151 results about "Production control system" patented technology

The invention provides a puree production line microbial pollution risk real-time monitoring and early warning method, which comprises the following steps: deploying multiple types of sensors, an industrial camera and an operation log interface, collecting environmental temperature and humidity, pH value, dissolved oxygen, image and operation behavior multi-modal data in a fermentation tank in real time, and carrying out edge calculation and standardized preprocessing to obtain the microbial pollution risk of a puree production line. Data missing, abnormity and time sequence difference are eliminated; multi-modal features and a dynamic knowledge graph constructed based on a production process and a pollution event are fused, and a deep learning model and a graph neural network are utilized to realize microbial pollution risk probability intelligent prediction; risk grading and a dynamic weighting algorithm are introduced, grading early warning signals and disposal suggestions are automatically generated, and a production control system is linked to execute response measures; according to the subsequent production state, continuous feedback is carried out, the model and the early warning threshold are adjusted in a self-adaptive mode, and the accuracy, response efficiency and production safety of pollution early warning are remarkably improved.

The invention relates to the technical field of equipment control, in particular to a feeding and discharging machining production control system and method based on a PLC, and the system comprises a multi-mode data sensing module which collects a three-dimensional point cloud and image sequence of a working scene through a laser radar and a visual sensor, and combines a vibration signal and a current signal of a machining main shaft; and after feature extraction, outputting a comprehensive state vector including the workpiece pose and the equipment health state. And the digital twinborn collaborative planning module receives the comprehensive state vector, drives a digital twinborn model to be synchronized with a physical environment in a virtual space, performs Monte Carlo tree search by applying a reinforcement learning algorithm, and generates a flexible control strategy with a time sequence mark. And the digital twinborn collaborative planning module adjusts a task allocation strategy according to the early warning signal, and corrects digital twinborn model parameters based on the execution log. According to the operation process corresponding to the modules, collaborative optimization of the feeding and discharging system and the machining rhythm is achieved, and the equipment utilization rate and the production efficiency are improved.

The application discloses a rapid batch online detection method and system for micro bearings, and relates to the technical field of bearings.The method comprises the following steps: cooperatively collecting micro bearings to generate a multidimensional detection data set; performing dynamic space registration on key detection areas to locate the key detection areas of the micro bearings; performing defect feature extraction on the key detection areas to generate a defect probability distribution graph, performing dynamic segmentation on the defect probability distribution graph, and generating a defect type label group; performing online sorting on the micro bearings based on the defect type label group to obtain a sorting instruction set, generating a detection quality report, and feeding back the detection quality report to a production control system.The application solves the technical problems of low detection efficiency, insufficient sampling accuracy, and difficulty in real-time online detection and quality control of the micro bearings in the prior art, realizes rapid batch online detection of the micro bearings, and improves the detection efficiency and accuracy of the micro bearings.

The invention belongs to the field of automation control, particularly relates to an ampoule bottle production control system based on a PLC, and aims to solve the problems of lack of a feed-forward adjusting mechanism and control lagging during ampoule bottle production control in the prior art. The system comprises a sensing unit which is configured to obtain raw material characteristic parameters used for representing raw material component fluctuation and process state parameters used for representing product quality in the ampoule bottle production process; the processing unit is in communication connection with the sensing unit so as to receive the raw material characteristic parameters and the process state parameters; the control execution unit is in communication connection with the processing unit, and the control execution unit is configured to receive a global optimization instruction; and analyzing the global optimization instruction into a control instruction for at least one station execution mechanism, and driving the at least one station execution mechanism to execute corresponding operation based on the control instruction. According to the invention, the process parameters of the downstream station can be adjusted in advance through a feed-forward adjustment mechanism.

The invention provides a heavy oil thermal-flow coupling development experimental device and method based on microwave-assisted gravity drainage, and belongs to the field of oil-gas field development. The experimental device comprises a three-dimensional oil reservoir simulation system, a microwave-assisted heating system, a horizontal well injection-production regulation and control system and a multi-field monitoring system; the microwave auxiliary heating system comprises a microwave generation regulation and control system, a microwave transmission system and a shaft integrated microwave radiator, the microwave generation regulation and control system comprises an industrial grade microwave generator, a power regulator and a PLC, and the microwave transmission system comprises a microwave coaxial cable and a microwave waveguide tube bundle; and the microwave generator is continuously connected with the microwave waveguide tube bundle and the shaft integrated microwave radiator. According to the heavy oil thermal-flow coupling development experimental device and method based on microwave-assisted gravity oil drainage, the technical problems that an existing deep heavy oil thermal recovery experimental device cannot reproduce a'thermal-flow-force 'multi-field coupling environment, the microwave heating adaptability is poor, and the experimental scale and the field deviation is large are solved. The heavy oil thermal-flow coupling development experimental device and method based on microwave-assisted gravity oil drainage solve the technical problems that an existing deep heavy oil thermal recovery experimental device cannot reproduce the'thermal-flow-force' multi-field coupling environment.

