2783 results about "Workstation" patented technology

The invention relates to the technical field of path planning, and discloses a path planning method and system of an AGV (Automatic Guided Vehicle) for a silver electrolysis process workshop. The method comprises the following steps: carrying out environment characteristic acquisition and electronic map construction on a silver electrolysis process workshop to obtain a silver electrolysis process workshop electronic map; calculating an initial optimal path of the AGV from the current position to the target workstation; detecting the actual driving resistance in the execution process of the initial optimal path to obtain a path correction parameter; performing local adjustment to obtain an energy-saving safe path; and in the process that the AGV executes the energy-saving safe path, the front moving obstacle and the electrolyte leakage area are monitored in real time, and a temporary detour path is generated. According to the application, the path planning is more suitable for the actual environment characteristics of the silver electrolysis workshop, the emergency situation of the silver electrolysis workshop can be timely handled, the equipment safety and the production continuity are guaranteed, the no-load rate of the AGV is reduced, and the overall logistics efficiency of the silver electrolysis workshop is improved.

The invention discloses a production line load balancing method based on an intelligent optimization algorithm, and the method comprises the following steps: S1, collecting the data of each station of a production line in real time, and carrying out the verification of the validity of the data; s2, performing multi-dimensional correlation analysis on the real-time dynamic data set; s3, multi-scale feature extraction is carried out through a Transform self-attention mechanism; s4, determining a real-time optimization value of the target weight coefficient by adopting a dynamic adaptive adjustment mode; s5, performing iterative optimization on the production task load of each station through a whale optimization algorithm, and generating an adjustment sequence of task allocation of each station in real time; s6, a task load active exchange strategy between stations is adopted, and a scheduling instruction is output; and S7, performing dynamic regulation and control on the production task executed by each station according to the scheduling instruction, and forming a real-time closed-loop feedback production line load dynamic balancing system. Through self-adaptive adjustment and a real-time feedback correction mechanism, the production efficiency and the equipment utilization rate are improved, and the energy consumption is reduced.

The invention belongs to the field of intelligent music generation, and relates to an intelligent music production system and method based on a model context protocol, and the system comprises a large language model, the model context protocol, and a digital audio workstation execution layer. The large language model is used for deconstructing a natural language instruction into structured operation logic and generating a semantic instruction based on the music knowledge base; the semantic instruction at least comprises a device parameter and a chord sequence; the model context protocol is used for compiling the semantic instruction into a JSON command and synchronizing working state data of the digital audio workstation in the digital audio workstation execution layer to a large language model so as to update a model context; the model context comprises track configuration, effect chain parameters and time sequence positioning information of the digital audio workstation; the digital audio workstation execution layer is used for converting the JSON command into music operation to obtain a music operation file; a man-machine cooperative music production mode is reconstructed, and the quality of music production is improved.

The invention discloses a full-automatic grinding method and system for steering knuckle flash based on 3D vision, and relates to the technical field of casting post-processing automation. A trimming-free direct polishing process is innovatively provided, a casting is scanned in real time through a high-precision 3D visual system, a flash space molded line is accurately captured, and one-key calibration of a camera, automatic generation and dynamic simulation of a flash path, multi-tool intelligent switching and self-adaptive adjustment of residual height are achieved in combination with self-developed off-line programming software. According to the system, a robot is adopted for grabbing workpieces to cooperate with a fixed type multi-cutter work station, a disordered feeding technology is integrated for 2D / 3D visual guiding grabbing, workpiece deformation and die difference are effectively dealt with, and flash residues are thoroughly eliminated. The method is characterized in that visual scanning, path planning and execution control are seamlessly fused, the dependence of traditional automatic grinding on the trimming process is broken through, the yield and efficiency are remarkably improved, and the industrial problem of full-process automation of casting flash is solved.

The invention provides a semiconductor equipment task scheduling control method and system, equipment and a medium, and the method comprises the steps: collecting multi-factor operation data and operation task data of an operation arm, splitting a task into a plurality of sub-tasks based on the motion type of the operation arm, and carrying out the task scheduling of the operation arm based on a task unique identifier, a sub-task identifier and an operation arm identifier; associating the multi-factor operation data with the operation task data, and constructing a mapping structure; constructing a node set based on the mapping structure, screening the node set to form a candidate node pair set, executing conflict detection according to a conflict detection strategy for each node pair in the candidate node pair set, generating a conflict edge set, and generating a path conflict graph based on the node set and the conflict edge set, the conflict detection strategy comprises station conflict detection, time conflict detection and space conflict detection; and dynamically adjusting the tasks in the candidate sub-task set in real time based on the path conflict graph and the conflict resolution strategy.

