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Raw data, also known as primary data, is data (e.g., numbers, instrument readings, figures, etc.) collected from a source. If a scientist sets up a computerized thermometer which records the temperature of a chemical mixture in a test tube every minute, the list of temperature readings for every minute, as printed out on a spreadsheet or viewed on a computer screen is "raw data". Raw data has not been subjected to processing, "cleaning" by researchers to remove outliers, obvious instrument reading errors or data entry errors, or any analysis (e.g., determining central tendency aspects such as the average or median result). As well, raw data has not been subject to any other manipulation by a software program or a human researcher, analyst or technician. It is also referred to as primary data. Raw data is a relative term (see data), because even once raw data has been "cleaned" and processed by one team of researchers, another team may consider this processed data to be "raw data" for another stage of research. Raw data can be inputted to a computer program or used in manual procedures such as analyzing statistics from a survey. The term "raw data" can refer to the binary data on electronic storage devices, such as hard disk drives (also referred to as "low-level data").
Multi-modal causal reasoning and explaining method, device, equipment and medium
The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a multi-modal causal reasoning and interpretation method, device, equipment and medium, and the method comprises the steps: obtaining original data streams of at least two different modals, and extracting modal features; a cross-modal attention mechanism is utilized to fuse modal features, and causal features are extracted through feature distillation; constructing a dynamic causal graph based on causal features, and updating an edge weight through a causal intensity function; identifying the causal relationship in the dynamic causal graph and performing anti-factual reasoning verification to evaluate the reliability of the causal relationship; and generating a causal interpretation result in combination with the dynamic causal graph and the causal relationship reliability. According to the method, the multi-modal data are fused, the causal features are extracted, and dynamic causal graph updating and anti-factual reasoning verification are combined, so that reliable modeling and explanation of the causal relationship in a complex scene are realized, the defects of single modal or simple fusion in the prior art are overcome, and the accuracy and interpretability of causal reasoning are improved.
Owner:PING AN TECH (SHENZHEN) CO LTD
Electric power design knowledge base construction method fusing multi-modal data and RAG technology
The invention relates to a multi-modal data and RAG technology fused power design knowledge base construction method, and belongs to the technical field of power software development. The method comprises the following steps: carrying out collection and information extraction on multi-source heterogeneous original data; the method comprises the following steps of: constructing a multi-dimensional knowledge element structure containing parameters, specifications and case relationships by carrying out classification, specialized and precise processing and cross-modal association on data; based on a vector, graph and relational database mixed storage architecture, semantic vector efficient retrieval, knowledge graph relation management and business data synchronization are achieved respectively; and a dynamic optimization result is subjected to hybrid retrieval, a dual-drive reasoning mechanism outputs compliance conclusions and bases, and a retrieval enhancement generation service ensures that output contents conform to specifications. And systematic management and intelligent application of the electric power design knowledge are realized.
Owner:常州常供电力设计院有限公司
System and method for orchestration of multi-agent operations using language models
In a described embodiment, a multi-agent system for processing information is provided including a data processing agent configured to ingest and normalize raw data inputs to produce standardized data and a standards integration agent configured to apply reporting standards into the standardized data thereby generating integrated reporting standards. The system further includes a performance alignment agent configured to align performance indicators based on the standardized data and the integrated reporting standards and an information synthesis agent configured to process narrative information from the standardized data and the integrated reporting standards. An orchestration framework configured to manage operations of the data processing agent, the standards integration agent, and the performance alignment agent to produce a regulatory repot compliant with regulatory requirements is further provided. The orchestration framework is further executable by a large language model.
Owner:STANDARD CHARTERED BANK SINGAPORE BRANCH
Threat Mitigation System and Method
A computer-implemented method, computer program product and computing system for receiving a message concerning an event within a computer platform, wherein the message concerns a technology type and includes raw data; defining a cipher for the technology type, thus defining an associated cipher; processing the raw data included within the message using the associated cipher to define supplemental data for the technology type; and forming enriched data for the technology type based, at least in part, upon the raw data and the supplemental data.
