4324 results about "Functional module" patented technology

The invention relates to the technical field of server upgrading, and discloses a server firmware remote upgrading method and system, and the method comprises the steps: a management node obtains a device identifier list and target firmware version information of a to-be-upgraded server, and uses a distributed task scheduling algorithm to divide tasks; transmitting an upgrading instruction and a data packet through an encryption channel, and generating an incremental packet by using a differential upgrading technology; data transmission is guaranteed through heartbeat detection and breakpoint continuous transmission; after pre-verification of the server-side security sandbox, upgrading and isolating tasks in an idle period; verifying by adopting a gray release strategy, and automatically rolling back if the verification fails; and storing an upgrade state and a log by means of a block chain network. The system comprises corresponding function modules. According to the method, the upgrading efficiency, safety and reliability are improved, the influence on services is reduced, data cannot be tampered and can be traced, the problems existing in a traditional upgrading mode are effectively solved, and the method is suitable for various server firmware remote upgrading scenes.

The invention provides an IMU (inertial measurement unit)-assisted depth SLAM (simultaneous localization and mapping) method and system fusing language-vision multi-mode perception, and the system comprises functional modules such as initial calibration and semantic map initialization, pre-integration prediction and key frame judgment, dense point cloud reconstruction and relative pose estimation, semantic embedding extraction, semantic guidance loopback detection and semantic three-dimensional map incremental updating. IMU motion priori, depth geometric constraint and language model semantic factors are subjected to combined modeling through a graph optimization framework, and high-precision positioning and labeled map construction in a complex dynamic environment are achieved. Compared with the prior art which only depends on geometric or inertial information, the method has the advantages that the loop-back mismatching rate is reduced, the closed-loop convergence efficiency and the long-time relocation robustness are improved, and a semantic interface is provided for upper-layer tasks such as natural language navigation and target retrieval. The method can be widely applied to the fields of service robots, security inspection, intelligent driving, post-disaster search and rescue and the like.

A prefabricated building production line and a prefabricated building structure. The prefabricated building production line comprises an assembly conveyor line, a functional module conveyor line, a transfer mechanical arm, an assembly mechanical arm, and a control platform; an assembly area, a testing area, and an inspection area are arranged in order along a transport direction of the assembly conveyor line; the assembly conveyor line is used for conveying a building unit main body to be assembled; a plurality of functional module conveyor branch lines are arranged at the side of the functional module conveyor line away from the assembly conveyor line; the functional module conveyor line and the functional module conveyor branch lines are used for transporting a functional module; the transfer mechanical arm is used for carrying a functional module and the building unit main body to be assembled; and the assembly mechanical arm is used for installing the functional module on the building unit main body to be assembled. The prefabricated building structure comprises: a lifting device for prefabricated building installation, an prefabricated building ventilation structure, a prefabricated building automated production fixture, etc.

The invention provides a compliance auditing method and system for multi-modal content. The method comprises the following steps: performing feature extraction on unstructured to-be-audited multi-modal content to obtain a structured feature vector; performing image-text semantic association on the text semantic feature vector and the image visual feature vector to obtain a fusion feature vector involving image-text semantic contradiction; constructing a domain knowledge graph based on the compliance guidance data of the domain to which the to-be-audited multi-modal content belongs; inputting the fusion feature vector into a domain knowledge graph, and performing compliance rule retrieval by adopting a sub-graph matching algorithm to determine a violation type corresponding to the fusion feature vector and a violated compliance term; and generating an interactive compliance audit report. The system comprises functional modules for realizing the steps in a one-to-one correspondence manner. According to the technical scheme, the problem that cross-modal semantic analysis of an existing multi-modal content compliance auditing method is not accurate can be solved.

The invention discloses an unmanned aerial vehicle flight control system vulnerability detection method based on data flow analysis and LLM, and belongs to the technical field of intelligent software testing. Comprising the following steps: extracting a code function module associated with user operation in an unmanned aerial vehicle flight control system through a data flow analysis method, and establishing an operation-code mapping relation library; generating a structured natural language semantic description for each function module code by adopting a large language model LLM, and forming a multi-dimensional semantic feature vector; based on correlation analysis of multi-module semantic features, a combined test scene is constructed, and a natural language test case is generated; the natural language test case is converted into an executable test code through reverse semantic mapping, and coding reconstruction of test logic is completed; and executing a test code and capturing a runtime log in an unmanned aerial vehicle simulation environment, and performing vulnerability feature extraction and root cause positioning by using a large language model. According to the method, the efficiency is improved, and meanwhile, the deep coverage test of a complex interaction scene is supported.

