25results about How to "Accurate decision" patented technology

The invention discloses an equipment fault prediction method and system, and belongs to the technical field of electric data processing. The method comprises the following steps: inputting state information of each component of equipment into a conditional generative adversarial network to generate time series data, and constructing a plurality of target maps with adjacency relations; time features and local graph features are extracted by using multi-branch convolution and a graph convolution structure of a convolution auto-encoder, and target graph features are obtained through splicing; performing channel weighting through a multi-scale attention module to obtain multi-scale image features; calculating cross attention weights among different target images and fusing the cross attention weights to obtain fused image features; and compressing the potential feature representation as a health index, constructing a health index time sequence, inputting the health index time sequence into a fault prediction model, and obtaining an estimated residual life of the equipment. According to the method, strong noise interference can be effectively filtered out, the problem of feature redundancy is solved, key degradation information is captured robustly, the equipment health state is accurately represented, and the residual life prediction precision is remarkably improved.

The utility model belongs to high -voltage electrical equipment monitoring technical field, concretely relates to a kind of integrated comprehensive monitoring system of high-voltage electrical equipment.Deployment multiple sensors on the upper portion of main transformer, distribution transformer, generator and other key equipment, realize the comprehensive monitoring of equipment operating condition.Monitoring camera and infrared thermal imaging camera collect video data, are transmitted to NVR hard disk video recorder and machine vision detection server by six kinds of shielded network cable;Electromagnetic oscillation sensor and filter are matched, data is sent to electromagnetic oscillation monitoring server by LoRa protocol;Partial discharge monitoring sensor and SF6 gas monitoring sensor respectively transmit data to corresponding algorithm server by TCP / IP protocol.Data processed by each algorithm server is transmitted to high-voltage electrical equipment online monitoring and diagnostic analysis system by optical fiber, the system integrates multi-source heterogeneous data, uses intelligent diagnostic technology to realize early hidden danger warning and fault diagnosis of equipment, and monitoring result is visualized by digital twin platform.

The invention discloses a corrugated paper production line virtual debugging and operation optimization system based on digital twinning. The system comprises a digital twinning building module, a multi-dimensional model building and training module, a dominant variable recognition module and a virtual debugging and optimization module. The digital twin construction module is used for acquiring physical entity data and operation condition data of a production line and constructing a digital twin consistent with the physical production line; and the multi-dimensional model construction and training module is used for synchronously constructing a multi-physical sensitive dimension model in the digital twin for key processes of a production line, and relates to the technical field of corrugated paper production. According to the corrugated paper production line virtual debugging and operation optimization system based on digital twinning, by constructing the digital twinning body and the virtual debugging module, the production process can be debugged and optimized in advance in a virtual environment, the debugging period of a traditional production line is remarkably shortened, and the debugging cost and risk in actual production are reduced.

The application teaching material updating relates to the technical field, discloses a kind of teaching material dynamic updating method, device, computer equipment and storage medium, the method includes: based on paper teaching material extraction knowledge point and corresponding knowledge chain;Get the evaluation result of this knowledge point and the average evaluation result of all knowledge points on knowledge chain;Determine the updating condition of knowledge point;Judgment updating condition corresponding update content whether touch paper update threshold, yes, then with the minimum printing total cost as constraint synchronous update paper teaching material and electronic teaching material, otherwise only update the knowledge point core content and corresponding case of electronic teaching material, and mark the location of update content in paper teaching material.The device, computer equipment and storage medium are all with the method corresponding.The application, realize teaching material updating from fixed cycle, one-sided decision, cost out of control to dynamic adaptation, accurate decision, economic and efficient change, let teaching material content can match the stability requirement of teaching, also can respond to the iterative change of industry technology.

The invention discloses a cooking process monitoring method and device, a storage medium and an electronic device, and relates to the technical field of intelligent equipment control, and the cooking process monitoring method comprises the steps: obtaining a food material image sequence in a target cooking process; obtaining a state recognition result of the target cooking process according to the dynamic fusion features of the food material image sequence; and performing cooking state regulation and control on the target cooking process according to the state recognition result and the cooking regulation and control strategy. According to the technical scheme, the dynamic change trend of the food material state in the cooking process can be accurately recognized, the accuracy and reliability of the recognition result are improved, an accurate control decision is made according to the dynamic change trend of the food materials, and the cooking effect is optimized.

