771 results about "Control layer" patented technology

According to the intelligent home environment intelligent regulation and control system and the control method thereof, various intelligent sensors are arranged, various environment data such as indoor temperature, humidity and illumination are monitored in real time, the data are preprocessed and then sent to a data analysis layer, data features are extracted according to the monitored data and historical data based on the deep learning technology, and user preferences are deduced; the control parameters are adjusted and sent to the equipment control layer, a specific instruction is sent to an indoor smart home, an air conditioner, a humidifier or a curtain and the like are controlled to accurately control the indoor environment, the living preference of a user is met, and in the process, the effect monitoring and dynamic adjusting layer monitors the adjusting condition in real time, and the user experience is improved. If the ideal effect is not achieved after adjustment, the equipment control layer is controlled to continue adjustment, in the process, the abnormal condition of the system is detected, the power consumption of the equipment and other data are monitored at the same time, normal work of the system is guaranteed, possible faults are predicted, a user is reminded in time, and safe and energy-saving operation of the whole system is guaranteed.

The invention relates to the field of industrial automation, in particular to a multi-camera vision stacking pose planning method and system for an intelligent loading and unloading robot. The method comprises the following steps: constructing a collaborative sensing system through a plurality of industrial cameras deployed in a target space, and collecting dynamic environment data of a stacking area in real time; generating a self-adaptive stacking pose based on a hierarchical pose planning mechanism: analyzing an initial pose parameter through a theme control layer and generating a preliminary placement instruction, and verifying the feasibility of the preliminary placement instruction based on environmental data of the collaborative awareness system through a visual verification layer, and a final placement coordinate is optimized by combining the accurate positioning layer with a virtual box matching algorithm. The problems that in the prior art, real-time environment sensing capacity is lacked, pose planning is disjointed with the actual environment, and dynamic change scenes cannot be processed are solved.

The invention belongs to the technical field of unmanned ship tracking control, and discloses a self-adaptive path tracking control method and device for an unmanned ship. The method comprises the steps of monitoring position data in real time through a boundary judgment algorithm to ensure that a ship is always in a preset safe area; multi-source data of ocean currents, radiation, batteries and the like are synchronously collected, three constraint conditions of predicting a drifting track, a charging area and remaining endurance time are constructed, a global optimal path is dynamically generated by applying a path planning algorithm, and the shortest distance, low energy consumption and high charging benefits are balanced. For energy management, a multi-stage power threshold is preset to trigger a differential loss reduction strategy. In a control layer, calculating propeller control parameters in real time based on path deviation, course deviation and environment interference; through collaborative optimization of global path planning and local control, the autonomous navigation capability, the energy utilization efficiency and the task sustainability of the unmanned ship in a dynamic environment are improved, and the method is suitable for ocean monitoring, resource exploration and other scenes.

The invention relates to an MPPT (Maximum Power Point Tracking) control method based on dynamic optimization of a lightweight convolutional neural network, and belongs to the field of artificial intelligence control power tracking. The method comprises the following steps: S0, constructing a convolution-fuzzy neural network model which at least comprises an input layer, a convolution layer, a fuzzy control layer, a deep reinforcement learning layer and an output layer; s1, key parameters of photovoltaic equipment are collected in real time to serve as input data of an input layer; s2, performing convolution operation on the input data by using a convolution layer, extracting a feature vector, and transmitting the feature vector to a fuzzy control layer; s3, combining a fuzzy control layer with a deep reinforcement learning layer, and dynamically adjusting an optimization process of a fuzzy rule through a reward signal; and S4, the fuzzy control layer generates a control signal, and the control signal is transmitted to a DC / DC converter of the photovoltaic system through the output layer. The control method is suitable for a dynamic environment of a photovoltaic power generation system, can be expanded to a grid-connected system, and provides a new thought and technical support for efficient operation of photovoltaic power generation.

