550 results about "Cooperative work" patented technology

The invention discloses a construction elevator intelligent dynamic scheduling system and method based on multi-modal deep learning, and relates to the technical field of elevator scheduling management, the system comprises a multi-modal data acquisition module, a multi-modal deep learning processing module, a hierarchical decision module, an adaptive learning module, a hybrid reinforcement learning scheduling module, and a conflict prediction and solution module; time sequence data, image data and text requirements are processed at the same time through a multi-mode deep learning architecture, a three-layer neural network decision architecture is adopted to realize full-process intelligent decision from strategy to execution, and a learning strategy and decision weight are automatically adjusted according to a project progress stage in combination with an adaptive learning system. The optimal scheduling scheme can be automatically generated according to information such as material types, quantity and latest completion time submitted by a team, the use efficiency of the construction elevator is effectively improved, resource waste and scheduling conflicts are reduced, and the method is suitable for scenes such as building construction elevator scheduling and a multi-elevator cooperative working environment.

The invention discloses a heterogeneous equipment intelligent management system and method based on an artificial intelligence technology, and relates to the technical field of computers, and the system comprises a heterogeneous equipment intelligent management platform: a heterogeneous equipment layer is provided with multiple types of equipment; the equipment access layer supports a plurality of communication protocols; the device adaptation layer is used for converting communication protocols and data formats of different devices into model context protocols, and abstracting the devices by using a heterogeneous device unified description language; the resource management layer is responsible for monitoring the resource use condition of each device in real time and carrying out dynamic resource allocation according to a preset strategy; the task scheduling layer is used for intelligently distributing tasks according to task requirements and equipment capabilities and realizing cooperative work among equipment; and the user interface layer is used for providing a user interface, so that a user can conveniently configure, monitor and manage the equipment. According to the invention, heterogeneous equipment can be effectively managed, the compatibility and efficiency of equipment management are improved, the management cost is reduced, and intelligent control is realized.

The invention relates to the technical field of robot control, particularly discloses a path planning and dynamic obstacle avoidance control method for multi-task collaborative operation of an industrial robot, and aims to solve the problems of task scheduling conflict, dynamic obstacle response lag and low collaborative efficiency in a multi-robot system. The method comprises the following steps: constructing a task-resource joint scheduling model and generating initial task allocation; planning a conflict-free collaborative path based on an improved space-time A star algorithm; predicting a dynamic obstacle trajectory by using an LSTM network and generating a space-time envelope; constructing a second-order safety barrier function fusing task priorities; local obstacle avoidance re-planning is realized through rolling horizon model predictive control; and the global rescheduling is triggered when the task delay exceeds the limit or the deadlock risk occurs. According to the technical scheme, closed-loop linkage of global task collaboration and local dynamic obstacle avoidance is realized, and the system collaboration efficiency, the obstacle avoidance success rate and the operation robustness are remarkably improved.

The invention relates to the technical field of artificial intelligence, and discloses a contract generation system and method based on multiple agents, and the system comprises a user interaction module which is used for receiving a contract demand inputted by a user and displaying a generation result; the knowledge base module is used for storing and retrieving legal terms, industry specifications and contract templates in a distributed manner; the agent cluster module comprises a demand analysis agent, a law expert agent, an industry expert agent, a risk assessment agent, a language optimization agent and a coordination control agent, the agents interact through a standardized communication protocol, and a coordination strategy is dynamically adjusted based on contract complexity calculated in real time; and full-process automation of contract generation is realized. Through cooperative work of multiple agents, the efficiency and quality of contract generation are improved, the law compliance and industry suitability of the contract are ensured, the risk in the contract generation process is reduced, and the user experience is improved.

The invention relates to the technical field of large language models, in particular to a large language model multi-agent cooperative working method, which comprises the following steps: S1, designing a plurality of agents to simulate social division and cooperation, so that each agent executes different professional abilities, the plurality of agents including a planning agent, a tool agent and a reflection agent; s2, when task input is obtained, the planning agent filters retrieved tools, and a complex task is decomposed into subtasks easy to understand in a code and annotation mode; s3, performing targeted tool enhancement on the filtered tool set by the tool agent, and executing specific operation planned by the planning agent to obtain a subtask result; s4, evaluating a subtask result by the reflection agent, and planning the task from different angles by combining static planning and dynamic planning; and S5, the planning agent feeds back a summary result according to execution of the subtasks.

