109results about How to "Easy data management" patented technology

The invention relates to the technical field of wire harness intelligent evaluation, in particular to a wire harness connection performance intelligent test method and system. The method comprises the following steps: collecting wire harness test data generated by a wire harness test device and a wire harness sensor in real time through an edge computing node; performing electrical performance detection extraction and mechanical performance detection extraction according to the wire harness test data to respectively obtain wire harness electrical performance detection data and wire harness mechanical performance detection data; performing electrical performance deep evaluation according to the wire harness electrical performance detection data to obtain wire harness electrical performance evaluation data, and performing mechanical performance deep evaluation on the wire harness mechanical performance detection data to obtain wire harness mechanical performance evaluation data; and performing environment pressure cross reference according to the wire harness electrical performance evaluation data and the wire harness mechanical performance evaluation data to obtain wire harness connection performance test evaluation data. According to the method, the accuracy of wire harness performance evaluation is improved, and reliable performance data can be obtained in different application fields.

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 auxiliary system and method for regular inspection of a pressure vessel, and aims to improve the intelligence, efficiency and accuracy of inspection of the pressure vessel. The system comprises a data acquisition module, a data processing module, a risk assessment module, an inspection plan generation module, a report generation module, a remote monitoring module and a historical data management module. Operation parameters of the pressure vessel are collected in real time through the sensor, the data processing module carries out elimination and trend analysis on abnormal data, and the risk assessment module assesses the operation state of the pressure vessel through machine learning and a fuzzy logic algorithm. The system dynamically generates an inspection plan according to an evaluation result and adjusts an inspection period through Bayesian updating, and a generated inspection report has a digital signature to ensure safety. The historical data management module stores and analyzes long-term data and supports trend prediction of equipment health conditions, and the remote monitoring module provides real-time state checking and early warning.

The invention discloses an LU-SGS implicit propulsion calculation method under a self-adaptive Cartesian grid, and relates to the field of numerical simulation, and the method comprises the steps: 1, generating equidistant and uniform initial Cartesian grids based on an aircraft model size parameter, an aircraft model motion parameter and an aerodynamic parameter, and distributing a multi-dimensional array number for each grid according to the dimension of a space; 2, on the basis of the geometric shape of the aircraft model, performing cross-tree adaptive encryption on grids within a preset range of an object plane boundary, and generating an adaptive Cartesian grid required by calculation; step 3, sorting the generated adaptive Cartesian grids to obtain a sorting result; 4, performing LU-SGS implicit propulsion calculation based on the sorting result to obtain a numerical simulation calculation result of the aircraft model; according to the method, LU-SGS implicit propulsion calculation under the adaptive Cartesian grid can be realized, so that convergence is accelerated to improve calculation efficiency.

The invention belongs to the technical field of spectral analysis, and discloses a spectral analysis and image recognition combined intelligent stoma evaluation system and method.A three-dimensional scanning module captures the three-dimensional form of a stoma and the three-dimensional form of surrounding tissue of the stoma through the high-precision laser or structured light scanning technology; the spectral analysis module is used for accurately analyzing the color change of the stoma; the tiny color difference of the stoma area is detected to help to identify potential tissue abnormality; the image recognition and processing module is used for analyzing the collected stoma image by using a deep learning algorithm and automatically recognizing morphological characteristics of the stoma; the data analysis and feedback system is used for automatically generating a stoma health assessment report according to the collected multi-dimensional data; through a set standard reference value, an actual measurement value is compared, and a corresponding suggestion is given, for example, whether a nursing scheme needs to be adjusted or further medical intervention needs to be carried out. According to the method, the real-time state of the stoma is accurately evaluated through non-contact scanning and spectrum detection.