The invention relates to the technical field of agricultural intelligent irrigation, in particular to an intelligent irrigation control system and method based on meteorological environment acquisition, and the system comprises a sensing layer, a transmission layer, a control layer, a cloud layer and an execution layer. Then meteorological environment data collected by the sensing layer is transmitted to the control layer through a wireless transmitting module and a wireless receiving module, and a controller of the control layer is integrated with an edge computing unit, a communication unit and a decision-making unit; the problems that an existing agricultural meteorological monitoring and irrigation control system is high in network transmission load coefficient, and the edge computing capability of sensor nodes cannot be effectively utilized; the problem that an irrigation control algorithm based on a static threshold mechanism or a single statistical model lacks adaptive processing of rainfall time sequence prediction and dynamic response ability of specific requirements of crop growth stages is solved.

The invention relates to a dynamic network reconstruction strategy of a digital electric power energy storage system in the technical field of electric power energy storage. The strategy comprises the following steps: S1, building an energy storage system; the system consists of an intelligent layer, a control layer and a data layer, s2, modeling an energy storage network; learning an optimal control strategy of the energy storage network by adopting a graph capsule neural network; s3, dynamic network reconstruction; generating a fault emergency response model based on a Markov decision process; by systematically optimizing a topological structure and an optimal control strategy of the energy storage network, rapid isolation of a fault area and dynamic adjustment and reconfiguration of working modes of energy storage equipment and load equipment are realized, the energy storage network is ensured to still operate stably in a fault situation, and the energy storage efficiency is improved. The flexibility and elasticity (fault tolerance) of the energy storage system in a dynamic environment are improved; by reducing the energy loss in the transmission process, balancing the network load and preventing local faults, the technical problems existing in the prior art are solved, and the sustainable development of a novel renewable energy system is promoted.

The invention provides a training and examination robot system based on a multi-modal large model, equipment and a computer program product, and aims to accelerate training transformation and upgrading and improve coping ability as basic appeals, and based on regular training work of teams, training and examination robot, sensor acquisition equipment and big data platform three-terminal equipment. A multi-modal data acquisition layer for realizing real-time attitude detection and motion capture by using an edge calculation algorithm, a data processing and analysis layer for finishing real-time image processing through localized edge calculation in a network-free or power-free environment, and system control functions for finishing intelligent decision making, evaluation, error correction and the like are provided; an intelligent decision-making and control layer of a training subject rewriting decision-making mechanism is established, cross-modal collaborative learning middleware is utilized to realize modal representation consistency while training subject transposition evaluation is realized, training and assessment operations of the same subject of multiple persons or different subjects of multiple persons are supported, and the training and assessment efficiency is remarkably improved.

Aspects of the present disclosure are directed to applying voice controls to a target virtual object in an artificial reality environment. User controls in an artificial reality environment can take many forms. Some user controls, such as ray casting or gaze tracking, can incorporate selection mechanics to select the artificial reality environment element (e.g., virtual object) that the user is targeting for interaction. Other forms of user controls, such as voice controls, may not include such selection mechanics. Implementations disambiguate user voice input to select a target virtual object and control the target virtual object based on the voice input. For example, a disambiguation and control layer can select the virtual object the user intends to target with voice input, format input for the target virtual object using the voice input, and control the target virtual object via execution of one or more applications that manage the virtual object.

The invention discloses an intelligent control system and method for a shield muck treatment site, and relates to the technical field of shield engineering muck treatment. In order to solve the problems of low efficiency and high pollution of the existing muck treatment mode, the invention provides the following technical scheme: the muck treatment system comprises a sensing layer, a transmission layer, a control layer and an application layer, and the sensing layer is mounted around a muck treatment site and is used for monitoring muck components, equipment operation states and environmental parameters in real time; the transmission layer transmits the data collected by the sensing layer to the control layer; the control layer processes data of the sensing layer and automatically adjusts equipment operation parameters according to a preset control logic and an optimization algorithm; and the application layer analyzes and decides the data processed by the control layer. According to the system, intelligent monitoring and control are achieved, equipment faults are early warned in advance, the downtime is shortened, meanwhile, resource recovery and cyclic utilization are achieved, the construction cost and the environmental influence can be reduced, and the shield muck treatment efficiency, the resource recovery rate and the environmental protection performance are remarkably improved.