The invention relates to the field of power distribution control, and particularly discloses a self-healing control system and method based on multi-agent collaboration, and the system comprises a regional agent and a local agent which are disposed in a power distribution network. Wherein the local intelligent agent is configured to obtain real-time operation data of a monitoring point in the power distribution network, and perform rapid fault detection on the real-time operation data; the regional intelligent agent is configured to fuse the fault analysis information of the plurality of local intelligent agents to determine fault position information when the power distribution network has a fault, generate a self-healing control strategy according to the fault position information, and send the self-healing control strategy to the local intelligent agents for execution; through cooperative work of the distributed intelligent agents, the problems of low response speed, low positioning precision, weak autonomous capability and the like in traditional power distribution network fault management are solved. In addition, the system does not need to depend on centralized control of a master station, can still operate autonomously when communication is interrupted, and improves the efficiency and reliability of fault processing through cooperation of multiple agents.

The invention discloses a flexible automatic production management and control system for a new energy high-power high-frequency transformer, and relates to the field of production management and control, the flexible automatic production management and control system comprises a production demand receiving module, a production resource management module, a production planning module, a production execution module and a quality control module, an order is received through an API or EDI, and a work order is generated; collecting equipment and material information in real time, and constructing a production resource association network; carrying out production scheduling and process matching by adopting an improved deep learning model; scheduling materials, procedures and equipment based on a multi-level analysis control model; the quality is evaluated by using a two-dimensional cloud model, and data recording is performed through a distributed database, so that the traceability of the quality problem is ensured. According to the system, the production efficiency and the quality management level are effectively improved, the problem that existing rigid automatic equipment lacks flexibility is solved, and efficient and accurate production of the new energy high-power high-frequency transformer is ensured through cooperative work of a plurality of modules so as to meet different production requirements.

The invention provides a multi-tenant-based centralized authentication and authorization method, system, device and medium, and belongs to the technical field of security and identity management, and the system comprises a unified portal layer, an authentication layer, an authorization layer, a strategy center and an audit monitoring layer. The unified portal layer receives a user request, identifies and injects a tenant identifier, and executes WAF rule verification, JWT signature verification and Token blacklist check; the authentication layer performs user or client credential verification on different accessed identity sources, generates and issues a JWT, and monitors the life cycle of a token; the authorization layer extracts an authority statement in the JWT and a locally cached strategy snapshot; the strategy center provides centralized storage, version management and visual editing of multi-tenant strategies; through cooperative work of each layer, accurate identification, unified authentication, centralized strategy management and comprehensive audit monitoring of tenants are realized. And the security, the expandability and the management efficiency of the system are effectively improved.

The invention provides a method, a device and a product for realizing intelligent scheduling and cooperative work of multiple unmanned aerial vehicles. The method comprises the following steps: step S1, receiving a task to be processed in real time and acquiring a real-time operation state of each unmanned aerial vehicle in an unmanned aerial vehicle group; s2, performing intelligent dynamic allocation on the tasks by using a pre-established task value scoring model, an unmanned aerial vehicle task adaptation degree model and a global multi-task dynamic allocation optimization model; the global multi-task dynamic allocation optimization model is a mixed integer programming model established by taking maximization of the total task income as a target under a predetermined constraint condition; and S3, after task allocation is completed, a pre-constructed three-dimensional grid airway model G (V, E) is used to plan an airway for each unmanned aerial vehicle executing the task. According to the technical scheme, the mixed integer programming algorithm and the particle swarm optimization are combined, and the global task allocation optimization model is constructed, so that task allocation can be efficiently solved, and various actual constraints can be met.

The invention relates to the technical field of underground structure management, in particular to an underground structure full life cycle management method and system based on fusion sensing data. According to the technical scheme, the system comprises a sensing layer, a data transmission layer, a data processing and analysis layer and a decision support and application layer. Through cooperation of the distributed optical fiber sensor and the multiple sensors, all-around and multi-parameter monitoring of the underground structure is achieved, the monitoring accuracy and reliability are improved, historical data and operation rules of the structure are automatically learned through a data driving prediction model, different geological environments and load conditions are adapted, a scientific basis is provided for maintenance decision making, and meanwhile, the system has good application prospects. The self-adjusting capability is realized; monitoring system application and data accumulation and utilization in each stage are considered, seamless connection and cooperative work are achieved, full-life-cycle integrated management is achieved, the overall performance of the structure is improved, the service life of the structure is prolonged, the maintenance cost is reduced, and sustainable development is promoted.