The invention discloses a welding wire production control system and method based on visual feedback, and belongs to the technical field of precision machining. The system comprises a multi-mode intelligent sensing subsystem, a self-adaptive model prediction controller and a safety and exception handling subsystem, and a two-stage control architecture of a quality closed loop and an execution closed loop is constructed. According to the method, the microcosmic roughness, macroscopic geometry, defects and other multi-dimensional quality characteristics of the surface of the welding wire are obtained in real time through multi-modal sensing and fused into a comprehensive quality index; carrying out rolling optimization by adopting a model prediction control algorithm for updating parameters on line, and generating a control instruction; meanwhile, trend early warning based on statistical process control and sudden fault diagnosis based on model residual analysis are operated in parallel, and active safety protection is achieved. According to the method, the problems of unstable quality, control lag and passive safety caused by supplied material fluctuation and tool time variation in the welding wire flaking machining process are solved, and self-adaptive accurate control and intelligent safety protection in the machining process are achieved.

The invention relates to the technical field of industrial internet, in particular to a control system and method for stirrer production. Comprising an edge data preprocessing unit, a flexible production instruction distribution unit and a working condition diagnosis and protection control unit. By constructing an integrated control parameter mapping model, an industrial operation signal is converted into a collaborative sensing digital primitive; the production task is compiled into an intelligent production execution process cluster based on a resource scheduling algorithm, and equipment is driven to execute differentiated production; and performing situation assessment on the digital primitives by using the anomaly detection model, and generating a regulation and control instruction to execute process logic recombination and safety protection. According to the invention, the problems of low production information integration level and tight data in each link of a production control system are solved, and flexible scheduling and active security defense in the production process are realized.

The invention discloses a pet food intelligent production management and control system and a traceability code spraying device thereof, and relates to the technical field of pet food production, and the pet food intelligent production management and control system comprises a production planning unit, a raw material management unit, a production control unit, an intelligent mistake proofing unit and a quality traceability unit. The production planning unit optimizes a production plan and accurately allocates resources, the raw material management unit performs supplier qualification evaluation, raw material multi-level quality inspection and intelligent inventory regulation and control, quality is controlled from the source, the supply chain risk is reduced, the production control unit depends on the equipment real-time monitoring and fault early warning technology, the stability of production parameters is guaranteed, and the production efficiency is improved. The intelligent error-proofing unit integrates OCR verification, threshold detection and prediction model construction, rejects error detection data, prevents data missing, realizes real-time early warning and closed-loop processing of quality risks, and eliminates quality problems in the bud stage, and the quality tracing unit performs real-time early warning and closed-loop processing on the quality risks through full-link data acquisition and a unique tracing code. And accurate positioning and rapid recall of problem products are supported.

The invention discloses an enterprise intelligent comprehensive carbon emission reduction method and system, and the method comprises the steps: collecting the carbon source emission, energy consumption and technological parameters of each production link of an enterprise, and transmitting the parameters to a carbon intelligence brain decision platform; inputting an intelligent carbon flow topology analysis model to construct a carbon flow topology network, and analyzing a carbon flow input and output relationship and intensity distribution; key influence factors are extracted, and multiple groups of emission reduction schemes are generated by combining a carbon emission reduction target input adaptive carbon trajectory optimization algorithm; cost, efficiency and potential parameters are introduced into the carbon intelligence brain decision-making platform to evaluate and screen an optimal scheme, and the optimal scheme is converted into a control instruction; and issuing to a production control system to adjust equipment and process parameters so as to realize closed-loop control. The system comprises a carbon data acquisition unit, an intelligent carbon flow analysis unit, an adaptive optimization unit, a scheme evaluation unit, a scheme screening unit and an instruction execution unit. The carbon emission reduction precision and the carbon emission reduction landing performance are improved, and the production efficiency and the cost are both considered.