The invention discloses a low-code platform development method and a low-code platform system, and belongs to the technical field of software development, the overall architecture design of a low-code platform is carried out based on Vue2 and TypeScript, and the method comprises the combination of modularization, data management and visual editing function modules; the system comprises a component management module which comprises a component library and user-defined component management; the visual editor is used for realizing real-time layout adjustment and attribute configuration; the user previews the modification effect in real time by dragging and adjusting the position, the size and the hierarchical relationship of the component; the data management module is used for realizing data binding, API integration and dynamic data management; and the performance optimization module comprises a virtual DOM (Document Object Model) optimization and on-demand loading mechanism. The invention provides a development environment which is high in expandability and easy to use. A complex coding process is simplified into visual operation, and cooperation between developers and non-technical users is promoted.

The invention discloses a mine disaster optical fiber intelligent monitoring, early warning and emergency rescue command decision-making system. The system comprises an industrial personal computer, an optical fiber ring network, a distributed optical fiber multi-gas monitoring subsystem, a distributed optical fiber temperature monitoring subsystem, a distributed optical fiber vibration monitoring subsystem and a distributed optical fiber mine pressure monitoring subsystem. The system has high sensitivity, multi-gas monitoring capability, high precision and comprehensive monitoring capability, and can monitor and early warn various parameter changes of a mine in real time, including gas concentration, temperature, vibration and pressure. The system has real-time monitoring and early warning capabilities, can accurately capture tiny changes and timely send out early warning signals, and helps mine monitoring personnel to take safety measures. The system has the functions of rescue command and emergency rescue, can quickly transmit environment information and disaster conditions to a rescue command center, and improves the rescue efficiency. The system also has strong data management and analysis capability, and helps mine monitoring personnel to better understand the environment change and trend of a mine and the change of disaster risks.

The invention discloses an ultrathin electronic glass roller way speed measurement support and a speed measurement method, and the support comprises a support which is connected to a mounting disc for fixing a supporting roller through a bolt, the support is fixedly provided with an encoder, a detection shaft of the encoder is connected with a connecting disc through a coupler, the connecting disc is clamped at the end part of the supporting roller, and a signal of the coupler is connected with a speedometer. And a driving control system and an alarm of the supporting roller are connected through a linear speed meter. The effect of improving the roller way rotating speed detection precision and frequency is achieved.

The invention relates to a power enterprise data full-link fault positioning method based on data consanguinity. The method comprises the following steps: step 1, constructing a data consanguinity map; 2, based on the data consanguinity map constructed in the step 1, metadata consanguinity full links are collected and monitored in real time; 3, based on the data blood relationship map constructed in the step 1 and the real-time monitoring data collected in the step 2, a state transition matrix is constructed by analyzing state change information, and a Markov chain model is defined; by using the Markov chain model, the system can identify potential fault points and carry out accurate positioning. According to the invention, the problems of high data link complexity, difficulty in fault positioning, low troubleshooting efficiency and the like in the prior art can be solved.

The invention relates to a stacking machine perception interaction system and method for operation interaction. The system communicates with a wharf central control system and comprises a stacking machine body, an electric control cabinet installed on the stacking machine body, a sensing module comprising a plurality of sub-modules and sensors, a decision module and an interaction module. The sensing module is used for acquiring self information and operation environment information of the stacking machine during operation; the decision module is used for controlling each sensor of the sensing module and calling each sub-module according to the operation environment information, and sending a request instruction to the interaction module; and the interaction module is used for interacting with a wharf central control system, acquiring task information, issuing the task information to the decision module, and reporting container number information, operation container truck number information and container position information to the wharf central control system after a container receiving and sending task is completed. Compared with the prior art, the system has the advantages that the operation safety is guaranteed, the intellectualization of operation interaction is realized, the operation of a driver is reduced, and the operation efficiency is improved.