The invention relates to the technical field of internet of things and intelligent control, and provides a medicine distribution device based on the internet of things. An existing medicine distribution system mainly depends on manual operation or single automatic equipment, so that the efficiency and precision in the distribution process are low, the medicine identification technology bureau is limited to simple package bar code scanning, and identification and distribution of unpackaged medicines are difficult to process. According to the multi-modal data fusion technology, two-dimensional images, three-dimensional forms and spectral data are combined, medicine is accurately recognized, and automatic grabbing and accurate distribution are achieved through the mechanical arm and the force feedback control device. And the control layer adopts an inverse kinematics algorithm, a path planning algorithm and fuzzy logic control to ensure accurate operation and safe grabbing of the mechanical arm. The system also utilizes a reinforcement learning algorithm to dynamically optimize a drug distribution strategy, and improves the accuracy and flexibility of the distribution process through a real-time feedback mechanism.

The invention discloses a process parameter switching method and device for multi-variety production, and a server side method comprises the steps: receiving a process parameter switching request sent by a manufacturing execution system used for monitoring a product production state, wherein the process parameter switching request carries production demand description information and a product batch model; according to the production demand description information, corresponding target process parameters are automatically obtained, the target process parameters are determined by adopting a preset comparison function, and the preset comparison function comprises a basic comparison term expression and a physical comparison term expression; pre-checking the target process parameters to obtain a checking result; and under the condition that the verification result indicates that the verification of the target process parameter is passed, binding the target process parameter to a product batch model, and issuing the product batch model to an equipment control layer. Therefore, by adopting the embodiment of the invention, the time required for searching and inputting the process parameters is avoided, so that the equipment can be switched to a new production task more quickly, and the production efficiency and the product quality are remarkably improved.

The invention discloses an intelligent courtyard ecological collaborative management system and method. The system comprises a sensing layer, a control layer and an execution layer. The sensing layer is provided with a multi-mode sensor array, comprises an environment monitoring module, an equipment state monitoring module and a biological recognition module, can collect multi-mode data such as illumination, temperature and humidity, equipment operation parameters and plant growth states, and transmits the multi-mode data to the control layer through wireless communication. The control layer adopts a federated learning framework to fuse multi-modal data, extracts features through a deep residual network, generates an environment state matrix by using an attention mechanism, and operates a Markov decision model to output a decision control command and a response level. And the execution layer adjusts the on-off state and operation parameters of the regulation and control equipment according to the output, so that intelligent cooperative control of the irrigation system, the lighting equipment and the like is realized. According to the system, through multi-modal data acquisition and deep fusion analysis, comprehensive perception and accurate regulation and control of the ecological environment of the courtyard are realized, and the management efficiency and the resource utilization rate are improved.

The invention relates to a coal mine equipment cooperative control system based on digital twinning, and belongs to the field of coal mine intellectualization. According to the system, the equipment state, environmental parameters and fault data are acquired in real time through the data acquisition layer; the data processing layer realizes multi-source data fusion and fault prediction by using a deep fusion neural network and a space-time attention network; the digital twinborn layer constructs a three-dimensional dynamic model based on unified geodetic coordinate system coupling equipment and geodetic survey information; and the control layer adopts a distributed stream computing framework to execute collaborative scheduling, active disturbance rejection speed control and fault prediction compensation. The problems that in the prior art, spatial position expression is missing, collaborative delay is high, data are not synchronous, and complex working condition adaptability is poor are solved. The method has the beneficial effects that total-factor high-precision space coupling is realized, the collaborative delay bottleneck is overcome, the adaptability to complex working conditions is enhanced, a closed-loop intelligent optimization system is constructed, and full-chain transparent management and control of the coal mine are promoted.