Owner:RELIAQUEST HOLDINGS LLC
Data analysis pipeline engine in a data intelligence system
PendingUS20260004135A1Data processing applicationsPlatform integrity maintainanceData sourceEngineering
Methods, systems, and computer storage media for providing a data analysis pipeline using a data analysis pipeline engine in a data intelligence system are described. A data analysis pipeline refers to a structured sequence of data processing steps that support transforming raw data into meaningful insights or actionable outcomes. The data analysis pipeline engine is an unsupervised learning pipeline based on clustering, topic modeling, and Large Language Models (LLMs). For example, the data analysis pipeline can use advanced machine learning techniques to automatically categorize emails into semantically similar clusters, enabling the data intelligence system to quickly identify and prioritize potentially high-risk emails for further investigation. The data analysis pipeline employs AI agents for context-aware graph induction relevance assessment. The AI agents employ induction and deduction loops to build and refine a data feature hypergraph (e.g., vulnerability hypergraph) that encompasses identified relevant data providing a holistic view of a contextual landscape.
Owner:MICROSOFT TECHNOLOGY LICENSING LLC
Gradienter attitude real-time calibration method based on multi-modal data fusion
The invention relates to the technical field of attitude measurement, and discloses a gradienter attitude real-time calibration method based on multi-modal data fusion, which comprises the following steps: acquiring multi-modal original data and completing unified preprocessing to obtain multi-modal data; reconstructing a liquid surface form in a physical domain neural operator layer, and outputting a physical domain attitude and a residual error; noise and drift are deduced in a sensing domain neural operator layer, and a sensing domain attitude estimation value, an offset parameter, a scale parameter and a residual error are output; establishing a deviation memory bank, updating by using residual errors and historical results, generating a long-term drift compensation amount, and superposing a sensing domain result; inputting a physical domain and a compensated sensing domain result into a dynamic constraint reversible transformation model, and outputting a fusion attitude and uncertainty; and executing slow variable refining compensation on the updated parameters, and outputting final real-time calibration attitude and quality information. According to the invention, by introducing multi-modal data fusion and double-layer reversible neural operator modeling, real-time, high-precision and long-term stable calibration of the attitude of the gradienter is realized.
Owner:NANTONG DIO AMP PHOTOELECTRIC TECH CO LTD
Wind field numerical simulation method based on multiple meteorological data sources
PendingCN121031426AGeometric CADIndication of weather conditions using multiple variablesTerrainGrid based
The invention relates to the technical field of wind field simulation, and provides a wind field numerical simulation method based on multiple meteorological data sources. The objective of the invention is to solve the problems of large simulation error, rough terrain boundary processing and poor turbulence model parameter adaptability caused by non-uniform coverage of a single data source, insufficient precision and unscientific multi-source fusion. The method is characterized by comprising the following steps: step 1, constructing a CFD three-dimensional grid based on a geometric model of a target area; 2, collecting original data of a ground station, satellite remote sensing, numerical forecasting and the like; 3, performing standardized preprocessing (abnormal value elimination, missing interpolation, radiation / geometric correction and resampling), determining a multi-source fusion weight by combining historical data analysis, and generating comprehensive meteorological data by adopting a weighted average method; and 4, inputting the comprehensive data into a CFD-RANS model, dynamically adjusting turbulence parameters, accurately setting terrain boundary conditions, and obtaining a wind field space-time distribution result through numerical solution. According to the invention, through combination of multi-source data fusion and CFD simulation, the wind field simulation precision and stability are improved.
Owner:SICHUAN GREEN ENERGY INTELLIGENT COMPUTING TECHNOLOGY CO LTD
Remote intelligent operation monitoring method and system of intelligent substation
The invention provides a remote intelligent operation monitoring method and system for an intelligent substation, relates to the technical field of intelligent operation and maintenance of substations, and relates to multi-source heterogeneous sensing, depth feature modeling, fault prediction evaluation and model self-optimization. According to the method, electrical, environmental and meteorological data are collected through heterogeneous sensors, a structured original data set is constructed, time sequence prediction is carried out in combination with a convolution-LSTM model, a Transform fusion network is utilized to output a fault probability and a confidence interval, online early warning and response control are realized, and the method has a federated learning driven adaptive updating capability.