The invention relates to the technical field of chip design, in particular to a system-on-chip design method and system and a medium. The method comprises the following steps that a chip design target and basic parameters are collected, a constraint condition set is generated through demand constraint analysis, the basic parameters of a system are subjected to parallel recombination, functional prototype data are generated, the functional prototype data are used for chip behavior design, functional unit groups are generated, a network architecture is reconstructed to form a functional module network, and the functional module network is used for chip behavior design. And carrying out clock domain mapping and competition compensation processing based on the network to obtain a function scheduling sequence, carrying out resource matrix remapping on the basic parameters according to the function scheduling sequence, generating hardware abstract data, carrying out chip layout simulation, and finally generating a simulation chip blueprint. According to the system-on-chip design method, the more efficient system-on-chip design method is achieved.

The invention relates to the technical field of agricultural information management, and particularly discloses an agricultural information management system and method based on a big data platform, and the method comprises the steps: firstly deploying a multi-source data collection module at an edge calculation node, and obtaining and standardizing the soil moisture content, meteorological environment and equipment operation data in real time; secondly, constructing a local dynamic irrigation strategy model, and realizing multi-objective optimization through a reinforcement learning algorithm; establishing a federated learning framework at the cloud, dynamically distributing node weights by adopting an attention mechanism, and realizing model aggregation of privacy protection in combination with secure multi-party computing; an optimal irrigation instruction is generated through a multi-source data fusion engine, and a three-level response exception handling mechanism is established; and finally, a closed-loop feedback system containing short-term incremental learning and long-term architecture optimization is formed. The corresponding management system comprises six functional modules, namely a data acquisition module, a local modeling module, a federated learning module, a real-time decision-making module, an abnormal monitoring module and a closed-loop optimization module.

The invention provides a vehicle-mounted display terminal man-machine interface interaction experience optimization method and system, and relates to the technical field of vehicle-mounted man-machine interaction, and the method comprises the steps: obtaining eyeball watching, hand operation and head rotation data of a driver, and carrying out the fusion to generate an attention distribution thermodynamic diagram; constructing a dynamic scene recognition model in combination with the vehicle running state and the environment information; and calculating a function module optimization index based on the thermodynamic diagram and scene prediction, and dynamically adjusting the position, the response area and the display level of the function module. According to the invention, the interaction efficiency of drivers can be improved, the operation distraction risk is reduced, and the driving safety is enhanced.

The invention discloses an end-side cloud collaborative intelligent fire-fighting fire monitoring system based on image fusion, and relates to the technical field of intelligent fire-fighting, the system is composed of a plurality of functional modules, and the system comprises a multi-modal image fusion module which generates a dynamic scanning priority map based on prior data, distinguishes a natural heat source from an abnormal fire by using a dual-light fusion algorithm, and sends an image fusion result to a cloud server; a scanning area is divided according to the thermal risk grade, and the thermal imaging resolution is dynamically adjusted; the distributed edge computing module is used for carrying out space-time synchronization on cross-modal data through a multi-modal feature alignment network, and carrying out dynamic allocation on a CUDA core and CPU resources through adaptive computing scheduling; an improved artificial bee colony algorithm is adopted, the bandwidth of the multi-sensor data flow is dynamically allocated through a time-sharing multiplexing protocol, and three-dimensional path planning is carried out; and the end-side cloud collaborative decision module constructs a federated learning driven model sharing network, and each edge node trains a lightweight YOLOv5s pruning model based on local data.

The invention discloses a data access permission control method and system based on a block chain, and relates to the technical field of block chains, the system is composed of a plurality of function modules, and the system comprises a hierarchical permission module which adopts a role hierarchical strategy and defines the access granularity of a role through an intelligent contract; the dynamic permission adjustment module is used for dynamically adjusting the permission range by analyzing user behaviors in real time through machine learning according to the principle of following the minimum permission in the permission distribution process; attribute encryption and zero-knowledge proof are introduced, an access key is dynamically generated according to user attributes, and sensitive information is hidden in the verification process; the multi-chain collaboration module is used for coding an intelligent contract through an authority rule, automatically executing access request verification, storing encrypted data through a private chain, managing an index and an access strategy through an alliance chain, isolating a storage domain from an access domain, and carrying out process traceability on a data request through a cross-chain verification mechanism; and the key management module is used for generating a true random number private key by adopting a hardware security unit.

