34 results about "Integration appliance" patented technology

The invention discloses an explosion-proof equipment full life cycle digital management system based on artificial intelligence, and relates to the technical field of equipment management. The working process of the system comprises the following steps: integrating equipment attributes, operation and maintenance records and environment variable data, calculating a performance attenuation value through a weighting formula, and standardizing the data; correcting an abnormal timestamp by adopting a dynamic time window, realizing cross-system equipment identity mapping in combination with Hash similarity and parameter matching degree, and reconstructing a three-dimensional feature tensor; equipment is divided into three types, and differential weighted pooling processing is executed to generate a classification feature matrix; a reference parameter curve is generated through exponential decay weighting, a normalized deviation score of the fusion environment factors is calculated, and a grading early warning mechanism is triggered; generating an early warning report; and implementing a closed-loop strategy according to the early warning level. The system solves the problems of equipment identity confusion, environment-parameter coupling quantification and the like, realizes full-chain intelligent management from data acquisition to risk disposal, and improves the safety and operation and maintenance efficiency of explosion-proof equipment.

The invention relates to the technical field of equipment fault intelligent diagnosis, in particular to an equipment fault intelligent diagnosis method and system based on a Modbus protocol. The method comprises the following steps: acquiring real-time operation data from target industrial equipment through a Modbus protocol, dynamically adjusting an initial sampling frequency based on an equipment operation state, and performing multiple verification and compensation correction on the acquired data to obtain a stable data stream; performing multi-scale decomposition and feature enhancement processing on the stable data stream, extracting a time-frequency domain mixed feature set, and constructing a feature evolution trajectory; inputting the feature evolution trajectory into a double-branch diagnosis model integrating equipment state prediction and fault classification, and outputting an equipment health degree score and fault type probability distribution; and constructing a dynamic fault threshold curved surface, carrying out multi-dimensional fusion decision by combining the equipment health degree score and the fault type probability distribution, and generating a graded fault early warning and maintenance strategy. According to the invention, the accuracy, timeliness and adaptability of industrial equipment fault diagnosis can be greatly improved.

The invention discloses a dynamic network access control method and system based on a zero-trust architecture, and the method comprises the steps: integrating equipment health degree evaluation through the triple dynamic binding of biological feature dynamic binding, equipment fingerprint salt value hash verification and environmental state perception, and constructing a real-time trust basis; dynamic risk quantification is realized based on a multi-source heterogeneous data fusion machine learning model, real-time upgrading and degrading self-adaptive adjustment of authority is realized through an AI driving strategy generation module according to a real-time risk score, a zero-trust sandbox limitation sensitive operation is triggered for high-risk access, and a minimum authority channel is started for low-risk access; performing fine-grained access control and intercepting an unauthorized request in real time by adopting an agent-free API gateway technology, and monitoring an operation behavior in combination with a block chain non-tampering storage access log and an anomaly detection algorithm; finally, a continuous self-adaptive evolutionary cycle is formed through a risk assessment-policy execution-abnormal feedback closed loop mechanism, and the static lag problem of traditional network access control is systematically solved.

The invention discloses a production batch digital archive generation and dynamic archiving method of integrated equipment real-time data, and relates to the technical field of informatization and data management. According to the method, the real-time performance and accuracy of a data source are ensured through automatic acquisition and situational identification of the equipment data; a non-repudiation credible evidence chain is constructed through man-machine data intelligent comparison and dual verification; activity and precision of quality control are realized through event driving and intelligent inspection triggering. Complete and consistent production batch digital twinning is formed through intelligent aggregation and structured generation of multi-source data; and finally, dynamic and credible management and full-process visual tracing of the archive are realized through physical digital twin binding and intelligent archiving. According to the closed-loop system, automatic and intelligent management of the whole production archive process from generation to utilization is achieved, and the production efficiency, the quality controllability and the supply chain transparency are remarkably improved.

Small and compact Deep Learning models are required for embedded AI in several domains. In many industrial use-cases, there are requirements to transform already trained models to ensemble embedded systems or re-train those for a given deployment scenario, with limited data for transfer learning. Moreover, the hardware platforms used in embedded application include FPGAs, AI hardware accelerators, System-on-Chips and on-premises computing elements (Fog / Network Edge). These are interconnected through heterogenous bus / network with different capacities. Method of the present disclosure finds how to automatically partition a given DNN into ensemble devices, considering the effect of accuracy—latency power—tradeoff, due to intermediate compression and effect of quantization due to conversion to AI accelerator SDKs. Method of the present disclosure is an iterative approach to obtain a set of partitions by repeatedly refining the partitions and generating a cascaded model for inference and training on ensemble hardware.