The invention provides a dynamic storage intelligent sorting method, system and equipment based on production takt, and a medium, which can improve the adaptability of the sorting system to the production takt, optimize the inventory circulation efficiency, reduce the risk of production interruption caused by material mismatching or supply delay, and improve the production efficiency. The method comprises the following steps: collecting real-time parameters of production takt of each key station on a production line, and obtaining demand information of target materials to be sorted; based on the real-time parameters of the production takt and the demand information, the production takt prediction parameters and the material demand prediction quantity of each key station in a future period of time are predicted, and in combination with the current inventory state, the equipment availability and the preset optimization parameters, a dynamic storage location adjustment plan and an optimal sorting task sequence currently suitable for a production line are generated and are used as the basis; and the flexible dispatching mechanism is dispatched to dynamically adjust the physical positions of the corresponding materials, then the sorting mechanism is called to sort out the target materials with the specified number from the dynamically adjusted storage locations, and then the target materials are sorted to the corresponding target stations.

A splice equipment assembly includes two routing paths along opposite sides of a splice region. The two routing paths do not cross. The two routing paths do not extend circumferentially around the splice region. The two routing paths provide adequate slack to allow a splice tray to be removed from the splice region and moved to a workstation outside of the splice equipment assembly. Multiple splice equipment assemblies can be mounted to the same rack (e.g., at a front and rear of the rack).

The invention provides a dynamic factory production line balancing method and system based on adaptive control, and the method comprises the steps: obtaining a real-time operation state set of a production line, carrying out the work station correlation feature analysis processing of the real-time operation state set of the production line, generating a work station correlation feature matrix, carrying out the production line bottleneck recognition based on the work station correlation feature matrix, and carrying out the dynamic factory production line balancing. Generating a bottleneck station feature set, wherein the bottleneck station feature set comprises bottleneck station identifiers and corresponding operation parameter deviation features and material overstock features; and generating a production line dynamic adjustment strategy set according to the bottleneck station feature set, wherein the production line dynamic adjustment strategy set comprises a parameter adjustment strategy and a material distribution strategy for the bottleneck station. According to the invention, the timeliness and effectiveness of production line balance control can be improved.

The invention discloses an intelligent manufacturing workstation safety control system oriented to man-machine cooperation, and belongs to the technical field of intelligent manufacturing and man-machine cooperation. The system comprises a multi-modal sensor array, a personnel state sensing module, a robot state monitoring module, a dynamic safety area adaptive calculation module, an intention prediction and risk assessment module, a cooperative control decision module and an execution feedback module. The dynamic safety area self-adaptive calculation module constructs geometric representation of a man-machine interaction space based on a topological manifold theory, and calculates a dynamic safety boundary in real time; the intention prediction and risk assessment module is fused with multi-source information to predict a future trajectory of a person and assess a collision risk; the cooperative control decision module performs multi-objective optimization with safety and efficiency as double objectives to generate an optimal adjustment strategy, the system realizes prospective safety control based on intention prediction, the cooperative efficiency is improved by 25%-45% on the premise of guaranteeing safety, and the working safety accident rate is reduced to be close to zero.

The invention relates to a packaging method for modeling and production unit combination of digital twin virtual equipment, which realizes modeling of the virtual equipment through an abstract process from top to bottom, and ensures high cohesion packaging of key attributes, states and behaviors of the virtual equipment in combination with an information hiding and uniform interface mechanism. A production unit-level combination and hierarchical packaging framework is further constructed based on the equipment model, and recursive combination and interoperation of multiple layers of modules are realized through unified station-level, production line-level and workshop-level interfaces and scheduling logic; according to the method, the modeling and packaging process of the digital twin virtual equipment is defined, the high cohesion packaging and interface uniformity of the model are highlighted, and cross-level combination and scheduling logic design are supported, so that the consistency and the implementability of the model in the system integration, evolution extension and module multiplexing processes are remarkably improved, and the modeling efficiency of the digital twin virtual equipment is improved. And universal and normalized technical support is provided for hierarchical construction and efficient deployment of virtual equipment in an intelligent manufacturing system.