The invention relates to an intelligent agent system optimization method and device based on intelligent fault analysis and cross-generation knowledge inheritance, and belongs to the technical field of artificial intelligence. According to the method, interaction abnormal signals are captured in real time by deploying a lightweight log probe, and a tool benefit prediction model based on reinforcement learning is constructed to automatically generate an improvement proposal when the failure rate exceeds a threshold value; an agent genealogy map is established to realize automatic inheritance of a new agent on core memory and abandonment of failure knowledge, and a disastrous forgetting blocker is deployed to dynamically extract a functional module from a genealogy to deal with key capability degradation. Aiming at the problems of fault response lag, knowledge inheritance fracture, key capability degradation and the like in an intelligent agent system iteration process, the invention creatively provides a cooperation mechanism of an intelligent fault analysis layer and a cross-generation knowledge inheritance network, and the fault self-healing capability, version stability and service continuity guarantee level of the system are remarkably improved.

The invention discloses a test case determination method and device, a computer readable storage medium and a processor. The method comprises the following steps: identifying a source code of software by utilizing a pre-trained large model to obtain a plurality of functional modules in the software and a dependency relationship among the plurality of functional modules; in response to updating of the source code of the software, determining a code updating part in the source code; determining a test case matched with the code updating part from a test case library of the software based on the code updating part and a dependency relationship among the plurality of functional modules, the test case being used for testing the code updating part; based on a test result of the test case, adjusting a selection strategy of the test case; and re-determining the test case for testing the code updating part based on the adjusted selection strategy of the test case. The technical problem that a traditional regression test strategy is low in test efficiency is solved.

The invention relates to the technical field of agent construction, and discloses an agent construction method and system based on agentive workflow, and the method comprises the following steps: defining an agent core function module and distributing a unique identifier, building an inter-module communication protocol standard, and determining a message format and a priority rule; the method comprises the following steps: distributing computing resources for each module, setting an elastic capacity expansion and contraction strategy, generating a module dependency graph and an architecture metadata file, detecting the loss and delay of multi-modal input data, generating compensation characteristics based on historical context, calculating the quality confidence of each modal, and carrying out dynamic weighted fusion. According to the invention, a three-level alignment architecture is provided to realize cross-modal semantic consistency, and the generated content is ensured to accord with real scene logic; a double-layer decision-making mechanism is designed to drive workflow dynamic optimization, and the system agility under a complex task is remarkably enhanced; a privacy-efficiency balanced federated architecture is constructed, and differential content generation is supported while enterprise data sovereignty is protected.

The invention relates to the technical field of chip development, and discloses a chip post-simulation verification acceleration method, system and device and a storage medium, and the method comprises the steps: collecting multi-dimensional data of a large-scale chip; collecting all module names of a given chip; establishing a mapping relation between a redundant module RTL and a corresponding gate-level netlist, ensuring that interfaces before and after replacement are completely consistent, and designing an automatic script identification and processing parameterization module; establishing a post-simulation verification environment, verifying the consistency of output responses before and after replacement, analyzing the time delay change of a key path, calculating the dynamic power consumption and static power consumption of each functional module before and after replacement, and generating a simulation verification result. According to the method, the hybrid simulation model is constructed, and part of the gate-level netlist irrelevant to the current simulation function is replaced with the RTL, so that the actual simulation scale of a chip is reduced, the problem of overlong simulation time after a large-scale integrated circuit is remarkably solved, and the simulation efficiency is effectively improved.

The invention discloses a mobile communication load collaborative scheduling system and method based on energy efficiency perception, and belongs to the technical field of mobile communication, energy consumption data of each functional module in a base station and external network environment parameters are collected in real time through a multi-source sensor network in the base station, and a dynamic energy efficiency map is generated; based on historical energy efficiency data and real-time load characteristics, constructing an energy efficiency construction prediction model, and predicting an energy efficiency hotspot area; based on the historical movement track of the user and the spatial and temporal distribution characteristics of the service flow, the movement trend of the user and the change trend of the service flow are analyzed, and in combination with an energy efficiency prediction model, a potential overload base station is identified, and overload early warning is triggered; after receiving the early warning information, screening candidate target base stations according to a preset radius by taking the overload base station as a core; and generating a load idle list in a descending order according to the real-time energy efficiency ratio of the candidate base station, and performing energy efficiency sensitivity priority grading on the to-be-migrated service, thereby generating a collaborative scheduling strategy and executing load migration.