The invention relates to the technical field of underwater robot cooperative control, and provides an elastic consistency control method and system of a multi-underwater robot system. The elastic consistency control method for the multi-AUV system comprises the following steps: discretizing and linearizing the multi-AUV system, introducing a performance index to describe the influence of communication topology on the dynamic behavior of the system, and calculating the elastic consistency of the multi-AUV system on the basis of a centralized optimal control method of a local decoupling system and a robust stability theory. And designing an elastic consistency controller and obtaining controller gain by solving a local algebraic Riccati equation so as to realize consistency control of multiple AUV system states. According to a sparse mode matrix spectrum of a distributed controller, a system stability condition is given, and efficient cooperation and stable operation of a multi-AUV system in a complex underwater environment are ensured. According to the method, the calculation and communication complexity is remarkably reduced, the method is suitable for a multi-AUV cooperative working environment, and a new technical solution is provided for cooperative control of the underwater unmanned system.

The invention discloses a multi-mechanical-arm flexible production line scheduling method and system based on a visual language model, and belongs to the technical field of production line scheduling. The method comprises the steps of obtaining a task target image and a task description text, and converting the task target image and the task description text into a task state joint embedding vector through a visual language model; the task urgency degree, the semantic matching degree between the task state joint embedding vector and the mechanical arm state embedding vector and the future state of the mechanical arm are introduced into a space-time weighted cost function, task allocation is conducted through the space-time weighted cost function, and a mechanical arm task is determined and executed; and the task completion state of the mechanical arm is determined, and the task of the mechanical arm is dynamically adjusted with the minimization of the space-time weighting cost and the feedback cost as the target. The multi-mechanical-arm cooperative work efficiency, the task scheduling precision and the production takt time stability can be improved in the dynamic production environment, and the problem that an existing multi-mechanical-arm flexible production line faces double bottlenecks of efficiency and reliability is solved.

The utility model discloses rectangular ring assembling equipment which comprises a tensioning claw, a clamping claw, a claw driving device and an adjusting module. The paw driving device comprises a tensioning driving block and a clamping driving block, and the tensioning driving block and the clamping driving block drive the tensioning paw and the clamping paw to open and close in the horizontal direction based on the same central point; the moving paths of the tensioning claw and the clamping claw are not intersected; the clamping driving block can further drive the clamping claw to ascend and descend in the vertical direction. The rectangular ring is grabbed and compressed through cooperative work of the tensioning claw and the clamping claw; the adjusting module drives the assembling module to convey the compressed rectangular ring to a mounting area in the workpiece, and then the clamping claw relieves grabbing and compression of the rectangular ring, so that the rectangular ring automatically resets to complete mounting; and therefore, the equipment integrates the functions of grabbing, compressing, transporting and installing the rectangular ring, the manufacturing cost and the maintenance difficulty of the equipment are reduced, the problem of cooperation between mechanisms is avoided to the greatest extent, and the reliability and the stability are improved.

The invention provides an AGV task scheduling method and system based on a graph neural network, and the method comprises the following steps: 1, receiving a task request, distributing a task to an AGV according to the task request, and continuously collecting the data of the AGV; 2, cleaning and standardizing the collected data; 3, calling in a graph neural network model, inputting the cleaned and standardized data into the graph neural network model, and performing real-time prediction and AGV task scheduling and execution adjustment through the model; 4, the AGV executes the task and updates the data in real time, and the graph neural network model continues to conduct task scheduling and execution adjustment according to the data updated in real time till the task request is completed. According to the invention, cooperative work of a plurality of AGVs can be realized, and conflicts are avoided, so that the overall working efficiency is improved, and scheduling management of cooperative tasks of the plurality of AGVs is optimized.

The invention discloses an electroencephalogram voice annotation calibration and scheduling system and method for individual differences. The system comprises an electroencephalogram signal collecting and preprocessing module, a voice instruction receiving and recognizing module, a rapid individual calibration module, a dynamic task scheduling module, an electroencephalogram feature online decoding and annotation module and an annotation storage and feedback module. Through cooperative work of the two core modules, namely the rapid individual calibration module and the dynamic task scheduling module, the problems that decoding performance is reduced during cross-subject and cross-task switching caused by individual differences, and multi-task labeling efficiency is low due to task scheduling strategy stiffness are solved accurately. Data persistent storage, model online updating and user interaction feedback are completed through storage, optimization and feedback links, periodic retraining is carried out by utilizing daily successful labeling data through a model continuous learning link, and finally, a zero-threshold individual rapid adaptation and high-efficiency multi-task collaborative labeling target is achieved.