The invention relates to the technical field of rock wool board production, in particular to a hot-melt slag regenerated rock wool board production control system based on an intelligent sensor. The data acquisition module comprises an image sensor and a thickness sensor; the production control module comprises an areal density determination unit used for determining whether areal density distribution of the cotton blank is uniform or not according to the areal density distribution characterization value and determining whether the areal density of the cotton blank is qualified or not according to the areal density distribution characterization value, and a correction unit used for determining whether to correct the areal density of the abnormal position or not based on the compensation area; the pendulum bob control unit is used for adjusting the lap joint overlapping degree of the cotton blanks based on the characterization difference value and adjusting the linear speed of the pendulum bob device based on a preset area, and is used for determining whether the thickness stability of the rock wool board is qualified or not based on the thickness fluctuation characterization value; and the curing oven control unit is used for adjusting the chain plate distance of the curing oven or optimizing the preset distribution characterization value. The thickness stability of the rock wool board is improved.

The invention provides a discrete workshop self-adaptive production control system based on a control theory. The problem that an existing production control system is insufficient in adaptability in a dynamic and changeable workshop environment is solved. A traditional modeling method cannot effectively analyze dynamic behaviors of a system and is difficult to deal with transient changes caused by disturbance such as emergency order insertion and equipment faults. By introducing an event-driven mechanism and a multi-target coordination control strategy, dynamic optimization and self-adaptive control of a workshop production system are realized. According to the system, work-in-process and overstock tasks are used as control targets, and dynamic adjustment is achieved by controlling the order input rate and the actual productivity. And the control strategy planning layer and the workshop operation decision-making layer are linked by adopting a centralized event-driven mechanism, and meanwhile, a distributed event-driven mechanism is used in the workshop operation decision-making layer to construct an intelligent unit autonomous decision-making mechanism. The method is suitable for dynamic production control of discrete manufacturing workshops, overcomes the defects in the prior art, and meets the requirements of complex, dynamic and changeable workshop operation environments.

The invention relates to the technical field of digital production control, in particular to a glass fiber cloth multi-process collaborative digital production control system, which is characterized in that a real-time tension sequence data stream is established through a data acquisition module, and a modal entropy extraction module is used for analyzing and generating a signal modal entropy sequence; mapping the sequence amplitude distribution interval into a virtual damping compensation coefficient by using an amplitude deviation mapping model, calculating an adjustment gradient in combination with a first-order differential characteristic, and generating a collaborative sampling control instruction subjected to smooth weighting through an adaptive correction model; the collaborative sampling control instruction drives the cyclic feedback execution module to dynamically adjust or lock the current sampling frequency, and the mechanism effectively gives consideration to the acute capture of transient tension abnormities and the efficient suppression of steady-state data redundancy during operation, and achieves the dynamic balance of the feature extraction precision and the calculation resource utilization rate.

The present application relates to the technical field of production process control, in particular to a prebaked anode grinding production control system based on feedback control, the system comprises: a deviation calculation module acquires acoustic vibration, flow and particle size and calculates filling state, output and particle size deviation, a state modeling module constructs an observation vector based on the deviation and performs Kalman filtering, a weighted comprehensive grinding state index is generated, a regulation and decision module performs PID operation on the index to generate static blade and turbine adjustment instructions, and a feedback module generates pulses and voltage to be sent to an actuator. In the present application, an observation vector is constructed and a state estimation value is output by filtering and removing noise, the deviation is weighted and fused to generate a comprehensive index reflecting the load of the mill, accurate driving instructions are obtained according to the index, dynamic closed-loop control is realized to compensate for the real-time fluctuation of the raw material characteristics, and the estimated results are used to cooperatively adjust the classification parameters to ensure that the finished product particle size meets the standards and improve the overall energy efficiency of the grinding operation.

The application relates to the technical field of carbon fiber die forming of automobile hubs, in particular to a production control system and method for carbon fiber die forming of automobile hubs, which comprises a pressure coordination control module, a temperature field dynamic adjustment module, a defect prediction and compensation module and a multi-source data tracing module. Through segmented pressure curve and temperature-pressure coupling control, combined with multi-source data collected by a distributed sensor array, accurate regulation and control and abnormal tracing in the forming process are realized. The deformation compensation and exhaust control submodule improves process stability, and space-time data modeling locates the root cause of the abnormality, thereby ensuring product quality. Through the cooperative design of hardware and algorithms, the application solves the problems of poor material characteristic adaptability, unstable deformation control and low process quality tracing efficiency, and improves the precision and reliability of carbon fiber hub production.