The invention relates to a prefabricated building quality defect tracing system and method applied to the field of building informatization, and the system comprises a user interaction layer, a data processing and storage layer, a data collection layer and a function layer, and the data collection layer is used for collecting key quality data of prefabricated building components in different links; the user interaction layers interact with each other through a network and the function module layer; the data processing and storage layer performs encryption, hash operation, scattered storage and index verification on the quality data transmitted by the data acquisition layer by using an intelligent contract, an IPFS network and a block chain; the function module layer provides support for each unit of the user interaction layer to trace quality defects, judge responsibility and take prevention measures, and the system can collect the quality data of the whole process of the prefabricated building, comprehensively manage the quality tracing process, strengthen multi-party collaboration and sharing, and improve the quality of the prefabricated building. And it is ensured that tracing of the quality defects of the fabricated building has comprehensiveness, transparency and non-tampering performance.

A hoisting posture control system and method, applicable to the technical field of modular construction. According to the hoisting posture control system, controllers corresponding to functional modules are called on the basis of data detected by sensors, to drive posture control of a hoisted object, thereby assisting a tower crane operator in making work decisions, so that the operator does not need to take risks to get close to a module to be installed hoisted in the air, ensuring the safety of workers and the accuracy and reliability of module installation. Thus, the labor cost in modular construction work can be reduced, and the assembly quality and efficiency of modules are improved.

The invention relates to the technical field of digital twinning simulation, and discloses a digital twinning-based intelligent simulation system for a lyocell fiber production line, and the system comprises a 3D modeling and digital twinning module which constructs a three-dimensional model of the lyocell fiber production line, associates the three-dimensional model with real-time production data, and finally forms a three-dimensional digital twinning model of the production line; the key equipment state prediction module predicts the residual life of the film evaporator according to the vibration data of the film evaporator; the energy consumption prediction module is used for obtaining key parameters of the glue making process and predicting an energy consumption value according to the process list of the lyocell fiber glue making process; the early warning module is used for early warning in an equipment model corresponding to the target film evaporator in the three-dimensional digital twin model according to the residual life prediction result; and the process management module is responsible for compiling, managing and issuing process files. According to the system disclosed by the invention, all the functional modules are fused and combined together to form a complete system, so that the system is of great significance in guiding lyocell production and can help enterprises to carry out better cost control.

The invention discloses a scheduling system of a content distribution network based on edge computing, and relates to the technical field of computer networks. An edge resource sensing module; an NLP semantic analysis module; reinforcing a learning scheduling engine; a semantic and resource linkage module; and a federation collaboration module. According to the scheduling system of the content distribution network based on edge computing, semantic understanding is carried out on a request of a user to analyze a deep intention of the user, edge node multi-dimensional state sensing data and a semantic label vector are integrated, a scheduling action is generated based on a node state and the user intention, and the scheduling effect is improved. Therefore, each edge node is fully utilized while user requirements are met, the edge nodes have caching, computing and scheduling capabilities, the limitation of surface feature matching of a traditional CDN is broken through, technical upgrading from traditional file type recognition to intention understanding and from a fixed rule to dynamic intelligence is realized, and finally, the resource efficiency and service quality of the CDN are improved.

The invention relates to the technical field of artificial intelligence, in particular to a business contract intelligent review and risk quantification method and device, and the method comprises the steps: building and maintaining a business contract key term information base; obtaining and preprocessing a to-be-rechecked contract text; processing the text based on a bidirectional long-short term memory network and a conditional random field model, and extracting semantic representation; identifying key information through a multi-level attention mechanism; executing multi-label learning to classify and identify clause types and attributes; utilizing a dependency syntactic analysis technology to extract logical association and a responsibility chain among terms, and constructing a knowledge graph; identifying risk terms and generating risk prompts; business indexes are extracted, and risk open values are calculated; generating a rechecking report; the corresponding device comprises nine functional modules such as an information base management module, a text preprocessing module and a semantic representation extraction module, risk terms in a contract can be automatically recognized, a quantitative risk assessment result is provided, and contract auditing efficiency and accuracy are effectively improved.

