79results about How to "Accurate traceability" patented technology

The invention provides an intelligent runoff pollution monitoring and response method and system, and the method comprises the steps: arranging a plurality of monitoring points in a runoff region, collecting water quality, hydrological and meteorological data in real time through a sensor, transmitting the data to a data processing center through a wireless network, carrying out the preprocessing, storage and analysis, and calculating the comprehensive pollution index of each monitoring point. And comparing with a set index threshold value. When the comprehensive pollution index exceeds a threshold value, the system identifies and evaluates key water quality parameters so as to determine a reasonable parameter threshold value; once data of a monitoring point exceeds a preset pollution threshold value, an alarm mechanism is triggered, then a pipe network water flow model and a geographic information system are combined to reversely track a pollution path, accurately position a pollution source and provide a basis for pollution control, and the process comprises the steps of screening suspected pollution source nodes, calculating a propagation path probability and preferentially checking a high-probability path. The traced pollution source or path probability is lower than a preset value.

The invention discloses a knowledge base AI original text accurate reading device containing a DLF dynamic layout file. A data acquisition offline module sets an acquisition website and offline webpages according to the hierarchical relationship of the webpages; the DLF file generation module is used for converting each offline webpage file into an OFD file and assembling a plurality of webpages into a dynamic layout DLF file according to a hierarchical relationship, the content extraction knowledge base storage module is used for extracting content information in each individual webpage and generating a file queue according to the extracted content information, the generated file queue is pushed to the inference model, and the dynamic layout DLF file is obtained. Forming a knowledge base containing the DLF file; the AI reasoning module performs logical reasoning on the input problem and returns a result; the traceability interpretation module is matched with an associated DLF file according to the obtained return data; and the combination comparison module compares and checks multiple page areas of different DLF files at the same time, so that AI original text tracing of various types of files is realized.

The invention discloses a small-scale greenhouse gas tracing method based on numerical simulation and data assimilation, and belongs to the technical field of greenhouse gas tracing. The method comprises the following steps: acquiring real-time meteorological monitoring data in a park, and performing cyclic assimilation; establishing a high-precision backward trajectory tracking system to obtain refined backward trajectory data of a monitoring station; establishing a high-precision greenhouse gas traceability calculation model to obtain greenhouse gas potential emission source distribution data; averaging the emission source distribution data to finally obtain potential emission source comprehensive probability distribution data; according to the invention, through a high-resolution numerical simulation and data assimilation technology, diffusion, transmission and chemical reaction processes of greenhouse gas in a small-scale range can be accurately simulated; meanwhile, the grid empirical weighting function of the traceability algorithm is optimized, the adverse effect of the low-track end point number on the final traceability result is effectively reduced, the robustness of the model is enhanced, and it is ensured that the traceability result is more accurate, reasonable and stable.

The invention provides a voice traceability determination method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining a to-be-detected voice signal; extracting voice features of the voice signal; generating model fingerprints according to the voice features, wherein the model fingerprints are feature sets used for distinguishing voice sources of different objects; performing clustering analysis on the model fingerprint to obtain a clustering result; and determining the voice traceability information of the voice signal according to the clustering result. In the embodiment of the invention, the model fingerprints are generated based on the extracted voice features, so that the system can capture fine voice features from massive voice features and perform clustering analysis on the model fingerprints to realize accurate voice classification and traceability, thereby improving the accuracy of voice traceability determination.

The invention discloses a backlight module processing coating flatness monitoring system based on machine vision, relates to the technical field of processing coating monitoring, and solves the technical problems that in the prior art, the influence of a coating material cannot be analyzed, and the execution efficiency of processing coating is reduced. The method specifically comprises the steps that a film covering influence analysis unit analyzes the processing film covering influence of the backlight module, film covering material thickness data and film covering glue matching data are collected, and whether the film covering material and a glue matching material are influenced or not is deduced through data comparison; the processing and laminating influence of the backlight module is analyzed, whether flatness floating is influenced by a laminating material or not in the processing and laminating process is deduced by analyzing the influence of the laminating material, so that the laminating material is repaired and replaced in time, and the situation that the use efficiency of the laminating material is reduced due to the fact that the influence of flatness floating cannot be solved due to reworking is avoided. And the film coating processing progress of the backlight module is influenced.