The invention provides a space recovery method and device, equipment and a medium, and relates to the technical field of computers.The method comprises the steps that a data area in a storage system is divided into a plurality of data blocks, and the utilization rate of each data block contained in the data blocks is obtained, the utilization rate of the data block is determined according to mapping of a logic address and a physical address of data contained in the data block; according to the interval where the utilization rate is located, determining a space recovery strategy corresponding to each data block; and according to the space recovery strategy, carrying out space recovery on the data block. And effective utilization of space resources of the storage system is ensured. And the space recovery strategy of each data block is determined according to the utilization rate, so that the storage space in the data blocks can be effectively and efficiently recovered, and the data management of each data block in the storage system can be optimized.

The invention discloses an intelligent alcohol detection method and system based on sensor fusion, and relates to the technical field of intelligent alcohol detection safety, and the method comprises the following steps: collecting alcohol concentration data, and processing the alcohol concentration data by adopting a self-adaptive filtering algorithm; transmitting the optimized alcohol concentration data to a detection cloud; and sharing alcohol concentration data detected by multiple users to finish supervision of an alcohol detection result. According to the invention, high-precision and low-noise alcohol concentration detection is realized, the intelligent level of the system is improved, the accuracy of data is ensured, and the overall efficiency and management efficiency of the system are improved, so that the alcohol detection system is remarkably improved in the aspects of precision, stability and data management, and the requirements of modern society on efficient and intelligent alcohol detection are met.

The invention relates to the technical field of data communication, in particular to a communication method based on multiple operating systems, which comprises the following steps: determining the data type of data to be transmitted and the sensitive type and sensitivity of each data type, and determining the data sensitive equivalent of each data packet, after data packets are divided into data transmission packets, the transmission channel occupation number of each data transmission packet is determined according to the data sensitive equivalent of the data packets so as to determine the occupied transmission channel, and the backup lower limit and the transmission lower limit of each data packet are determined according to the association type of each data packet so as to determine the to-be-transmitted packet and the partial transmission packet of the corresponding data packet. And determining an actual transmission packet of each data transmission packet, and performing data communication according to the actual transmission packet of each data transmission packet and the occupied transmission channel. According to the method, resource waste is reduced, the overall response capability and efficiency of the system are improved, and a basis is provided for cross-system communication.

The invention relates to the technical field of information processing, in particular to an electronic license code scanning real-name authentication service method, device and equipment and a storage medium, a salesman carries a mobile service terminal equipped with a code scanning recognition technology when going to a door, the terminal can directly scan two-dimensional code scanning information on a user electronic license, and the two-dimensional code scanning information is stored in the mobile service terminal. The information of the user is quickly identified and read, so that the process of real-name authentication is completed, the user does not need to go to a service window to queue and wait, the service process is simplified, the time and energy of the user are saved, the user experience is improved, related information is subjected to security encryption processing and transmitted to a service system, and the user experience is improved. The security risk in the information transmission process is effectively reduced, the integrity and confidentiality of the data are ensured, data management by a management department is facilitated, real-name authentication transactions of each time are recorded by adopting a block chain technology, the data are ensured not to be tampered, and the requirements of supervision transparency and traceability are met.

The invention belongs to the field of information analysis and management, and relates to an intelligent mass information analysis method based on big data, which comprises the following steps of: integrating keyword tags, theme tags, time tags and space tags of newly introduced data items on that day to generate index tags, and taking the index tags as a pointing basis for storing the index tags into a target database; the data management quality of a target database is greatly improved, retrieval data of all archived data items in the target database at a preset time point after the day is collected, all high-frequency data items and all low-frequency data items in the target database are recognized, index tags and storage positions are optimized for the high-frequency data items, and the data management efficiency is improved. According to the method, the low-frequency data special library transfer processing is performed for the low-frequency data items, the oversaturation state of the low-frequency data special library is identified, and the data cleaning operation is further performed, so that the retrieval efficiency and the storage resource utilization rate of the target database are improved, the storage cost is reduced, and the data management capability is enhanced.

