166 results about "Information space" patented technology

An intelligent analysis method based on medical document structure perception and multi-modal fusion comprises the following steps: carrying out structure topology modeling on a medical document, extracting visual layout, text meta-information, space coordinates and semantic keyword features, constructing a semantic topological graph and dynamically shielding irrelevant contents; selecting an extraction path according to a document type, performing deep semantic analysis and entity recognition on a text-type document, and performing visual enhancement OCR recognition on a scanning-type document; the features are injected into a medical knowledge graph, and feature fusion, semantic verification, relation reasoning and information completion are achieved through a graph neural network; a three-stage strategy optimization model of basic pre-training, domain adaptation and online reinforcement learning is adopted; and large-scale processing is realized through a dynamically aggregated distributed architecture. The method is used for intelligent analysis and structured conversion of documents of hospitals, medical insurance and medical scientific research. The problems that heterogeneous medical document analysis adaptability is poor, multi-modal fusion is difficult, medical knowledge utilization is insufficient, and large-scale processing efficiency is low are solved.

The invention discloses a patent disclosure auxiliary writing method and system based on multi-agent collaboration. The method comprises the steps that a multi-agent system composed of a collaboration agent, an agent agent and an expert agent is constructed, a knowledge base and a decision module of each agent are configured, and a collaboration architecture of a task scheduler, an arbiter and a shared information space is established; the method comprises the following steps: receiving an original technical scheme of a user, and constructing a structured intermediate representation through multi-agent parallel semantic analysis and feature extraction; based on the representation, a writing task sequence is generated through dynamic task decomposition, intelligent agent division is coordinated through a contract network protocol, and content generation and verification are completed based on a multi-round debate mechanism; performing multi-dimensional consistency detection on the generated draft, and eliminating logic conflicts and expressing defects through iterative revision; and finally, an interest portrait is generated based on the user technical scheme and the optimized draft, interest retrieval is performed, a technical content report is output, and the efficiency and quality of disclosure book writing are improved.

The invention relates to an offshore wind power operation environment scene construction method considering typhoon forecast errors. The method comprises the steps of selecting similar historical typhoon forecast data according to current typhoon forecast information; based on wind speeds of similar historical typhoon forecast and current typhoon forecast, combining marine environment element information to construct a marine environment scene information space; a kernel density estimation model of historical typhoon wind speed forecast errors is constructed, corresponding kernel density bandwidths are calculated and updated according to different typhoon forecast timeliness, and historical forecast wind speed error distribution is obtained; and inputting the marine environment scene information space and the historical forecast wind speed error distribution into the improved generative adversarial network, and generating a marine environment scene of which the wind speed interval meets the historical typhoon wind speed forecast error distribution through the wind speed interval constraint loss. Compared with the prior art, the marine environment scene is updated according to the wind speed error distribution under different forecast time periods of the typhoon, and the scene generation quality is improved.

The invention discloses a weak light image enhancement method and device, equipment and a storage medium, and relates to the technical field of image enhancement, and the method comprises the steps: obtaining a to-be-enhanced image and a target normal illumination image, and optimizing an initial image enhancement model to obtain a target image enhancement model; performing feature extraction and manifold distribution estimation on the target normal illumination image by using the initial image enhancement model to obtain first distribution manifold information; performing feature extraction and manifold distribution estimation on the to-be-enhanced image by using the target image enhancement model to obtain second distribution estimation information; fusing the first distribution manifold information and the second distribution estimation information by using a target image enhancement model, and establishing a mapping relation between target high-dimensional feature information vectors and feature information vectors by using the target image enhancement model based on a fused target high-dimensional manifold information space; and obtaining a target projection and target manifold distribution according to the mapping relationship, and decoding the target manifold distribution by using a decoder to obtain a target image enhancement result. And image adaptive enhancement is realized.

The invention discloses a zero-trust API dynamic access control method, a computer device and a medium. The method comprises the following steps: processing all collected original identity information of a user in different systems through a preset aggregation strategy, and generating a unified decentralized digital identity label of the user based on a block chain; a basic governance structure of DAO is configured on a block chain network, and based on the structure, an initial access strategy corresponding to each user is determined in a DAO member voting mode; acquiring multi-dimensional information for initiating access, and performing multi-dimensional risk assessment on the multi-dimensional information including time dimension information, space dimension information, equipment dimension information and network dimension information based on a preset multi-dimensional weight to obtain comprehensive risk assessment information; and obtaining an access control strategy according to the comprehensive risk assessment information and the initial access strategy. The method can adapt to rapid identity authentication in different service systems and security environments, and is high in flexibility and security.

