570 results about "Distributed control system" patented technology

The invention discloses a dynamic intelligent control method and system for improving the efficiency of a rectifying tower, particularly relates to the technical field of chemical process control, and is used for solving the technical defect that an operation variable is mismatched with a physical state due to the fact that an existing distributed control system cannot recognize a hidden degradation state of equipment. The method comprises the following steps: acquiring temperature gradient distribution of each tower plate of a rectifying tower, thermal load of a reboiler and tower top condensation load parameters in real time, calculating a mass transfer efficiency offset by combining the temperature gradient distribution to generate a scaling trend index, and synchronously calculating a local entropy yield based on the thermal load and the condensation load to generate a thermodynamic irreversibility index. When the double indexes exceed a preset threshold value, it is judged that a recessive degradation state is entered, then a backflow ratio correction coefficient is reversely derived through a dynamic correlation model, and the correction coefficient is input into a distributed control system to dynamically adjust backflow ratio operation parameters; the product purity is maintained, the tower plate scaling process is obviously delayed, and long-term efficient operation of the rectifying tower is guaranteed.

The invention relates to the technical field of industrial distributed control system architecture, and discloses a dual-redundancy design method for a virtual controller VDPU, which comprises the following steps of: deployment of a four-network-port redundant network architecture: dividing four physical network ports into two groups of independent channels, and simultaneously configuring a network link automatic switching mechanism, the working states of the four network ports are monitored in real time, then double isolation of a physical layer and a protocol layer is achieved, and an independent heartbeat transmission channel is established; main / standby heartbeat monitoring and switching control: the main / standby controller periodically interacts state information packets through a special heartbeat channel, and establishes a three-level fault determination mechanism at the same time to perform seamless main / standby switching; a multi-mode data synchronization mechanism is implemented, namely initialization synchronization, increment synchronization during operation and exception recovery synchronization are started, separation of heartbeat signals and data synchronization can be realized through two groups of independent channels, and the fault-tolerant capability and the switching efficiency of the system are improved, so that the operation stability of the system is guaranteed.

The invention discloses an electromechanical equipment distributed control system based on the Internet of Things, which belongs to the technical field of distributed control, and specifically comprises the following steps: splitting a control task into task units, registration dependencies, data entries and task levels at an edge gateway, and generating a candidate scheduling range according to registration items; a calibration heartbeat with a reference segment is issued, and a driving node executes and returns a measurement record in an idle window for calibrating hardware fingerprints and link overhead and dynamically updating matching parameters; when computing power saturation is triggered, splitting a low-level task unit into suspensible fragments, setting a de-duplication execution identifier, opening a state interface, and completing migration check; selecting a target control node and a transmission path according to a calibration result, issuing fragment and state interface information, driving a target node to continue fragments according to an execution template, and guiding a source node to release occupied resources in sequence; and checking and comparing the execution result, and when the rule is triggered, recovering to the previous stable state according to the mapping rollback table.

The invention provides an AGC signal intelligent correction and control method, device, equipment and medium, and the method comprises the steps: collecting an AGC instruction signal of a power grid dispatching side, an actual power feedback signal of a power plant side and a unit operation state parameter, and constructing multi-source heterogeneous data; inputting the multi-source heterogeneous data into a pre-trained digital twinborn model to obtain a predicted value of the real power of the unit; calculating a real-time deviation between the predicted value of the real power and the actual power feedback signal, and dynamically compensating the AGC instruction signal based on the real-time deviation to generate a corrected AGC instruction signal; and on the basis of the corrected AGC instruction signal, a feedforward control signal is generated, and is superposed to a basic control instruction of a unit distributed control system (DCS) in an increment form, so that full-load section accurate control is realized, and the problems of accurate correction of the AGC signal, accurate prediction of real power and dynamic compensation are solved.