The invention discloses a customer service question and answer processing method and device based on a multi-Agent large model, equipment and a medium, and the method comprises the steps: obtaining the dialogue data of a customer service and a user, carrying out the preprocessing of the dialogue data, and generating a preprocessed dialogue text; performing semantic analysis on the dialogue text, identifying user questions and customer service answers, and generating question and answer pairs containing question solving states; judging whether the customer service answer perfectly solves the user question or not, and generating a question-answer pair set marked as perfectly solved; classifying and sorting the question and answer pair set marked as the perfect solution so as to conclude similar question and answer pairs and extract structured knowledge entries; storing similar question and answer pairs into a professional knowledge base based on the structured knowledge entries, and updating the professional knowledge base; and in response to the received actual user service question, providing a corresponding answer to the customer service based on the professional knowledge base. Through cooperative work of multiple Agents, the answering efficiency and accuracy of the customer service staff to the user questions are improved.

The invention discloses a multi-agent collaborative production optimization method and system based on an industrial large model, and relates to the technical field of production control, and the method comprises the steps: connecting an industrial knowledge base platform, carrying out the platform retrieval and interpretation reconstruction of a target production scene, and determining a production line interaction chain; aiming at a production line interaction chain and a driving agent construction interface, calling and splicing optimization of a code fragment library are carried out, lightweight construction of agents is carried out, multi-agent integration is carried out by introducing an intelligent interaction contract, and an industrial large model is established; and deploying the industrial large model in an industrial production system, establishing interaction with production line equipment, triggering the industrial large model along with the start of a target production scene, and performing automatic production management of the production line equipment through multi-agent cooperative control driven by an intelligent interaction contract. The technical problem that in the prior art, an industrial production system lacks intelligent and multi-dimensional collaborative optimization is solved, and the technical effects of improving the production efficiency, the resource utilization rate and collaborative work of production line equipment are achieved.

The invention discloses a multi-robot cooperative work method based on a contrast learning role representation reinforcement learning algorithm, and belongs to the field of multi-agent reinforcement learning. Comprising the following steps: each robot obtains observation information of a current environment, and performs time sequence modeling, role modeling, spatial modeling, action selection, award value obtaining and state value generation respectively; in the process, observation information of each robot, global state information of the current environment, a reward value, role representation and the like are stored in an experience playback pool, the steps are repeated, and finally model optimization is completed by using data stored in the experience playback pool. The intelligent agent behavior homogenization problem and the reputation distribution problem in the multi-robot cooperative work process are solved, cooperative contribution between the robots can be effectively quantified, and therefore the robots are stimulated to work cooperatively better in future tasks, the robots preferentially select behaviors beneficial to the whole system, and the overall operation efficiency is improved.

The invention relates to the technical field of engineering project management, and discloses an engineering project supply chain collaborative management system, which comprises a unified data interface module used for acquiring multi-source business data from heterogeneous information systems of an engineering project general package party, a sub-package party, a material supplier and a logistics service provider, processing the multi-source business data into a standardized business data model; and a business process management module. By adopting the technical scheme that a unified data interface module and a workflow engine cooperatively work, the technical effects of connecting information systems of all participants of a supply chain and realizing automatic synchronization of purchasing, inventory and construction progress data and linkage of a business process are achieved; compared with the technical scheme that each party adopts an incompatible information system and depends on manual information transmission in the prior art, the defect that the accuracy of a project plan is damaged due to difficulty in collaborative operation caused by data obstruction is overcome.

The invention provides an unmanned aerial vehicle and unmanned tractor collaborative operation method, which comprises the following steps: step 1, scanning and constructing a two-dimensional grid map of a field environment through a laser radar installed on an unmanned aerial vehicle, and sending the two-dimensional grid map to an unmanned tractor; step 2, the unmanned tractor carries out field full-coverage path planning based on the two-dimensional grid map and by considering tractor steering constraints; step 3, performing a path tracking task by the unmanned tractor based on field full-coverage path planning; and 4, when the path tracking task is carried out, information obtained by real-time scanning of a laser radar carried by the robot is fused, obstacle detection is carried out, and the path is dynamically updated to be a collision-free path according to the obstacle.