The invention discloses a thyroid nodule benign and malignant prediction method based on automatic segmentation and semi-supervised learning. The thyroid nodule benign and malignant prediction method comprises the following steps of data set establishment, image preprocessing, thyroid nodule segmentation model training, mask and image fusion processing, thyroid nodule benign and malignant classification model training and semi-supervised learning model construction. According to the method, the thyroid nodule effective area is segmented firstly, subsequent benign and malignant classification tasks are assisted, and information space is expanded and learned through semi-supervised learning, so that the problems of high medical image marking cost, insufficient data and limitation on deep learning model performance in the prior art are solved; and meanwhile, the second-generation basic model of the sliding window layered visual converter after mixing fusion is carried out on the basis of pre-training and by using the nodule region generated by the thyroid segmentation model realizes good performance, and high-precision thyroid nodule benign and malignant classification prediction can be realized.

A video compression system and method integrates geometric compression with cognitive understanding through a persistent cognitive machine interface. The system employs a hierarchical encoder generating multi-scale compressed representations organized within a Lorentzian manifold structure. A geometric processor maintains temporal causality through time-like geodesics and light cone constraints while organizing video content according to semantic relationships. A cognitive interface creates thought bundles as navigable submanifolds, enabling semantic access to compressed content beyond traditional temporal indexing. The system supports real-time processing through progressive refinement, streaming coarse representations immediately while adding detail in parallel. Symbolic anchors mark semantically significant points, enabling concept-based navigation through compressed video. Federated learning capabilities allow distributed systems to share geometric patterns while preserving content privacy. The architecture enables improved compression ratios while maintaining both temporal causality and semantic navigability, transforming video from sequential media into an intelligently accessible information space.

The invention relates to the technical field of geographic information big data processing, and discloses a geographic information space-time big data real-time aggregation and cleaning method based on edge computing, and the method comprises the following specific steps: S1, deploying edge computing nodes in a geographic information collection terminal coverage area, constructing an edge computing network, an acquisition terminal pushes original geographic information spatio-temporal data including geographic coordinates (x, y, z), an acquisition timestamp t and attribute information to an edge node through a protocol, and the edge node establishes a data buffer queue and preliminarily classifies and stores the data according to a spatio-temporal dimension. According to the geographic information space-time big data real-time aggregation and cleaning method based on edge computing, efficient and low-delay transmission of geographic information space-time big data is achieved through edge computing node deployment and a multi-algorithm fusion aggregation cleaning strategy, and the bandwidth and delay problems of a traditional centralized architecture are solved; multi-dimensional collaborative cleaning (geographic constraint, statistics and machine learning) is combined with an intelligent algorithm, and abnormal data are accurately recognized and processed.

The invention provides a textile flexible production line multi-material scheduling system, which comprises a physical execution layer and a multi-material scheduling layer, wherein the physical execution layer comprises reconfigurable textile production equipment; the intelligent sensing layer is arranged at key nodes of the physical execution layer; the central scheduling and control layer is in communication connection with the physical execution layer and the intelligent sensing layer; and the digital twin layer is a virtual mapping of the physical execution layer in an information space, and forms a closed loop with the central scheduling and control layer and the physical execution layer. According to the method, the perspectiveness and the global optimization capability of a scheduling decision are realized through a digital twinning technology, the system places an initial production scheduling scheme in a high-fidelity virtual production line model for millisecond-level concurrent simulation deduction, and potential process bottlenecks and quality risks during blending production of different materials are accurately predicted; and by taking the production efficiency, the energy consumption and the quality qualification rate as multi-target reward functions, completing iterative optimization of massive strategies in a virtual space, thereby obtaining an approximately globally optimal scheduling instruction before the physical production is put into use.