The invention discloses a fresh commodity after-ripening regulation and control planning method oriented to maturity grading, and relates to the technical field of food science and biologication.The method comprises the steps that physiological parameters of fresh commodities are collected in real time based on a multi-modal sensor, and the physiological parameters comprise the epidermis pigment content, the ethylene release rate, the fruit hardness and the respiration intensity; the collected physiological parameters are input into a multi-objective optimization model based on deep learning, the model fuses a metabolic kinetic equation and an LSTM time sequence prediction algorithm, and a regulation and control parameter combination adaptive to the current mature stage is output; according to the regulation and control parameter combination, the temperature, the relative humidity and the O2 / CO2 concentration gradient of the controlled atmosphere storage equipment are synchronously regulated through a distributed control system, and a plant hormone antagonist is injected through an ultrasonic atomization device; and constructing a supply chain collaborative network based on a block chain technology, binding a grading result with logistics path planning, and adjusting a temperature control strategy and a shelf life countdown parameter of the cold chain transport vehicle in real time through an edge computing node.

The invention relates to the technical field of flow chart automatic testing, and provides a flow chart automatic testing method, system and device of a control system and a storage medium so as to solve the problems of low testing efficiency and poor accuracy. The method comprises the following steps: acquiring a film thickness and transverse tension fluctuation curve by using an intelligent textile sensor array, generating a tension compensation factor based on a phase difference to correct the film thickness, and establishing a thickness distribution topology model; performing non-contact scanning by using a terahertz wave emission array, and activating a defect mark cluster when Doppler frequency shift is detected; transmitting the thickness distribution model and the defect characteristics to a test platform, reconstructing a control logic and generating a test script, and realizing a virtual-real synchronous test through a communication protocol; and generating a process parameter correction factor according to a test result, and feeding back the process parameter correction factor to the distributed control system to optimize the tension closed-loop control module, and generating a matched terahertz verification map. According to the technical scheme provided by the invention, the efficiency and accuracy of automatic testing of the flow chart can be improved.

The invention discloses a DCS operation and maintenance method based on fusion dynamic weight distribution and fault chain deduction, and relates to the technical field of operation and maintenance of a distributed control system, and the method comprises the steps: obtaining a plurality of groups of source data of a monitoring region; corresponding monitoring periods are determined according to the multiple groups of source data, and differential monitoring period information is obtained after combination; according to the technical key points, a multi-source data fusion module is utilized to associate data of a DCS system, an associated production system and a cross-plant cooperative system, and fragmented data such as equipment operation data, production load fluctuation and cross-plant interaction information are woven into a complete data network through adjustment of space-time alignment and multi-dimensional verification; the global sensing capability not only solves the one-sidedness of traditional single data judgment, for example, environmental interference is easily misjudged by only depending on equipment temperature data, but also can capture cross-system implicit associated faults; and secondly, when the multi-source data are mutually verified, an evidence chain is formed through logic consistency verification, so that the misjudgment rate of suspected faults is greatly reduced.

The invention relates to the technical field of distributed control systems, and discloses a distributed valve body remote control system which comprises a valve body state acquisition module, a remote communication analysis module and the like. The valve body state acquisition module acquires parameters such as opening, fluid pressure and surface temperature of a multi-area valve body according to a monitoring period, and a high-frequency monitoring mode can be started; the remote communication analysis module evaluates communication delay; the distributed coordination module synchronizes parameters when communication is normal, and calculates a dynamic regulation factor through a formula to generate a regulation instruction; the instruction distribution module determines an instruction distribution sequence according to a priority weight formula, and is provided with delay and forced distribution strategies; and the abnormal response module gives an alarm and marks the position code of the valve body when the communication delay exceeds the limit or the weight is continuously too low. And the system also checks and complements the acquired data. The system improves the monitoring control precision and reliability, and is suitable for remote monitoring of multi-area valve bodies.