The invention provides a standard electronic transformer angular difference traceability device and method based on square waves, and belongs to the technical field of power system measurement. And the delay phase determination module is used for determining a fundamental wave delay phase corresponding to the square wave voltage signal according to the rising time or falling time of the square wave voltage signal. And the standard analog-to-digital conversion mutual inductance module is used for carrying out filtering and analog-to-digital conversion sampling on the square wave voltage signal according to the clock synchronization signal to obtain a digital voltage signal. And the calibration angle difference determination module is used for carrying out discrete Fourier transform on the digital voltage signal to obtain a fundamental wave phase corresponding to the digital voltage signal, and carrying out angle difference tracing on the detected electronic transformer according to a calibration angle difference obtained by calculating the fundamental wave phase and a fundamental wave delay phase. Through the device and the method provided by the invention, the calibration angular difference of the standard analog-to-digital conversion mutual inductance module can be accurately obtained, the tested electronic transformer is traced, the accuracy of angular difference traceability is improved, and the problem of low accuracy is solved.

The present invention relates to the technical field of water pollution source tracing, and in particular to a graph theory driven water pollution source tracing method based on hydrodynamics and water quality models, including monitoring each monitoring point; calculating correlation coefficients; constructing a graph model to determine pollution source monitoring points; simulation calculation; calculating and verifying correlation coefficients, and adjusting or issuing key pollution source prompts according to the calculation results. The present invention evaluates the accuracy of the model by comparing the Pearson correlation coefficient of the simulation results with the actual monitoring data, and adjusts the number of monitoring points or the standard value of the correlation coefficient according to the evaluation results to optimize the accuracy and efficiency of the source tracing method, and finally issues an early warning prompt of the pollution source, effectively combining the hydrodynamics and water quality models and graph theory analysis methods, improving the accuracy and response speed of water pollution source tracing, and effectively solving the problems of complex and inefficient source tracing analysis due to incomplete and uneven distribution of water quality monitoring data, and increased difficulty in source tracing caused by the combined effects of multiple pollution sources.

The invention provides an answer tracing method and device, equipment and a storage medium. The method comprises the steps that an answer output by a knowledge retrieval system for a user question is acquired; based on the answers, a preset semantic grading limiting text and a grading result output format, constructing semantic grading prompt words of the answers; based on the semantic grading prompt words, performing semantic grading on the answers to obtain semantic grading results of the answers; and obtaining traceability information of the answers based on a semantic grading result. Through the method disclosed by the invention, accurate tracing of the answers can be realized.

The invention provides a robot skill knowledge characterization method based on Granger causality test. The method comprises the following steps: collecting original video stream data in a robot operation process; standard operation steps and sudden abnormal conditions of the robot are coded into a standard operation state and a random event state respectively, stage variables are formed, executable operation after the standard operation or the random event occurs is coded into an executable operation state, and action variables are formed; modeling the sequential relationship between the historical stage variable and the current action variable by using a VAR model to obtain a VAR-based stage-action model; performing Granger causality test on variables in the stage-action model based on the VAR to confirm the causality between the variables; and according to the result of the Granger causal test, constructing a causal relationship network in the robot operation process, and forming a causal rule device. According to the method, the real dependency relationship in the time series data can be deeply mined, and a skill characterization framework based on a causal mechanism is established.

The invention discloses a multi-source heterogeneous data pollution traceability and management system based on end-edge-cloud collaboration. The system comprises a multi-source heterogeneous data acquisition module, a cloud-edge collaboration data management and control module, an environment traceability graph embedded sensing module, an interpretable traceability analysis module, a closed-loop regulation and control decision module and a pollution abatement feedback module. A sensing end multi-dimensional sensor collects various types of data, edge end preprocessing and cloud deep analysis cooperation are carried out, an abnormal sensing algorithm is embedded based on an environment traceability graph, a dynamic pollution source identification mechanism is constructed by an interpretable environment pollution traceability analysis model, and a strategy is adjusted in combination with a data pollution closed-loop regulation and control decision model. And the links of early warning, patrol, traceability, disposal and feedback are covered. According to the system, the robustness and maintainability of a multi-source data system are improved, rapid response, accurate traceability and intelligent closed-loop management of pollution events are realized, the problems of insufficient monitoring data collaboration and poor traceability treatment closed-loop performance are effectively solved, and the fine management requirement of environment monitoring is met.