The invention discloses a disease risk assessment method and screening device based on a multi-group student physical collaborative digital network, and relates to the field of intelligent medical detection. In order to solve the defect that multi-omics-level system collaborative analysis and robust risk assessment are difficult to realize in the prior art, the technical scheme provided by the invention is as follows: acquiring a plasma sample, acquiring a spectral signal by adopting an attenuated total reflection Fourier transform infrared spectrum, and establishing a plasma spectrum digital information space; the method comprises the following steps: constructing a biological collaborative digital network containing four nodes of protein, lipid, saccharides and nucleic acid based on pathophysiology priori knowledge, and defining node strength, edge weight and network collaborative efficiency; a health baseline configuration file is established by using a health sample, a standardized deviation score of a to-be-tested sample is calculated, a comprehensive risk score is obtained, a disease screening result is output in combination with a machine learning model, and digital evaluation of multi-omics collaborative characteristics is realized. The method is suitable for non-invasive rapid screening and risk assessment work of neurodegenerative diseases and mental diseases.

The invention discloses a multi-branch power distribution network fault positioning method and system based on multi-dimensional fault characteristics. The method comprises the following steps: acquiring fault voltage traveling wave waveform data; performing phase-mode transformation on the waveform data to extract a line-mode component, extracting wave head coordinates, amplitude and slope information of a fault traveling wave in a set time window, and after redundancy elimination, determining a feature matrix, an adjacent matrix and an edge feature tensor based on a wave head information space so as to construct a multi-dimensional fault feature space; constructing a section identification model and a precise positioning model, and performing hyper-parameter tuning on the models by adopting a parameter-setting-free harmony search algorithm; and whether fault section positioning is carried out is judged based on the multi-dimensional fault feature space, if yes, the multi-dimensional fault feature space is input into a section recognition model to obtain a section recognition result, and if not, the multi-dimensional fault feature space is input into a precise positioning model to obtain a positioning result. And dual targets of power distribution network fault section identification and accurate positioning are realized from two aspects of multi-dimensional fault feature space extraction and a power distribution network fault positioning model.

The invention provides an abnormal event positioning model training method, an abnormal event positioning method, an abnormal event positioning device and abnormal event positioning equipment. The abnormal event positioning model training method comprises the following steps: acquiring a sample monitoring image and corresponding text description information; inputting a preset chain frame reasoning template, the sample monitoring image and the text description information into the initial visual language model for reasoning to obtain multiple groups of reasoning results corresponding to the sample monitoring image, and determining format reward information of each group of reasoning results according to a preset reasoning output format and an output format of the prediction bounding box; determining space reward information of each group of reasoning results according to the prediction bounding box and the real bounding box; determining semantic reward information of each group of reasoning results according to the prediction region features and text features of the text description information; according to the format reward information, the space reward information and the semantic reward information of each group of reasoning results, parameter adjustment is carried out on the initial visual language model, and a target visual language model is obtained and used for abnormal event positioning.

The invention provides a BIM-based electromechanical pipeline intelligent collision detection and automatic optimization adjustment method, which comprises the steps of analyzing a BIM model database, and extracting component information of electromechanical components; establishing a spatial index and an adjacency relationship between the electromechanical components, constructing a component spatial relationship database, and storing the component information, the spatial index and the adjacency relationship in the component spatial relationship database; calling data in the component space relation database to carry out multi-level collision detection; performing collision optimization adjustment on the electromechanical component based on a result after multi-level collision detection, and generating an optimized BIM model to be fed back to constructors; according to the method, the optimized BIM model is subjected to 3D display, meanwhile, a figure roaming scene is constructed, the moving view angle of a constructor in a building space is simulated, collision points are secondarily checked in the roaming process, the collision recognition precision can be improved through multi-level collision detection, collision conflicts are eliminated through optimization adjustment, design errors are reduced, and the engineering efficiency is improved.

The invention discloses a numerical control machine tool twin model moving body general construction and expression method, and belongs to the technical field of machine tool digital twin modeling, and the method comprises the following steps: constructing a numerical control machine tool assembly geometric model, and carrying out the splitting and lightweight processing of the model; determining the motion characteristics of each part of the machine tool and the relative motion relation among the parts, and performing over-mapping processing on the geometric model and the motion characteristics; constructing a machine tool twin model topology file comprising geometric features, motion features, state features and physical motion rules; and importing the three-dimensional model of the machine tool and the topological file into a three-dimensional engine, quickly constructing a twin model mapping a physical entity of the machine tool in an information space, and carrying out visualization processing. According to the method, the geometric features, the motion features, the physical motion rules and the like of the numerical control machine tool are uniformly expressed, so that the multi-axis numerical control machine tool twin model moving body in any structural form is quickly constructed.