This application discloses an intelligent companion robot and method for the elderly based on emotion recognition, relating to the field of robot control. It first uses video and audio data to make a preliminary judgment on the elderly person's external behavior, identifying the presence of negative states. Then, it compares real-time collected physiological data with a pre-stored personalized physiological baseline model for the user, thereby obtaining a quantified physiological abnormality score. Finally, through a gating fusion mechanism, this physiological abnormality score is used as the key judgment criterion: if the score significantly deviates from the baseline, it is determined to be physiological discomfort, triggering corresponding health monitoring actions; conversely, it is confirmed as an emotional problem, and emotional reassurance is performed. This method effectively avoids the risk of misjudging physiological discomfort as negative emotions, enabling the robot to deconstruct the true causes behind the appearance, thereby making accurate and safe decisions.

The invention discloses a payment aggregation channel management method based on an adaptive strategy. The payment aggregation channel management method comprises the steps of 1, collecting structured feature information of a payment transaction request and running state information of a payment channel; 2, performing normalization and embedded coding on the structured feature information; 3, constructing a payment channel structure chart; step 4, a structure embedding vector is generated through the improved GraphSAGE network; 5, constructing an improved Sugeno fuzzy model, and generating a scheduling priority score value and a scheduling intention label; 6, generating a payment transaction request scheduling strategy; 7, collecting transaction feedback information, and generating a channel performance index set, a comprehensive evaluation value and a channel evaluation grade; and step 8, updating the improved GraphSAGE network and the Sugeno fuzzy model, and optimizing a payment transaction request scheduling strategy. According to the invention, the intelligence, stability and adaptive decision-making capability of payment channel scheduling are improved.

The application relates to the technical field of network security, in particular to an abnormal network intrusion detection system based on FPGA and artificial intelligence. The system obtains and analyzes network message information of a network link entering the FPGA through a network perception unit, generates a data packet for AI intrusion detection model reasoning based on the obtained data information; an intrusion detection unit is constructed based on an AI model, outputs an intrusion detection result based on the input data packet, so that an intrusion response unit can more accurately determine a response processing mechanism based on the intrusion detection result and adjust the response processing mechanism; the analysis unit determines the intrusion detection state based on the detection rate in the preset period after the adjustment of the response processing mechanism, adjusts the corresponding parameters based on the intrusion detection state, generates AI detection model fine-tuning parameters, so that the intrusion detection state can be more effectively adjusted to be qualified. The application improves the abnormal detection efficiency of high-speed network traffic.

The embodiment of the invention relates to the technical field of intelligent driving, and provides a display method and device based on a driving scene, a medium and electronic equipment. The method comprises the steps of displaying a current rendering asset corresponding to a sensing object in a display screen based on a current rendering style; wherein the sensing object comprises at least one of a dynamic sensing object and a static sensing object; determining a to-be-applied risk level corresponding to the current driving scene based on the collected driving scene information; in response to the difference between the to-be-applied risk level and the current effective risk level, determining a target rendering style based on the to-be-applied risk level; and based on the target rendering style, determining a target rendering asset corresponding to the perception object, and displaying the target rendering asset in a display screen. According to the method provided by the invention, corresponding rendering styles and rendering assets can be adopted according to different risk levels, so that personalized visual experience and safety requirements in extreme scenes are effectively balanced.

The application relates to a robot autonomous navigation method based on local information, which comprises the following steps: step 1, a virtual navigation platform is built, an autonomous navigation model is designed, and training data of a virtual navigation process are collected; step 2, based on the training data, a deep reinforcement learning algorithm is used to train the autonomous navigation model; step 3, the trained autonomous navigation model is derived and encapsulated; and step 4, the encapsulated autonomous navigation model is applied to an actual navigation task. Compared with the prior art, the application has the advantages of high scene applicability and low calculation complexity.