The utility model discloses a factory power supply control system based on an uninterruptible power supply (UPS), which adopts two sets of UPS equipment to supply power to a field DSC system load in a centralized manner, replaces a traditional dispersed UPS independent power supply mode, and saves the investment of the UPS equipment of each site on site. And the concentration of the UPS equipment facilitates the management, maintenance and monitoring of the equipment, and fault hidden dangers can be found and eliminated in time through background monitoring. Meanwhile, storage battery maintenance and UPS equipment maintenance problems are considered in the design, a parallel operation mode is adopted, when one set of UPS equipment is out of fault, the other set of UPS equipment is seamlessly connected with a conversion power supply for power supply through STS static change-over switches of all sites on site, load disturbance-free and uninterrupted power supply of the DCS on site is achieved, the maintenance efficiency of the equipment is effectively improved, and the service life of the UPS equipment is prolonged. And stable operation of an enterprise production control system is ensured, production is not interrupted, and production cost is reduced.

The invention discloses a full-automatic folder gluer production control system based on the industrial internet, and relates to the technical field of production control, and the system comprises a data acquisition module, a feature conversion module, a sequence construction module, a data loading module, a matching calculation module, a root cause locking module and an information pushing module. According to the method, multi-source data fusion and events are realized by constructing a multi-modal event triggering judgment model, deep fault diagnosis is performed by utilizing time sequence event chain matching and a Bayesian root cause locking model, and the root cause of the glue line defect is automatically, accurately and quickly positioned, so that a maintenance decision is effectively guided, and the maintenance efficiency is improved. The overall efficiency of the production line and the product quality stability are improved, and the problems that in the prior art, due to the fact that single visual inspection is relied on, the root cause of rubber line defects cannot be automatically positioned, operation and maintenance response is slow, and the production quality is unstable are solved.

The application provides a revocation method based on AI analysis and double repeated verification of tracking logic, and belongs to the technical field of intelligent manufacturing of steel products. The method comprises the following steps: based on the material number information identified by the identification device at the entrance of the tracking area, the equipment action signal in the tracking area, the roller running signal and the cold and hot detection signal, a bottom layer logic for tracking the material is established, and a real-time tracking picture is formed; based on the video picture obtained by the on-site camera, the AI analysis system analyzes the video, and obtains the crane feeding and discharging signal and the material position information; when the online material is judged to have the abnormal lifting-off situation of material clamping, the material number information is put into the revocation cache; before the production is reported, the revocation cache is compared with the material completion information in the production control system, and the revocation cache is updated. The application can accurately, reliably and effectively monitor and count the abnormal offline revocation situation of the material in the tracking area.

The invention discloses a fiber bragg grating production control system and method, and belongs to the technical field of optical fiber sensor manufacturing, and the method comprises the steps: obtaining a pre-stress spectrum curve and an ultraviolet laser parameter set of a target optical fiber before writing, and constructing a feature vector reflecting the disturbance sensitivity of the optical fiber; in the laser writing process, acoustic emission signals and laser parameters are collected in real time, and a joint disturbance function is constructed; identifying a nonlinear stress disturbance event through dynamic matching with the sensitive feature vector, and extracting occurrence time and disturbance intensity of the nonlinear stress disturbance event; constructing a prediction model based on disturbance history, predicting a future disturbance trend and adjusting laser parameters; after writing, a grating reflection spectrum is collected and compared with a target template spectrum, and if the similarity requirement is not met, a disturbance error path is traced back, and parameter compensation writing is executed; according to the invention, real-time perception and response regulation and control of micro-disturbance can be realized, and the writing precision and consistency of the fiber bragg grating are improved.

The invention is suitable for the technical field of extrusion injection molding, and provides a production control system based on an automobile heat insulation sheath, which comprises an extrusion molding assembly, and a feeding assembly is fixed at the material conveying end of the extrusion molding assembly; the feeding assembly comprises a material storage part fixed to the extrusion forming assembly in an inserted connection mode, a rotating part rotationally matched with the material storage part, a pushing part fixed to the material storage part in an inserted connection mode and a sliding part slidably matched with the pushing part. The moisture absorption of the raw material particles is achieved, in the forming process, water is subjected to injection forming along with melting of the raw material particles, but the water in the raw material particles can be vaporized at high temperature, bubbles are easily generated in the automobile heat insulation sheath in the forming process, and dents appear on the surface of the automobile heat insulation sheath; therefore, the technical problems are solved, and the technical effect that the raw material particles can be fully dried and preheated is achieved.