The invention discloses a method for automatically reconstructing a complex BIM (Building Information Modeling) in a finite element platform, which relates to the technical field of finite element platforms and comprises the following steps of: acquiring geometric dimension information, spatial position information, physical parameter information and contact information of all final bodies in a model in the BIM platform; disassembling the final body to obtain Boolean operation of forming the final body by the basic body, and obtaining external calculation geometric feature information of the basic body, the process body and the final body; according to Boolean operation and external calculation geometric feature information obtained by disassembling the final body, selecting a corresponding body in the finite element platform to carry out Boolean operation, and reconstructing the final body; and selecting a corresponding final body to establish contact, and endowing the final body with corresponding physical parameter information. According to the method, geometric automatic reconstruction, contact automatic establishment and attribute automatic endowing of the BIM model in a finite element platform are realized.

The invention provides a prefabricated building component intelligent docking system based on a BIM model, and the system comprises a BIM model processing module which is used for importing the BIM model of a prefabricated building, and extracting the three-dimensional model information, geometric parameters and preset docking position information of each prefabricated component; the component sensing module is used for collecting actual position information and space attitude information of the to-be-butted component in real time; the data processing and analysis module is used for performing comparative analysis on the actual position information and the space attitude information of the to-be-docked component and preset docking position information in the BIM model, and calculating position deviation and attitude deviation; and the docking control module is used for generating an adjusting instruction according to the position deviation and the attitude deviation. According to the invention, precision limitation of traditional manual docking is broken through, intelligent management and control of the component docking process are realized, and docking precision and efficiency are improved.

The invention discloses a multi-intersection traffic signal control method fusing non-neighborhood information space-time perception. Traffic signal control of multiple intersections is optimized by adopting a reinforcement learning strategy, each intersection is used as a reinforcement learning agent, and space and time sequence characteristics of each intersection are extracted as state information. Non-neighborhood information spatial-temporal characteristics of multiple intersections are realized by using a non-neighborhood spatial characteristic enhancement graph transformer and a two-way multi-head cross attention mechanism to perform action decision, optimal control of a multi-intersection traffic network is realized, and spatial-temporal association of traffic flow and global road network situation awareness are realized.

The invention provides a construction progress intelligent dynamic identification and modeling method based on laser radar fused binocular and depth camera data. The method comprises the following steps: data acquisition: acquiring a construction site two-dimensional RBG image and three-dimensional point cloud data containing construction progress information through a multi-mode construction progress data acquisition system; performing data processing and analysis: performing fusion processing on the acquired two-dimensional RBG images and three-dimensional point cloud data by using a construction state recognition algorithm based on artificial intelligence, recognizing type information, spatial position information and time feature information of the components, performing construction progress quantification based on spatial volume difference to obtain construction progress information of each component, and performing data processing and analysis; forming a component point cloud data set; and performing three-dimensional progress dynamic reconstruction based on the building information model: dynamically reconstructing the progress information through the building information model BIM by using the component point cloud data set. According to the invention, dynamic and accurate evaluation and scientific guidance of the construction progress are realized through unmanned, intelligent and three-dimensional visualization means.

Apparatus and methods are provided for CSI enhancement for multi-TRP coherent joint transmission. A user equipment (UE) receives signals from a plurality of transmission and reception points (TRPs). The UE determines, based on the signals, multiple TRP (multi-TRP) coherent joint transmission (CJT) channel state information (CSI) report information for a codebook based on a spatial basis selection matrix, a combination coefficient matrix, and a frequency basis selection matrix. The spatial basis selection matrix is layer common, polarization common, and TRP independent. The UE reports, to one or more of the plurality of TRPs, the multi-TRP CJT CSI report information.

The invention belongs to the technical field of distributed computing and data twinning, and provides a digital twinning method and system for the industrial Internet of Things, and the method comprises the steps: obtaining a multi-dimensional dynamic mapping model and a multi-modal time series data flow of a physical entity in the industrial Internet of Things in an information space; edge-cloud collaborative processing is carried out on the obtained multi-modal time series data flow, and fusion data used for driving the multi-dimensional dynamic mapping model is generated; performing hierarchical architecture deployment on the generated fusion data based on containerized micro-service; performing closed-loop control of industrial Internet of Things interruption on an edge side close to a physical entity by combining the obtained hierarchical architecture deployment and fusion data; and performing cloud data processing of the physical entity according to a closed-loop control result, and establishing a maintenance mechanism in which the edge and the cloud are synchronous and consistent, thereby completing digital twinning oriented to the industrial Internet of Things.

