronic tag;Step 2, RFID reader-writer passes through signal sending device to the state signal and environmental parameter of physical object to one or more of data center, mobile terminal or operating equipment;Step 3, data center real-time acquisition physical flow direction in each link basic data, data layer carries out data storage and calculation;Step 4, based on the calculation result of data layer, build physical flow direction control model, based on physical flow direction control model, carry out the management of physical object whole course flow direction.The present application realizes the data, visualization of business flow by constructing physical flow direction intelligent management and control, improves the standardization and transparency of material management, and enables physical flow direction lean management with data elements.

The invention discloses a chemical production process abnormity monitoring method. The method comprises a pollution source abnormity characteristic acquisition process, a data preprocessing process, a conventional data entry process and an abnormity monitoring parameter bidirectional evaluation process. Through adding a pollution source abnormal characteristic acquisition process, distributed monitoring deployment is carried out, monitoring coverage and real-time performance are improved, monitoring blind areas are avoided, acquisition efficiency of data of each monitoring point is improved, and after data preprocessing, obvious abnormity and normal fluctuation can be clearly distinguished from data acquired by the pollution source abnormal characteristic acquisition process. After conventional data are input, conventional floating parameters are set based on non-overrun real-time data, the conventional data are corrected for the second time based on the floating parameters, real change of a judgment value is carried out by adapting to the change of a production environment, and in a subsequent abnormal monitoring parameter two-way evaluation process, through comparison of two kinds of references, the abnormal monitoring parameter is evaluated. And the influence on accuracy caused by single reference deviation is avoided.

The invention discloses a glass curtain wall sphere building double-curved-surface hollow glass installation process, which belongs to the technical field of building construction, and is characterized by comprising the following steps: step 1, clamp positioning and installation: S1, steel keel real-time monitoring, S2, three-dimensional data acquisition and processing, S3, glass size datamation and collision inspection, and S4, clamp angle calibration and production; 2, double-curved-surface hollow glass is positioned and installed, specifically, S1, glass pre-assembling and checking are conducted, S2, on-site hoisting installation is conducted, and S3, glass parameter datamation storage is conducted. Compared with the prior art, the double-curved-surface hollow glass has the advantages that high-precision positioning installation of the double-curved-surface hollow glass is achieved, and the problems of layer staggering and uneven stress existing in a traditional installation process are solved.

The invention, which relates to the technical field of building performance analysis and adjustment, discloses an integrated building performance analysis and optimization design platform system comprising a building form performance acquisition module, a building performance analysis module, a layout optimization module and a building impact simulation module. The system has the advantages that a performance comparison table of extreme weather-building shape-basic material arrangement-performance is constructed through the building form performance acquisition module, strong association of design parameters and extreme weather resistance is achieved, collaborative evaluation of safety performance and use functions is achieved through the design of comprehensive analysis and special unit combination, and the system has a good application prospect. Through linkage of the layout optimization module and the building impact simulation module, an optimization-simulation-re-optimization closed loop is constructed, building safety risks in extreme weather are reduced fundamentally, and through datamation, modularization and closed-loop technical logic, extreme weather adaptability is upgraded to a core driving factor from additional consideration of traditional building design.

The present application belongs to the technical field of data analysis, and discloses a rural tourism information data analysis feedback method, comprising the following steps: S100, obtaining photos of tourists and scenic spots; S101, obtaining photo information, the photo information including photographing location data; S102, importing the photographing location data into a scenic area map, associating the photos corresponding to the location data with the position in the scenic area map, generating marking information at the position corresponding to the location in the scenic area map, and displaying the photos by clicking the marking information; S103, comparing and analyzing the number of photos contained in the marking information with a set threshold value, and judging whether to generate prompt information; the feedback method obtains the number of times that different locations are approved by tourists, fully understands the preferences of tourists from the perspective of tourists by analyzing data, collects and develops unexploited scenic spots, increases the favorite scenic spots of tourists, increases customer loyalty, reduces unnecessary development of scenic spots, and reduces the construction cost of rural tourism.