This invention provides a control and management system for seamless steel pipe production, relating to the field of steel pipe production control system technology. The system includes: real-time monitoring of raw material process management and comprehensive analysis to obtain raw material quality index and raw material matching degree; real-time monitoring of seamless steel pipe production process management and comprehensive analysis to obtain process stability index and equipment efficiency factor; real-time monitoring of seamless steel pipe quality management and comprehensive analysis to obtain product qualification rate and quality fluctuation coefficient; comprehensive analysis of raw material quality index, raw material matching degree, process stability index, equipment efficiency factor, product qualification rate, and quality fluctuation coefficient to obtain optimization schemes; and construction of a predictive model for the entire seamless steel pipe production line based on a machine learning model to generate expected optimization schemes, thereby improving the controllability, stability, and resource utilization rate of the seamless steel pipe production process.

The invention relates to a production control apparatus (100) for a production system (10), in which a product with predefined product features is to be produced, comprising: input means (102) configured to input predefined product parameters and to input quality step process information; processing means (106) configured to perform a quality process (112) having a plurality of quality steps (114-122) associated with the predefined product features, wherein said quality steps (114-122) are to be selected by an input command, the processing means (106) being configured to determine a sequence of the quality steps (114-122), in which the quality steps (114-122) are to be accomplished, and to link the product parameters to the quality steps (114-122), said quality process further comprising execution steps (124-130), said execution steps (124-130) being executed for each quality step (114-122) and beginning with a first quality step, the execution steps (124-130) comprising: granting access (124) to the respective quality step, accomplishing (126) the respective quality step by processing the quality step process information for said respective quality step, and monitoring (128) the progress of the respective quality step; output means (108) configured to output at least one production control signal (132), in particular to the production system (10), for producing the product after the selected quality steps (114-122) are accomplished.

The application relates to the technical field of lithium battery material preparation, and discloses an LFP positive electrode high-density homogenate process optimization method, a system and a storage medium. The method comprises the following steps: collecting slurry state and process parameter data in real time, analyzing a correlation strength index, identifying an abnormal slurry state mode, extracting a quantitative feature index, obtaining historical upstream and downstream data if the quantitative feature index is not in a preset range, combining an initial slurry state to evaluate the influence degree of upstream fluctuation, generating a risk level, formulating a compensation scheme according to the risk level, verifying the effectiveness of the scheme through virtual simulation, generating an adjustment instruction and delivering the adjustment instruction to a production control system, updating process parameters and storing the process parameters in a historical database, and the application improves the self-adaptive capacity of the homogenate process to upstream fluctuation.

The invention discloses a metal filter screen production control system and method for a semiconductor device, and relates to the technical field of semiconductor device manufacturing, and the system comprises a predetermined demand obtaining module which is used for obtaining a predetermined demand of a metal filter screen; the optimal structural feature acquisition module is used for performing structural feature optimization analysis on the metal filter screen by taking the predetermined application environment as optimization constraint to obtain an optimal structural feature; the detection and analysis module is used for activating an edge detection chip to detect and analyze a real-time filter screen image produced based on the optimal structural characteristics to obtain a real-time production quality index; and the production control and adjustment module is used for carrying out preposed production control and adjustment on the metal filter screen. The technical problems that in the prior art, the production quality is unstable and the efficiency is low due to the fact that the metal filter screen production process depends on manual control and quality detection lags behind are solved, and the technical effects that full-automatic control over metal filter screen production is achieved, and the production quality and efficiency are improved are achieved.

The invention relates to a method for quickly realizing forbidden and limited operation of a cavity during product production, which comprises the following steps that: a manufacturing execution system provides an interface, and a PLC (Programmable Logic Controller) working data address area is added on the manufacturing execution system to match with an automatic production control system; and the manufacturing execution system provides a message interface, generates a chamber forbidding and limiting signal and sends the forbidding and limiting signal to the CVD and DRY equipment through working data, and the equipment automatically realizes chamber forbidding and limiting operation according to the signal after receiving the chamber forbidding and limiting signal. According to the method for quickly realizing the forbidden and limited operation of the chamber during product production, equipment can quickly obtain information and cannot send the existing product to the forbidden and limited chamber through upstream and downstream command control, so that the cost loss is reduced, and the production ex-warehouse efficiency is improved.