The invention discloses a network asset management system and a risk assessment method. The network asset management system comprises an asset surveying and mapping module, a safety detection module, a control module and a risk assessment module. Through cooperative work of the sub-modules, potential threats can be quickly and comprehensively identified and coped with, the identification capability of unknown vulnerabilities is improved, reasonable allocation of security resources is realized, meanwhile, specific environments and requirements in a service scene are fully considered, more efficient, more accurate and more intelligent network security decision assistance is provided for users, and the user experience is improved. The safety is improved; and the risk is reduced.

The invention relates to the technical field of information, and discloses a hotel resource digital management method and system and a storage medium. The method comprises the following steps: constructing a unified semantic data model; multi-source data fusion and real-time state perception visualization are realized; cross-department collaborative arrangement is carried out; and intelligent decision support and optimization are realized. According to the invention, a comprehensive digital management platform based on a unified semantic data model, multi-source data fusion, real-time state perception, cross-department collaborative workflow arrangement and intelligent decision support and optimization is constructed. According to the platform, global visualization and real-time dynamic management of each core resource of the hotel are realized, and the operation efficiency and the fine management level of the hotel are remarkably improved. The departments of guest rooms, catering, conference rooms, spare part inventory, human resources, finance and the like do not combat each other, but perform cooperative work based on a unified data view.

The invention relates to the technical field of production management, and particularly discloses a bearing processing productivity optimization and production scheduling system, which comprises a process state sensing module, a dynamic bottleneck identification module, a self-adaptive buffer control module, a collaborative scheduling decision module and a productivity optimization execution module. Through cooperative work of the dynamic bottleneck identification module and the adaptive buffer control module, a static management mode of a traditional fixed buffer area is thoroughly changed. The system can sense the change of a production flow in real time, accurately identify a bottleneck, and dynamically adjust the target inventory level of a buffer area based on a fuzzy control algorithm, so that a buffer strategy can adaptively match a current production state. The problem that upstream and downstream processes wait for each other due to improper arrangement of a buffer area is solved, and passive blockage and material interruption between the processes are converted into active and flexible rhythm cooperation, so that systematic equipment waiting time is remarkably shortened, hidden capacity is released, and the equipment comprehensive utilization rate and output efficiency of a whole production line are improved.

The invention discloses a lightweight spliced bridge vibration monitoring system for cooperative work performance intelligent perception, and belongs to the technical field of bridge structure health monitoring, and the lightweight spliced bridge vibration monitoring system comprises a lightweight targeted sensing subsystem which comprises a plurality of perception assemblies arranged in a targeted manner; the intelligent edge acquisition and transmission subsystem has an independent addressing function and a time synchronization function and is used for preprocessing and lightweight processing; the cloud edge collaborative storage management subsystem performs hierarchical storage, security control and efficient retrieval on the data to form monitoring data; and the cooperative performance perception early warning subsystem realizes state evaluation and graded early warning of the cooperative work performance of the spliced bridge through multi-index fusion. By adopting the lightweight spliced bridge vibration monitoring system for cooperative work performance intelligent perception, the problems of insufficient lightweight and targeting performance, low data processing, transmission and storage efficiency, and inaccurate cooperative performance evaluation, damage positioning and early warning of traditional spliced bridge vibration monitoring are solved.

The invention discloses automatic laser texturing equipment for a tire inner wall application layer, and belongs to the technical field of laser cleaning. Comprising a machine tool body, a laser texturing assembly, conveying assemblies and a main controller, and the conveying assemblies are two roller type conveying belts which are located on the two sides of the machine tool body respectively; the laser texturing assembly comprises a laser component, a dust removal assembly, a rotary clamping assembly and an overturning discharging assembly, the laser component is combined and connected with the dust removal assembly, the overturning discharging assembly is used for receiving defective products and sending the defective products out of the machine tool body, and the machine tool body is provided with a material taking opening at the overturning discharging assembly; through cooperative work of all the assemblies, automatic laser texturing treatment of an application layer on the inner wall of the tire is achieved, all-round surface texturing is conducted on the designated area and the designated breadth of the inner wall of the tire, the roughness of an airtight layer of the inner wall of the tire is increased, and therefore the pasting capacity of mute cotton is enhanced; the scheme has the advantages of high texturing precision, high automation degree, convenience in recovery and the like, and the production quality and efficiency of tires can be effectively improved.