The invention discloses a definition calibration method and device, a storage medium and computer equipment. Comprising the following steps: acquiring a to-be-tested camera module shooting an image card to obtain an image card image; identifying a plurality of statistical areas with equivalent texture features in the graphic card image; calculating the definition of the statistical area; and comparing the definition of the statistical area at the same preset test position with the reference value, and / or comparing the definition of the statistical area at different preset test positions, and determining a calibration result of the to-be-tested camera module. According to the method, quantitative evaluation of camera performance definition and uniformity can be realized through multi-region definition statistical comparison on the same graph card image, test errors during cross-module, cross-region and cross-time sequence detection are avoided, accurate definition verification is realized, additional arrangement of an independent work station and a module disassembly and assembly process are avoided, and the detection efficiency is improved. One-button four-corner definition quantitative comparison is realized, and time, manpower and space costs are remarkably reduced.

The utility model provides a powder assembly production line for eye shadow production, which comprises a support, a conveying mechanism arranged on the support, a plurality of eye shadow boxes arranged on the conveying mechanism in a linear array, and a plurality of powder assembly work stations arranged along one side of the conveying mechanism in a linear array. The powder assembling work station comprises a cabinet, a mechanical arm mechanism arranged in the cabinet, a conveying assembly arranged close to the mechanical arm mechanism and an upper computer arranged on the cabinet, and eye shadow powder blocks are arranged on the conveying assembly; the conveying mechanism is controlled through a speed regulator, the conveying assembly is controlled through a PLC, the mechanical arm mechanisms are all connected to the upper computers through doMot ion controllers, and the conveying mechanism and the upper computers are all connected to the main computer. According to the powder combining production line for eye shadow production, eye shadow powder blocks of different colors and types can be automatically placed in the eye shadow box, time and labor are saved, the production efficiency is greatly improved, and the production cost is reduced.

The invention discloses a hydropower station computer monitoring operator station fusion system, which comprises a controlled plant computer monitoring system and an operator station fusion system, and is characterized in that a fusion operator workstation is directly connected with a local switch and a controlled plant switch through double independent network interfaces; a man-machine interface module is fused to uniformly manage monitoring and control of cross-plant equipment; and the data server and the switch adopt a dual-computer redundancy architecture and STP / LACP link redundancy, and are combined with AES-256 encryption and instruction bidirectional verification to improve the security. The system fuses multi-source data through an improved adaptive weighted Kalman filtering algorithm, predicts an equipment state trend by using an LSTM model, supports local / controlled priority mode switching, and automatically triggers data caching and instruction degradation when a network is abnormal. An original system does not need to be transformed, through physical direct connection and logic fusion, the framework is simplified, the operation and maintenance cost is reduced, efficient integration and reliable redundancy of multi-plant monitoring functions are achieved, and the system is suitable for large hydropower stations and one-plant multi-station scenes.

According to the electrolyte characterization testing work station, the electrolyte characterization testing system and the electrolyte characterization testing method, unmanned electrolyte characterization testing can be achieved through automatic design, the characterization testing process is accurately controlled, the testing efficiency is greatly improved, repeated testing can be autonomously completed, and the working efficiency of the electrolyte characterization testing work station is greatly improved. Standardized test data are collected, and high-throughput and standardized full-data-link management is achieved.

The invention relates to the technical field of data processing, in particular to a generator circuit breaker box production line monitoring method and system. The method comprises the following steps: acquiring multi-modal data of each station on a production line, and extracting station fusion features; constructing a graph network, and obtaining a station state vector of each station containing the accumulated influence of the upstream process through the graph network; inputting the station state vectors into a prototype network and a reconstruction network trained by normal working condition data in parallel; and for any box body on the production line, the station state vectors corresponding to the stations are connected in series according to a production time sequence, a production quality evolution track of the box body is constructed, the evolution track is compared with a reference track generated based on a plurality of standard workpieces under a normal working condition, and a final quality evaluation index of the box body is obtained. The method has the effect of improving the quality monitoring precision.

The invention provides an automatic production station working hour statistical system and method based on near field communication, the system comprises five layers of architectures including an identity recognition layer, a data acquisition layer, an edge computing layer, a cloud service layer and a terminal interaction layer, and the method completes the steps of initialization, NFC interaction triggering, multi-mode mistaken touch prevention verification and the like by means of the system. NFC, a sensor and a face recognition technology are fused, core modules such as task intelligent matching, energy consumption-man-hour linkage accounting and cross-station collaborative man-hour splitting are designed, and the system further has the functions of offline intelligent caching and multi-dimensional man-hour analysis. According to the invention, automation and precision of man-hour statistics are realized, single-station standardization and multi-station collaborative production scenes are adapted, data are ensured to be reliable and free of loss, deep fusion of production data is realized, enterprise hardware and management costs are reduced, and the intelligent manufacturing fine management level is improved.