The invention discloses a DCS (Distributed Control System)-based ignition and temperature rise mode of a copper anode slime roasting rotary kiln, which specifically comprises the following steps of: setting initial control conditions, drawing a temperature rise curve according to a target temperature, a temperature rise period and a temperature rise gradient, and then starting ignition preparation. Before natural gas is introduced into the combustion chamber for combustion, rotary kiln operation and combustion-supporting air purging are carried out, after purging is carried out for a period of time, combustion-supporting air and natural gas are introduced for ignition at the same time, and meanwhile the ignition condition is judged through a monitor. And if ignition fails, under the condition of no abnormity, purging can be repeated, and natural gas is introduced for re-ignition. According to the method, the natural gas flow and the combustion-supporting air volume are automatically controlled by the DCS according to the drawn temperature rise curve. The system has the beneficial effects that multiple ignition conditions can be controlled at the same time, remote automatic ignition is achieved, the ignition condition is fed back in time, the natural gas flow is flexibly controlled, the combustion temperature is controlled, the ignition effect of the rotary kiln is guaranteed, and meanwhile production operation safety of the rotary kiln is guaranteed.

The invention belongs to the technical field of distributed control, and discloses an AI intelligent control cabinet distributed control system and method. Comprising the steps of obtaining running state data and control task data; constructing a task priority vector of each intelligent control cabinet in each control period; generating a global task conflict graph based on the task priority vectors of all the intelligent control cabinets in the same control period; obtaining a task conflict probability and a task execution sequence of each intelligent control cabinet in the same control period according to the global task conflict graph; based on the task conflict probability and the task execution sequence, a control task execution strategy of each intelligent control cabinet is adjusted, and an optimized control task sequence of each intelligent control cabinet is obtained; and according to the optimization control task sequence, distributed cooperative operation of each intelligent control cabinet in the next control period is controlled, and the overall operation efficiency and the conflict occurrence rate of the distributed system can be effectively balanced.

The invention discloses an intelligent deep peak regulation system for a coal-fired power generation unit, and particularly relates to the technical field of power generation control, and the system comprises a multi-source data collection module which carries out the real-time parallel collection of all-dimensional operation parameters through a sensing network and unit decentralized control system interface disposed at a key node, and builds a multi-modal time sequence data flow; according to the method, a foresight control strategy is formed by constructing a fusion prediction model, sensing the running state of a unit in real time and predicting the change trend of key parameters, the defect of response lag of a traditional system is effectively overcome, and the purposes of accurate load tracking and advanced regulation and control under the working condition of deep peak regulation are achieved; a global optimization decision-making mechanism is established by adopting a deep reinforcement learning algorithm, optimal control parameters are calculated in real time through the intelligent peak regulation module, a boiler, a steam turbine and an environmental protection system are dynamically coordinated, the problem of insufficient stability caused by subsystem independent control is solved, and the optimal balance of safety, stability and economic benefits is achieved.

The invention relates to the technical field of distributed control systems, and provides a fault diagnosis and early warning method and system for a distributed control system, and the method comprises the steps: collecting mechanical vibration data, equipment surface temperature field distribution data and power supply current waveform data in real time through deploying a plurality of groups of sensor arrays at key nodes of the distributed control system; and comparing the fault mode with a preset safety threshold and a fault mode in a historical fault case library. And when the data is abnormal, the system tracks a vibration propagation path of adjacent nodes through graph structure modeling, locates a fault source in an amplitude difference direction, and matches an undetermined fault topology network generated in real time with a predefined reference fault topology network. The propagation characteristics of the vibration waveform are utilized to reversely deduce the fault origin, and intelligent diagnosis is realized in combination with a historical fault mode library. The dynamic analysis of the fault trend is realized, and the fault identification accuracy is improved through real-time data comparison and topology matching.

The invention relates to the technical field of coal-fired units, and discloses a coal-fired unit fault identification method, device and equipment and a medium, and the method comprises the steps: obtaining parameter data of a coal-fired unit, the parameter data comprising operation parameters of a distributed control system in the coal-fired unit, structured data of a coal quality database and environmental data of an environmental sensor; inputting the parameter data into a pre-trained health index prediction model, outputting an equipment health index, and fusing support vector machine anomaly detection and time sequence prediction by the health index prediction model by adopting integrated learning; based on a clustering analysis result of the historical parameter data of the coal-fired unit, setting a self-adaptive early warning threshold value of the coal-fired unit; and if the equipment health index is lower than the self-adaptive early warning threshold value, inputting the parameter data into a pre-trained fault positioning model to predict the fault position of the coal-fired unit.