The intelligent twist lock for the container ship comprises a lock body master control box, an upper lock head driving box and a lower lock head driving box are arranged on the upper portion and the lower portion of the lock body master control box respectively, an upper lock head is arranged on the top of the upper lock head driving box in a sliding mode, and a lower lock head is arranged at the bottom of the lower lock head driving box in a sliding mode; an upper lock head driving assembly is arranged in the upper lock head driving box, and a lower lock head driving assembly is arranged in the lower lock head driving box. A lock body information chip convenient for a ship remote control platform to remotely operate the twist lock is arranged on the front side of the upper lock head driving box; the lock body information chip and the control module are additionally arranged on the twist lock, and the twist lock is in communication connection with the ship remote control platform, so that key data basis and equipment support are provided for intelligent stowage and yard automatic management of the container ship; the driving motor is matched with the precise spiral lifting and rotating mechanism, so that the whole process automation of locking and unlocking of the twist lock is realized, the working efficiency is greatly improved, and the labor intensity is reduced.

The application discloses a multi-source education data attribution analysis system and method based on a large model Function Call, and belongs to the technical field of computers. The system comprises: a multi-source data access module for constructing a unified education data warehouse; an intelligent semantic routing module for identity recognition and intent analysis; a function registration and execution module for triggering atomized analysis functions; and a comprehensive attribution analysis module for generating an attribution report in combination with a knowledge base. The method comprises the following steps: accessing multi-source education data and preprocessing, guiding the large model to identify the intent by using the prompt engineering, outputting a structured instruction to trigger the function call, and finally performing causal reasoning. The application realizes the deep fusion and accurate attribution of multi-source education data, reduces the interaction threshold, and provides a scientific basis for teaching decisions.

The invention belongs to the technical field of flue gas monitoring, and provides a multipoint patrolling method, system and device. The method comprises the following steps of adaptive sampling and preprocessing, distributed full-dimensional self-diagnosis and fault early warning, fault root cause mining and processing, LIBS spectral analysis and 4D pollution diffusion model construction, environment-data dual-drive dynamic calibration mechanism and data fusion and collaborative analysis. According to the method, LIBS spectral analysis and a CFD model are coupled to construct a 4D pollution diffusion model, and an environment-data dual-drive dynamic calibration mechanism is combined, so that accurate simulation and prediction of a pollution diffusion rule are realized; through space fusion and time trend prediction, a scientific basis is provided for pollution source responsibility division and emission reduction decision, adaptive sampling, multi-modal fault diagnosis and dynamic pollution modeling are integrated, closed-loop and environment-data dual-drive dynamic calibration from data acquisition to decision support is achieved, limitation of a traditional static model is broken through, multi-dimensional collaborative decision support is achieved, and the method is suitable for large-scale popularization and application. And a landing emission reduction scheme is provided.

The application provides a release film surface defect detection method and system, relates to the technical field of defect detection, and the method comprises the following steps: through the non-contact multi-physical field information collection on the same detection area of the continuously running functional film to be detected on a film production line, holographic quality field original data are acquired, space-time correlation fusion is performed on corresponding real-time process parameters, the quality field data cube is input into a pre-trained defect diagnosis model, double-channel defect traceability diagnosis and performance attenuation prediction are executed in parallel, and a release film surface defect diagnosis result is generated. The technical problem that the prior art only performs simple detection on the surface defects of the release film, cannot distinguish whether the performance has defects, and leads to the reduction of release film defect detection precision is solved. Through multi-physical field synchronous detection and space-time fusion analysis, accurate defect traceability and performance attenuation prediction are realized, and the technical effects of improving the release film detection precision and performance reliability are achieved.

The invention relates to the technical field of motor vehicle exhaust pollutant analysis and monitoring, and particularly discloses a motor vehicle emission supervision method and system based on remote measurement and OBD fusion, and more accurate motor vehicle emission supervision is realized by combining a road remote measurement technology and OBD data. The method comprises the following steps: firstly, acquiring vehicle passing characteristics, actually measured emission concentration and OBD real-time parameters, and generating a group reference interval to perform credibility evaluation; generating a dynamic self-inspection instruction packet for the suspicious vehicle, triggering the vehicle-mounted terminal to execute a diagnosis excitation script at the target remote measurement point, and collecting excitation response data; generating a deep diagnosis conclusion by analyzing the dynamic response consistency of the tail gas concentration in the excitation period and the excitation response data, updating the credibility score of the vehicle data according to the deep diagnosis conclusion, and generating an emission supervision instruction; according to the invention, data authenticity and law enforcement credibility are improved, and optimal configuration of supervision resources is realized.