The invention discloses an intelligent animal epidemic disease monitoring management and early warning workstation, which comprises a multi-modal data acquisition module, an epidemic disease risk assessment module, a dynamic early warning threshold generation and judgment module, a visual human-computer interaction interface and a block chain storage module, the multi-modal data acquisition module is used for acquiring animal data of each monitoring point in a preset monitoring area and environment data of animals; the epidemic disease risk assessment module is used for comprehensively analyzing the animal data and the data of the environment where the animals are located to obtain epidemic disease risk indexes of all monitoring points in the current monitoring area; the dynamic early warning threshold generation module is used for dynamically generating an early warning threshold and judging an epidemic disease risk index to obtain an epidemic disease risk level and an epidemic disease risk area; the visual human-computer interaction interface is used for displaying the epidemic disease risk condition in the monitoring area; and the block chain storage module is used for data storage. According to the invention, the accuracy and timeliness of early warning of epidemic diseases are improved.

The invention discloses a digital twinning-based three-dimensional visual management system and a digital twinning-based three-dimensional visual management method for an anode assembly workshop. The system comprises a triple binding index module, a unified time axis alignment module, a view cone inverse solution positioning module, a safety linkage arrangement module and a resume playback module, and is provided with a process template library and a network isolation / main / standby module. Three-dimensional positioning and PTZ linkage of an AI / threshold event are realized by establishing mapping of a three-dimensional object, a camera and a PLC point location; the batch / bracket / station events, the PLC time sequence and the video slices are indexed in a unified mode; shadow verification, interlocking check, instruction issuing, read-back and video consistency confirmation and trace leaving are executed according to the process, and a safe closed loop from warning to disposal is formed. The method comprises the steps of access and calibration, triple binding, time axis alignment, event positioning and stream taking, linkage processing and resume filing. The positioning and handling efficiency can be improved, the misoperation risk is reduced, and cross-production-line reuse and tracing evidence obtaining are supported.

The invention relates to the technical field of cigarette production, in particular to an automatic auxiliary material tray matching work station suitable for full-specification production. Comprising an industrial robot module, a 3D visual camera module, a code reader module, a tool clamp module, a clamp storage module, a cigarette auxiliary material and a tray. The tool clamp module and the clamp storage module are arranged on the two sides of the industrial robot module respectively, the 3D visual camera module is located above to-be-prepared auxiliary materials to be used for positioning and sending position information, the code reader module is arranged between an industrial robot and the prepared auxiliary materials to be used for scanning codes, and an automatic gun changing disc at the tail end of the industrial robot can switch corresponding clamps. And after the industrial robot receives the position information, the clamp is switched to grab the to-be-prepared auxiliary materials, and the auxiliary materials are placed on the prepared auxiliary material tray after being matched with the code reader to scan codes. Through multi-module cooperation, full-process automation of tray distribution is achieved, manual operation is reduced, production efficiency is improved, meanwhile, by means of accurate positioning and code scanning, the material recognition accuracy is guaranteed, and the workshop automation and intelligence level is remarkably improved.

The invention discloses a workstation electrical parameter real-time monitoring and fault early warning method, which belongs to the technical field of electrical equipment monitoring, and comprises the following steps: acquiring voltage parameter data, current parameter data and temperature parameter data through a multi-source sensor deployed in a workstation, and performing timestamp alignment processing; initial electrical parameter data are obtained and preprocessed, and preprocessed electrical parameter data are generated; historical electrical parameter data are acquired and analyzed and calculated in combination with the preprocessed electrical parameter data, and a dynamic early warning threshold value is generated; extracting multi-parameter characteristics based on the preprocessed electrical parameter data, calculating a correlation coefficient, performing collaborative analysis in combination with a dynamic early warning threshold, and generating a fault prediction result; and performing fault diagnosis according to the fault prediction result, and generating and outputting an early warning instruction. According to the invention, a mode of generating the dynamic early warning threshold and carrying out multi-parameter collaborative analysis is adopted, so that accurate prediction and intelligent graded early warning of the electrical fault of the workstation can be realized.