The application discloses a kind of unmanned vehicle global environment exploration route planning method assisted by unmanned aerial vehicle, belong to the field of environment modeling and path planning.It includes: firstly, in outdoor environment, two-dimensional overhead picture of environment is acquired by unmanned aerial vehicle from air with large viewing angle, high mobility, rapidity and low cost mode, and the picture stream is obtained by panoramic splicing based on FREAK feature, obstacle segmentation is carried out based on Unet3+ neural network to obtain environment obstacle binary graph;Secondly, the passable area is extracted for the obstacle binary map, and the improved hierarchical Vino graph road network modeling method is further used to obtain the environment hierarchical passable network topology node graph;Then, the environment hierarchical passable network node graph constructed is converted into Euler graph by minimum weight matching mode;Finally, the exploration path of ground unmanned vehicle global environment is obtained by solving Euler loop for any starting point through improved Fleury algorithm.

The invention discloses a wood product dust risk prediction method and system, and relates to the technical field of industrial safety and disaster prevention and control. The method comprises the following steps: acquiring original data of each process parameter and historical dust concentration of a wooden product in real time; a multi-step preprocessing process including data cleaning, feature extraction, normalization processing, feature dimension reduction based on correlation analysis and the like is adopted; constructing a deep learning model based on an LSTM neural network to perform dust concentration prediction, performing automatic optimization on hyper-parameters of the neural network by using Bayesian optimization, and calculating dust risk factors such as dust intake, dust concentration forward change rate, average dust concentration and the like based on prediction data; and calculating a comprehensive risk value of each sample through combined weighting of an entropy weight method and an analytic hierarchy process, and finally outputting different risk levels corresponding to each sample and corresponding early warning strategies. According to the invention, the dust concentration of the workshop is accurately predicted, the dust harm is reduced, and the health of workers is guaranteed.

The application discloses a kind of based on digital ray technology's transmission line strain clamp nondestructive testing method, it is related to transmission line strain clamp detection field, method includes: collection strain clamp radiographic image and geometric dimension, stress and so on multidimensional parameter, data fusion is carried out by hypergraph structure, multidimensional heterogeneous strain clamp analysis model is calculated and analyzed in edge side using optimized hypergraph neural network and edge computing gateway, to visualize presentation detection result in the form of double screen linkage, while realizing intelligent diagnosis and defect early warning;The application provides an efficient, accurate and reliable solution for the intelligent operation and maintenance of transmission line strain clamp, effectively improves the safe operation level and operation and maintenance efficiency of power grid.

This invention discloses an AI-driven big data fusion-based anti-misoperation interlocking system for wind farm booster stations, relating to the field of anti-misoperation interlocking technology for wind farm booster stations. It includes a data acquisition module that collects real-time electrical parameters, operating status, and environmental parameters of the equipment, and uploads them after preprocessing; a big data fusion storage module that categorizes and stores multiple types of data according to a hierarchical strategy, optimizing access and retrieval; an AI intelligent analysis and decision-making module that integrates multi-source data to generate precise interlocking strategies; an anti-misoperation interlocking execution module that executes interlocking in a three-level mode and provides status feedback; a communication interaction module that achieves internal and external data interaction through a dual-mode architecture; a status monitoring module that monitors the operating status of each module and identifies faults; and an emergency handling module that initiates a response mechanism and restores operation after self-checking following fault resolution. This invention relies on AI and big data fusion technology, dynamically adapting interlocking thresholds to equipment and environmental conditions; supporting unattended operation and intelligent maintenance, providing reliable assurance for the safe operation of wind farm booster stations.

The application discloses a kind of knowledge base conflict decision system and method, belong to retrieval processing technical field, its system includes knowledge base retrieval module for according to user question to knowledge base is retrieved, obtains retrieval result;Conflict detection module is used to sequentially carry out semantic understanding, logic verification of natural language and physical rationality verification to the retrieval result, determine the global conflict index of the retrieval result, according to global conflict index determines the to-be-optimized retrieval result;Index calculation module is used to calculate the multi-dimensional index of the to-be-optimized retrieval result under different dimensions according to user question;Intelligent decision module is used to obtain the comprehensive index of the to-be-optimized retrieval result according to the weight to multi-dimensional index is weighted, according to the comprehensive index determines decision scheme.The application realizes authoritative conflict identification and adaptive accurate decision by the multi-layer conflict identification and adaptive multi-dimensional index weighting of retrieval result.