A method for supporting troubleshooting software and hardware issues in a distributed control system (DCS) associated with an automation equipment in industrial plant includes monitoring data; detecting an anomaly in the monitored data based on predetermined anomaly detection rules; based on a result of the detecting, performing, for a detected anomaly, a similarity search on historic anomaly data associated with the DCS and / or the automation equipment; based on a result of the performed similarity search, querying a large language model (LLM) for diagnosis and / or recommendation for troubleshooting the detected anomaly; based on the querying, obtaining an output from the LLM, wherein the output is indicative of a diagnosis and / or recommendation for troubleshooting the detected anomaly; and providing the output to a user.

The invention discloses an equipment fault diagnosis method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence. The pre-training joint reasoning model is used for comprehensively analyzing the multi-dimensional data to generate an equipment fault probability prediction result, a composite fault mode can be effectively recognized, dynamic working condition changes can be adapted, meanwhile, tracing analysis is conducted on a fault propagation path in combination with the graph neural network, the effectiveness of feature extraction and modeling is improved, and therefore the fault probability prediction result is obtained. The technical problems that in an existing equipment fault diagnosis system, a threshold model is difficult to recognize a composite fault, a physical model cannot adapt to a dynamic working condition, and the fault traceability of a correlation analysis model is limited can be solved, and the purposes of improving the accuracy and adaptability of equipment fault diagnosis, enhancing the fault traceability and improving the reliability of equipment fault diagnosis are achieved. And the technical effect of promoting predictive maintenance to develop to higher-level intellectualization is achieved.

The invention relates to the technical field of digital twinning, and discloses a process industry digital twinning platform system, which comprises a process mechanism modeling module used for constructing a multi-scale first principle model system according to physical and chemical laws of the process industry; the dynamic coupling engine is used for collecting process data in real time and carrying out coupling solution by combining the first principle model system and the equipment operation state model; the closed-loop optimization control interface is used for carrying out two-way communication with the distributed control system, generating an optimization set value based on a solving result and executing control; and the visual diagnosis module is used for carrying out multi-dimensional analysis, fault root cause tracing and early warning response on process parameter deviation. First principle equations of reaction kinetics, heat transfer theory and the like are directly embedded into the virtual model through the process mechanism modeling module, so that the model has physical and chemical interpretation capability on complex chemical reactions and energy transfer, and high precision is still kept under complex working conditions.

The invention discloses a power distribution network flexible mutual supply control method considering load uncertainty, and relates to the technical field of power system control. The method includes: acquiring historical operation data of a power distribution network, and establishing a robust optimization model; based on the robust optimization model, a flexible mutual supply control strategy is designed, and an adaptive control mechanism is introduced; evaluating a system state, and performing distributed coordination control based on the evaluated system state; carrying out robust stability analysis according to the characteristics of the distributed control system; and evaluating the index system. According to the invention, the robust optimization model is established to effectively cope with load fluctuation; a flexible mutual supply control strategy is designed based on the model, power distribution is optimized by combining a hierarchical architecture and a self-adaptive control mechanism, and the response capability of the system to sudden changes is enhanced; an improved Kalman filtering algorithm is used for evaluating the system state, distributed coordination control is implemented, and the communication cost is reduced; a Lyapunov direct method is adopted to carry out robust stability analysis, and stable operation of the system is ensured.