The invention provides a control method of an unequal-arm independent vacuum manipulator, which comprises the following steps: S1, the vacuum manipulator sets a corresponding control mode according to an instruction sent by an upper computer and in combination with a taught station position, and the control mode comprises single-taking single-placing, multi-taking multi-placing and cross-taking-placing; s2, according to the selected control mode and the station position, planning to obtain a motion track; s3, through a forward or backward kinematics algorithm, a manipulator joint coordinate system and a motor coordinate system are converted, and position point decoupling is carried out on the motion trail; and S4, the vacuum manipulator transmits the wafer according to the decoupled position point and the motion trail. In the wafer transmission process, the vacuum manipulator supports multiple transmission modes including single-mechanical-arm-assembly wafer taking and placing, double-mechanical-arm-assembly simultaneous wafer taking and placing and double-mechanical-arm-assembly cross wafer taking and placing, and the wafer transmission efficiency of the manipulator is improved to the maximum extent.

The invention relates to the technical field of torque sampling inspection, in particular to an intelligent mechanical torsion control method and system. Comprising the following steps: dynamically binding a plurality of intelligent wrenches to a specified station through a system server, namely distributing an independent IP and a communication port for each wrench, and establishing a three-dimensional mapping relationship among an operator account, a station number and a wrench serial number; constructing a dynamic torque calibration model based on the environmental parameters and the equipment state, and correcting the original measurement value of the wrench in real time; uploading a tracking card number to a server through a station code scanning gun, and establishing a binding relationship between the tracking card number and a station number; the intelligent wrench uploads real-time tightening data through a multi-path redundancy transmission mechanism, and the server associates and stores the data with the station number and the tracking card number; and dynamically distributing a process program sequence according to the historical efficiency of the station, and issuing the process program sequence to the wrench for execution through the handheld controller. The scheme provides a novel torsion management and control system with dynamic resource scheduling, total element data connection and intelligent process adaptation.

The invention discloses a cloud desktop resource pool dynamic prediction method, system and device, a medium and a product, and relates to the field of cloud computing, remote cloud desktop management and resource scheduling, the method comprises the following steps: preprocessing original data collected in real time based on a workstation graph node, and constructing a multi-dimensional feature vector; inputting the multi-dimensional feature vector into a machine learning model, and predicting the number of cloud desktop connection requests in a future time period; dynamically calculating cloud desktop resource pool parameters according to the number of cloud desktop connection requests; inputting the parameters of the cloud desktop resource pool into a cloud desktop session management system, dynamically adjusting the number of started cloud desktops in the cloud desktop resource pool, and synchronously updating a scheduling strategy; and according to the scheduling strategy, predicting needed available resources of the session demand in advance, and when the workstation graphic node receives the session demand initiated by the user side to the client side, calling the needed available resources. The resource utilization rate and the intelligent prediction capability are improved, and the response delay is reduced.

The invention discloses a secure cloud workstation and a resource scheduling method suitable for a high-altitude weak network environment, and the secure cloud workstation comprises a virtualization management platform which is used for carrying out the virtualization processing of core computing components of a plurality of servers contained in a back-end server cluster, and forms a plurality of virtual hosts; the front-end thin client only reserves display and input functions, establishes connection with the virtualization management platform, receives a virtual host human-computer interface pushed by any virtual host in the virtualization computing resource pool, and feeds back a user operation instruction to the virtualization management platform; the transmission protocol optimization module is used for integrating graph, input and audio data transmission channels, monitoring the network bandwidth and the delay state of a high-altitude area in real time by adopting a self-adaptive compression algorithm, and dynamically adjusting the transmission image quality and the frame rate of a virtual host human-computer interface; and the resource scheduling module is used for automatically allocating computing resources to the plurality of virtual hosts based on the load data of the virtualization management platform so as to realize cross-server load balancing.

The invention relates to the field of data processing, in particular to a processing production line monitoring method and system for a fan controller. The method comprises the following steps: acquiring multi-modal time sequence data; constructing a production line topological structure diagram, processing the data by using a space-time diagram convolutional network, and extracting space-time correlation features; judging whether the production line is in an abnormal state or not in real time; calculating the gradient contribution degree of the health entropy of the production line to the input characteristics of each station, and positioning an abnormal root station with the highest contribution degree; and inputting the time-space correlation characteristics into a track prediction module based on Kalman filtering and an attention mechanism to generate an evolution track of the health entropy of the production line in a future preset time window, the evolution track including a predicted value and a confidence interval, and being used for performing early warning on potential deterioration of the state of the production line. By adopting the method provided by the invention, the systematic risk of the fan controller processing production line can be effectively predicted, and the troubleshooting efficiency and accuracy are improved.