Owner:GUANXI POWER GRID CORP HEZHOU POWER SUPPLY BUREAU
A federated learning system for data protection-compliant data exchange and collaboration
A federated learning system (100) for data protection in data sharing and collaboration, consisting of: a module for data acquisition and local preprocessing that is configured to clean, normalize and standardize local data sets at each participating node without transferring raw data externally; a local model training module configured to train a machine learning model on the pre-processed local dataset; a secure model update and encryption module configured to encrypt and secure model parameters or updates before transmission using privacy protection techniques; a federated aggregation and coordination module configured to aggregate encrypted updates from multiple participating nodes into a global model; a module for monitoring and ensuring data protection compliance, configured to enforce data protection budgets and audit protocols and to ensure compliance with data protection regulations; a performance optimization and resource management module configured to optimize communication, computation, and resource utilization across all nodes; and a module for global model delivery and feedback, configured to redistribute the aggregated global model to participants and integrate performance feedback for iterative improvements.
Owner:MEMON NOORI MORTON GROVE
Multi-parameter intelligent sensing and state monitoring system for power transformation equipment
The invention relates to the technical field of power transformation equipment state monitoring, in particular to a power transformation equipment multi-parameter intelligent sensing and state monitoring system which comprises a sensing unit, a data processing unit, a state analysis and diagnosis unit and an upper computer monitoring and management unit. Through data collection preprocessing, lightweight AI model anomaly preliminary screening and hierarchical edge cloud cooperative transmission strategies, efficient cleaning of original data, rapid edge end anomaly identification and optimal utilization of network resources are realized, data transmission bandwidth occupation is greatly reduced, monitoring real-time performance is improved, and the method is suitable for large-scale popularization and application. The method integrates technologies such as digital twinning, federated learning and a time-space attention network, realizes equipment cross-time-space fault accurate positioning, fault type reliable identification and residual life dynamic prediction in combination with a quantification algorithm, triggers hierarchical early warning through hierarchical health assessment, and provides scientific and accurate decision support for refined operation and maintenance of power transformation equipment.
Owner:STATE GRID ZHEJIANG ELECTRIC POWER CO LTD NINGBO POWER SUPPLY CO +1
Large language model federated fine-tuning method and apparatus based on gradient compression
PCT designated stageWO2025260391A1Biological modelsComputer security arrangementsData privacy protectionData set
Disclosed in the present invention are a large language model federated fine-tuning method and apparatus based on gradient compression. The method comprises the following steps: constructing, on the basis of a gradient tensor generated during fine tuning of a large language model, a raw data set having a time series relationship, performing inference by means of an autoencoder to obtain a reconstructed gradient data set, and constructing a reconstruction loss function to optimize the autoencoder; and initializing a base model of the large language model as a global model at a server end, the server end updating the global model to a client, using a pre-trained encoder to obtain a compressed gradient at the client, and at the server end, using a pre-trained decoder to decode and aggregate the compressed gradient, and then updating the global model. The present invention can improve the fine-tuning efficiency of the large language model and reduce computing resource requirements while ensuring data privacy protection, and is suitable for application scenarios such as communication optimization improvement and privacy protection enhancement in the process of scientific computing-oriented large model fine-tuning and training.
Owner:ZHEJIANG LAB
System and method for data-driven decision optimization for autonomous driving
PendingUS20260084708A1Internal combustion piston enginesExternal condition input parametersEngineeringData-driven
A data-driven autonomous driving decision optimization system and method, comprising: a data production module, a data screening module, a model encapsulation module, and a parameter tuning module; the data production module takes human driving data as input, annotation, preprocessing, format conversion, extracts key features and performs standardization, normalization, and encoding to generate raw data for the data-driven process that meets the algorithm input requirements; the data screening module screens corresponding data from training data by the decision-making module and performs effective classification; the model encapsulation module encapsulates C++ decision code and constructs a trajectory-pair evaluation cost map required for training using a ground-truth evaluation method based on trajectory pairs; the parameter tuning module, based on screened data under different scenarios, the encapsulated decision algorithm model, and the trajectory-pair evaluation cost map, employs black-box optimization to obtain decision parameters for the corresponding scenarios under the current decision algorithm.