In some implementations, an integrated broadband network gateway (BNG) device can communicate management information with a particular distributed BNG user plane device. The integrated BNG device can communicate control packets with the particular distributed BNG user plane device. The integrated BNG device can communicate session control and state information with the particular distributed BNG user plane device. The management information, control packets, and session control and state information can be communicated via respective interfaces between the integrated BNG device and the particular distributed BNG user plane device. Thus, the integrated BNG device can provide a BNG control plane for the particular distributed BNG user plane device.

The invention provides an application system of equipment detection and inspection on a GIS mobile platform, and relates to the technical field of equipment detection, the application system comprises an architecture layer and a system layer, the architecture layer comprises a data source layer, a business service layer, a service container layer, a business system layer and a portal platform, the data source layer is used for integrating equipment detection data and associated business data, and the system layer is used for integrating equipment detection data and associated business data; constructing a unified data center; the business service layer provides data transparent access capability for a business system through a service interface; the service container layer comprises an enterprise service bus and a service combination module; according to the system, a layered architecture is adopted, functions of equipment detection, data acquisition, data analysis, early warning notification and the like are divided into independent units, system expansion and maintenance are facilitated, a cloud computing technology is utilized, a data center is built, centralized storage and processing of data are realized, a big data analysis technology is adopted, data are mined and analyzed, abnormal states are automatically identified, and the system is convenient to use. Early warning is carried out in advance, and overdue detection and missing detection of equipment are avoided.

The invention discloses an industrial equipment asset intelligent management system based on the Internet of Things, and relates to the technical field of industrial equipment asset management. According to the system, equipment asset cards, equipment health states, inspection, maintenance, repair, scrapping and warehouse management modules are integrated through a digital platform, and vibration and current data are collected and intelligently analyzed in combination with the Internet of Things; the problems that existing equipment management characters and processes are large in workload, information is prone to being lost, inquiry is inconvenient, data value is difficult to mine, and real-time monitoring of the equipment health state is insufficient are solved. The method has the beneficial effects that the workload of personnel is reduced, the equipment management efficiency is improved, the data asset value is mined, the equipment health state is controlled in real time, the operation stability is improved, and the equipment management and operation cost is reduced. The method is suitable for various industrial enterprises, and full-life-cycle management of equipment assets is achieved.

The invention relates to a whole-process anti-misoperation simulation method and system for a dispatching operation order, and belongs to the technical field of dispatching automation of a power system. Comprising the following steps: constructing a power grid equipment digital twinborn model library, and integrating equipment static parameters, real-time state quantity and an anti-error rule set; generating an initial operation order step sequence based on the scheduling instruction and the power grid topology constraint; operation ticket simulation rehearsal is executed step by step in the simulation environment; generating an anti-misoperation verification report according to the simulation result, and prompting to modify or confirm the operation order; in the operation order execution stage, the state of field equipment is collected through the Internet of Things terminal, and a simulation rehearsal result and practical operation data are compared in real time; establishing an operation order full life cycle anti-error file, and associating simulation data with an actual execution record; the defect that a traditional operation ticket system depends on manual checking and cannot dynamically pre-judge linkage risks is overcome, the misoperation accident rate is remarkably reduced, and the operation safety of a power grid is improved.

The invention provides a transformer substation multi-dimensional parameter non-contact measurement system, and relates to the technical field of power equipment monitoring. Comprising an equipment screening module, a path planning module, a measurement point marking module, a multi-mode non-contact sensor array, an edge calculation and data fusion module, a parameter measurement module, a parameter report module and a wireless communication and cloud platform module. According to the invention, by integrating equipment intelligent screening, path planning, non-contact multi-parameter measurement and edge computing technologies, efficient and accurate monitoring of the equipment state is realized; the system can adaptively select a measurement mode, generate an equipment health report and remarkably improve the operation and maintenance efficiency and safety of the transformer substation, and equipment screening, path planning and non-contact multi-parameter measurement are fused to form a closed-loop monitoring system, so that the integration efficiency of the system is improved; and the synchronous and asynchronous modes are adaptively selected according to the measurement coefficient, and the efficiency and the precision are balanced, so that the intelligence of the system is improved.