The utility model relates to an intelligent cleaning device for a sand box, and belongs to the field of industrial automation and intelligent manufacturing. According to the scheme, the rail type RGV is adopted to automatically convey the sand box to the closed intelligent cleaning work station, and the information of the sand box is read through the RFID tag and synchronized to the information system. The cleaning robot scans the position of the sand box through the visual recognition device, and the tool changing robot grabs the adaptive drill bit from the drill bit tool library according to a system instruction and assembles the adaptive drill bit to the electric hammer chuck. And the cleaning robot drills and dredges the sand guide hole of the sand box, returns to the quick change frame to replace the electric pick, and performs multi-angle shoveling and scraping operation on the cavity of the sand box. And after cleaning is completed, the cleaning robot is switched to the sand blasting gun, and fine sand cleaning on the surface of the sand box is completed. The scheme aims at solving the problems that traditional manual cleaning is low in efficiency, severe in environment and large in potential safety hazard.

A method comprises: at a workstation with a biometric keyboard that has keys with fingerprint readers: accepting a login to the workstation by a first user; receiving, from the fingerprint readers, first fingerprint readings indictive of first fingerprints of the first user responsive to typing on the keys by the first user; upon first determining the first fingerprint readings match known first fingerprints for the first user, authenticating the first user as an authorized user; receiving, from the fingerprint readers, second fingerprint readings indicative of second fingerprints of a second user responsive to typing on the keys by the second user; and upon second determining that the second fingerprint readings do not match the known first fingerprints of the first user, automatically logging-out the first user to prevent the first user from using the workstation.

The invention discloses a hybrid office efficiency optimization system based on digital twinning and space calculation, and relates to the technical field of computer science and technology, and the system comprises a data collection module which captures the station layout parameters, the personnel movement track, the equipment use state and the environment parameters of an entity office space in real time through an Internet of Things sensor array, and transmits the parameters to a server; the sensor array comprises a positioning base station, a thermal imager, an intelligent electric meter and an acoustic sensor. The hybrid office efficiency optimization system provided by the invention can accurately and comprehensively map the office environment through the real-time data acquisition and multi-source fusion technology, solves the problem of single data acquisition of the traditional system, and improves the efficiency of the office by utilizing the space calculation and three-dimensional modeling technology. According to the system, a three-dimensional space model comprising an interactive station unit, an equipment entity and a personnel virtual avatar is constructed, a basis is provided for dynamic modeling and intelligent optimization, and a multi-objective optimization algorithm and a genetic algorithm are combined, so that the system can be under complex constraint conditions.

The invention provides a conveying control method for an electric energy meter tray. The conveying control method comprises the following steps: determining a path node and a target station which the electric energy meter tray needs to pass through, and a scheduling adaptation relationship among the three; according to the scheduling adaptation relation, constructing a three-dimensional state tensor so as to perform dynamic modeling on the scheduling intention of the electric energy meter tray, and constructing a task priority scoring function; acquiring a currently conveyed electric energy meter tray and a physical position, current to-be-processed quantity of each target station, current cache quantity of each path node and current congestion condition to the target station, and combining the maximum processing quantity of each target station, the physical position of each path node and the corresponding flow velocity to obtain a task priority score function; and obtaining a task priority score so as to perform task optimization control on each electric energy meter tray which is being conveyed at the current moment. By implementing the method and the system, the conditions of path congestion change, load of the target station and the like can be dynamically adapted, so that the problems of resource waste, task processing delay, production efficiency reduction and the like are solved.

The invention provides a non-IP architecture light moment seat control system and method. The system comprises a comprehensive control terminal, a workstation, a light moment host and a plurality of groups of seats, the comprehensive control terminal generates a scheduling instruction according to a pre-acquired seat demand and sends the scheduling instruction to the workstation, and generates a control instruction according to the pre-acquired seat demand and sends the control instruction to the light moment host; the work station is electrically connected with the optical moment host through at least two sending link optical fibers, and the work station executes a scheduling instruction, converts audio and video signals into optical signals and sends the optical signals to the optical moment host; the optical moment host receives the optical signal sent by the work station, executes the control instruction to match the corresponding seat, and sends the optical signal to the corresponding seat; and each seat is electrically connected with the optical moment host through at least two receiving link optical fibers, receives the optical signals and converts the optical signals into audio and video signals for display. According to the invention, a non-IP architecture non-inductive scheduling data transmission mode is adopted, and the data transmission reliability is improved.