Owner:SHANGHAI JIAOTONG UNIV
Intelligent anti-terrorism early warning system based on image recognition and big data analysis
The invention relates to the technical field of anti-terrorism early warning, in particular to an intelligent anti-terrorism early warning system based on image recognition and big data analysis, and the system comprises a multi-source data collection module which is used for collecting video streams, image data and environment parameters through a monitoring camera, a sensor and an Internet of Things device in a deployment region, executing target detection and desensitization operation at the edge computing node, and caching original data to a distributed message queue; and the data standardization processing module is connected with the message queue and is used for carrying out space-time alignment and semantic mapping on the multi-modal heterogeneous data. According to the invention, monitoring videos, sensor data, Internet of Things information and the like are preprocessed and desensitized at edge nodes, space-time alignment and semantic unification are completed through a data standardization processing module, and cross-modal feature fusion is realized through a multi-modal fusion analysis module, so that barriers among different types of data are broken through, and the accuracy of data fusion is improved. Scattered information forms an organic whole, and a comprehensive and consistent data basis is provided for abnormal behavior recognition.
Owner:CPI HENAN POWER LTD CO
Robot track online compensation and precision control method and system based on multiple sensors
The invention discloses a robot track online compensation and precision control method and system based on multiple sensors, and belongs to the technical field of robot track control. The method comprises the following steps: acquiring target trajectory data and original data of each sensor, and performing time alignment on the original data of each sensor to generate a fusion data set comprising vibration acceleration data and pose data; performing time-frequency feature extraction based on the vibration acceleration data to obtain a dominant vibration frequency spectrum; constructing a mechanical transfer function model of the joint driving torque and the tail end vibration displacement; based on the mechanical transfer function model, constructing an adaptive notch filter to generate a feed-forward compensation sequence; according to the target trajectory data, the pose data and weight parameters, updated in real time, of the sensors, a trajectory fusion deviation value is obtained through calculation; and after the feedforward compensation sequence and the trajectory fusion deviation value are integrated, a joint driving current instruction is generated based on a fuzzy PID control algorithm. The robot trajectory control precision can be improved.
Owner:SUZHOU UNIV
Electric meter metering error correction method and system based on time sequence anomaly detection and electric meter
ActiveCN120951224AElectrical measurementsNeural learning methodsElectric power systemMulti source data
The invention discloses an electricity meter metering error correction method and system based on time sequence anomaly detection and an electricity meter, relates to the technical field of electricity meter metering error correction, and provides an intelligent anomaly detection method integrating multi-source data preprocessing, online learning and federation cooperation for a power system in which distributed energy and diversified loads coexist. The method comprises the following steps of: 1, dynamically filtering and caching original data by adopting a suspicious degree function, and outputting high-quality input; secondly, online learning is carried out through multi-algorithm fusion and expert knowledge constraint, and accurate judgment of traditional and emerging modes is achieved; 3, realizing multi-region cooperative gain based on difference parameter sharing and global aggregation; and 4, deploying a lightweight model at the edge end by using feedback evaluation and model distillation, thereby improving the real-time performance and reliability. In conclusion, the false alarm rate and the missing report rate can be remarkably reduced, various changes of load behaviors are effectively adapted, the operation and maintenance efficiency of a power grid is improved, and meanwhile data privacy safety and collaboration are guaranteed.