The application discloses a kind of time difference risk hedging method and device of insurance fund custody, it is related to financial risk control technical field, the method includes: creating virtual sub-account for each user and being bound with corresponding policy account one by one to realize fund physical isolation;When consumption incentive enters the custody special account, it is frozen to corresponding virtual sub-account by calling bank freezing interface and generates directional payment instruction;When daily business ends, generate custody fund flow sheet snapshot, before batch deduction of insurance company next day, pre-reconciliation is carried out to custody fund flow sheet snapshot and to-be-deducted list, and according to result, unfreezing transfer or difference processing is executed;Risk reserve pool is established simultaneously, when unilateral account is abnormal, first pay, complete account adjustment to realize error recovery after finding out reason and clearing up.The application realizes fund physical isolation by virtual sub-account binding and fund freezing directional transfer, effectively hedges the supervision and operation risk caused by fund circulation time difference, and improves the stability of fund custody.

The application provides a data processing system and fluidized bed reactor, comprising: a data acquisition module, a data processing module and a man-machine interaction module; the data acquisition module is used for collecting process parameters of the fluidized bed reactor; the data processing module is used for filtering and engineering unit conversion of the collected process parameters, and real-time control according to a preset process logic; the man-machine interaction module is used for determining a process flow chart, parameter values and alarm information based on the process parameters, and displaying the process flow chart, parameter values and alarm information. In this way, full-link accurate tracing can be realized, the system supports multi-dimensional data association, the root cause can be quickly locked and the problem can be prevented from recurring; data deep value mining can also be realized, and intuitive trend curves, flexible data export and advanced analysis tools are provided.

The invention discloses a railway precast beam full-period digital delivery and disease tracing method and system, and the method comprises the following steps: S1, collecting and sorting precast beam data, and building an IFC entity model based on the data; s2, pre-burying a two-dimensional code plate and an RFID tag on the precast beam, and recording the digital identity of the precast beam; s3, obtaining the completion coordinate of the precast beam, and binding the digital identity of the precast beam with the completion coordinate at one time; s4, performing block chain evidence storage on the application data of the precast beam; s5, developing a front-end APP, and judging whether the precast beam meets a traceability condition or not; s6, all data of the precast beam meeting the traceability condition are called, and root cause judgment is conducted based on the IFC entity model. According to the method, by establishing the IFC standard data link which runs through design-production-operation and maintenance, data barriers of links of design, production and operation and maintenance can be broken through, data run-through is achieved, data islands are avoided, and comparison time consumption is greatly shortened.

The invention discloses an equipment maintenance cost management and control system and method, and relates to the technical field of industrial equipment management. The system comprises an Internet of Things data sensing layer, a maintenance digital twinborn construction module, a multi-dimensional dynamic preventive maintenance cost prediction engine, a cost control and execution layer based on an intelligent contract and a self-adaptive cost allocation and optimization feedback loop. The method comprises the following steps: collecting data in real time and constructing an equipment maintenance digital twinborn body; the prediction engine generates a virtual maintenance unit containing predicted cost based on the twinborn body data; when the risk exceeds a threshold value, a block chain intelligent contract is automatically triggered, and automatic and traceable management and control are carried out on budget, process and payment; after maintenance is completed, cost is automatically shared, and data is fed back to optimize the model. According to the method, the change of the maintenance cost from passive response to active prediction and from post-event recording to whole-process automatic management and control is realized, transparency is ensured through an intelligent contract, a self-optimization closed loop is formed, and the refinement level and cost effectiveness of cost management and control are improved.

The invention relates to the field of session semantic merging, in particular to a session semantic extraction intelligent merging method for audio semantic recognition, which comprises the following steps of: obtaining an audio-metadata binding set with a unique fragment identifier and candidate semantic fragments, obtaining a semantic unit set with a multi-dimensional attribute index, constructing a high-dimensional feature vector space by taking a semantic unit set with a multi-dimensional attribute index and a cross-queue candidate association index as input, obtaining a clustering cluster set, extracting a core semantic topic of each clustering cluster in the clustering cluster set, constructing an intra-cluster semantic unit association graph, and obtaining a core dominant unit; and obtaining a preliminary combined semantic text of the clusters, and obtaining a complete semantic text after the clusters are combined. According to the method, the standardized high-dimensional feature vector space is constructed based on the multi-dimensional features, the core attributes of the semantic units are comprehensively represented, the reasonability and accuracy of cluster division are improved, and meanwhile, accurate tracing of the features and the semantic units is achieved through the feature vector-semantic unit mapping table.