The invention provides an energy efficiency optimization and predictive regulation and control method for a building electromechanical system based on digital twinning. The method comprises five layers of architectures including a physical entity layer, a data acquisition and interaction layer, a digital twinning model layer, an energy efficiency analysis and optimization layer and a predictive regulation and control layer. The dynamic digital twinborn body interacting and synchronizing with the physical electromechanical system in real time is constructed, fundamental transformation from passive lag control to prospective predictive control is achieved, a high-fidelity virtual model is used as a nondestructive testing platform, countless operation strategies can be safely and rapidly simulated and evaluated in a virtual space, and therefore accurate optimization is achieved, and the real-time dynamic digital twinborn body is obtained. The overall energy efficiency of the system is remarkably improved, the dilemma that the traditional method makes consideration and loses others is eliminated, and the leap-type improvement of the comprehensive operation quality is achieved.

The invention relates to the technical field of intelligent control of injection molding machines, in particular to an injection molding machine closed-loop mold adjustment control system and method based on multi-sensor fusion and a self-adaptive algorithm, and the system comprises a sensing layer which adopts a multi-sensor fusion closed-loop feedback architecture and comprises a pressure sensing array, a displacement sensing unit and a temperature sensing array. The data acquisition module is used for synchronously acquiring mold clamping force, position and temperature data of a mold, constructing a three-dimensional error compensation model and realizing dynamic correction of the parallelism of the mold through space force field analysis; the execution layer comprises a servo motor, a belt wheel and a ball screw and is used for adjusting the position of the template; a double-closed-loop control module is arranged in the control layer, the double-closed-loop control module comprises outer ring mold clamping force control and inner ring position control, mold clamping force deviation serves as input of an outer ring, position correction is generated through a self-adaptive PID algorithm, the inner ring converts the position correction into a servo motor rotation angle instruction, and therefore precise control over the mold clamping force is achieved.

The invention provides a flow and form decoupling cooperative processing method, and relates to the technical field of business flow management, and the method comprises the steps: constructing a layered architecture, separating a flow control layer from a form service layer, defining a flow node jump rule by the flow control layer based on a BPMN standard, and dynamically defining a form structure by the form service layer through JSON Schema; a form identifier is declarated in the process definition file, a corresponding form template is matched through a dynamic mapping service according to context information, and the context information comprises a process instance state, a user role, a device type and a service type; establishing a data sandbox isolation mechanism, generating a unique data space identifier for each process instance, and managing data access authority through a multi-dimensional isolation strategy of a tenant level, a service level and a process instance level; deploying an event bus communication mechanism, triggering two-way communication between a process engine and a form engine through a predefined event type, and ensuring the consistency of cross-system operation by adopting a transaction compensation mechanism.

The invention provides a dynamic energy-saving control method and device for garden landscape lighting, and the method comprises the steps: obtaining comprehensive monitoring data, such as multi-point environment illumination, people flow distribution and time period characteristics, and generating a partition lighting demand matrix through multi-dimensional fusion processing; identifying a contradictory region between the lighting demand and the energy consumption limitation, generating a conflict level mark based on energy efficiency analysis, and reversely deducing minimum power configuration; constructing a dynamic energy-saving constraint condition, carrying out boundary testing, generating a flexible energy-saving boundary, and determining an energy consumption control range; establishing a hierarchical control architecture of a main control layer and an auxiliary control layer, and generating a basic dimming instruction sequence and a supplementary control rule; analyzing an illumination influence relation of adjacent areas to establish a linkage mechanism, and optimizing operation parameters through cooperative control; the illumination power is dynamically adjusted by adopting an envelope modulation technology, a periodic fluctuation feature is extracted to identify an optimal energy efficiency mode, a self-adaptive control strategy is constructed, and intelligent dynamic energy-saving control of garden landscape illumination is realized.