The invention relates to the technical field of logistics management, in particular to a logistics order transportation management and control system based on digital driving, and the system comprises a data collection module which is used for collecting order data of a logistics order, environment data of an initial path and traffic data, carrying out the preprocessing of the collected data, and carrying out the fusion construction of a basic data set after the processing; and the path evaluation module is used for carrying out trafficability risk evaluation on the initial path based on the basic data set and judging whether to adjust the initial path based on an evaluation result. According to the invention, through cooperative work of the data acquisition module, the path evaluation module and the path planning module, full-process digital management of logistics transportation is realized; by utilizing dynamic path planning and multi-dimensional risk assessment, the influence of extreme weather on logistics transportation is effectively solved, and the transportation timeliness is guaranteed, especially under the conditions of road closing, icing and the like in snowy weather.

The invention provides a truss structure autonomous design system and method based on multiple agents. A layered multi-agent architecture is adopted, a general control agent is taken as a core, and a high-level design intention is analyzed and a plurality of downstream special agents are arranged for cooperative work; the whole design process realizes automatic closed loop through a graph-based workflow engine; the core innovation of the method is a hybrid intelligent optimization algorithm of LLM heuristic exploration and genetic algorithm accurate fine tuning, and the algorithm is driven by an original and quantifiable design quality scoring system to efficiently carry out analysis-diagnosis-optimization iteration so as to cooperatively improve the safety and economy of the design. The design time can be shortened from several hours to several minutes, about 7.0% of material consumption is saved on average, it is ensured that the scheme completely conforms to industry specifications, the design efficiency, economy and reliability are greatly improved, and meanwhile the use threshold of professional design software is remarkably reduced through natural language interaction.

The invention discloses a turnover telescopic injection type shallow water lotus root planting machine which comprises a walking device, a lotus root seedling storing, sorting and conveying device, an adjustable barrel entering device, a turnover telescopic seeding device and an integrated digging and burying device. The lotus seedling storing, sorting and conveying device is arranged at the top of the walking device, the adjustable barrel entering device is arranged on the walking device and close to the lower portion of the tail end of the lotus seedling storing, sorting and conveying device, and the turnover telescopic seeding device is arranged on the walking device and close to the lower portion of the tail end of the adjustable barrel entering device. According to the overturning telescopic seeding device, a series of complex actions such as overturning, stretching and injecting are completed through cooperative work of various mechanisms, and the integrity of lotus seedlings in the planting process and accurate control over the planting depth and inclination are guaranteed.

The embodiment of the invention provides a task information processing method and device, equipment, a storage medium and a program product, and relates to the field of artificial intelligence. The method comprises the following steps: acquiring configuration information of a target task input by a user; according to the configuration information, target scheduling plan information of the target task about an execution tool is generated through the planning agent, and the target scheduling plan information comprises at least one subtask of the target task and a preset execution tool needing to be scheduled by the subtask; according to the target scheduling plan information, determining an input parameter of each preset execution tool needing to be executed through the execution agent, and according to the input parameter, controlling the preset execution tool to execute a corresponding sub-task in the target scheduling plan information; and according to the target scheduling plan information, the execution result of each preset execution tool is converted through the expression agent and then is output to the user. According to the invention, multiple different agents work cooperatively, so that the decision accuracy and applicability of the task processing process are improved.

The utility model provides a novel QSFP-DD packaging optical module comprising a pedestal, the left side of the pedestal is detachably connected with a reset pull ring, and the interior of the pedestal is fixedly connected with a PCB device group. According to the novel QSFP-DD packaging optical module, the base, the reset pull ring, the upper cover, the heat dissipation teeth, the heat dissipation cover and other structures are arranged, the base serves as a core support, the PCB device set, the reset pull ring and the reset spring are accurately positioned and stably installed through a limiting groove, an installation cavity and a spring groove in the base, cooperative work is ensured, the reset pull ring is installed on the left side of the base, and the upper cover is arranged on the left side of the base. The state of the reset spring can be mastered in real time through the observation groove; the upper cover and the base are tightly connected through screws, internal components are covered and protected, external adverse factors are resisted; assembly and maintenance are also facilitated through screw connection; the heat dissipation teeth and the heat dissipation cover construct an efficient heat dissipation system, and heat dissipation is rapid; influence of over-high temperature on performance is avoided, and stability, reliability and service life of the optical module are improved.