The invention provides a printing method and device of an Excel-based printing template system. The method comprises the following steps: making an Excel template according to a receipt printing template requirement of a unit; carrying out the binding of the Excel template; the Excel template obtains data from a database, data filling is carried out through the Apache POI technology, and a complete Excel file filled with the data is generated; converting the Excel file into an HTML (Hypertext Markup Language) code; matching all bound functions in the HTML code through a regular expression, running corresponding function code blocks, and replacing the bound functions with function running results; according to the printing size configured by the template, a script is embedded in an HTML code, and the scaling is adjusted; and the browser executes the printing operation to complete printing, so that the user can quickly print, and the operation difficulty is reduced.

The invention provides a data persistence storage method and device for a vehicle-mounted system and a storage medium. The method comprises the steps that vehicle configuration information is written into a persistent storage area in a key value pair mode; determining a target storage area according to the received key value pair information; vehicle configuration information is written or updated in the target storage area, the vehicle configuration information is stored in a preset format, and data of different partitions are isolated and managed according to identities or permissions of callers; when the vehicle configuration information is read, a reading request is sent to the persistent service module through the persistent service interface by utilizing the upper-layer application, so that the persistent service module determines a corresponding storage area according to the key value pair information in the reading request, and the corresponding vehicle configuration information is acquired from the storage area. According to the invention, the data consistency can be ensured, the data management is simplified, and the scheme can be efficiently integrated in different system environments.

The embodiment of the invention discloses a multichannel annular access method and system for meteorological observation data, and belongs to the technical field of meteorological data processing. According to the embodiment of the invention, the annular buffer structure is adopted to manage meteorological observation data, and compared with a traditional linear stack, the annular buffer has obvious advantages. The linear stack is low in efficiency when the data volume is large, and the annular buffer supports multiple independent data streams to share a storage space, so that continuous writing and cyclic coverage are realized, for example, different sensor data streams can be stored orderly. Read-write pointers circularly move to ensure continuous access of data, the parallel access capability is improved in speed and efficiency, and the multi-task concurrence requirement of meteorological services is met. And an overflow and underflow detection mechanism and a capacity management strategy guarantee data integrity and system stability, and prevent problems of data loss or system crash and the like. Attribute knowledge mining and related mapping are beneficial to accurate management of data, management is carried out according to data characteristics, decision accuracy and efficiency are improved, and data management and operation of a meteorological service system are optimized.

The invention discloses a steel plate drilling automatic online detection system based on machine vision, and relates to the technical field of steel plate drilling machining systems. The system comprises a control system module, the input end of the control system module is electrically connected with an image processing module, the input end of the image processing module is electrically connected with an image acquisition module, and the output end and the input end of the control system module are electrically connected with a deep learning module. The output end and the input end of the control system module are electrically connected with a data processing module. According to the invention, the deep learning module uses a deep learning algorithm to train a large number of drilling images, automatically learns the characteristics and modes of drilling, improves the accuracy and robustness of detection, can continuously optimize the performance of itself, adapts to different types of steel plates and drilling requirements, and improves the accuracy and robustness of detection. And the intelligent diagnosis module is combined with an expert system and data analysis to perform intelligent diagnosis on a detection result.

The invention provides a low-code system for data analysis and data cleaning based on Internet of Vehicles data. The low-code system comprises a multi-protocol adapter, a user-defined analysis rule writing interface, a dragging type rule configuration interface, a data processing module, a forwarding mechanism unit, a monitoring and log tracking unit and a message labeling and fingerprint generation unit. Wherein the multi-protocol adapter is used for supporting log data acquisition of various network protocols; the user-defined analysis rule writing interface allows a user to write specific analysis logic according to a data format and a service requirement; meanwhile, for compatibility of various data codes and formats, rule templates and examples are provided to guide a user to compile analysis rules, and the user is helped to quickly position and correct problems in the analysis rules by integrating corresponding error detection and debugging tools; and a user carries out graphical operation combination input, output and analysis on rule nodes through the drag-and-drop rule configuration interface.