The invention provides a trailing suction dredger loading operation parameter optimization real-time recommendation system and method, and relates to the technical field of trailing suction dredger dredging engineering.The system comprises a data collection layer, a real-time calculation layer, an intelligent recommendation layer and a feedback control layer, the data collection layer is used for collecting trailing suction dredger loading operation parameters in real time, and the real-time calculation layer is used for calculating the real-time calculation layer; the real-time calculation layer can calculate energy consumption and yield in real time based on edge calculation equipment, the intelligent recommendation layer can generate a Pareto optimal solution set through a multi-objective optimization algorithm, and the dynamic weight adjustment module adjusts energy consumption and yield weight coefficients in real time according to the construction stage. The feedback control layer issues the collected loading operation parameters of the trailing suction dredger to an execution mechanism in real time through a PLC, and monitors the operation state of equipment to update a historical database, so that collaborative optimization of energy consumption and yield can be achieved, and the optimization precision is continuously improved through historical data.

The invention relates to the technical field of medical informatization and intelligent scheduling, and particularly discloses a ward nursing process prediction and dynamic scheduling method and system.The ward nursing process prediction and dynamic scheduling method comprises the steps that firstly, a digital twinborn simulation environment synchronized with a physical ward in real time is established, and a nursing process is simulated through a multi-agent network; carrying out multi-time sequence deduction based on the environment, generating a prospective scheduling instruction set, and issuing and executing the prospective scheduling instruction set; calculating a prediction mismatch degree index by collecting actual execution data and comparing the actual execution data with a plurality of dimensions of an expected state; when the index exceeds a dynamic threshold value, a meta control layer is triggered to carry out self-adaptive adjustment on simulation environment parameters, and the self-adaptive adjustment comprises reconstruction of an agent behavior logic weight or switching of a scene deduction mode; and deducing and generating an updated instruction set again based on the adjusted environment to form closed-loop optimization.

The invention provides a tire crane automatic control system and method based on embedded edge calculation, and relates to the technical field of port automation, the tire crane automatic control system comprises a sensing and detecting layer used for collecting motion states and operation environment information of a cart, a trolley and a lifting appliance of a tire crane in real time; the core control layer is used for processing sensor data in real time and generating a control instruction; the action execution layer comprises a PLC gateway, a main control PLC and a driving motor, the PLC gateway communicates with the core control layer and is used for receiving a control instruction, and the main control PLC drives the motor to execute corresponding actions of a cart, a trolley and a lifting appliance; and the task management layer comprises an intelligent remote control console, is in communication connection with the core control layer, and is used for issuing the operation task instruction to the core control layer and receiving the system state data from the core control layer. Unmanned operation of the tire crane can be achieved, and a complete technical base is provided for port automation.

The invention discloses a beam line station synchronous data acquisition device and method, and belongs to the technical field of beam line station control, and the device comprises an equipment control layer and an application layer. The equipment control layer comprises a plurality of acquisition cases, an upper computer and a time service unit, the plurality of acquisition cases are respectively connected to the upper computer, and the time service unit is respectively connected to the timing module in each acquisition case; the application layer comprises an equipment abstraction module, a process abstraction module, a queue server module, a data storage module and a data visualization module. Unified abstract packaging is carried out on beam line station equipment and an experimental process, so that the same set of software framework is universal in all experimental modes and methodology, and a unified architecture for controlling a spectroscopy, imaging and diffraction experimental process is realized; experiments can be executed autonomously according to the queue sequence, automation of the experimental process is achieved, data acquisition efficiency is improved, and then the problems that in a beam line station, multi-device synchronization efficiency is low, and synchronization signal lines are prone to interference are solved.