The application discloses an intelligent marketing document generation device and method based on multi-source data fusion, and the method comprises four processes: user instruction analysis, regular cleaning, model extraction parameter, Neo4j knowledge graph verification, and output of structured parameters; external data acquisition, parameter calling of a Baidu large model to collect data, de-duplication, semantic enhancement, and weighted screening of high-quality data; internal case processing, regular slicing of case storage, filtering, propagation calculation, multi-dimensional scoring, and generation of a CoT reasoning chain report; multi-modal output, format adaptation, data integration by a BART model, and output of a metadata document. The device and the method are coordinated, multi-source fusion, knowledge graph association and multi-modal conversion are realized, high-quality marketing documents suitable for multiple industries are efficiently generated, decision-making is supported, and the market response and output efficiency of enterprises are improved.

This invention provides a traffic situation perception method, device, electronic device, and storage medium, belonging to the field of intelligent transportation technology. The method includes: acquiring multi-dimensional heterogeneous data, including human-dimensional data, vehicle-dimensional data, road-dimensional data, and cloud-dimensional data; acquiring the target scene categories corresponding to the multi-dimensional heterogeneous data and determining the scene priorities corresponding to the target scene categories; dynamically configuring perception resources according to the scene priorities to obtain configured perception resources, which are used to characterize sensor sampling frequency, sensor cooperation mode, and redundant device on / off status; and performing traffic situation perception based on the configured perception resources to obtain traffic situation perception results. The above solution can achieve real-time and accurate assessment of traffic situations, providing lane-level refined information for traffic management departments, supporting accurate decision-making, and effectively alleviating road network congestion and accident risks.

This invention discloses a system and method for constructing earthquake-themed scenarios based on multi-source 3D GIS data, belonging to the field of 3D geographic information system technology. It aims to solve the technical problems of data silos, limited information display, delayed data updates, and lack of end-to-end connectivity in earthquake emergency response. The system adopts a layered architecture consisting of a data resource layer, a data fusion layer, a service support layer, and an application display layer. The method involves building a basic 3D GIS emergency scenario, aggregating multi-source earthquake data, achieving spatiotemporal data fusion and event correlation, and completing integrated 3D display and decision support. This enables unified spatiotemporal fusion and real-time dynamic updates of earthquake data across all dimensions, as well as 3D visualization and spatiotemporal simulation of the entire pre-earthquake, during-earthquake, and post-earthquake chain. This provides global and three-dimensional decision support for earthquake emergency command, significantly improving the efficiency, accuracy, and systematic nature of earthquake emergency response.

The application provides an engineering vehicle lifting axle control method, device, electronic equipment, storage medium and engineering vehicle, and the method comprises the following steps: based on target data of the engineering vehicle at the current moment, obtaining the front-rear axle load ratio and longitudinal center of mass position of the engineering vehicle at the current moment and the center of mass dynamic change amplitude of the engineering vehicle at the current moment relative to the last moment; the target data of the engineering vehicle comprises deformation variable data of the axle housing of the engineering vehicle and running state information of the engineering vehicle; the running state information comprises acceleration information and slope information of the road; based on the front-rear axle load ratio and longitudinal center of mass position of the engineering vehicle at the current moment and the center of mass dynamic change amplitude of the engineering vehicle at the current moment relative to the last moment, a lifting axle action execution instruction is generated. The application improves the intelligent level of the engineering vehicle lifting axle control, can more accurately control the lifting axle under complex working conditions, and significantly improves the load balance and stability of the engineering vehicle during dynamic driving.

The invention discloses a fresh meat whole industry chain information fusion decision-making system based on digital twinning, and belongs to the technical field of fresh meat management. Target links of all link ends are identified according to industry chain information, and link acquisition ranges and additional acquisition ranges of the link ends are determined according to the target links; carrying out data acquisition according to the link acquisition range and the additional acquisition range, obtaining comprehensive acquisition data, obtaining a decision analysis demand of a user, and establishing a digital twinborn model according to the decision analysis demand; acquiring comprehensive acquisition data of each link end in real time; distributing additional acquisition data in the comprehensive acquisition data to the corresponding basic link parties to obtain link acquisition data of each basic link party; and performing decision simulation analysis on the link acquisition data of each reference link party based on the digital twin to obtain a decision analysis result of each decision analysis demand, and performing association simulation analysis on the link acquisition data of each basic link party to obtain a data real result of a corresponding data item.