The invention relates to the technical field of data processing, in particular to a data processing device and method for automatically training a mouth shape model, and the device comprises a video input module which is used for receiving a video data stream to be processed; the video segmentation module is used for segmenting an input video data stream into small segments; the single-person and multi-person detection module is used for detecting persons in the video and identifying the appearance of a single person or multiple persons; the video audio and lip synchronization detection module is used for analyzing the audio and the mouth shape in the video so as to detect the audio and lip synchronization condition; the data storage and management module is used for storing and managing all the processed data, including the segmented video clips, the figure detection result and the audio and lip synchronization data; compared with the prior art, efficient data processing, accurate character detection, synchronous sound and lip detection and optimized data management and storage can be realized, progress in the field of mouth shape model training is promoted, and powerful support is provided for development and improvement of voice-related applications.

The invention discloses a wool fineness determination method and system based on deep learning, and belongs to the field of wool fineness determination, and the method comprises the following steps: S1, collecting a wool fiber image, and obtaining a data set; s3, obtaining fineness characteristics of wool; s4, constructing a convolutional neural network model, inputting the training set into the convolutional neural network model for training, inputting the verification set into the trained convolutional neural network model, and verifying and evaluating the convolutional neural network model by using cross validation; s5, inputting the test set into the verified convolutional neural network model, predicting the fineness of the wool fibers by using the convolutional neural network model, and outputting a fineness evaluation report; and S6, displaying and storing a result. By adopting the wool fineness determination method and system based on deep learning, wool fineness determination can be efficiently and accurately completed, the advantages of simple operation, non-contact measurement, reliable result and the like are achieved, and the automation level of wool detection is greatly improved.

The invention relates to a cold storage system control method, in particular to a method for achieving cold storage control through edge calculation. The control method comprises the following steps that the edge computing terminal outputs a corresponding control instruction according to whether the detected temperature of the refrigeration storage reaches a preset temperature range or not, and basic refrigeration control is achieved for the refrigeration storage system; after the edge computing terminal carries out primary processing on the data, uploading the temperature, the superheat degree, the valve opening degree and other data with a time sequence to a cloud server side in a wireless communication mode, and storing the data in a database; at the cloud server side, deep analysis is carried out on the temperature data by using an RNN recurrent neural network algorithm, and corresponding valve opening parameters of the electronic expansion valve are output; the control parameters are transmitted to an edge computing terminal in a wireless communication mode, the refrigeration house electronic expansion valve is accurately controlled, and self-adaptive control over the refrigeration house system is achieved.

This invention relates to a tire including an electronic device with a data structure for tire management. The invention provides a tire including an electronic device with a data structure for tire management, the tire being configured to have the electronic device, the electronic device comprising: a substrate portion having circuitry formed thereon; an antenna portion disposed on the substrate; and an EPC memory portion disposed on the substrate; the EPC memory portion being configured to record and read tire IDs of 96 bits or more, and the EPC memory portion having a plurality of memories configured to divide and store product serial number portions.

The invention relates to the technical field of gas sensor module testing, and provides a gas sensor module batch testing method and system, and the method comprises the steps: selecting a testing bottom plate as a main testing bottom plate, and selecting other testing bottom plates as auxiliary testing bottom plates; the test bottom plate is provided with one or more gas sensor modules to be tested; a test signal is sent to the test controller of the master test base plate, and the test controller of the master test base plate sends a test signal to the test controller of the slave test base plate; the test controller sends a test instruction to the gas sensor module, and the gas sensor module tests gas in the test cavity and generates test data; carrying out statistics and analysis on the test data, carrying out performance calibration on the gas sensor module, and carrying out parameter calibration on the gas sensor module. The gas sensor module test board aims to solve the problems that the test capacity is limited and the test efficiency is low when gas sensor modules are tested, and the gas sensor modules on the same test board are mutually independent and do not interfere with one another.