The invention discloses an operation management method and system for a server cluster, and belongs to the technical field of server operation management, and the method comprises the steps: constructing a computing power unit pool containing a plurality of service blocks, combining the resource state of a function module with application label information, recognizing the operation situation of the function module, and generating a scheduling adaptation factor model, link capacity, position distribution and communication delay among service blocks are further fused to construct an expansion structure map, a deep self-adjusting engine is adopted to carry out offline reinforcement learning training, and an optimal capacity expansion strategy under multiple situations is generated; the system can dynamically judge the capacity expansion behavior based on the current state, and performs strategy updating by continuously collecting capacity expansion feedback, so that intelligent, self-adaptive and high-efficiency control of resource scheduling is realized.

The embodiment of the invention provides a multi-configuration relay-oriented aircraft electrical box parameter measurement system and method, and belongs to the field of aircraft electrical box test and diagnosis. According to the hardware level, flexible access of a multi-configuration relay electrical box is achieved based on a universal adapter interface, core parameter measurement is completed in combination with an integrated measurement and control circuit, and synchronous acquisition and processing are conducted on multiple paths of signals through a signal acquisition and processing unit; according to the software level, the pull-in / release time, the rebound time and the voltage parameters are accurately calculated through a parameter calculation module on the basis of waveform feature point recognition and dynamic excitation-response theories, and the functions of fault diagnosis, safety protection and data storage are integrated. According to the method, the crossing from on-off judgment to parameterized precise evaluation is realized, the detection efficiency, the measurement precision and the equipment reliability evaluation capability are remarkably improved, and an integrated solution is provided for external field maintenance and state prediction of the aircraft relay.

The invention relates to the technical field of artificial intelligence, and discloses a multi-agent collaborative data question-answering system and method based on a large model, and the system comprises an agent cluster module which is composed of five special agents, namely a data question-answering agent, a data extraction agent, a data analysis agent, a visualization agent and a quality examination agent, and achieves the task decomposition and collaborative execution through dynamic scheduling; the knowledge management module comprises a business knowledge base, a data element knowledge base and a user feedback base, and adopts a hierarchical knowledge fusion technology to provide domain knowledge support for the intelligent agent; and the supporting function module covers a front-end dialogue component and a verification and execution engine and is responsible for interactive interface rendering and result reliability verification. According to the method, the fine tuning requirement on the large model is remarkably reduced, the illusion of the large model is effectively intercepted through a dual verification mechanism, and the accuracy and reliability of question and answer results are improved.

The invention relates to the field of webpage design, and discloses a webpage generation method and system, computer equipment and a storage medium, the webpage generation method comprises the following steps: sending a webpage configuration request to a server at a client and receiving dynamic configuration data and business logic data returned by the server; a predefined node generation rule is matched according to the function module identifier to generate and mount an interactive page element set, and then a browser rendering engine is triggered to generate a visual webpage; meanwhile, when the user operates on the webpage and packages and submits operation data to the server, the server can update the business logic data and the configuration state and return the business logic data and the configuration state to the client again, and continuous dynamic adaptation and real-time updating of the webpage are achieved. Compared with the prior art, the method has the advantages that the compiling quantity of front-end adaptive and compatible codes is effectively reduced, redundant codes and complexity are reduced, the flexibility and expandability in a multi-environment and multi-device scene are enhanced, and the webpage rendering performance and the user interaction experience are remarkably improved.

The invention discloses an intelligent monitoring, operation and maintenance platform and method for a soil covering tank based on digital twinning, and belongs to the technical field of digital twinning. A digital twinborn platform is used as a core, a physical geometry simulation module, an algorithm prediction module, a sensing communication module and a virtual visualization module are integrated, and the functional modules perform data interaction and cooperative work through the digital twinborn platform. Firstly, a physical geometric simulation module establishes a three-dimensional geometric model based on the actual structure of the soil covering tank and obtains multi-working-condition mechanical response data; secondly, collaborative prediction of external load distribution, structural response characteristics and fatigue damage is achieved through an algorithm prediction module; thirdly, the sensing communication module collects and processes sensor data in real time, and the model is driven to be dynamically updated; and finally, the virtual visualization module dynamically presents the multi-physical field state and damage evolution trend of the soil covering tank through a multi-source data fusion rendering technology. According to the invention, the comprehensive monitoring capability and failure early warning precision of the earthing tank are obviously improved, predictive maintenance decision is supported, and the operation and maintenance cost is reduced.