The invention relates to the field of safety monitoring, and particularly discloses a calcium formate production process safety monitoring method and system, which utilize a distributed control system to collect original production data, and ensure time consistency of all monitoring variables through data synchronization processing, thereby laying a foundation for subsequent analysis. Thirdly, performing feature engineering processing on the synchronized data, extracting features such as short-term and medium-term change rates, moving average values and standard deviations of temperature, pressure and stirrer current, constructing state features of the reaction kettle, and capturing dynamic operation information of the system; in order to predict potential risks, a trend prediction model based on deep learning is adopted, a historical temperature sequence is converted into a future temperature trajectory, and prospective pre-judgment on the temperature trend is provided; meanwhile, the current system health condition is evaluated in combination with a state recognition model, the risk level is determined through a decision tree model according to the abnormal score and the predicted temperature maximum value, and graded early warning is achieved.

The invention provides a distributed control system and a time synchronization method, and the method comprises the steps: a target data station determines whether time pulse signals are transmitted abnormally based on three received continuous time pulse signals; if not, the data station generates a contention owner request and sends the contention owner request to other data stations, and the contention owner request at least comprises a data station identifier; all data stations determine time data stations based on all contention owner requests of the round; and the time data station sends time information to other data stations in response to time synchronization requests sent by other data stations through a preset protocol, so that other data stations synchronize the received time information as current time to complete time correction of all data stations. The time signal is diagnosed, and the standard time source is dynamically adjusted, so that the accuracy and consistency of the time of the distributed system are ensured.

The invention discloses a distributed control system topological structure optimization method and system oriented to a gas turbine, and belongs to the technical field of gas turbine control. The method comprises the following steps: establishing a double-feature grid coding system fusing space coordinates and an adjacent distance matrix, and updating a shortest path between nodes by using a Floyd algorithm; designing a function-resource allocation scheme by combining engineering constraints such as node working temperature limitation and bus load uniformity; the position of a central intelligent node of the star topology structure is optimized by adopting a particle swarm algorithm, and the local wire harness length is shortened; the node connection sequence of the annular topological structure is optimized through a genetic algorithm, and the redundancy of key nodes is improved; and finally, a hybrid topological structure is formed. The example verifies that the total wire harness length of a certain type of gas turbine control system is reduced by 61.6% compared with that of a traditional centralized architecture, the signal transmission reliability is remarkably improved, the development and maintenance cost is reduced, and the method has important engineering application value.

The invention discloses an electrolyte blending control method based on a distributed control system, which develops an automatic control program of a blending kettle through a DCS platform, and realizes remote automatic control of the whole process from raw material unloading, blending, infusion to product loading. According to the core scheme, multi-material feeding sequence self-defining and valve interlocking logic are adopted, and the raw material dosage is accurately controlled; dynamically adjusting the temperature and pressure of the blending kettle through a PID algorithm; after feeding, nitrogen is automatically triggered to purge pipeline residues, and misoperation and leakage risks are avoided. Through integration of software, hardware and a process, the problems of multi-material accurate feeding and complex interlocking control in an industrial scene are solved, and the blending efficiency and the product quality consistency are remarkably improved; flexible adjustment of parameters and raw material routes is supported, and different production requirements are met; pressure control, a flow accumulation algorithm and a valve interlocking mechanism can be extensively applied to tank field working sections in the fields of petroleum, chemical engineering and the like and automatic control of other types of reaction kettles, and safety and economical efficiency are both achieved.

The invention provides a sponge rural ecological landscape drainage and storage system, and relates to the technical field of drainage and storage. The sponge rural ecological landscape drainage and storage system comprises a storage module, a drainage unit, a super-hydrophobic water collection module and a distributed control system. According to the invention, the system can switch the intelligent drainage valve from a high-resistance state to a low-resistance state at a millisecond level at the moment of monitoring rainstorm by utilizing the real-time adjusting capability of the electromagnetic coil embedded in the magnetorheological valve body to the viscosity of the MRE material, so that large-drift-diameter full-open flood discharge is realized, and when the rain vigor is weakened or a dry season water storage stage is entered, the intelligent drainage valve can be switched from the high-resistance state to the low-resistance state at the moment of monitoring rainstorm, so that the large-drift-diameter full-open flood discharge is realized. And the high viscosity can be quickly recovered to be close to a fully-closed state, so that the runoff water source is efficiently locked in the reservoir body. According to the high-response and high-precision flow adjusting mode, the opening degree can be automatically adjusted according to the rainfall intensity and the water level change, so that the two extreme working conditions of flood drainage and water storage are optimally balanced, and the emergency capacity of the system for sudden heavy rainfall events and the dry season water resource guarantee capacity are remarkably improved.