Owner:LIYANG HUAPENG ELECTRIC POWER METER
High-altitude environment-oriented sonde multi-source data quality control processing method and system
ActiveCN120950501ADigital data information retrievalSpecial data processing applicationsRadiosondeQuality control
The invention relates to the technical field of data processing, in particular to a sonde multi-source data quality control processing method and system for a high-altitude environment, and the method specifically comprises the steps: obtaining a space-time asynchronous error, a sensor physical conflict and navigation data abnormity based on the original data of a sonde; analyzing a data quality index of the sonde based on the space-time asynchronous error, the sensor physical conflict and the navigation data anomaly; obtaining an environmental adaptability correction coefficient based on the atmospheric environment characteristics of the height layer where the sonde is located and historical sounding data; analyzing a dynamic measurement error based on the flight attitude and motion state data of the sonde; and the credibility weight of the sonde during multi-source data fusion is predicted based on the data quality index, the environmental adaptability correction coefficient and the dynamic measurement error of the sonde, and whether the data of the sonde meet the high-altitude detection quality standard is judged. The fusion credibility of the multi-source data under the extreme condition is predicted, and the quality control precision of the high-altitude detection data is improved.
Owner:NANJING DAQIAO MASCH CO LTD
Federated Codebook Optimization and Neural Upsampler Training for Distributed Device Networks
A federated system and method for data compression optimization in distributed device networks. The system comprises multiple edge devices that analyze local data patterns to generate device characteristic profiles while performing local compression optimization and maintaining data privacy. Edge devices contribute to collaborative learning by generating privacy-preserved updates without transmitting raw data. A central coordination system aggregates encrypted contributions using secure multi-party computation protocols, identifies device groups based on data pattern similarities, and generates optimized compression parameters for each group. The system coordinates collaborative training of data reconstruction models across device groups and deploys group-optimized reconstruction capabilities. Device grouping is performed by calculating similarity scores between device characteristic profiles and clustering devices with scores above predetermined thresholds. The system dynamically adapts compression and reconstruction parameters through federated learning while preserving individual device data privacy, enabling efficient data compression and near-lossless recovery across heterogeneous Internet-of-Things networks.
Owner:ATOMBEAM TECH INC
Energy storage cabinet multi-parameter intelligent monitoring device based on MEMS sensor array
The invention relates to the technical field of energy storage cabinet safety monitoring, in particular to an energy storage cabinet multi-parameter intelligent monitoring device based on an MEMS sensor array, a sensor array unit in the energy storage cabinet multi-parameter intelligent monitoring device comprises distributed MEMS temperature and vibration sensors, the temperature sensors are installed in a non-vertical mode, detection deviation caused by direct blowing of airflow is avoided, and the energy storage cabinet multi-parameter intelligent monitoring device based on the MEMS sensor array is obtained. The airflow disturbance correction unit corrects temperature original data in real time and eliminates interference of airflow on module body temperature detection by means of a heat dissipation airflow vector field dynamic model and a compensation algorithm, and the multi-parameter coupling analysis unit processes vibration and temperature signals in a double-channel mode, extracts tab loosening high-frequency micro-vibration characteristics and correlates the temperature rising rate. Early fault logic is triggered through two-stage judgment, the fault decision and output unit fuses the correction temperature, the coupling strength coefficient and the speed-up ratio, graded early warning is generated through a fault tree model and transmitted to an external monitoring system, and accurate monitoring of early faults of the energy storage cabinet is achieved.
Owner:WEICHU NEW MATERIALS CO LTD
Bid invitation file generation method and system and storage medium
The invention provides a bid invitation file generation method and system and a storage medium, and the method comprises the steps: obtaining original data from a plurality of modalities, the original data comprising a project demand text, a design model file, a law and regulation text and historical bid invitation case data; performing multi-module semantic deep analysis and structured processing on the original data, and respectively generating a project demand sub-graph, a spatial logic sub-graph, a structured regulation knowledge base and a historical case strategy feature library; performing cross-modal dynamic fusion on the project demand sub-graph and the spatial logic sub-graph to construct a unified knowledge graph, and performing dynamic knowledge tracing and strategy injection in the fusion process based on a structured regulation knowledge base and a historical case strategy feature library; and generating a first bid invitation file draft based on the unified knowledge graph, performing compliance verification on the first bid invitation file draft, and determining the first bid invitation file draft passing the verification as a final bid invitation file. The bid invitation file generation accuracy can be improved.