The invention discloses a flowmeter self-calibration method and system based on big data analysis. The method comprises the steps that multi-source data collection is conducted, and multiple kinds of data are collected and stored in a big data platform with a block chain evidence storage function; data preprocessing: adopting multiple algorithms to improve data quality; feature extraction and analysis: identifying key factors and monitoring fluid states by means of multiple technologies; calculating calibration parameters, and considering various coefficients and uncertainty analysis; performing automatic calibration, encrypting and writing parameters after digital twin simulation, and reserving a copy; and verifying the calibration effect by adopting a multi-mode verification mechanism. The system comprises a plurality of functional modules which work cooperatively. According to the invention, the data acquisition comprehensiveness is improved, the calibration period is shortened, the production efficiency is improved, the data integrity and reliability are ensured, key factors are accurately identified, the fluid state is monitored in real time, the calibration parameter adjustment is simulated, and the calibration effect is verified in a multi-mode manner, so that the reliability and accuracy of a flowmeter measurement system are improved.

The invention discloses a software project development method based on a low-code platform, which belongs to the technical field of software development, and specifically comprises the following steps: receiving original demand description through an embedded natural language parser, and establishing a semantic incidence matrix to extract demand elements; encoding the demand elements into three-dimensional structured demand vectors; mapping the demand vector to a three-dimensional orthogonal feature space, calculating the coordinates of a functional module, and generating an initial topological structure based on a Delou inner triangulation algorithm; rendering an interactive three-dimensional network map on a visual interface; monitoring user operation, and recalculating the adjacency relation of the affected module when the displacement of the module exceeds a threshold value or the connection edge is reconstructed; compared with a historical version, when a key service path is interrupted or a data flow ring is broken, a compensatory connection bridge is activated; a deployable architecture with a version traceability identifier is output, and a traceability code is built in the module to reversely map an original demand vector.

The invention discloses a terminal equipment interface display method and system based on user habits, and belongs to the technical field of digital display, key features such as user intention deviation degree and interface attention stability index are extracted by collecting behavior data of a user for interaction objects and function modules, and a user preference weight table is calculated and dynamically updated; interface module sorting is further carried out in combination with a deep learning model, a fuzzy logic evaluation mechanism is introduced to carry out interpretable scoring on a sorting result, when a scoring result is lower than a threshold value, the system automatically corrects a sorting strategy based on user feedback, and finally optimized interface display content is output. Personalization, dynamics and controllability of interface display are achieved, and the man-machine interaction experience and the user satisfaction degree of the terminal equipment are effectively improved.

The invention belongs to the technical field of computer information processing, and relates to a scientific research performance information analysis and evaluation system and a processing method thereof.The scientific research performance information analysis and evaluation system comprises a data collection module, a weight distribution module, a real-time feedback module and an execution engine function module; weight distribution receives the first signal and analyzes a current strategic target priority identifier and a historical performance evaluation record contained in the first signal, a weight parameter space dynamically matched with a target priority is constructed through an online learning algorithm, and a second signal containing a real-time weight mapping relation is generated; real-time feedback is carried out, a multi-dimensional performance evaluation matrix is constructed based on the weight mapping relation in the second signal, and a third signal is generated; the execution engine receives the third signal, analyzes an abnormal positioning code of the third signal, and aggregates intervention records in a period to form a fourth signal; according to the method, the defects that traditional performance information analysis depends on static weight, the data dimension is single, and real-time dynamic adjustment is lacked can be overcome, and the analysis efficiency is improved.

The invention relates to the technical field of intelligent work order scheduling platform design, and discloses an intelligent work order scheduling system, method and device and a medium, and the method comprises the steps: the system achieves the efficient and intelligent scheduling of a device fault work order through integrating a plurality of function modules. Firstly, the work order access module receives equipment fault information of different channels, and it is ensured that the information is comprehensive and timely. Then, the portrait construction module constructs a multi-dimensional ability portrait by using the historical service data of the maintenance personnel, and provides a data basis for intelligent matching; and then, the intelligent distribution module accurately matches and associates the most suitable maintenance personnel with the work order according to the portrait data and the work order parameters. And the order grabbing interaction module generates a to-be-grabbed work order list and an order grabbing interface, so that the scheduling flexibility is enhanced, and the scheduling efficiency is improved. The execution tracking module monitors the work order processing progress in real time, and transparent and controllable scheduling is ensured. And finally, the knowledge base question and answer module provides professional knowledge support for the maintenance personnel and helps the maintenance personnel to quickly solve the work order problem.