The invention discloses a real-time dynamic scheduling system and method for an industrial production line, and relates to the technical field of industrial automation control, and the system comprises a data collection and preprocessing module which comprises an Internet of Things sensor cluster and an edge calculation unit, and achieves the real-time collection and preprocessing of production data, and the real-time transmission of the production data to a cloud server; the dynamic evaluation and decision-making module is used for integrating an equipment state evaluation model, a task allocation algorithm and a path planning engine, calculating equipment availability based on real-time data, and generating an optimal task allocation scheme and a robot motion track; and the cooperative control and execution module comprises an equipment controller and a robot control cabinet, receives and executes the scheduling instruction, and feeds back an equipment state to the data acquisition and preprocessing module to form closed-loop control. Through multi-source data fusion and an intelligent algorithm, real-time dynamic scheduling of the industrial production line is realized, and the production efficiency and the flexibility level are effectively improved.

This invention relates to the field of power system technology and discloses a half-wavelength controllable tuning method under the background of dual-carbon and new power systems. The method includes: system assessment and demand analysis, collecting grid information and integrating the demands of dual-carbon and new power systems to determine tuning objectives and key parameters; half-wavelength tuning strategy design, using particle swarm optimization to determine tuning parameters, formulating strategies, and performing simulation optimization; selection and configuration of half-wavelength controllable equipment, evaluating performance indicators to select equipment and rationally configuring, installing, and debugging; system integration and communication network construction, integrating equipment and building a reliable communication network to ensure information transmission; and tuning implementation and monitoring, developing a control system to issue commands, collecting and analyzing data to evaluate performance, and optimizing based on the results. This invention enhances grid stability and adaptability, promotes intelligent development, optimizes resource allocation and structure, ensures safe and sustainable development, and can effectively address the challenges of dual-carbon and new power systems.

The invention relates to the technical field of artificial intelligence and wind power generation, in particular to a large-model-driven intelligent operation and maintenance decision-making method and system for a wind turbine generator, and the method comprises the steps: fusing sensor, text, vision and environment multi-dimensional data, and constructing unified representation through cross-modal feature alignment; combining a dynamic RAG engine to realize knowledge matching of timeliness weight optimization, and injecting a causal reasoning engine of domain constraint to analyze a fault logic chain; and finally, the equipment health degree, the meteorological window and the cost constraint are integrated to generate a Pareto optimal strategy, a'data fusion-knowledge enhancement-causal deduction-dynamic optimization 'closed-loop system is formed, accurate fault association and explainable diagnosis are realized, the operation and maintenance response efficiency is improved, and the full-life-cycle management cost is reduced.

The invention discloses a data center three-working-condition efficient condensation and heat recovery system and method based on a combined type heat exchanger, the core of the system is a single combined type heat exchanger, a fluorine path channel and a water path channel in the single combined type heat exchanger are thermally coupled through shared aluminum fins, and controllable distribution of heat of three media of Freon, water and air is achieved; a multi-working-condition cooperative control algorithm is built in the intelligent control unit, and the intelligent control unit comprises a working condition judgment module, an energy value evaluation module, a condensation pressure monitoring module, a heat recovery load calculation module, a fan intelligent cold supplementing module, a cooperative control module and a self-adaptive learning module. High integration of three functions of air cooling, water cooling and heat recovery is achieved, the number of devices is remarkably reduced, the occupied space of a machine room is remarkably reduced, the annual comprehensive energy efficiency ratio is greatly increased, the PUE of a data center is greatly reduced, the payback period is remarkably shortened, the annual carbon dioxide emission reduction effect is remarkable, and good economic benefits and environmental benefits are achieved.

The invention relates to the technical field of power system intelligent operation and maintenance and project acceptance, in particular to a power distribution network project intelligent acceptance method based on a multi-modal visual large model and a product. A device identification head, an OCR identification head and a space distance measurement head are integrated on a trunk of a visual large model, and a distance measurement result of the space distance measurement head is semantically associated with a device identified by the device identification head and a text identified by the OCR identification head, so that distance measurement is aligned with semantics, and the relevance between data is improved. After the acceptance rules and other existing industry rules are imported into the project acceptance rule engine, the model can associate the distance data, the equipment recognition result and the semantics of the rule base, and therefore the judgment capacity of the model when the model conducts judgment through the rule base is improved. Therefore, the technical problems that the information obtained by the existing acceptance method is fragmented and the automatic discrimination capability is weak are solved.