A light control sheet includes a first electrode sheet including a first transparent electrode layer, a second electrode sheet including a second transparent electrode layer, and a light control layer. The first sheet, second sheet, and control layer form a driver section in which the first sheet, second sheet, and control layer are overlaid, a first non-driver section in which the first sheet is exposed from the control layer and second sheet, and a second non-driver section in which the second sheet is exposed from the control layer and first sheet. The non-driver sections have a sealing section covering end face of the control layer. The first electrode layer includes a non-conductive section in the first non-driver section. The non-conductive section is not connected to a first driver portion in the driver section. The first non-driver section includes a disconnection section separating the non-conductive section from the first driver portion.

The invention discloses a multi-tenant management and control system and method for a big data platform, and relates to the technical field of data management, and the system comprises a data basic management and control module layer and a data processing collaborative management and control layer. The data basic management and control module layer comprises a big data component management module, a tenant management module, a unified login authentication module, a project management module, a data resource authority management module and a computing resource management module; the data processing collaborative management and control layer comprises a component health monitoring sub-module, a resource prediction distribution sub-module, a dynamic desensitization encryption sub-module, a task collaborative management sub-module and a data quality management and control sub-module; the problems of weak tenant basic management and control, low resource allocation efficiency and insufficient component reliability and data security management and control in the existing multi-tenant management and control technology are solved, and the defects of lack of cross-tenant cooperative capability, lack of task and data quality management and control and insufficient data security management and control caused by the problems are overcome.

The invention discloses a multi-mode perception collaboration and real-time synchronization system, which breaks through the limitation of vision / hearing in the prior art, covers vision, hearing, smell and movement, and realizes more accurate cooperation through a perception layer, a control layer and an execution layer. According to the invention, an immersive experience space full of shock and reality can be created, synchronous output of visual, auditory, tactile and olfactory signals is realized by means of high-precision equipment, and a series of cross-sensory signal superposition schemes are designed on the basis of response characteristics of human physiology and psychology to various sensory stimuli. Therefore, the overall perception of the experiencer to the space atmosphere is enhanced. Meanwhile, through weight distribution and conflict resolution, the system can flexibly adjust the sensing mode according to the environment and the user state. The multi-device cooperation error can be controlled at millisecond level and millimeter level, and the natural fusion of virtuality and reality is realized.

The invention relates to the technical field of advertisement marketing analysis, in particular to a data diversity identification advertisement marketing system, which comprises a data diversity identification module, a double-loop control module and a cross-layer information sharing channel module, and is characterized in that the data diversity identification module is used for calculating dynamic diversity indexes of multi-source heterogeneous data in real time; the double-circulation control module comprises an outer circulation strategy optimization layer unit and an inner circulation real-time control layer unit, the outer circulation strategy optimization layer unit operates at an hour-level time scale, a reinforcement learning algorithm is adopted to carry out long-term advertisement marketing strategy optimization, and an optimization objective function of the outer circulation strategy optimization layer unit is fused with a dynamic diversity index; the internal circulation real-time control layer unit operates at a second-level time scale, and adopts a parameter self-adaptive control algorithm to adjust an advertisement putting strategy in real time; and the cross-layer information sharing channel module is used for realizing strategy parameter transmission between the outer circulation and the inner circulation and applying strategy consistency constraint conditions so as to collaboratively optimize an advertisement marketing strategy.

The invention provides a display module and a display device, and the display module comprises a display panel which comprises a plurality of pixel units arranged in an array; the light control device is arranged on the light emitting side of the display panel, the light control device comprises a first regulation and control layer and a second regulation and control layer which are sequentially arranged on the display panel in a stacked mode, the first regulation and control layer comprises a first refraction layer and a second refraction layer covering the first refraction layer, the first refraction layer comprises a plurality of lenses arranged in an array mode, and the second refraction layer comprises a second refraction layer covering the second refraction layer; the orthographic projection of each lens on the display panel at least covers two pixel units, the refractive index of the first refraction layer is larger than that of the second refraction layer, when the display module is in a three-dimensional display state, liquid crystal molecules in the second regulation and control layer do not deflect, and when the display module is in a two-dimensional display state, liquid crystal molecules in the second regulation and control layer do not deflect. And the second regulation and control layer is equivalent to a plurality of lens units arranged in one-to-one correspondence with the lenses. The display module provided by the embodiment of the invention can reduce view crosstalk in a three-dimensional display state.