This application relates to the field of quality inspection technology, and discloses a method for human-machine interaction assembly quality inspection of a theodolite-type spaceborne laser coarse pointing mechanism based on HCPS. In the design stage, a design scheme is generated based on design requirements; in the manufacturing stage, the similarity of production tasks and the skill levels of manufacturing personnel are evaluated, tasks are matched with corresponding skills through strategy transfer, combined with AI technology and diverse interaction modes, feedback from manufacturing personnel is continuously collected and an adaptive strategy for human-machine interaction is implemented, and incremental learning based on events or historical data is autonomously carried out through a human-machine collaboration system; in the assembly stage, when the coarse pointing mechanism is assembled using equipment in physical space, based on the support of the information space, the quality of all components is checked before assembly; in the inspection stage, a test workstation is set up to offset the gravity influence of the mechanical structure, multiple parameters are measured, and the assembly quality is determined according to corresponding inspection principles. This application is based on human-machine collaborative CPM assembly quality inspection to ensure accuracy.

The invention relates to the technical field of data security management, and discloses a security management system for data access control. The system comprises an access request receiving unit, a hierarchical analysis unit, a space mapping unit, a permission decision unit and a permission execution unit. The access request receiving unit obtains a data access request of a user, and analyzes a request main body identifier and a request resource identifier. The layering analysis unit carries out layering processing on the resource identification and extracts resource level feature information. And the space mapping unit retrieves the historical access log according to the main body identifier, and constructs an access behavior space distribution model. And the authority decision-making unit generates a dynamic access authority strategy in combination with the resource level characteristics and the access behavior space model. And the permission execution unit controls the access operation of the user to the resources according to the strategy. The system can adapt to a complex data resource structure and realize fine-grained dynamic access control.

The invention relates to the technical field of soil remediation, in particular to a contaminated site soil remediation amount optimization determination method based on multi-source monitoring data fusion, which comprises the following steps: acquiring a drilling position and in-situ data, extracting a pollution boundary, identifying a low-lying area and a pollution overlapping area, calculating a pollution cumulant, and dividing remediation types. According to the method, the in-situ concentration and apparent resistivity data are collected, a unified depth splicing structure is constructed, pollution information space fusion is achieved, the recognition precision is improved, mutation points are extracted, a three-dimensional grid is generated, and the integrity and adaptability of boundary reconstruction are enhanced; the method combines elevation and slope direction data to identify a low-lying catchment area, judges a migration trend, accurately captures a high-risk block, calculates cumulant according to pollution concentration and volume, determines different pollution levels, fuses terrain and pollution load features to extract sorting indexes, optimizes resource allocation efficiency, and promotes conversion from restoration to precise treatment.

The invention discloses a rural sewage treatment station inspection management control system based on an intelligent wearable terminal. The system generates a first preset path based on inspection task requirements and environment distribution information through a path generation module, and guides an inspector to move according to the path through a sending module; the obtaining module collects position information and behavior characteristics of inspection personnel in real time. And the prompt module triggers a preset warning event according to the inspection data and sends prompt information. Meanwhile, the system optimizes path generation by adopting a preset multi-dimensional data analysis model, and realizes image information space positioning through a multi-view stereoscopic vision algorithm and the like. The system effectively solves the problems of difficulty in personnel monitoring, single equipment function and the like in rural sewage treatment station inspection, and can monitor the state of inspection personnel in real time, provide efficient communication and emergency support, improve the inspection efficiency and standardization, guarantee personnel safety and enhance the emergency response capability of the system in a complex environment.

The invention provides a remote sensing image road extraction method based on deep learning, a remote sensing image is processed through a trained generator to obtain a road segmentation map, and the generator comprises an encoder module, a decoder module, a multi-scale feature fusion module and an output module; wherein an enhanced decoder module is constructed in a decoder structure, multi-level semantics and information space are fused through an up-sampling path and a transverse connection path, and a channel attention and space attention mechanism is introduced into the decoder to enhance the attention capability to a road area; and unified alignment, channel compression and fusion are carried out on the output of each stage of the decoder through the multi-scale feature fusion module, so that the modeling capability of road structures with different widths and changeable forms is improved. According to the method, high precision and robustness are still kept under the conditions of complex background and weak supervision, the problems of road breakage, adhesion and wrong segmentation can be effectively relieved, and the method has good engineering application value and popularization potential.