The invention discloses a property complaint submitting and intelligent order sending method and system, and relates to the technical field of property management, a plurality of data acquisition terminals are established to acquire resident related information, the resident related information is processed into corresponding complaint work orders, and the complaint work orders are stored in edge distribution equipment after data security protection is carried out on the complaint work orders. Constructing a data channel between each edge distribution device and the cloud integrated device, transmitting the complaint work order in each edge distribution device to the cloud integrated device through the data channel, deploying a work order pool at the cloud integrated device, carrying out feature analysis on the plurality of complaint work orders through the work order pool, and carrying out feature analysis on the plurality of complaint work orders through the cloud integrated device. According to the method and the system, the complaint work orders are acquired, a work order feature data set corresponding to each complaint work order is obtained, distribution operation is performed on the complaint work orders based on the work order feature data sets, matched property management personnel are matched to process each complaint work order, standard acquisition, safe transmission and accurate distribution of the complaint work orders are realized, and property management efficiency and resident satisfaction are improved.

The invention discloses a package digital soft proofing VR interaction system and method, and the system comprises a mobile terminal WebVR application which is provided with an interaction layer and a process simulation module; a cooperation and sharing module; and the intelligent recommendation module is used for carrying out packaging scheme recommendation. The 720-degree visualization and VR interaction technology of the mobile terminal packaging structure is achieved, the design iteration process is greatly accelerated, dependence on traditional physical sample piece manufacturing is reduced, the size deviation of a virtual sample piece and a final finished product is reduced, the accuracy of a design scheme is ensured, and through a multi-user real-time cooperative operation mode, the design efficiency is improved. Time delay and information deviation in traditional communication are reduced, meanwhile, by integrating VR / AR equipment, the immersive experience of previewing virtual packages in a real scene by a user is improved, and through an intelligent recommendation module, according to specific demand parameters input by the user and huge background package big data, the user can be recommended to the real scene. Therefore, a collaborative and sustainable packaging proofing digital interaction mode is constructed, and digital transformation and upgrading of the whole packaging industry are promoted.

The invention relates to the technical field of Internet of Things video monitoring, and particularly discloses a WebRTC video stream Internet of Things platform automatic access method based on an ONVIF protocol. The objective of the invention is to solve the problem that an RTSP video stream of ONVIF equipment cannot be directly played at a browser end and the delay is high in the prior art. Comprising the following steps: constructing a unified platform architecture integrating ONVIF equipment management, streaming media transfer and WebRTC signaling service; equipment is automatically found through an ONVIF protocol, an RTSP stream address is obtained, and then an RTSP video stream is converted into a media stream available for WebRTC; webRTC connection between the browser and the streaming media service is established through the signaling server, and low-delay playing of a video stream in the browser is achieved; meanwhile, an ONVIF control instruction is separated from a WebRTC video stream channel, so that the control delay is reduced; according to the method and the device, one-key access and low-delay watching of any equipment supporting the ONVIF protocol in the standard browser under the condition that a plug-in is not needed are realized, and the user experience and the system integration degree are remarkably improved.

The invention discloses a transformer substation remote visual operation and maintenance system and an exception handling platform, the visual operation and maintenance system is constructed based on a three-dimensional lightweight model of transformer substation BIM and laser point cloud fusion, and the exception handling platform is established by using a multi-source heterogeneous data intelligent analysis engine. The system comprises a four-layer architecture including a control layer, a network layer, a sensing layer and an application layer, a platform integrates equipment state diagnosis, fault prediction, AR remote cooperation and emergency decision, equipment association analysis is realized through a dynamic topology reconstruction technology, and cross-station abnormal migration learning is realized by using a federated learning algorithm. The method further improves the fault recognition rate, shortens the exception handling time, and reduces the manual inspection intensity.

