8results about How to "Improve management accuracy" patented technology

The utility model discloses a portable intelligent substation microstation equipment inspection device, including front end equipment, back end equipment and cloud equipment. Front end equipment is handheld inspection terminal, and integrated main control board, camera, display screen, fingerprint identification, communication interface etc. parts are used for information collection and interaction, and cloud equipment includes equipment information database, fault log record library, solution library, and is connected with front and back end equipment through information interaction module, realizes data storage and scheme calling, and back end equipment includes video processing, state monitoring, fault prediction, personnel scheduling and information transmission etc. module, forms the automation inspection and fault processing process. The device has the advantages of flexible deployment, accurate identification, efficient response, and can improve the intelligent degree of inspection and the substation operation and maintenance efficiency.

The application discloses an intelligent conference management system and method based on a large model, relates to the technical field of intelligent conference management, and comprises the following steps: extracting and processing a project sequence of multiple conferences to obtain an enhanced representation of a current conference; recognizing audio data of the current conference to obtain a text segment sequence; projecting the text segment sequence and the enhanced conference representation to obtain a context-aware segment representation and calculate a dynamic importance weight to obtain a first candidate decision point set; iteratively compressing the first candidate decision point set through a double-constraint strategy to obtain a second candidate decision point set; for each decision point in the second candidate decision point set, extracting a feature vector of the decision point from multi-modal data of the current conference and projecting the feature vector into a projection vector; calculating a cosine similarity between the projection vectors to obtain a final confidence; and associating the final confidence with the corresponding decision point to obtain a third candidate decision point set.

This utility model relates to the field of film winding technology, and more particularly to an intelligent electric film winding machine, comprising: a mechanical drive mechanism, which includes a motor housing, a winding motor housed within the motor housing, a gearbox connected to the output end of the winding motor, and a rotating shaft driven to rotate by the gearbox; and a control mechanism, which includes a control housing and a control motherboard disposed within the control housing, on which a signal processing unit and a 4G communication module are integrated. This utility model, by setting up a control motherboard integrating a 4G communication module and a signal processing unit, solves the technical problem that traditional equipment cannot be remotely intelligently controlled and interact with data, achieving the technical effect of building the core of the Internet of Things and realizing comprehensive remote management.

The invention discloses a power distribution network demand response capability dynamic prediction and potential analysis method based on deep learning, and belongs to the field of intelligent power distribution network optimization, the method adopts a CNN-BiLSTM-Transform double-layer model for demand response capability dynamic prediction, and compared with a single traditional model, the method has the advantages that the dynamic prediction efficiency is improved, and the power distribution network demand response capability dynamic prediction and potential analysis efficiency is improved. The complex coupling relationship among the load, the weather and the excitation signal can be described more accurately; multi-dimensional demand response potential calculation is carried out, and a demand response potential source is systematically analyzed from the perspective of a distribution network side and a development trend according to response characteristics of different user types, so that comprehensive identification of adjustable resources is facilitated, and the management precision of a demand side is improved; a long-term and short-term demand response potential quantification mode based on a space envelope domain is provided, the space envelope domain is introduced to quantify the potential, a potential expectation value is obtained, potential changes under different time scales and influence factors can be represented in a unified form, and the defect that a traditional method only carries out qualitative analysis and lacks unified quantitative indexes is overcome.

This invention discloses a method, system, and device for identifying the working state of forging operations, relating to the field of industrial automation technology. The method includes: S1 acquiring multi-view images of the working area; S2 detecting core production components and auxiliary operation-related objects using a YOLOv11 target detection model; S3 generating multi-dimensional instantaneous state codes and mapping them to basic states; S4 constructing a state time series and analyzing the macroscopic working state using a hierarchical state machine; and S5 outputting state and statistical information. This invention supplements the YOLOv11 loss function, instantaneous state encoding, and state transition algorithm formulas, solving the problems of incomplete state definitions, missing transition state identification, and inability to finely identify auxiliary operations in existing technologies. It achieves accurate and robust identification of the entire forging production process, providing data support for lean production management, with low deployment costs and strong scalability.

The invention relates to the technical field of computers, and particularly provides a server management method and device, equipment, a medium and a product. The method comprises the following steps: acquiring target service load data of a target server; wherein the target service load data represents an association relationship between a service layer and a service layer corresponding to the target server; based on a pre-established power consumption model, determining target actual power consumption corresponding to the target server according to the target service load data; wherein the pre-established power consumption model represents a service layer corresponding to the at least one server, a mapping relationship among a server layer and a power consumption layer, the pre-established power consumption model is used for quantifying actual power consumption of each server in different service scenes, and the target server is a server in the at least one server; and dynamically managing the target server based on the target actual power consumption. By combining the relationship between the business layer characteristics and the service layer power consumption of the cloud computer, the server management accuracy can be improved.

This application provides a full-cycle management system for tunneling machine cutterhead hobs, comprising: a hob status tracking module for real-time tracking and recording of the position and mileage of each hob using a calibration-then-tracking method; a voice control module for obtaining the current measured wear value of the corresponding hob or controlling the rotation angle of the cutterhead based on voice information; a hob wear prediction module for real-time prediction of the current wear value of the hob based on a preset prediction model; an anomaly warning module for determining whether abnormal wear has occurred in the cutterhead hobs based on the wear value and issuing a timely warning when abnormal wear occurs; and a data processing and storage module for receiving and recording the data output from each module, and real-time matching and storing the hob data with surrounding rock parameters, tunneling parameters, and cutter maintenance status in a database. This application realizes full-cycle management of the cutterhead hobs from parameter acquisition, data processing and storage, wear prediction, anomaly alarms to auxiliary control for cutter inspection and replacement.

The invention relates to the technical field of digital twinning, in particular to an intelligent material storage management system based on digital twinning, and the system comprises a sensing module which is used for collecting storage index parameters and risk index parameters of target storage materials in a historical period; the analysis module is used for analyzing the storage index characterization value and the risk index characterization value; the evaluation module is used for determining whether target material storage meets a standard or not based on a difference result between the storage index characterization value and a preset storage index characterization threshold value; the prediction module is used for determining whether the target material meets a risk assessment standard based on a comparison result of the risk index characterization value and a predetermined risk index characterization value; the regulation and control module is used for determining a processing strategy based on a difference result between the risk indicator characterization value and a predetermined risk indicator characterization threshold value. According to the method, the risk assessment decision-making precision and efficiency of the digital twin technology are improved through adaptive regulation and control.