This invention relates to a method and system for accessing the trusted space of inland waterway shipping data under zero-trust conditions. It includes defining the shipping trust status and transformation rules of participating entities, constructing a risk scoring model to calculate the risk score of shipping behavior, introducing federated learning to improve the accuracy of the shipping behavior risk score, constructing a trust calculation function to calculate dynamic trust values ​​in real time, designing hierarchical access decision rules for hierarchical authorization to achieve access control, and submitting the hash value of logs to the blockchain to drive the update of shipping trust status, forming a closed loop of credit update and access control. This invention provides a systematic solution for the Jianghuai inland waterway shipping industry that balances strict security, business efficiency, and compliance requirements, achieving the coordinated evolution and proactive improvement of the security defense capabilities of the entire Jianghuai inland waterway shipping ecosystem.

This utility model relates to the field of casting technology and discloses a device for quickly identifying the flow sequence of a cast billet. The device includes a billet exit section vision system, a flow sequence binding module, and a fixed numbering unit. The billet exit section vision system is installed above the post-cutting conveyor roller (1) and the steel transfer machine (2) to capture the number and position of the cast billet (3) in real time. The flow sequence binding module is configured to associate the number of the cast billet (3) with the flow sequence information through an image processing server and transmit it to the display screen (4) for real-time display. The fixed numbering unit is configured to communicate with the flow sequence binding module and spray numbers onto the cast billet (3) after it has been collected and unloaded according to the binding information. This device for quickly identifying the flow sequence of a cast billet simplifies roller operation, improves work efficiency, realizes the identification of flow sequence information, and makes product traceability more convenient and accurate.

The application relates to the technical field of testing, and discloses a test method for an application system, which comprises the following steps: acquiring a system configuration file, a local application program package and a corresponding local Java bytecode file of a local application system, and determining a target full-amount corresponding relationship of the local application system; acquiring different Java bytecode files of different versions of application program packages, and determining a program difference list; acquiring an outbound configuration file, and combining the target full-amount corresponding relationship and the program difference list to determine a first full-amount test range of the local application system and a plurality of second full-amount test ranges of a plurality of other application systems, and then testing the application system to obtain a target test result of the application system, which realizes bidirectional accurate analysis of a test range of a local program change on itself and other systems and of other system changes on the local system, comprehensively covers transaction interface and business function test requirements among multiple systems in an enterprise, and guarantees the overall operation stability of the application system.

The invention relates to the technical field of data security, and discloses a database access control method and a storage medium, the method is applied to a server, and the method comprises the following steps: when a connection between a first client and a database is monitored, establishing a first connection between a network probe and the database, and establishing a second connection between the network probe and the database; a second connection between the network probe and the database firewall is established, the network probe is arranged in the server, when the first client side sends an access data packet to the database, the access data packet is sent to the network probe through the first connection, and the access data packet is processed through the network probe; the network probe is used for processing the access data packet and sending the processed access data packet to the database firewall through the second connection, the processed access data packet comprises the first client information of the first client, and the network probe enables the first client directly connected with the database to be included in the management and control range of the database firewall. Therefore, the database firewall realizes accurate tracing of database operation behaviors.

The application discloses a data quality evaluation system and method based on artificial intelligence, and relates to the technical field of data quality evaluation.The total quality loss score is determined according to the first state parameter value and the second state parameter value of the media data; the time cumulative damage component, the abnormal jitter frequency and the jitter peak cumulative amount are calculated according to the instantaneous transmission rate, the rate representative value and the transmission time delay jitter in the media data transmission process; the minimum transmission guarantee strength is calculated according to the maximum jitter peak value, the transmission guarantee failure coefficient is determined, the concurrent scheduling pressure loss coefficient is calculated according to the concurrent scheduling layer and the jitter peak cumulative amount, and the transmission scheduling comprehensive damage value is obtained in combination with the transmission guarantee failure coefficient; the BP neural network model is constructed, the time cumulative damage component, the abnormal jitter frequency, the jitter peak cumulative amount and the transmission scheduling comprehensive damage value are input into the model, the data transmission quality loss score is obtained, the data receiving and transmitting quality loss score is further obtained, and the quality optimization suggestion is generated.