The invention discloses an ecological sensitive area construction disturbance threshold value dynamic regulation and control method, which comprises the following steps of S1, acquiring basic environment data of an ecological sensitive area, and performing preprocessing; s2, according to the preprocessed basic environment data, constructing an initial construction disturbance threshold value system in combination with an environmental protection threshold value database, and determining ecological disturbance control references of different construction links; s3, multi-dimensional disturbance indexes in the construction process are monitored in real time based on the intelligent construction technology, the initial construction disturbance threshold value is dynamically corrected, and a construction disturbance threshold value dynamic regulation and control model is constructed; the invention relates to the technical field of ecological protection and engineering construction management. According to the dynamic regulation and control method for the construction disturbance threshold value of the ecological sensitive area, the disturbance index in the construction process is monitored in real time, the initial construction disturbance threshold value is dynamically corrected in combination with the ecological model, dynamic regulation and control of the construction disturbance threshold value are achieved, and the changing ecological environment condition in the construction process can be flexibly coped with.

The application relates to the technical field of electric digital data processing, and discloses a power inspection task unloading state coding method and system, which comprises the following steps: acquiring multi-modal original observation data collected by an inspection terminal in a power inspection task, and identifying key components and state information of a target power equipment based on an image analysis model; performing defect analysis on the key components to generate an evaluation result containing defect types and quantitative severity; fusing task calculation attributes, communication environment parameters and equipment resource states to construct a multi-dimensional state vector; performing normalization and vectorization processing on the dimensional features of the multi-dimensional state vector to output a state space representation for task unloading decision-making of a reinforcement learning intelligent agent. The application solves the problems of disconnection of general state coding, inaccurate decision-making and untimely response in the prior art, and achieves the purposes of precise decision-making, targeted response and energy efficiency improvement.

The invention provides an information management method and system based on an integrated management platform and electronic equipment, and the method comprises the steps: carrying out the preprocessing of original multi-source data collected by a preset interface, and carrying out the classified storage of the preprocessed data and the configuration data of the integrated management platform; judging whether the integrated management platform triggers hierarchical alarm or not based on the classified and stored data; if the integrated management platform triggers grading alarm, alarm information is generated based on a preset alarm grading processing strategy, the alarm is processed, and then root cause analysis is carried out based on the alarm information and the classified and stored data; and performing visualization based on the target data to generate visual information and displaying the visual information. According to the invention, the infrastructure, the application performance, the interface operation and the business log can be monitored in a centralized and classified manner, the fault positioning efficiency is improved, and related personnel can make accurate decisions based on the business data.

The application provides a rare earth ore multi-stage particle size dry screening separation control method and system, relates to the screening separation control technical field, acquires ore particle size data of target rare earth ore feed, determines a target feed particle size spectrum based on the ore particle size data; determines a multi-stage screening particle size state vector according to real-time discharge particle size data, performs screening detection according to the target feed particle size spectrum and the multi-stage screening particle size state vector, and obtains a screening deviation rate; determines a screen health index according to a screen characteristic vector, performs information fusion according to the screen health index and the screening deviation rate, and obtains a screening efficiency index of the target rare earth ore feed during dry screening; and determines a screening control strategy according to the screening efficiency index. The application can fuse process deviation and equipment state, realize adaptive optimization and precise control of the rare earth ore dry screening process, and thus improve the efficiency and stability of the rare earth ore dry screening process.

The invention provides an embedded large model decision control method and system fusing multi-modal sensing information, and relates to the field of intelligent decision control, and the method comprises the steps: receiving multi-modal data of a space non-cooperative target, carrying out the preprocessing and feature extraction of the multi-modal data, and obtaining a multi-modal sensing information fusion model; deep semantic fusion is realized through unified semantic space projection and a dynamic confidence weighting strategy, and a unified environment representation vector is output; constructing an input representation fusing a time sequence context, domain knowledge Prompt and a sample example, performing target intention recognition and risk level evaluation in stages through a lightweight deployed large model, and generating a structured decision strategy; a structured decision strategy is converted into a spacecraft motion instruction, and a target control sequence is solved through a designed simplified MPC controller. According to the method, the non-cooperative target sensing precision and the data utilization efficiency can be improved, the autonomous intelligent decision-making capability of the terminal is enhanced, and safe and efficient capture and on-orbit service tasks are supported.