The invention relates to the technical field of PE lamination production control, and discloses a distributed control system for a high-speed PE lamination production line. A base material state monitoring module of the system collects surface tension parameters and thickness distribution data of a base material in real time, and a dynamic base material state matrix is generated in combination with the operation speed of the base material; the temperature field coordination module is used for matching a preset melt temperature gradient curve according to thickness distribution data in the dynamic base material state matrix and generating a partition temperature regulation and control instruction set; the extrusion pressure balance module analyzes the pressure fluctuation historical record of each extrusion section based on the partition temperature regulation and control instruction set, calculates the pressure compensation amount of adjacent sections and generates a pressure balance parameter table; the film layer fusion control module receives the compensation amount data, adjusts the rotating speed difference of the double-screw extruder and the opening degree parameter of a die head in combination with the real-time melt casting speed, and outputs a film layer fusion quality index; and the distributed execution module decomposes the film fusion quality index into independent control instructions and synchronously issues the independent control instructions to each execution unit.

The invention discloses a nuclear power plant distributed control system and control method, and relates to the technical field of nuclear power plant digital control, and the method comprises the steps: a global optimization layer generates a cross-unit general control strategy library based on a transfer learning algorithm according to the decision period of the global optimization layer; when the coordination control layer operates by using the transferable control strategy corresponding to the unit equipment where each two-loop subsystem is located, the corresponding two-loop subsystem control weight is dynamically allocated based on the multi-agent attention network according to the decision period of the coordination control layer; when the execution control layer operates by using the dynamically distributed two-loop subsystem control weight, the first-loop temperature, the first-loop pressure and the coolant flow are obtained according to the decision period of the control layer, a safety constraint matrix is calculated through a safety manifold projection module, and a quadratic programming problem with a relaxation factor is solved; and the corrected control weight of the two-loop subsystem is obtained and converted into a control instruction to be issued to a DCS field control station.

The invention discloses a multi-language internationalization translation method and system, a medium and equipment, and is applied to a distributed control system.The method comprises the steps that a background processing program reads a user visible text wrapped by an internationalization identifier in a source file and stores the user visible text as a json file; the automatic translation large model translates the user visible text to obtain the translated user visible text, and the background processing program stores the translated user visible text into the json file again; when the distributed control system runs based on a source code, automatically loading a dynamic library, matching a user visible text required to be translated of an internationalized identifier package with a json file, and displaying the user visible text required to be translated as a translated user visible text based on a result returned after matching, the multi-language version can be obtained without modifying a large number of source codes, the system language switching efficiency is improved, the labor cost is reduced, and the system maintenance efficiency is improved.

The invention provides a thermal runaway early warning and grading suppression method and system for a lithium iron phosphate energy storage battery for AGC frequency modulation of a 300MW and above thermal power generating unit. The method comprises the following steps: acquiring four-dimensional parameters including battery cell temperature, characteristic gas concentration, battery cell voltage and internal resistance and battery cabin vibration amplitude; performing graded early warning on the lithium iron phosphate energy storage battery based on the four-dimensional parameter to obtain an early warning signal; sending the early warning signal to a DCS (Distributed Control System) and an AGC (Automatic Gain Control) system of the thermal power generating unit so as to share the risk level and the battery module positioning information; matching and executing a corresponding hierarchical suppression strategy based on the early warning signal; and based on the shared risk level and the battery module positioning information, linkage suppression is carried out through a DCS system and an AGC system of the thermal power generating unit. According to the method, the four-dimensional parameters are obtained for graded early warning, the graded suppression strategy is matched, linkage suppression is carried out with the DCS and AGC system of the thermal power generating unit, and the thermal runaway risk is effectively prevented and controlled.