The present application provides a kind of village area spatial function characteristic measure method based on multi-source geographic information data, comprising: obtaining the geographic information space data of regional space, pre-processing geographic information space data;Participatory evaluation method is used to data analysis to the pre-processed geographic information space data;The data after analysis is counted, and multi-source geographic information data is obtained;Multi-source geographic information data is fused;The accurate identification of regional production-life-ecological space is carried out to the data after fusion;According to the identification result, the spatial function measure index system based on production-life-ecology-vitality is constructed;Based on the spatial function measure index system, the function of the region is measured, and the space resource is distributed according to the measurement result;The present application focuses on village scale, and carries out household survey, and this research scale and method selection has unique advantage.

The application provides a goaf overburden strata settlement calculation method based on internal damage characteristics of overburden, and the method comprises the following steps: obtaining a detection image; determining a fractal description of a damage variable by using a digital image processing technology and a fractal box covering method according to the detection image; calculating a crack area distribution weight of overburden at different depths, and determining an optimal fractal box size according to a relationship between an information space dimension and a box covering fractal dimension; determining a fractal damage constitutive model by determining an overburden body damage factor according to the fractal description of the damage variable and the optimal fractal box size; calculating additional stress of overburden at different depths according to a stress balance principle, and calculating the settlement of overburden at different depths by using a layer summation method. By using the fractal damage constitutive relationship, the application constructs a goaf overburden strata settlement calculation model, so that the settlement of overburden at different depths is calculated, the calculation precision is improved, and the purpose of calculating the goaf overburden settlement by using the fractal theory is achieved.

The invention discloses an intelligent interactive door control system, and relates to the technical field of door control systems. An image acquisition module is used for acquiring image information in front of a door in real time; the space processing module is used for processing and analyzing the collected images and human body movement tracks, automatically identifying the identity of the visitor and judging behaviors; the voice interaction module is used for generating a voice conversation with a visitor; the control module is used for calling the voice interaction module to communicate with the visitor according to the recognition result of the space processing module; according to the invention, active and intelligent noise suppression is realized, and the interaction reliability in a severe acoustic environment is ensured. The core of the system is to break the barriers of vision and hearing, and the system can understand the meaning of speech by performing feature-level fusion on the visual information and the voice acoustic features, so as to make distinct and highly personalized responses. By bypassing strong dependence on a final text recognition result, fusion is creatively carried out on a feature level.

The application discloses a parameterized model construction method and device of a power distribution line and an application system, wherein the method comprises the following steps: acquiring account information, spatial position information and topology information of each power distribution device in the power distribution line; extracting model information of each point device from the account information, and constructing a three-dimensional model of the corresponding point device according to the model information; performing step-by-step segmentation on the power distribution line based on the topology information, obtaining a plurality of line sections, and generating section registration information corresponding to each line section; acquiring actual position information of each tower, and calculating actual position information of a wire hanging point corresponding to each tower according to the actual position information of the tower and hanging point information; calculating wire T junction position information on a branch tower, and obtaining actual position information of a wire corresponding to each line section. The parameterized modeling of the power distribution line and the visual presentation of the power distribution line based on the parameterized modeling are realized.

The present invention provides an intelligent management construction method and system for hydraulic metal structure equipment based on digital twin. The method includes: constructing a physical space including the physical environment of the water conservancy project and the physical entities of the hydraulic metal structures, and simultaneously constructing an information space including the twin environment of the water conservancy project and the digital twins of the hydraulic metal structures. The physical space and the information space interact through twin data including historical data, online data, and prediction data. By constructing digital twins of the hydraulic metal structure equipment and its operating environment, the present invention can achieve state monitoring, operation and maintenance, and safety assessment throughout the entire life cycle of the hydraulic metal structure equipment. The formed intelligent management system for hydraulic metal structure equipment has the characteristics of being well-organized, digitalized, integrated, and visualized, and can, to a certain extent, reduce the problems of inadequate safety monitoring, incomplete information integration, low resource regulation efficiency, and untimely risk warning during the operation and service of the hydraulic metal structure equipment.