An integration device is configured to execute: mount processing in which a virtual volume is created for each database and mounted to the storage location information; first generation processing in which, from the first table of each of the plurality of devices, the DB name and the storage location information are acquired, second generation processing in which, from the second table of each of the plurality of devices, the schema name, the table name, and the DB area ID are acquired, and third generation processing in which, from the third table of each of the plurality of devices, the DB area ID and the relative file path of the file are acquired, and a third integrated table is generated by associating the changed-to DB name, the DB area ID, and the relative file path with one another for each database.

1. The name of the design product: smart park management visualization graphical user interface for electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: the content displayed by the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: a visualization graphical operation interface for smart park management, which realizes accurate decision-making and efficient management of the park by integrating device data, spatial geographic information, and business system data. 7. The change process of the graphical user interface: after entering the username and password in design 1 front view and clicking "login", the interface jumps to design 1 interface change state diagram 1; click "intelligent security" in design 1 interface change state diagram 1, the interface jumps to design 1 interface change state diagram 2. After entering the username and password in design 2 front view and clicking "login", the interface jumps to design 2 interface change state diagram 1; click "intelligent management and control" in design 2 interface change state diagram 1, the interface jumps to design 2 interface change state diagram 2.

The invention discloses an enterprise brain dynamic decision-making system based on digital twinning, and relates to the technical field of intelligent manufacturing and industrial automation. According to the system, factory digital twin bodies are constructed through 3D modeling, equipment sensors and ERP, MES and QMS business system data are integrated, real-time interaction and visual monitoring of a physical scene and a virtual space are achieved, and refined management and control of the whole process of production equipment, material circulation and quality tracing are supported. The system utilizes historical data to train an AI model, has self-learning and self-adaptive optimization capabilities, can simulate the influence of market fluctuation on a production plan, dynamically adjusts resource allocation and a production scheduling strategy, remarkably improves the equipment utilization rate, shortens the production cycle, and enhances the quality tracing capability and the emergency response efficiency. According to the system, through virtual-real fusion and an intelligent decision-making mechanism, the limitation that a traditional production management system is lagged in response, data islands and decision-making depends on manpower is overcome, and real-time optimization and closed-loop management of the whole enterprise operation process are achieved.

The invention belongs to the technical field of remote monitoring of industrial equipment, and particularly discloses a remote monitoring system and method for digital shipyard workshop numerical control equipment, and the system is composed of a plurality of clients, a server, a monitoring end and a maintenance end which are arranged on the numerical control equipment. The client comprises a production data acquisition module and a client side signal transmission module and is used for acquiring and transmitting production data; the server integrates various modules such as an equipment identification code storage module and a production data storage module, and can store data, judge equipment faults, analyze data trends and predict fault time; the monitoring end is used for displaying data and scheduling maintenance; and the maintenance end receives and displays the maintenance scheduling information. The method comprises the steps that the client collects transmission data, the server stores and judges, the monitoring end dispatches, the maintenance end executes maintenance, the client records transmission maintenance data, the server analyzes and predicts and the like, and real-time monitoring, timely fault judgment and processing and predictive maintenance of the numerical control equipment are achieved.

The present invention provides an authentication integration device that supports multiple authentication methods and can handle authentication judgment output results corresponding to each authentication method. [Solution] An authentication integration device connected to an authentication execution device that executes multiple authentication methods, comprising: an authentication method determination unit that receives a user authentication request from a user's terminal, determines the authentication method based on the authentication method ID included in the user authentication request, and requests user authentication information corresponding to the authentication method from the user's terminal; an authentication execution request unit that receives user authentication information from the user's terminal, extracts pre-stored authentication execution request information according to the authentication method based on the user ID included in the user authentication information, and transmits the authentication method and authentication execution request information to the authentication execution device to request authentication execution; an authentication execution result receiving unit that receives authentication execution result information corresponding to the authentication method from the authentication execution device; and an authentication determination unit that determines whether authentication is successful or unsuccessful based on the authentication execution result information.

We provide the system. [Solution] A means of receiving data in different formats and structuring it into a unified format, A means of managing and integrating structured device information in real time, A means of monitoring the device status and automatically generating maintenance notifications, A means of providing integrated device information via a user interface, A means to manage the lifecycle of devices, identify and delete information about unnecessary devices, A system that includes this.