Owner:HANGZHOU GOLDEN SOFTWARE SYST INC
Seismic wave identification method based on deep learning
A seismic wave identification method based on deep learning comprises the following steps: step 1, acquiring seismic wave signals to obtain original data, and performing center interception and normalization processing to obtain unified signals; 2, decomposing a unified signal by using CEEMDAN to obtain a plurality of orders of intrinsic mode functions and residual components, carrying out coarse graining processing on each order of mode function according to a preset time scale parameter to divide into subsequences, constructing a similarity criterion through a fuzzy membership function, calculating fuzzy entropy values of the subsequences, and integrating the fuzzy entropy values into a feature matrix; and 4, inputting the feature matrix after the dimension reduction into a CTCM-1D-CNN model optimized by a tribe competition and member cooperation algorithm, predicting the type of an output seismic wave, and completing seismic wave identification. Therefore, the design has good seismic wave identification precision and stability.
Owner:HUBEI EARTHQUAKE ADMINISTRATION (SEISMOLOGY RES INST OF CHINA EARTHQUAKE ADMINISTRATION)
Photovoltaic grid-connected box electric energy quality monitoring system based on Internet of Things data acquisition
The invention relates to the technical field of intelligent monitoring and fault diagnosis of a photovoltaic power generation system, in particular to a photovoltaic grid-connected box electric energy quality monitoring system based on data acquisition of the Internet of Things. Comprising an environment perception and time domain synchronization unit which is used for triggering sampling by using a unified clock source and generating a full-dimensional synchronous original data stream; the ideal reference physical reconstruction unit is used for calculating a theoretical output amplitude envelope and generating an ideal state reference vector; the fault mechanism parameterization evolution unit is used for converting the fault mechanism into a fault operator, selecting a high-risk fault mode according to the current operation condition, and superposing the corresponding fault operator onto the ideal state reference vector to generate a theoretical damaged state waveform; the double-rail-difference manifold extraction unit is used for obtaining a real residual vector and a theoretical fault residual vector; and the isomorphic feature coupling judgment unit is used for calculating the similarity between the real residual vector and the theoretical fault residual vector. According to the invention, the robustness of power quality monitoring under complex meteorological conditions is significantly improved.
Owner:SICHUAN ABA JINCHUAN HUADIAN NEW ENERGY CO LTD
Sensing data intelligent recommendation system
PendingCN120929667ADigital data information retrievalSpecial data processing applicationsPersonalizationData acquisition
The invention relates to the field of artificial intelligence and personalized recommendation, and discloses a sensing data intelligent recommendation system. The system comprises a perception data acquisition module, a multi-dimensional feature analysis module, a user portrait construction module, an intelligent recommendation decision module and an enhanced feedback optimization module. The method comprises the following steps: acquiring original data through a multi-source sensing device, and extracting multi-dimensional statistical characteristics after standardization processing; a user portrait model is constructed in combination with user historical behaviors, candidate recommendation vectors are generated, a recommendation strategy is dynamically optimized based on user feedback, efficient, accurate and personalized recommendation results are achieved, and the method is suitable for complex application environments such as intelligent interaction, mobile terminals and intelligent scenes.
Owner:HUAIAN JIASHUO TECHNOLOGY CO LTD
Virtual power plant optimization control system based on source network load storage cooperation
PendingCN121308079AAc network load balancingAc network voltage adjustmentData acquisitionMulti source data
The invention relates to the technical field of virtual power plants, and discloses a virtual power plant optimization control system based on source-grid-load-storage collaboration, which comprehensively acquires and preprocesses wind and light output, load, weather and power grid operation data through a multi-source data acquisition module, provides accurate original data for error analysis, and improves the accuracy of the system. The prediction error space-time correlation analysis module mines space correlation and time self-correlation characteristics of errors and generates an error scene set containing correlation characteristics, the source load scene library module combines with the error scene set to update and form a dynamic scene library containing risks, and the robust optimization scheduling module carries out robust optimization scheduling on the basis of the dynamic scene library. A scheduling scheme is solved by taking economy and robustness as targets, and a real-time scheduling execution module is linked with a system monitoring feedback module, so that error perceptibility, scene dynamic updating and scheduling adaptive adjustment are integrally realized, the ability of a virtual power plant to deal with uncertainty is improved, the economy and power grid stability are guaranteed, and the method is suitable for large-scale popularization and application. And the reliability and competitiveness of system operation are enhanced.