The invention discloses an intelligent motor start-stop prediction control method and system for a decentralized control system, and relates to the technical field of start-stop control, and the method comprises the steps: determining an element number array based on system control elements for the decentralized control system; aiming at a target control scene, determining a series-parallel connection relation of the decentralized control system, performing initialization on a data interface at an acquisition side, performing packaging of an element number array and transmitting the element number array back to a controller; and the auxiliary controller executes a cascade control decision under serial packaging, determines a start-stop strategy according to verification deviation correction based on trusted start-stop and soft start-stop, and executes start-stop control in response to the motor set. According to the invention, the technical problems of untimely motor start-stop response, inaccurate control decision and insufficient short-time shutdown transition management in the decentralized control system in the prior art are solved, the intelligence and reliability of motor start-stop prediction and control in the decentralized control system are improved, and the reliability of the motor start-stop prediction and control in the decentralized control system is improved. And the technical effects of stable transition and start-stop optimization management of the motor under short-time shutdown are realized.

The invention relates to the technical field of tobacco feeding rollers, and discloses an automatic cleaning device for a tobacco feeding roller, which comprises a DCS (Distributed Control System), a compressed gas treatment device, a tap water treatment device and a cleaning assembly, and the compressed gas treatment device and the tap water treatment device are both connected with the DCS. According to the automatic cleaning device for the tobacco feeding roller, when the roller needs to be cleaned, the cleaning assembly can be adjusted to a proper position, a compressed gas treatment device, a tap water treatment device and a driving mechanism on a rack are driven by a remote control function, and at the moment, a connecting pipe can be driven by the driving mechanism to slowly advance and slide; the high-pressure injection mechanism can supply gas or liquid into the connecting pipe, the spray head can spray the gas or liquid into the inner wall of the roller, cleaning of the roller is achieved, and start and stop, delay time, linked intervals and the like of spray washing can be set and operated through the human-computer interface.

The invention provides a cross-domain access method and system for a decentralized control system, computer equipment and a storage medium, and belongs to the technical field of cross-domain access control. The method comprises the steps of dividing security domains of a unit plant and a public system; determining a security domain to which the cross-domain access service belongs and control node information; constructing a mapping relation between the alias points and the data source points and a privilege point list; registering cross-domain access service node information at the control node; creating a virtual data node in a security domain where the alias point is located so as to bind a real-time synchronization channel of the data source point; under the condition that a control node initiates a cross-domain request, a requester security domain identifier and a data point unique ID are added and sent to a cross-domain service node; and under the condition that the cross-domain service node verifies that the request security domain is valid, stripping the security domain identifier and executing the target operation. The problem of mutual operation between units caused by configuration errors is avoided, the stability and safety of the operation units are improved, and then the continuity of power plant production is improved.

The invention discloses a cabinet temperature control method and device for a distributed control system, and the method comprises the steps: reconstructing a three-dimensional temperature distribution model in a cabinet through the combination of real-time temperature data and a spatial interpolation technology, so as to obtain the current temperature distribution data; and based on a neural network, in combination with the historical thermal load data, the operation state data of the system, the external environment data and the temperature distribution data, determining thermal load prediction data and temperature distribution prediction data in a future preset time period. And based on the real-time temperature data, the thermal load prediction data and the temperature distribution prediction data, a multi-objective optimization algorithm is adopted to optimize the control instruction of the temperature adjustment equipment in each partition in the cabinet. According to the optimization result of the control instruction, the temperature adjusting device of each partition in the cabinet is controlled, partition temperature control of the cabinet is realized, the thermal load and the temperature are predicted by using a spatial interpolation technology in combination with a neural network, partition control instruction optimization is carried out on the cabinet, and the precision and the response speed of the temperature control method are improved.