147results 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 relates to the technical field of quality traceability management, in particular to an organic fertilizer quality safety traceability management method based on multi-source data. The method comprises the following steps: collecting organic fertilizer source data in real time from links of organic fertilizer production, circulation, storage and use, performing standardization processing, and performing production batch synchronous set processing and traceability association connection file establishment to generate an organic fertilizer multi-source data traceability association connection file; and carrying out production batch tracing extraction processing on the organic fertilizer multi-source data traceability association connection file, carrying out organic fertilizer quality index evaluation analysis and quality index error limitation analysis, carrying out organic fertilizer quality safety abnormity traceability processing and abnormity decision support processing, and generating an organic fertilizer quality safety abnormity problem decision support report. Therefore, the corresponding organic fertilizer quality safety abnormity traceability problem management work is executed. The scientificity and accuracy of organic fertilizer quality safety management can be improved.

The invention discloses an industrial part defect traceability method, and relates to the field of quality prediction and quality traceability of industrial parts, and the industrial part defect traceability method comprises the following steps: obtaining defect data of the industrial parts; performing classification prediction on the preprocessed defect data based on a sequential logic regression tree model, and generating influence factors of process parameters on part defect formation in the industrial part production process based on a classification prediction result; constructing a causal graph database based on the influence factors of the process parameters on part defect formation, and performing causal graph modeling on industrial part defects to obtain an industrial part defect causal graph; and constructing a quality traceability model based on the industrial part defect causal graph, and performing quality traceability on the defect path by using the quality traceability model. According to the invention, the quality management efficiency and accuracy of industrial part production are improved, and the problem source can be quickly and accurately traced.

The invention discloses a plain river network area in-river pollution analysis method based on a watershed hydrology and water quality model, and belongs to the technical field of water environment comprehensive treatment. According to the method, aiming at the problems that complicated hydrological characteristics and pollution sources in a plain river network area are difficult to trace to the source, accurate analysis of pollutants entering a river is realized through riverway topological relation carding, sub catchment partition division, basin hydrological water quality model construction, pollution load calculation and pollution source composition analysis; the method comprises the specific technical steps of river channel screening and topological relation carding, ArcSWAT-based sub catchment partition division, basin hydrology and water quality model building and simulation, pollution load calculation and pollution source identification. The method can reasonably divide catchment zones, simulate the flushing and river entering processes of pollutants, improve the accuracy of pollution source analysis, significantly improve the treatment efficiency, realize accurate traceability and quantitative analysis of pollutants in plain river network areas, and provide powerful data support and theoretical basis for accurate comprehensive treatment of water environments.

The invention relates to the technical field of consumable management, and discloses an intelligent monitoring and tracing management method for SPD medical consumables in an operating room. Comprising the following steps: if entering a traceability management state, extracting traceability characteristics from a calling event, marking traceability nodes, obtaining comprehensive calling data of the traceability nodes, calculating node abnormal coefficients, if giving out an early warning traceability prompt, marking abnormal nodes, marking abnormal parameters of the abnormal nodes, and formulating a traceability management mode according to the abnormal nodes; compared with the prior art, the method has the advantages that integral simulation display can be carried out on the calling and using process of the consumables in the calling and using process, meanwhile, abnormal point locations of the consumables in the calling and using process can be accurately recognized, and a tracing management mode matched with the condition of abnormal calling and using of the consumables is formulated according to the condition of abnormal calling and using of the consumables; according to the method, the effect of accurately tracing the original position of the abnormal condition when the consumables are called and used is achieved, and it is ensured that the medical consumables in the operating room can be efficiently monitored, traced and managed.

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 provides a production data management system based on artificial intelligence, and relates to the technical field of data processing. The system comprises a production data acquisition module, a multi-dimensional time sequence feature extraction module, a dynamic manifold analysis module, a production path optimization module, a vulcanization process anomaly analysis module and a vulcanization process optimization module. Multi-dimensional time sequence feature extraction and dynamic manifold analysis are carried out on key data, obtained by a data acquisition module, of a vulcanization process, a production manifold feature space containing complex dynamic characteristics of the vulcanization process is generated, a target vulcanization process path and a process interval are constructed based on the feature space, and reference is provided for follow-up process deviation detection; the deviation vector is utilized to detect the process abnormality, and the inverse mapping model is combined to realize the precise reduction and tracing of the process parameters, so that the production process is always maintained within the optimal path, and the vulcanization process flow is more intelligent and automatic.

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 belongs to the technical field of source tracing of pollution sources, and particularly relates to a heavy metal pollution source tracing method based on artificial intelligence. Carrying out abnormal value processing and standardization on the collected heavy metal concentration detection data, carrying out terrain segmentation and feature extraction on terrain data, and carrying out spatial interpolation and time pairing on rainfall data; the data dimension is further enriched by acquiring historical pollution event records and wind speed and wind direction data and constructing interaction characteristics of rainfall and gradient. Then, the processed multi-dimensional feature matrix is input into the trained prediction model to obtain accurate heavy metal concentration and spatial distribution features, and finally, the position of the pollution source is deduced by adopting a Bayesian reverse modeling method, so that accurate tracing of the heavy metal pollution source is realized, the accuracy and reliability of a tracing result are improved, and the method is suitable for popularization and application. The technical problem that a tracing result in a traditional method is not scientific and systematic enough is effectively solved.