The invention belongs to the technical field of veterinary instruments, and particularly relates to a clinical vaccination auxiliary device and method for veterinarians, the clinical vaccination auxiliary device comprises a vaccination gun and a needle tube mounted at the end of the vaccination gun, the vaccination gun is provided with a bottle seat for placing a vaccine bottle, and the bottle seat is provided with a puncture needle for puncturing the vaccine bottle; the adjusting mechanism comprises a sleeve disc which is fixedly arranged on the vaccination gun in a sleeving manner, and a connecting frame with a sliding plate is fixedly mounted on the sleeve disc; through the design of a connecting frame, a sliding plate, an adjusting plate and an adjusting groove, the length of the needle tube entering the poultry body is controllable, and the length of the needle tube penetrating into the poultry body is rapidly adjusted according to the actual requirements of different poultry. Therefore, the device adapts to the body types, day ages, fat and thin degrees and injection site differences of different poultry, and avoids the situations that vaccines cannot be effectively absorbed and immune fails due to too shallow needle insertion, or internal organs, blood vessels and nerves are damaged due to too deep needle insertion, and stress and tissue damage of the poultry is aggravated.

The invention relates to a pressure system micro-leakage online monitoring method and device, equipment and a storage medium, and the method comprises the steps: obtaining the identity information of a to-be-monitored pressure system, associating the identity information with the monitoring process, and generating a bound monitoring task; performing pressure initialization; acquiring reference state data (reference pressure and reference temperature) of the to-be-measured pressure system and starting monitoring; in the micro-leakage monitoring process, actual state data of the to-be-measured pressure system at the current moment are circularly obtained and recorded at a preset time interval, and the actual state data comprise an actual pressure value and an actual temperature; according to the reference pressure, the reference temperature and the actual temperature, calculating a theoretical pressure value in a leakage-free state at the current moment; comparing the actual pressure value with the theoretical pressure value to obtain a pressure difference, and judging whether the pressure system leaks or not according to the pressure difference to obtain a monitoring result. The method has the effect of improving the accuracy of the micro-leakage monitoring result of the pressure system.

The invention provides a spacecraft general assembly data fusion processing system and method, and the system comprises a dual-core architecture which comprises a general assembly cooperation model module and a knowledge-driven engine module; the hierarchical classification database is connected with the dual-core architecture; the version penetration management module is used for establishing a product version penetration management mechanism based on a preset code; and a rule verification engine for automatically verifying the data based on a preset rule. The method comprises the following steps: carrying out collaborative sharing and intelligent decision making through a dual-core architecture, storing spacecraft general assembly data into a hierarchical classification database for standardized storage, establishing a product version penetration management mechanism, and automatically checking the data based on a preset rule obtained from a knowledge-driven engine module. According to the method, the data normalization and accuracy can be remarkably improved, the full-life-cycle accurate tracing of the data is realized, and the cross-professional collaboration efficiency is improved.

The application discloses a SKU-level delivery decision path mapping method and system based on Shapley value and deep learning, and relates to the technical field of data processing. The method collects multi-channel SKU-level user behavior data and pre-processes the same, quantizes contact contribution values based on an improved Shapley value algorithm and an LSTM modeling, stores the same to an optimization database to support tracing, constructs a visual engine to output a key path, and integrates data to establish quality monitoring, thereby solving the problems that SKU-level data deep analysis, contact contribution accurate attribution and decision path efficient visualization are difficult to realize in the prior art, and having the advantages that SKU-level data deep analysis, contact contribution accurate attribution and decision path efficient tracing and dynamic visualization can be realized, and marketing efficiency and effect are improved.

The invention discloses a direct current electric energy traceability method, system and device considering dynamic characteristics, and relates to the technical field of electric energy metering traceability. The technical key points are as follows: a direct-current electric energy meter uploads electricity consumption data and identification information of electricity consumption each time to a server; the server associates and stores the metering date, the metering starting time, the metering ending time, the load information, the direct current electricity consumption and the alternating current electricity consumption included in the electricity consumption data with the identification information, and counts the total electricity consumption of the metering date; the direct-current electric energy meter receives query information for querying historical electricity consumption, generates a query request according to the query information and sends the query request to the server; and the server queries the power consumption data according to the query request and sends a query result to the queried direct current electric energy meter. The direct-current electricity consumption and the alternating-current electricity consumption are respectively subjected to time dynamic measurement, so that accurate and rapid source tracing of data of the direct-current electric energy meter is realized.