The invention provides a blast furnace condition diagnosis method based on a multi-time granularity dynamic reasoning mechanism, which comprises the following steps: S1, setting a plurality of time granularities, and establishing a furnace condition diagnosis rule base according to a preset rule; s2, collecting data in real time, storing the data in a dynamic database, extracting the data of the dynamic database every first time granularity, performing furnace condition diagnosis of the first time granularity according to rules of a furnace condition diagnosis rule base, and storing a diagnosis result in a process database; s3, calling data of the process database and the dynamic database every Nth time granularity, performing furnace condition diagnosis of the Nth time granularity according to rules of the furnace condition diagnosis rule base, and storing a diagnosis result in the process database; and S4, calling diagnosis results of different time granularities. According to the blast furnace condition diagnosis method with multiple time granularities, a dynamic reasoning mechanism can reduce a large amount of database read-write burden, and the calculation performance of a furnace condition diagnosis model is improved.

The invention relates to an automatic microbiological detection system and a control method thereof. The system comprises a loading module, a bottle pushing module, a bottle feeding module, a culture module, a detection module and an alarm module. The control method comprises the steps of bottle placing, detecting, analyzing, bottle feeding, culturing, growth condition detecting, bottle taking, placing and the like. Each bottle sleeve assembly comprises a bottle sleeve and a plunger, the loading module is provided with a conveying belt, a rotating disc and the like, the bottle pushing module is provided with a clamping jaw, a module and a guide groove, the bottle feeding module is provided with a clamping jaw, a driver and the like, the culture module is provided with a rotating shaft, a motor and the like, and the detection module is provided with a camera, a sliding block module and a light source. The device has the advantages that full automation of microbiological detection is realized, and the detection efficiency and accuracy are improved.

The invention discloses a digital economic data acquisition system and method based on 5G communication, and relates to the technical field of electronic digital data processing. The digital economic data acquisition system and method based on 5G communication comprises the following steps: S1, collecting digital economic related data; s2, preprocessing the digital economic related data stored in the database by using an automatic detection tool; s3, performing data standardization processing on the to-be-detected digital economic related data according to the data standardization detection value; S4, performing data fusion on the to-be-fused economic related data by using an Apache Kafka technology, and storing the to-be-fused digital economic related data after data stream integration by using a data lake technology of Apache Hadoop and Amazon S3; and S5, making corresponding optimization processing measures according to the data fusion detection value. The problem that in a traditional digital economic data acquisition system based on 5G communication, data is difficult to fuse due to diversity of data sources and heterogeneity of data formats and types is solved.

The present invention discloses a data management method and system based on a knowledge graph, including: obtaining historical record data of various fields and standardizing it to obtain standardized data corresponding to each field; constructing a knowledge graph of the corresponding field based on the standardized data corresponding to each field to obtain a standard knowledge graph library; obtaining data to be processed and determining the field information of the data to be processed; querying the standard knowledge graph library based on the field information of the data to be processed to determine a target knowledge graph of the field corresponding to the data to be processed; managing the data to be processed based on the target knowledge graph; constructing knowledge graphs for different fields, and determining the target knowledge graph based on the field of the data to be processed, so as to more accurately classify and manage the data to be processed and improve the efficiency and accuracy of data management.

The present invention relates to a specimen data information processing method, system, device and storage medium, the method comprising: performing multi-stage separation processing on the acquired original specimen data to obtain specimen image data and specimen type data; performing node analysis processing on the specimen image data and specimen type data in sequence to obtain image node data and feature node data; performing image cutting processing on the specimen image data according to the image node data to obtain a specimen region image, performing image analysis on the specimen region image to obtain specimen image information, performing feature extraction on the specimen type data according to the feature node data to obtain feature type data, and performing structural analysis on the feature type data to obtain specimen type information; performing association analysis and node extraction on the specimen region image and the feature type data to obtain specimen association data and pathology association nodes. The present invention can comprehensively, quickly and accurately parse multi-dimensional data.