Owner:INNER MONGOLIA ELECTRIC POWER (GRP) CO LTD TRAINING CENT
Anti-interference control method and system for Mecanum wheel omnidirectional robot
The invention discloses a Mecanum wheel omnidirectional robot anti-interference control method and system, and relates to the technical field of robot anti-interference control, and the method comprises the steps: collecting multi-source original data, and carrying out the preprocessing; multi-source data fusion is carried out, a current operation condition is identified based on a fusion result, and an augmented state is generated; calculating a baseline control instruction; inputting to the reinforcement learning agent, and outputting a corresponding compensation instruction; adding the baseline control instruction and the compensation instruction to obtain a candidate control instruction; inputting to the security constraint projector, and correcting to obtain a final control instruction; issuing to a motor driver of the Mecanum wheel for execution; and actual state data of the executed robot is collected as execution feedback data, and the execution feedback data and a new target instruction are used for generating standardized observation data at the next moment. According to the invention, cross-working-condition high-precision, fast-recovery, low-energy-consumption and compliant-constraint omnidirectional chassis anti-interference control is realized, and the tail robustness and the system safety and reliability are improved.
Owner:JINAN VOCATIONAL COLLEGE
Engineering project management digital model generation method and device, equipment and medium
The invention provides a method, a device, equipment and a medium for generating an engineering project management digital model, and the method comprises the steps: collecting original data related to engineering project features, carrying out the preprocessing, forming a standardized project data set, constructing a space-time reference frame based on the data set, fusing a multi-dimensional feature tensor of multiple engineering features, and carrying out the construction of a space-time reference frame. The method comprises the steps of generating a project progress node and an integrated feature tensor, fusing the project progress node and the integrated feature tensor to generate a multi-source association graph containing entity relationships and feature semantics, generating a verified engineering project management digital model according to the project progress node, the integrated feature tensor and the association graph, and dynamically updating and optimizing the model in response to change data in project execution. According to the method, the problems of data dispersion, lack of association and static stiffness of the model in a traditional method are solved, automatic construction and dynamic evolution from multi-source heterogeneous data to an intelligent decision-making model are realized, and the accuracy, real-time performance and intelligent level of project management are remarkably improved.
Owner:CISDI INFORMATION TECH CO LTD
Multi-source data fusion method based on AGV cooperative positioning
The invention relates to the field of data processing, in particular to a multi-source data fusion method based on AGV cooperative positioning, and the method comprises the steps: carrying out the collection and preprocessing of AGV positioning original data through multi-source sensor fusion, and obtaining a standardized feature value and a prediction parameter for cooperative updating; carrying out noise factor optimization adjustment by fusing the physical propagation characteristics and the ranging fluctuation information to obtain a UWB measurement noise variance subjected to preliminary dynamic correction; deviation risk identification is carried out through risk factor adjustment based on innovation consistency inspection, and a final dynamically corrected UWB measurement noise variance is obtained; constructing a variance matrix through the dynamic variance and executing filtering updating to obtain corrected AGV state estimation and variance; by optimizing a state estimation result and recursively inputting a prediction process, dynamic updating of multi-AGV cooperative positioning is realized, so that the stability and the overall performance of AGV positioning in a dynamic environment are enhanced.