The invention relates to the technical field of artificial intelligence and data engineering, in particular to an intelligent data development treatment system and method based on a large model, the system is composed of a data access layer, a large model treatment engine, an intelligent feature factory, a compliance control layer and an application interface layer, and all the modules cooperate to achieve intelligent transformation of the whole data development process; the method has the beneficial effects that the potential mode of the multi-source heterogeneous data can be automatically identified, for example, transaction records, user behavior data and system monitoring information are distinguished from mixed log files, and manual rule pre-definition is not needed. And dynamically adjusting the protection intensity according to the data use scene.

The invention relates to the technical field of mine safety monitoring, and discloses a mine high-temperature heat damage monitoring system based on multi-mode Internet of Things data, and the system comprises a prediction and control integrated system architecture module which constructs a prediction and control integrated system architecture, and builds a three-layer PCIS architecture of a perception layer, a prediction layer and a control layer; the thermal field and flow field combined optimizer module is used for constructing a thermal field and flow field combined optimizer and realizing direct coupling of a prediction model and a control algorithm; the self-adaptive anti-interference control mechanism module is used for implementing a self-adaptive anti-interference control mechanism and realizing system fault tolerance through a fault mode library and dynamic reconstruction; the performance self-optimization module is used for implementing system performance self-optimization and continuously improving the system performance through incremental learning and knowledge migration; according to the method, through multi-modal data fusion and the space-time diagram convolutional network, the heat damage prediction precision is improved, the prediction time range is expanded, and more sufficient response time is provided for heat damage prevention and control.

The invention discloses a cigarette cut tobacco batch production circulation control system and method based on single-point condition judgment, and the system comprises a work order parameter verification module which is used for receiving a work order issued by a scheduling system, and carrying out the work order information integrity verification, process parameter compliance verification and equipment suitability verification; the regular expression configuration module is used for providing a visual interface and configuring a regular judgment rule set of equipment starting conditions, ending conditions and abnormal ending conditions; and the single-point judgment execution mechanism is embedded into the PLC control layer, acquires equipment parameters in real time, dynamically evaluates regular conditions based on a finite-state machine model, and triggers an equipment start-stop instruction. According to the system, the cigarette cut tobacco batch switching time is remarkably shortened, and the work order circulation efficiency is improved; the manual intervention frequency is further reduced, and the misoperation rate is further reduced; and the problem of production interruption caused by disconnection of the equipment state and the process parameters is solved.

According to the deep ultraviolet LED device provided by the invention, a first stress regulation and control layer and a second stress regulation and control layer are sequentially arranged between an electron injection layer and a quantum well active layer, and the Al component content x2 of the first stress regulation and control layer and the Al component content x3 of the second stress regulation and control layer meet the following relations: x3 < = (x4 + x5) / 2, x2 > = (x1 + x3) / 2, x4 > x3 > x5; according to the invention, by regulating and controlling the Al component content of each layer, the lattice mismatch between the second stress regulation and control layer and the quantum well active layer is reduced, and the lattice mismatch among the electron injection layer, the first stress regulation and control layer and the second stress regulation and control layer is reduced, so that the tensile stress can be applied to the quantum well active layer, and the performance of the device is improved. Therefore, the pressure stress generated by the bottom epitaxial structure on the quantum well active layer is compensated, and the light-emitting efficiency of the deep ultraviolet LED device is finally improved.