This invention discloses a digital production control system for processing lithium metal solid-state battery anode composite materials, belonging to the field of digital production technology. The system includes: a digital production control master node module, used to connect several production process sub-node modules and synchronize real-time data transmitted by the production process sub-node modules; production process sub-node modules, used to collect real-time data of the production processes during the processing of lithium metal solid-state battery anode composite materials and summarize it to the digital production control master node module; a synchronization monitoring module, used to determine whether the delay of the synchronization data between the digital production control master node module and the production process sub-node modules is abnormal; if an abnormal delay time exists, the synchronization control module is invoked; the synchronization control module is used to adjust the synchronization frequency when the delay time of the synchronization data is abnormal. This invention can enhance the level of digital production and improve product quality and yield.

The invention relates to the technical field of intelligent beekeeping, and discloses a mature honey standardized production control system based on strong group multiple box bodies, which comprises a dielectric spectrum sensing array integrated on a comb foundation, a data acquisition module, a central processing module and a user interface module. According to the system, the micro interdigital capacitor unit is used for independently detecting electromagnetic characteristics of substances in cells, the central processing module obtains complex impedance spectroscopy and temperature data, a content classification model and a polynomial regression model containing temperature cross terms are operated in parallel, the types of the contents in the cells are recognized, and the water content of honey is accurately calculated. The system establishes data mapping between a super production area and a hive breeding area, respectively calculates a mature honey harvest index and a breeding health degree score, and automatically generates a honey extraction recommendation or a health alarm. According to the invention, lossless, in-situ and high-resolution monitoring of the internal state of the beehive is realized, and the problems that the bee colony is interfered by manual box opening and the honey maturity is lack of quantitative standards are solved.

The application relates to the technical field of device control, and in particular relates to a PLC-based feeding and discharging processing production control system and method, which comprises a multi-modal data sensing module that collects three-dimensional point clouds and image sequences of a work scene through laser radar and a visual sensor, combines vibration signals and current signals of a processing spindle, carries out feature extraction, and outputs a comprehensive state vector comprising a workpiece pose and a device health state. A digital twin collaborative planning module receives the comprehensive state vector, drives a digital twin model and a physical environment to be synchronous in a virtual space, uses a reinforcement learning algorithm to carry out Monte Carlo tree search, and generates a flexible control strategy with a time sequence mark. The digital twin collaborative planning module adjusts a task allocation strategy according to an early warning signal, and corrects digital twin model parameters based on an execution log. The application realizes collaborative optimization of a feeding and discharging system and a processing beat according to the operation process of the above module, and improves device utilization and production efficiency.

The invention discloses a steel coil specification optimization method and device, equipment and a medium, and relates to the technical field of quality control, and the method comprises the steps: preprocessing order data through width de-weighting and weight merging, generating a combination set satisfying a preset width and coil number range, determining the number of initial steel coils, and constructing an initial combination scheme group; the tabu search algorithm is used for optimizing the combination scheme, the steel coil width variance is made to be minimum, the unified steel coil specification is determined, the result is sent to the production control system to execute the longitudinal cutting and coil dividing operation, the accuracy and efficiency of steel coil specification optimization are improved, the inventory pressure is reduced, and high production efficiency and high resource utilization rate are achieved.

The application discloses a device and method for spraying S-ethofenprox in tobacco threshing and redrying online. The device comprises a dosing unit, a spraying unit and a controller. The controller is connected with an online production control system. The spraying unit is connected with a leaf moistening drum equipment. The dosing unit comprises a medicine tank and a medicine transmission pipeline. The medicine tank is used for storing S-ethofenprox medicine. The spraying unit is used for spraying S-ethofenprox medicine on tobacco in the leaf moistening drum equipment. One end of the medicine transmission pipeline is connected with the medicine tank. The other end of the medicine transmission pipeline extends into the leaf moistening drum equipment and is connected with the spraying unit. A pneumatic diaphragm regulating valve connected with the controller is arranged on the medicine transmission pipeline. The device and method for spraying S-ethofenprox in tobacco threshing and redrying online can spray biological medicine online in tobacco threshing and redrying, so that the purpose of preventing and controlling insect pests of tobacco is achieved. The fumigation and insect killing process in the later storage process of cut tobacco is reduced. The device and method not only save cost, but also reduce chemical pollution and residues.