Owner:ZHEJIANG YIQIAO SOFTWARE DEV CO LTD +1
Three-rotor flow meter device, control method and control system
ActiveCN120947758AVolume meteringVolume/mass flow by mechanical effectsControl systemControl engineering
The invention discloses a three-rotor flow meter device, a control method and a control system, the three-rotor flow meter device comprises a shell, a plurality of rotors and a data acquisition unit, and the data acquisition unit is used for acquiring multi-modal data such as front and back pressure difference, medium temperature, absolute viscosity, vibration spectrum and rotating speed of the rotors in real time. The control system carries out real-time fusion and processing on collected original data through a decision making unit, calculates simulation slip flow based on a digital twinning dynamic compensation model, and corrects pulse equivalent in real time through an execution unit, so that high-precision dynamic compensation of flow output is achieved, and it is ensured that measurement errors are always within a preset range. Meanwhile, the system has an intelligent early warning function, and early fault diagnosis and predictive maintenance can be realized based on multi-parameter threshold comparison. According to the three-rotor flow meter, the measurement precision, stability and reliability of the three-rotor flow meter under the complex working condition are remarkably improved, and the three-rotor flow meter is particularly suitable for flow measurement under the high-viscosity medium condition.
Owner:XIAN INT INSTR MEASURE & CONTROL EQUIP
Power system data integrity verification system based on dynamic data block division mechanism and block chain
The invention discloses a power system data integrity verification system based on a dynamic data block division mechanism and a block chain. The system comprises a data preprocessing module, a hash generation module, a block chain storage module and a verification processing module. The data preprocessing module divides original data into data blocks with dynamically adjustable sizes; the Hash generation module adopts an iterative Hash algorithm to generate a chain Hash structure and an integrity Hash abstract; the block chain storage module uploads the hash data to a block chain network through a smart contract; and the verification processing module outputs a verification result by recalculating and comparing the hash values. The system realizes efficient and reliable data integrity verification, and has the advantages of high storage efficiency, good verification precision and low system load.
Owner:ELECTRIC POWER SCI & RES INST OF STATE GRID TIANJIN ELECTRIC POWER CO +2
Fire scene spreading time sequence reconstruction method and system based on Doppler weather radar mountain fire echo
The invention relates to the technical field of forest fire monitoring and power grid safety prevention and control, and discloses a fire scene spreading time sequence reconstruction method based on Doppler weather radar mountain fire echoes, which comprises the following steps: acquiring original data of the Doppler weather radar mountain fire echoes and carrying out quality control processing to obtain radar echo data; performing automatic segmentation of a smoke plume area on radar echo data by adopting an optimized Otsu-Unet network model, and extracting a centroid coordinate of a mountain fire echo area; a Kalman filtering algorithm is used and combined with external three-dimensional wind field data to predict a future motion trend of centroid coordinates of a forest fire echo region so as to reconstruct a continuous fire scene spreading time sequence voxel sequence; performing 3DTiles slicing processing on the fire scene spreading time sequence voxel sequence, and performing real-time rendering display on a power grid monitoring platform by using a WebGL technology; and obtaining an external expansion boundary of fire scene spreading based on the fire scene spreading time sequence voxel sequence, and calculating the distance between the external expansion boundary and the power transmission line GIS data in real time. The fire prevention and control capability of the power transmission line of the power grid is improved.
Owner:STATE GRID SICHUAN ELECTRIC POWER CORP ELECTRIC POWER RES INST
AI model intelligent training and reasoning integrated method and system
The invention provides an AI model intelligent training and reasoning integration method and system, and the method comprises the following steps: receiving a model training instruction, and carrying out the preprocessing of original data, and obtaining a training data set; executing model training based on the training data set, monitoring task priorities and resource requirements through a dynamic resource scheduling algorithm, and dynamically adjusting training resource allocation according to a real-time monitoring result; when the model reaches a preset performance index, performing model pruning and quantification to generate an optimization model, and performing parameter fine tuning on the optimization model to obtain a final deployment model; generating reasoning service configuration according to calculation characteristics of the final deployment model, migrating the model and the configuration to a reasoning environment, and starting reasoning service; and dynamically adjusting the number of reasoning nodes according to the real-time network flow of the reasoning service. By implementing the technical scheme provided by the invention, through bidirectional dynamic resource scheduling and model deep optimization, the computing resource utilization rate and the model deployment efficiency are improved, and the high availability of the reasoning service is guaranteed.
Owner:BEIJING HIZHI TECH CO LTD