The invention relates to a coal mine major equipment supervision method and system based on HarmonyOS, and belongs to the technical field of coal mine safety production. The system solves the problems that existing major equipment monitoring subsystems are separated, data are isolated, unified specifications are lacked, alarming is not timely and the like, standardized automatic collection of equipment such as an elevator, a drainage system, a main ventilator, a belt conveyor, a gas drainage pump and the like is achieved through the unified specifications based on an OPC UA protocol, high-concurrency data uploading and persistent storage are achieved through Kafka, and real-time monitoring is achieved. The background carries out fault self-diagnosis and safety brief report generation, interacts with a mobile terminal APP based on a HarmonyOS of a Kwan Mongolia operating system through a standard WebAPI, and integrates the functions of equipment file query, operation condition monitoring, process configuration diagram and video real-time monitoring, active alarm pushing, focus attention and safety brief report. The system realizes mobile supervision of major coal mine equipment anytime and anywhere.

The invention discloses an intelligent dispatching operation method for material piling and taking equipment of a circular coal yard, and belongs to the technical field of industrial automation and control. The method comprises the following steps: data acquisition: acquiring three-dimensional point cloud, equipment accurate positioning, coal quality batch and equipment state data of a coal yard in real time through a laser scanner arranged at the top of the coal yard and sensing equipment on a stacker-reclaimer; intelligent decision making: based on the fused multi-source data, automatically generating a material piling and taking operation strategy through an intelligent scheduling algorithm, including analyzing material pile characteristics based on a PCA algorithm and planning a material taking path; and dynamic execution and adjustment: controlling the stacker-reclaimer to execute an operation strategy, and in the process, realizing real-time collision prevention based on a distance field collision monitoring algorithm and a two-stage safety envelope, realizing constant-flow reclaiming through coal flow scanning and PID closed-loop control, and integrating equipment state predictive maintenance and industrial video monitoring. According to the invention, intelligent scheduling and safe and efficient operation of the circular coal yard stacker-reclaimer from manual operation to full-automatic unattended operation are realized.

The invention discloses a collaborative design method and device for compressor unit equipment based on a COMOS platform, a storage medium and computer equipment, and the method comprises the steps: receiving and analyzing a design demand file to obtain equipment parameters, and integrating the equipment parameters, a standard card of a general compressor unit and a basic object database in the platform; creating a project catalog on a platform, and creating a device object category catalog under the project catalog; calling a plurality of basic objects from a basic object database integrated by the platform according to the equipment parameters, and setting each basic object under a corresponding function label; and assigning a value to the basic object under each function label to obtain a basic object instance, and constructing a connection relationship between the basic object instances; and performing connection reliability check on the basic object instances for constructing the connection relationship based on the standard card, and generating an equipment data table, an inquiry list, a pricing list and an equipment technical document of each function tag based on the basic object instances under each function tag after the connection reliability check is passed.

The present invention provides an authentication integration device that supports multiple authentication methods and can handle authentication judgment output results corresponding to each authentication method. [Solution] An authentication integration device connected to an authentication execution device that executes multiple authentication methods, comprising: an authentication method determination unit that receives a user authentication request from a user's terminal, determines the authentication method based on the authentication method ID included in the user authentication request, and requests user authentication information corresponding to the authentication method from the user's terminal; an authentication execution request unit that receives user authentication information from the user's terminal, extracts pre-stored authentication execution request information according to the authentication method based on the user ID included in the user authentication information, and transmits the authentication method and authentication execution request information to the authentication execution device to request authentication execution; an authentication execution result receiving unit that receives authentication execution result information corresponding to the authentication method from the authentication execution device; and an authentication determination unit that determines whether authentication is successful or unsuccessful based on the authentication execution result information.

The invention provides a multi-modal collaborative root cause analysis method fused with a large language model, and relates to the technical field of IT service fault analysis. According to the method, a tool feature vector space is constructed, a mixed retrieval algorithm (semantic similarity and historical calling frequency) is adopted to realize real-time dynamic sorting of a tool set, and a Top-K high-matching-degree tool is pushed based on a sliding window strategy; an Attention-Path mechanism based on the fault propagation weight is established, and a topology reasoning path related to the context is dynamically generated; multi-source heterogeneous data such as equipment logs, performance indexes and topological relations are integrated, and feature level fusion is achieved through a cross-modal alignment module. The problems of cognitive redundancy caused by full-amount context information overload, decision complexity of a multi-tool calling path, inherent illusion deviation diffusion of a generative model and high consumption of computing resources caused by long sequence processing in existing IT system fault diagnosis can be effectively solved.