The embodiment of the invention discloses a digital service watermark encryption method and device, and a tracing method and device, and the method comprises the steps: extracting a customer number of a service calling party from a digital service calling request, and extracting a target character from a target account according to a watermark identifier in a watermark fingerprint secret key associated with the customer number; performing consistency matching on each target character and a corresponding matching character set in the watermark fingerprint secret key to obtain a matching result, and performing encryption processing based on parity adjustment on the original model score with a preset adjustment amplitude according to the matching result to obtain a watermark model score, the minimum affine transformation can be implemented on the original model score by presetting the adjustment amplitude, and only the parity of the original model score is adjusted, so that the influence on the model score is reduced, the effectiveness of the model score is improved, the digital watermark in the watermark model score obtained by encryption is difficult to perceive, the encryption secrecy is good, and the user experience is improved. The method can be widely applied to the technical fields of cloud computing, artificial intelligence and the like.

The invention provides a VoWiFi voice service position tracing method based on satellite communication and related equipment. The method comprises the steps of determining a corresponding intranet address and an intranet port number based on a public network address and a public network port number of a session request in a position traceability request in response to the received position traceability request about the session request; obtaining an MAC address of a satellite terminal corresponding to the session request based on the intranet address and the intranet port number; and obtaining geographical location information of the satellite terminal based on the MAC address of the satellite terminal, and obtaining a location traceability result of the session request.

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 invention discloses a big language model-driven spinning high-carbon emission process root cause analysis method, and belongs to the technical field of carbon emission root cause analysis in industrial production. The method comprises the following steps that firstly, in order to meet the input requirement of a large model, a production process data structure and a semantic text representation method are predefined, and production process log data, graph data and the like related to domain knowledge stored in a local information management system are subjected to process summarization and textualization representation; secondly, similar case matching is carried out by using a proximity retrieval method based on production process data to form a support basis for subsequent large model analysis; and finally, carrying out two-stage confidence evaluation based on a proximity retrieval case and a large model root cause analysis result, and outputting a decision result. Compared with the existing design, the method can carry out traceability analysis and process optimization assistance on the carbon emission problem, and is beneficial to discovering the carbon emission influence factors of each specific process, thereby improving the production process.

The invention relates to a surgical instrument recognition device and a recovery method and system. The surgical instrument recognition device is used for counting and recycling surgical instruments and comprises a support, a working table arranged on the support and a control module. The working table comprises an induction recognition area and a weight recognition area. And an induction identification module and a weight identification module which are in communication connection with the control module are correspondingly arranged in the induction identification area and the weight identification area. And the induction identification module is used for identifying the electronic tag of the to-be-recycled surgical instrument so as to obtain the instrument information of the to-be-recycled surgical instrument. And the weight identification module is used for obtaining weight information of the to-be-recycled surgical instrument and obtaining instrument information of the to-be-recycled surgical instrument according to the weight information. According to the invention, each surgical instrument can be accurately traced, so that each surgical instrument is accurately managed, and surgical requirements are guaranteed.

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 invention provides a data traceability method and device, electronic equipment and a storage medium, and relates to the technical field of computers, the data traceability method comprises the steps that to-be-traced data and the traceability type of the to-be-traced data are acquired, and the to-be-traced data has a corresponding data identifier; change information related to the data identification is obtained, the change information is used for describing the distribution condition and change condition of a first identification and / or a second identification in the process of generating the to-be-traced data, the first identification is used for describing a data field of the source table, and the second identification is used for describing a row record of the source table; and generating traceability path information corresponding to the traceability type according to the change information, thereby solving the technical problem that traceability cannot be accurately performed on data fields and line records in the data table in the prior art.

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 invention discloses an air pollution traceability analysis method. The method comprises the following steps: acquiring actually measured meteorological data of monitoring points in a target area; meteorological scene data matched with the actually measured meteorological data are determined according to a meteorological scene library, and the meteorological scene library comprises various kinds of meteorological scene data; pollution traceability data matched with the meteorological scene data are determined according to a pollution traceability library, and the pollution traceability library comprises multiple kinds of pollution traceability data in one-to-one correspondence with the multiple kinds of meteorological scene data; and determining an emission source of the matched pollution traceability data and a concentration contribution value corresponding to the emission source according to the CALPUFF mode. The method is suitable for industrial parks with high density, numerous emission sources and complex pollutant components, the specific pollution characteristics of a certain emission source in the industrial parks and the concentration contribution value of pollutants can be accurately measured, and accurate, efficient and reliable traceability is achieved. The invention further discloses a computer storage medium and a computer program product.

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 relates to the field of agricultural product management, and particularly discloses an agricultural product quality safety traceability system, method and device. A sales end server, a farmer end server, a supply end server and a production processing end server are networked in different places, and a traceability query request sent by a query client through scanning a two-dimensional code is received; and according to sales end identification information contained in the tracing query request, respectively obtaining peasant end data, supply end data and production processing end data from a peasant end server, a supply end server and a production processing end server, and forming complete quality safety tracing data together with sales end data to be fed back to the query client. According to the invention, rapid and accurate tracing of agricultural product full life cycle data is realized through remote networking, and the tracing efficiency and accuracy are improved.

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.